Threads of Resemblance in New Australian Gothic Cinema

Article excerpt

   '... unlikely to be endorsed by Australian tourist commission'
   (Leonard Maltin's closing sentence in his review of Wake in Fright
   [Kotcheff, 1971] (1))

THERE IS A PECULIAR PRESENCE in the catalogue of Australian feature films, sitting in the shadow of the highly visible and culturally laudable success stories. Tending towards the eccentric, and occasionally perverse, this presence has received attention from only a handful of film theorists and cinephiles. It is the small, yet consistent flow of malevolence and disorder that is never far from the surface in Australian productions. It appears in some instances as an entire feature film, and in others as a single scene, demonstrating tendencies that resonate indiscriminately throughout the entire body of Australian Cinema. Not even the commercially oriented, high-profile and high-budget production is guaranteed to emerge untouched. It is this 'presence', this off-centre, almost intangible element of sinister peculiarity in Australian productions that has been described by theorists as 'Australian Gothic'.

It is reasonable to expect that such a seemingly appropriate title would have an equally appropriate body of theoretical work behind it. After all, a word with a strong cultural presence in history, architecture, literature and film would seem to demand attention in this context. However, when placing what has been written about the subject under closer scrutiny, 'Australian Gothic' appears to be an almost arbitrary title. The theoretical engagements that exist, while providing some details of the relationships between particular films and aspects of the traditional Gothic novels of the early eighteenth century, seem somewhat inadequate. In this article, we will revisit some of the texts that are generally regarded as Australian Gothic, adding our interpretation of their significance, in order to demonstrate the new perspectives our position offers.

Before proceeding, it is important to place some of what follows in context. As will be clear from the outset, we engage with genre on different levels. As such, it is helpful to envisage this project as occupying territory somewhere along a 'continuum' of theoretical approaches to genre in film. Our project is situated somewhere between the 'practical', economic, and industry-based concepts of genre, and the more abstract theoretical models, such as those offered by disciplines like philosophy and literary theory. Our intention is to conduct the following argument with an awareness of, and sensitivity towards these very different perspectives on the nature of genre. In the broadest of terms, this paper seeks to extend and modify existing explanations of Australian Gothic Cinema, as a kind of film-making in Australia, while not treating genre as an immutable apparatus of categorical differentiation.

Even a cursory consideration of the term 'Gothic' illuminates an array of cliches. We might reasonably imagine tales of the ruined castle or haunted house, or be reminded of stories about 'undead' monsters and repressed sexuality. Demonstrably, 'Gothic' is a word with a broad range of cultural literacies. Accordingly, one might expect that Australian Gothic Cinema is a cultural entity that would be clearly intersected by these literacies. This is, however, not entirely the case. A somewhat peculiar collection of Australian films has been retrospectively gathered under the umbrella of 'Australian Gothic', while bearing little apparent similarity to those texts more commonly held as indicative of the Gothic aesthetic. Although a well-established style in literature and popular culture, the Gothic presence in Australian Cinema is not 'typical', containing very few (if any) examples of such cliches.

Heidi Kaye offers a useful perspective on the history of Gothic film, prefacing her investigation by remarking that Gothic film is inherently difficult to explain, as 'Gothic elements have crept into filmic genres from science fiction to film noir and from thriller to comedy'. …


Article excerpt

From the perspective of the fifth-century Greeks the Peloponnesian War was legitimately perceived as a world war, causing enormous destruction of life and property, intensifying factional and class hostility, and dividing the Greek states internally and destabilizing their relationship to one another, which ultimately weakened their capacity to resist conquest from outside. It also reversed the tendency toward the growth of democracy. When Athens was powerful and successful, its democratic constitution had a magnetic effect on other states, but its defeat was decisive in the political development of Greece, sending it in the direction of oligarchy.

The Peloponnesian War was also a conflict of unprecedented brutality, violating even the harsh code that had previously governed Greek warfare and breaking through the thin line that separates civilization from savagery. Anger, frustration, and the desire for vengeance increased as the fighting dragged on, resulting in a progression of atrocities that included maiming and killing captured opponents; throwing them into pits to die of thirst, starvation, and exposure; and hurling them into the sea to drown. Bands of marauders murdered innocent children. Entire cities were destroyed, their men killed, their women and children sold as slaves. …


The first in a series of exercises designed to teach you more about regular expressions, written by a guy who got partway through writing a regex book.

But first, a word about tools. It's a lot easier to use a tool to do this sort of thing than it is to write code to do it. So, I suggest one of the following:

So, S stands for simple, 1 stands for 1, so this first one is going to be pretty simple.

S1 - Match a Social Security Number

Verify that a string is a social security number of the format ddd-dd-dddd.

Answer and explanation to follow.


Boston Society of Architecture “Research in Architecture Grant” The Secure City: Design and Perception of Public Space Post 9/11

Susan Silberberg was awarded a competitive research grant from the Boston Society of Architects to investigate the design and perception of public space post 9/11.  Terrorist events have caused many cities and the federal government to rethink issues of public accessibility, open space design and perimeter building protection.  This redesign and retrofit of public space to create a secure public realm has prompted responses ranging from organized efforts to identify roles for professionals and win government design contracts, to public outrage at the changes to urban space and the erection of new barriers to accessibility and openness.  Susan Silberberg’s original research seeks to discover and explore the people and forces that are re-shaping the public realm in major cities to provide comprehensive information to design professionals, public officials, and academics about the decision-making processes and the impacts of public realm securitization.  Beginning in Boston in 2006, her research continues to seek answers to the following questions:

  • What specific motives, funding and regulations have prompted secure urban design efforts?
  • Which efforts are coordinated and “designed” and which are ad hoc responses, and why?
  • How do these efforts affect both the physical design of public space and the actual use?  What are changes in the public perceptions of these retrofitted secure urban spaces?
  • Who is involved in securitization and what roles do they play within the private and public sectors?

Through field work, scholarly research, interviews and case study assessment, Susan Silberberg’s research team continues to explore these questions in Boston and New York City.  Findings from her Boston research are presented in ““Pretext securitization of Boston’s public realm after 9/11: Motives, actors and a role for planners” in Policing Cities: Securitization and Regulation in a 21st Century World (Routledge, 2013).


The National Catholic Review
Belief and the bench

Work as a federal prosecutor can require long hours at the office, stressful court situations that drain one’s energy and powers of thinking, and complicated legal problems that require all of one’s mind and judgment. Sometimes the day feels unequally divided: 80 percent for work and 20 percent for the “rest of life.” In that rest of life are the things that really matter: marriage, raising children, family, friendships and activities like home and lawn maintenance, recreation, social occasions and exercise. Somewhere in there are also church, faith and spiritual life.

I know it is not supposed to be that way, that spirituality should not be a separate item on the rest-of-life menu, something to take up like a hobby after work. If active and strong, faith is like character; we take it with us into any situation. It influences how we think and act, whether consciously or not. But as much as I recognize and occasionally pursue the goal of integrating spiritual life into daily work, most of the time I am too busy to think about God or to reflect or pray as the day flies by.

Does this mean that my Catholic faith does not affect my work? I’ve whispered too many “Hail Mary’s” on my way to receive a jury verdict, grappled with ethical issues that required asking for divine guidance, and have thanked God too many times for helping me stay cool when attacked by opposing counsel not to know that faith affects my outlook on life, my values, my approach and attitudes toward the people and problems I encounter as a prosecutor.

Apart from the murmured prayers (or muttered curses) that may erupt during the day, faith’s deeper influence on my work comes from the way fundamental beliefs translate into values and eventually into patterns of conduct. A believing Catholic embraces a tradition with a deep consciousness of God’s presence in the world, particularly in each human person. Seeing God in people is a belief that, for me, translates into the value of humility, a value not often associated with lawyers or prosecutors. In practice, humility means treating each person with equal dignity, deserving of respect.

For a prosecutor, the accused—regardless of how terrible the crime—deserves respect as a person just as much as do the judge, the other lawyers, the jury or the witnesses, agents or police officers. The defendant in the dock is at that moment the least of our brothers or sisters. Ensuring fair treatment and the right to due process is as much the prosecutor’s responsibility as is proving guilt. Respect for human dignity also influences how one treats opposing counsel, witnesses, victims and professional colleagues. Respect and humility involve more than being polite and professional. These fundamental values have given life to many of the ethical standards intended to ensure fairness in criminal trials. Animated by such values, a prosecutor will want to vigorously ensure that any and all evidence (especially evidence that hurts the government’s case) is turned over to the defense as required under criminal discovery rules. Full disclosure of the facts, “warts and all,” follows from an approach that values each person’s dignity.

Judges often say that sentencing is their most difficult task. Sitting in judgment over a fellow human being is an awesome responsibility. So is the responsibility prosecutors have in representing the people’s interests at the time of sentencing. Those interests usually call for punishment, deterrence and protection of the public. When the question is no longer the fairness of the trial but the nature of the crime and the appropriate punishment—that is when it is hardest to see the convicted person as worthy of the same dignity society accords to the judge, the lawyers or others in the courtroom.

Yet as a Catholic I remember that Jesus (though innocent) once stood where that defendant stands, about to be sentenced by Pilate, his prosecutor and judge. Suddenly the values of humility and the equal dignity of the defendant seem to fit at the time of sentencing as well.

The high pressure, deadline-driven job of a federal prosecutor can make one feel that there is no time for the peaceful, meditative practices of the spiritual life. And the competitive nature of the adversarial judicial process can sometimes enshrine “winning” as the highest goal. Faith illuminates different values, however, like acting with humility and seeing God in others.

Seeing God in people is a belief that for me translates into the value of humility.

Terrence Berg is a federal prosecutor in Detroit, Mich. The views expressed in this article are those of the author and are not intended to express the views of the U.S. Department of Justice.

David Smith | 3/6/2011 - 1:25am
Would you say that Jesus received a fair trial?


F-35 fleet grounded after engine crack found

F-35 fleet grounded after engine crack found
FILE - In this Monday, Dec. 17, 2012 photo, Master Sgt. Andrew Ehlers does repairs on an F-16 fighter plane in South Burlington, Vt. (AP Photo/Toby Talbot)
WASHINGTON (AP) - The Pentagon on Friday grounded its fleet of F-35 fighter jets after discovering a cracked engine blade in one plane.

All versions - a total of 51 planes - were grounded Friday pending a more in-depth evaluation of the problem discovered at Edwards. None of the planes have been fielded for combat operations; all are undergoing testing.

A watchdog group, the Project on Government Oversight, said the grounding is not likely to mean a significant delay in the effort to field the stealthy aircraft.

"The F-35 is a huge problem because of its growing, already unaffordable, cost and its gigantically disappointing performance," the group's Winslow Wheeler said. "That performance would be unacceptable even if the aircraft met its far-too-modest requirements, but it is not."


EVENING. Health. PARENTING. Letters.

Q. Our 3-year-old is in day care, and the teacher says she...

April 18, 1994|By Evelyn Petersen, | By Evelyn Petersen

Q. Our 3-year-old is in day care, and the teacher says she uses time-out as a discipline method, having the child sit on a chair for a few minutes when he or she has misbehaved. What do you think of time-out?

A. Time-out can be an effective discipline tool, but only when it is implemented in a developmentally appropriate way. For example, if the child is 2 or 3 and does not understand what he or she has done wrong, sitting in the time-out chair will not teach the child what behavior the adult expects.

First, children need to understand what the adult wants from them and what behavior is not acceptable. They need to know ahead of time that if they behave in ways that are not acceptable, they will need to take time-out to calm down and think about their behavior, returning to play or to the group when they feel sure they can behave appropriately. This kind of thinking can be easily understood by children at age 4 and older, and sometimes can be successfully understood by 3-year-olds.

I believe that time-out is most successful when children are not told to sit in a chair or time-out space for an arbitrary, adult-mandated amount of time. I think it works best when the child has to be responsible for the length of time-out. The child should be able to let the adult know when he or she feels ready to return to play or to the group, and the child should also be able to verbalize what the behavior was that was inappropriate.

Some adults feel that they should set the length of time-out, and often set limits of minutes that roughly match the age of the child, four minutes for a 4-year-old, for example. I feel that this is purely arbitrary and might not make sense. If a 5-year-old can calm himself down and explain clearly what he did that was incorrect and state the correct behavior in two minutes, why do time-out for five minutes?

Like any discipline method, modifications must often be made in time-out to make the method effective for individual children.


home improvement

Question by  ruff (34)

What are some good home decorating ideas to go with a gray sofa?

Answer by  Amom (701)

A grey sofa would especially look nice with a coordinating color in the cool tones, such as red, royal purple, or white. Go to the local paint store, pick out some paint chips, and see which colors will go best with your sofa and then pick out wall color, pillows, drapes, and accessory that best match your choices.

Answer by  Betty0320 (734)

Paint the wall behind the sofa a bold color to offset the bland gray. This is called an accent wall. Use throw pillows, afghans or wall hangings to add texture and color to the room and sofa. Make sure the lighting is appropriate and is not making the sofa look drab. If push comes to shove, reupholster!

Answer by  BillS (50)

Chairs colored red or black would provide contrasting colors, especially if the pieces are leather. Wooden end tables and perhaps a coffee table made of cherrywood or mahogany will add to the effect. Framed pictures or posters with black and gray as dominant colors located wawy from the sofa will also enhance the look of the room.

Answer by  kctaxlady (187)

Start with a sleek gray sofa, add teak tables and white accents for a sophisticated color scheme. For a more modern look, use blonde wood tables with red and yellow toss pillows, lampshades and other accents. If the sofa is more traditional shape, try rich, dark wood with wine and cream accents.

Answer by  racheljh (72)

Brighten up a gray sofa with pillows in brighter colors; blues and deep maroon work well. Choose pillow colors to also pick up colors from other chairs or draperies in the room.

Answer by  Anonymous

I have a new gray sectional, recover?????

You have 50 words left!


I'm in. Chris and I will be lugging our LF stuff, but anyone is welcome; Holga, Hasselblad, Widelux, pinhole, et al.

The KC Union train station has been restored and is an oustanding example of the Art Deco major railroad stations in the US. Just one of the possible subjects. The old KCP&L building downtown is also renowned for its Art Deco architecture. Plenty of red brick buildings with vintage signage if you like that.


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Good Country People character analysis

“Good Country People” The short story, “Good Country People”, written by Flannery O’Connor, is a story that captivates one by usage of symbolism and theme. The story centers on the meaning of being a good person, in the sense of leading a Christian, pious life, worthy of salvation. O’Connor contrasts mindless chatter about “good country people” with questions about the true meaning of religious faith. There is also a class hierarchy formed that includes stereotypes about “good country people” and literal and symbolic meanings of events, objects, and characters. Through exclusive use of the third person narrator, O’Connor’s narrative style poises a tension between the realistic (characters in typical settings performing natural acts) and symbolic (where names, signs and other common objects represent larger issues). She also employs the technique of the epiphany, where a single moment of illumination “awakens” the character and reveals the deeper meanings of the text. O’Connor describes the story’s characters as distorted versions of humanity, and virtually none are sympathetic in the traditional nature of the hero or heroine with whom a reader might identify.
Hulga is the dual dimension main character that goes through a complete change throughout the story. She changes her name to Hulga, an “ugly” name, to reflect her feelings about her injured body and self, as the name is the opposite of her real name “Joy”, as is her personality. The significance of Joy remaining conscious even though terribly injured as a child when “her leg was blasted off” indicates that Joy seems to have rejected her own body by choosing a life of intelligence and of the mind. As with her missing limb, Hulga’s “weak heart” operates as a symbolic as well as literal affliction. Hulga closes her heart just as she rejects her body. Hulga’s mother, Mrs. Hopewell, convinced that Hulga would have “been better without a useless PhD. degree in philosophy”, has no comprehension of the one true meaning of life to her daughter: “Such is after all the strictly scientific approach to Nothing. We know it by wishing to know nothing of Nothing.” This reference is to nihilistic philosophy, which denies the existence of any basis for truth. It rejects belief in concepts such as religion and morality, and generally recognizes no authority.
Manley Pointer, a young misperceived country boy who sells bibles, is an illusion of appearance versus reality. Pointer is so heavily weighted down by his suitcase that he is lopsided and has to “brace himself to prevent collapsing”. This heaviness foreshadows a quality of falsehood that one carries that makes their mind, soul, and body heavy. Like Joy/Hulga, he is physically awkward, suggesting a lack of balance. His name, also a symbol, can be interpreted as humorous, sexual, and ironic as his name was an invention of his mind. Misplaced faith in appearances is central to the themes of this story. Appearance and deception conflict with reality and truth, as Pointer assures Mrs. Hopewell that he is like her and can exchange generalizations about “good country people” as readily as Mrs. Freeman. The biblical quotation, Matthew 10:30, foreshadows the story’s ironic ending. Mrs. Hopewell prides herself in not being taken for a fool, but this boy seemed “so sincere, so genuine and earnest.” In a way, both literally and ironically, Pointer is a missionary, though not as Mrs. Hopewell believes. Furthermore, the seduction of Glynese foreshadows Pointer’s seduction of Hulga. Pointer plays up to each person’s expectations. Everyone thinks he is young, innocent, and wholesome, leading to Hulga’s fantasy about seducing him and having to deal with his remorse. But, despite her advanced academic degree, Hulga’s misguided thinking is apparent in her fantasy that she will mercilessly seduce the boy, and in her “dabbing of Vapex” (a pungent and medicinal ointment) on her collar instead of perfume.

    More on Good Country People character analysis...

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Cultural reproduction

Cultural reproduction is the transmission of existing cultural values and norms from generation to generation. Cultural reproduction refers to the mechanisms by which continuity of cultural experience is sustained across time. Cultural reproduction often results in social reproduction, or the process of transferring aspects of society (such as class) from generation to generation.

  1. Groups of people, notably social classes, act to reproduce the existing social structure to preserve their advantage

Reproduction as it is applied to culture, is the process by which aspects of culture are passed on from person to person or from society to society. There are a number of different ways in which this has happened. Historically, people have moved from different countries taking with them certain cultural norms and traditions. For centuries cultural reproduction has occurred in a profound way through a hidden agenda. Cultures transmit aspects of behavior which individuals learn in an informal way while they are out of the home.

Examples of Cultural Reproduction

An example of cultural reproduction is enculturation which one sociologist describes as "a partly conscious and partly unconscious learning experience when the older generation invites, induces, and compels the younger generation to adopt traditional ways of thinking and behaving". Although, Enculturation in many ways duplicates and copies many similar norms and traditions of previous generations it does not always replicate everything that is the same. Enculturation is the reason why, for example, people born in the U.S. drive on the right side of the road while people in England drive on the left. Parents and educators continue to be two of the most influential enculturating forces of cultural reproduction.

Another example of cultural reproduction is diffusion. Diffusion, the act of spreading out occurs when dependable cultural behaviors or norms are passed from one society to another. Diffusion is the reason why U.S. citizens enjoy the Japanese delicacy Sushi, and make everyday use of words like “boutique”, a common French word.

The concept of cultural reproduction was first developed by the French sociologist and cultural theorist Pierre Bourdieu in the early 1970's. Initially, Bourdieu’s work was on education in a modern society. He believed that the education system was used solely to ‘reproduce’ the culture of the dominant class in order for the dominant class to continue to hold and release power. Bourdieu’s ideas were similar to those of Louis Althusser's notion of ‘ideological state apparatuses’ which had emerged around the same time. He began to study socialization and how dominant culture and certain norms and traditions effected many social relations.

One of Pierre Bourdieu and Jean-Claude Passeron main concepts on Cultural Reproduction was in their book Cultural Reproduction and Social Reproduction. Bourdieu’s main focus was the structural reproduction of disadvantages and inequalities that are caused by cultural reproduction. According to Bourdieu, inequalities are recycled through the education system and other social institutions . Bourdieu believed that the prosperous and affluent societies of the west were becoming the “cultural capital”. High social class, familiarity with the bourgeois culture and educational credentials determined one’s life chances. It was biased towards those of higher social class and aided in conserving social hierarchies. This system concealed and neglected individual talent and academic meritocracy. Bourdieu demonstrated most of his known theories in his books The Inheritors and Reproduction in Education, Culture and Society. Both books established him as a progenitor of “Reproduction theory”

Bourdieu also pioneered many procedural frameworks and terminologies such as cultural, social, and symbolic capital, and the concepts of habitus field, and symbolic violence. Bourdieu's work emphasized the role of practice and embodiment in social dynamics. Bourdieu’s theories build upon the conjectures of Ludwig Wittgenstein, Maurice Merleau-Ponty, Edmund Husserl, Georges Canguilhem, Karl Marx, Gaston Bachelard, Max Weber, Emile Durkheim, and Norbert Elias, among others.

Debate Over Cultural Reproduction

Bourdieu is best known for his theoretical principles, conceptual devices and political intentions. He theorizes that what is taught to younger generations is dependent on the varying degrees of social, economic, and cultural capital. Those cultures have gained cultural capital and are considered the dominant group among the rest. However, in order to acquire cultural capital one must undergo indiscernable learning and these cultural norm must be used in the earliest days of life.

Through Cultural Reproduction, only those members of the dominant culture can acquire knowledge in relation to the way it is taught from within this cultural system. Therefore, those who are not members of the dominant culture are at a disadvantage to receive cultural information, and therefore will remain at a disadvantage. Capitalist societies depend on a stratified social system, where the working class has an education suited for manual labor: leveling out such inequalities would break down the system. Therefore, schools in capitalist societies require a method of stratification, and often choose to do so in a way in which the dominant culture will not lose its hegemony. One method of maintaining this stratification is through cultural reproduction.

Bourdieu Central Issues

Bourdieu's sociological work was dominated by an analysis of the mechanisms of reproduction of social hierarchies. In opposition to Marxist analyses, Bourdieu criticized the premises given to the economic factors, and stressed that the capacity of social actors to actively impose and engage their cultural productions and symbolic systems plays an essential role in the reproduction of social structures of domination. What Bourdieu called symbolic violence (the capacity to ensure that the unpredictability of the social order is ignored—-or misrecognized as natural—-and thus to ensure the legitimacy of social structures) plays an essential part in his sociological analysis.

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..never odd or even..

Thoughts on computer science, maths, languages.

Rearranging equations using a zipper

Whilst experimenting with some ideas for a project, I realised I needed a quick piece of code to rearrange equations (defined in terms of +, *, -, and /) in AST form, e.g., given an AST for the equation x = y + 3, rearrange to get y = x - 3.

I realised that equations can be formulated as zippers over an AST, where operations for navigating the zipper essentially rearrange the equation. I thought this was quite neat, so I thought I would show the technique here. The code is in simple Haskell.

I’ll show the construction for a simple arithmetic calculus with the following AST data type of terms:

data Term = Add Term Term
          | Mul Term Term
          | Div Term Term
          | Sub Term Term
          | Neg Term
          | Var String
          | Const Integer

with some standard pretty printing code:

instance Show Term where
    show (Add t1 t2) = (show' t1) ++ " + " ++ (show' t2)
    show (Mul t1 t2) = (show' t1) ++ " * " ++ (show' t2)
    show (Sub t1 t2) = (show' t1) ++ " - " ++ (show' t2)
    show (Div t1 t2) = (show' t1) ++ " / " ++ (show' t2)
    show (Neg t) = "-" ++ (show' t)
    show (Var v) = v
    show (Const n) = show n

where show' is a helper to minimise brackets e.g. pretty printing “-(v)” as “-v”.

show' :: Term -> String
show' (Var v) = v
show' (Const n) = show n
show' t@(Neg (Var v)) = show t
show' t@(Neg (Const n)) = show t
show' t = "(" ++ show t ++ ")"

Equations can be defined as pairs of terms, i.e., ‘T1 = T2′ where T1 and T2 are both represented by values of Term. However, instead, I’m going to represent equations via a zipper.

Zippers (described beautifully in the paper by Huet) represent values that have some subvalue “in focus”. The position of the focus can then be shifted through the value, refocussing on different parts. This is encoded by pairing a focal subvalue with a path to this focus, which records the rest of the value that is not in focus. For equations, the zipper type pairs a focus Term (which we’ll think of as the left-hand side of the equation) with a path (which we’ll think of as the right-hand side of the equation).

data Equation = Eq Term Path

Paths give a sequence of direction markers, essentially providing an address to the term in focus, starting from the root, where each marker is accompanied with the label of the parent node and the subtree of the branch not taken, i.e., a path going left is paired with the right subtree (which is not on the path to the focus).

data Path = Top (Either Integer String)  -- At top: constant or variable
           | Bin Op                -- OR in a binary operation Op,
                 Dir               --    in either left (L) or right (R) branch
                 Term              --    with the untaken branch
                 Path              --    and the rest of the equation
           | N Path                -- OR in the unary negation operation

data Dir = L | R
data Op = A | M | D | S | So | Do

The Op type gives tags for every operation, as well as additional tags So and Do which represent sub and divide but with arguments flipped. This is used to get an isomorphism between the operations that zip “up” and “down” the equation zipper, refocussing on subterms.

A useful helper maps tags to their operations:

opToTerm :: Op -> (Term -> Term -> Term)
opToTerm A = Add
opToTerm M = Mul
opToTerm D = Div
opToTerm S = Sub
opToTerm So = (\x -> \y -> Sub y x)
opToTerm Do = (\x -> \y -> Div y x)

Equations are pretty printed as follows:

instance Show Path where
    show p = show . pathToTerm $ p
instance Show Equation where
    show (Eq t p) = (show t) ++ " = " ++ (show p)

where pathToTerm converts paths to terms:

pathToTerm :: Path -> Term
pathToTerm (Top (Left c)) = Const c
pathToTerm (Top (Right v))= Var v
pathToTerm (Bin op L t p) = (opToTerm op) (pathToTerm p) t
pathToTerm (Bin op R t p) = (opToTerm op) t (pathToTerm p)
pathToTerm (N p)          = Neg (pathToTerm p)

Now onto the zipper operations which providing rebalancing of the equation. Equations are zipped-down by left and right, which for a binary operation focus on either the left or right argument respectively, for unary negation focus on the single argument, and for constants or variables does nothing. When going left or right, the equations are rebalanced with their inverse arithmetic operations (show in the comments here):

left (Eq (Var s) p)     = Eq (Var s) p
left (Eq (Const n) p)   = Eq (Const n) p
left (Eq (Add t1 t2) p) = Eq t1 (Bin S L t2 p)   -- t1 + t2 = p  -> t1 = p - t2
left (Eq (Mul t1 t2) p) = Eq t1 (Bin D L t2 p)   -- t1 * t2 = p  -> t1 = p / t2
left (Eq (Div t1 t2) p) = Eq t1 (Bin M L t2 p)   -- t1 / t2 = p  -> t1 = p * t2
left (Eq (Sub t1 t2) p) = Eq t1 (Bin A L t2 p)   -- t1 - t2 = p  -> t1 = p + t2
left (Eq (Neg t) p)     = Eq t (N p)             -- -t = p       -> t = -p

right (Eq (Var s) p)     = Eq (Var s) p
right (Eq (Const n) p)   = Eq (Const n) p
right (Eq (Add t1 t2) p) = Eq t2 (Bin So R t1 p)  -- t1 + t2 = p -> t2 = p - t1
right (Eq (Mul t1 t2) p) = Eq t2 (Bin Do R t1 p)  -- t1 * t2 = p -> t2 = p / t1
right (Eq (Div t1 t2) p) = Eq t2 (Bin D R t1 p)   -- t1 / t2 = p -> t2 = t1 / p
right (Eq (Sub t1 t2) p) = Eq t2 (Bin S R t1 p)   -- t1 - t2 = p -> t2 = t1 - p
right (Eq (Neg t) p)     = Eq t (N p)

In both left and right, Add and Mul become subtraction and dividing, but in right in order for the the zipping-up operation to be the inverse, subtraction and division are represented using the flipped So and Do markers.

Equations are zipped-up by up, which unrolls one step of the path and reforms the term on the left-hand side from that on the right. This is the inverse of left and right:

up (Eq t1 (Top a))        = Eq t1 (Top a)
up (Eq t1 (Bin A L t2 p)) = Eq (Sub t1 t2) p -- t1 = t2 + p -> t1 - t2 = p
up (Eq t1 (Bin M L t2 p)) = Eq (Div t1 t2) p -- t1 = t2 * p -> t1 / t2 = p
up (Eq t1 (Bin D L t2 p)) = Eq (Mul t1 t2) p -- t1 = p / t2 -> t1 * t2 = p
up (Eq t1 (Bin S L t2 p)) = Eq (Add t1 t2) p -- t1 = p - t2 -> t1 + t2 = p

up (Eq t1 (Bin So R t2 p)) = Eq (Add t2 t1) p -- t1 = p - t2 -> t2 + t1 = p
up (Eq t1 (Bin Do R t2 p)) = Eq (Mul t2 t1) p -- t1 = p / t2 -> t2 * t1 = p
up (Eq t1 (Bin D R t2 p))  = Eq (Div t2 t1) p -- t1 = t2 / p -> t2 / t1 = p
up (Eq t1 (Bin S R t2 p))  = Eq (Sub t2 t1) p -- t1 = t2 - p -> t2 - t1 = p

up (Eq t1 (N p))           = Eq (Neg t1) p    -- t1 = -p     -> -t1 = p

And that’s it! Here is an example of its use from GHCi.

foo = Eq (Sub (Mul (Add (Var "x") (Var "y")) (Add (Var "x")
           (Const 1))) (Const 1)) (Top (Left 0))

*Main> foo
((x + y) * (x + 1)) - 1 = 0

*Main> left $ foo
(x + y) * (x + 1) = 0 + 1

*Main> right . left $ foo
x + 1 = (0 + 1) / (x + y)

*Main> left . right . left $ foo
x = ((0 + 1) / (x + y)) - 1

*Main> up . left . right . left $ foo

*Main> up . up . left . right . left $ foo

*Main> up . up . up . left . right . left $ foo

It is straightforward to prove that: up . left $ x = x (when left x is not equal to x) and up . right $ x = x(when right x is not equal to x).

Note, I am simply rebalancing the syntax of equations: this technique does not help if you have multiple uses of a variable and you want to solve the question for a particular variable, e.g. y = x + 1/(3x), or quadratics.

Here’s a concluding thought. The navigation operations left, right, and up essentially apply the inverse of the operation in focus to each side of the equation. We could therefore reformulate the navigation operations in terms of any group: given a term L ⊕ R under focus where is the binary operation of a group with inverse operation -1, then navigating left applies ⊕ R-1 to both sides and navigating right applies ⊕ L-1. However, in this blog post there is a slight difference: navigating applies the inverse to both sides and then reduces the term of the left-hand side using the group axioms X ⊕ X-1 = I (where I is the identity element of the group) and X ⊕ I = X such that the term does not grow larger and larger with inverses.

I wonder if there are other applications, which have a group structure (or number of interacting groups), for which the above zipper approach would be useful?

Automatic SIMD Vectorization for Haskell and ICFP 2013

I had a great time at ICFP 2013 this year where I presented my paper “Automatic SIMD Vectorization for Haskell”, which was joint work with Leaf Petersen and Neal Glew of Intel Labs. The full paper and slides are available online. Our paper details the vectorization process in the Intel Labs Haskell Research Compiler (HRC) which gets decent speedups on numerical code (between 2-7x on 256-bit vector registers). It was nice to be able to talk about HRC and share the results. Paul (Hai) Liu also gave a talk at the Haskell Symposium which has more details about HRC than the vectorization paper (see the paper here with Neal Glew, Leaf Petersen, and Todd Anderson). Hopefully there will be a public release of HRC in future.

Still more to do

It’s been exciting to see the performance gains in compiled functional code over the last few years, and its encouraging to see that there is still much more we can do and explore. HRC outperforms GHC on roughly 50% of the benchmarks, showing some interesting trade-offs going on in the two compilers. HRC is particularly good at compiling high-throughput numerical code, thanks to various strictness/unboxing optimisations (and the vectorizer), but there is still more to be done.

Don’t throw away information about your programs

One thing I emphasized in my talk was the importance of keeping, not throwing away, the information encoded in our programs as we progress through the compiler stack. In the HRC vectorizer project, Haskell’s Data.Vector library was modified to distinguish between mutable array operations and “initializing writes”, a property which then gets encoded directly in HRC’s intermediate representation. This makes vectorization discovery much easier. We aim to preserve as much effect information around as possible in the IR from the original Haskell source.

This connected nicely with something Ben Lippmeier emphasised in his Haskell Symposium paper this year (“Data Flow Fusion with Series Expressions in Haskell“, joint with Manuel Chakravarty, Gabriele Keller and Amos Robinson). They provide a combinator library for first-order non-recursive dataflow computations which is guaranteed to be optimised using flow fusion (outperforming current stream fusion techniques). The important point Ben made is that, if your program fits the pattern, this optimisation is guaranteed. As well as being good for the compiler, this provides an obvious cost model for the user (no more games trying to coax the compiler into optimising in a particular way).

This is something that I have explored in the Ypnos array language, where the syntax is restricted to give (fairly strong) language invariants that guarantee parallelism and various optimisations, without undecidable analyses. The idea is to make static as much effect and coeffect (context dependence) information as possible. In Ypnos, this was so successful that I was able to encode the Ypnos’ language invariant of no out-of-bounds array access directly in Haskell’s type system (shown in the DSL’11 paper; this concept was also discussed briefly in my short language design essay).

This is a big selling point for DSLs in general: restrict a language such that various program properties are statically decidable, facilitating verification and optimisation.

Ypnos has actually had some more development in the past year, so if things progress further, there may be some new results to report on. I hope to be posting again soon about more research, including the ongoing work with Tomas Petricek on coeffect systems, and various other things I have been playing with. – D

The Four Rs of Programming Language Design (revisited)

Subcategories & “Exofunctors” in Haskell

The Hask category

Subcategories as type classes

      Eq a => a

Functors in Haskell

class Functor f where

Using Set.map to define an instance of the Functor class for Set causes a type error:

instance Functor Set where
   fmap = Data.Set.map

    No instances for (Ord b, Ord a)
      arising from a use of `Data.Set.map'
    In the expression: Data.Set.map
    In an equation for `fmap': fmap = Data.Set.map
    In the instance declaration for `Functor Set'

The type error occurs as the signature for fmap has no constraints, or the empty (always true) constraint, whereas Set.map has Ord constraints. A mismatch occurs and a type error is produced.

The type error is however well justified from a mathematical perspective.

Haskell functors are not functors, but endofunctors

The Set data type is not an endofunctor; it is a functor which maps from the Ord-subcategory of Hask to Hask. Thus Set :: OrdHask. The class constraints on the element types in Set.map declare the subcategory of Set functor to which the morphisms belong.

Type class of exofunctors

{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE TypeFamilies #-}

class ExoFunctor f where
   type SubCat f x :: Constraint

We can now define the following instance for Set:

instance ExoFunctor Set where
   type SubCat Set x = Ord x
   fmap = Set.map

instance ExoFunctor [] where
    type SubCat [] a = ()
    fmap = map

Conclusion (implementational restrictions = subcategories)

Constraint kinds in Haskell, finally bringing us constraint families

class Expr sem where
    constant :: a -> sem a

data E a = E {eval :: a}

instance Expr E where
     constant c = E c

    No instance for (Num a)
      arising from a use of `+'

class Expr sem where
    constraint Pre sem a

instance Expr E where
    constraint Pre E a = Num a
    ... -- methods as before

We could add some further instances:

data P a = P {prettyP :: String}

instance Expr P where
    constraint Pre P a = Show a
    constant c = P (show c)

"1 + 2"

Show :: * -> Constraint

~ :: * -> * -> Constraint

i.e. it takes two types and returns a constraint.

type ShowNum a = (Num a, Show a)

class Expr sem where
    type Pre sem a :: Constraint

instance Expr E where
    type Pre E a = Num a

The constraint kinds extension can be turned on via the pragma:

{-# LANGUAGE ConstraintKinds #-}

submission if you can’t wait!

, [author’s copy with corrections] [On SpringerLink]

The four “R”s of programming language design

Because I have some serious work to do for an impending deadline I have become particularly good at inventing ways to not work that I can convince myself are “worthwhile”. To this end I have decided to post on my (dead) blog, which I am planning to revive with at least monthly posts.

Last year the Cambridge Computer Lab started an informal lecture course taught by PhD students aimed at final year undergraduates and MPhil students with the rough aim of providing lecturing experience to PhD students, and for disseminating more ideas from research to undergrads/MPhils/each other. In my group, the CPRG (Cambridge Programming Research Group), part of the bigger PLS (Programming, Logic, and Semantics Group), four of us decided to do a mini-series about aspects of programming language design. The slides/notes from our lectures can be found here on the dates of May 10th, 11th, 14th, and 24th.

To bind the mini-series together we prepared an informal, general summary of the ideas contained within which concludes with the summary:

The development of programming languages, and abstraction away from
machine code, has greatly aided software development. Programming lan-
guages are a conduit between man and machine, with much of programming
language research aiming to improve this interaction and to help us better
express our ideas. We can attempt to improve languages for ease of reading,
ease of writing, and ease of reasoning, and improve our evaluation systems
to use less resources (whether it be processor time, memory, power, etc.)
whilst still providing a predictable system. Such facets of programming
language design are often non-orthogonal, thus a language designer must
trade-off certain improvements for others. Often, a motivating application
domain or purpose can help distill which features of a language are most
important. This lecture series should give some food for thought in various
areas of general programming and programming language design.

From which I offered the following general slogan:

The four “R”s that programming language design must improve of programs: reading, ‘riting, reasoning, and running.

A bit of a generalisation perhaps, but hopefully a useful “elevator-pitch” slogan to get more people thinking about programming language design, and with a bit of humour (see The three Rs).

Paper: Haskell Type Constraints Unleashed

[draft pdf submitted to FLOPS 2010]

Paper: Ypnos, Declarative Parallel Structured Grid Programming

Max Bolingbroke, Alan Mycroft, and I have written a paper on a new DSL for programming structured grid computations with the view to parallelisation, called Ypnos, submitted to DAMP ’10]

Any feedback is welcome.

Talk: @BCTCS’09 “Lucian: Dataflow and Object Orientation”

Slides from my BCTCS talk entitled Lucian: Dataflow and Object Orientation:

BCTCS ’09 was held at Warwick University- the university that I studied for my undergraduate degree at. I enjoyed the conference particularly, as I got to spend time with Steve Matthews and Sara Kalvala (my undergraduate project supervisors from my 3rd and 4th years), old friends from my undergraduate days, new friends from other universities, and also Bill Wadge, co-creator of Lucid, who was invited to speak at BCTCS ’09 all the way from Victoria, Canada.

If you have ever had a conversation with me about computer science you will know I have a particular proclivity for the Lucid programming language, so getting to chat about all things Lucid for a few days was great fun. Bill supervised Steve back when Bill was at Warwick, in the early days of Lucid. The quip is that Bill is my grandsupervisor.
The Lucian language is my own object-oriented hybrid of Lucid. I started Lucian as my 3rd year project and dissertation- quite some time ago now. The ideas developed further after discussions with Bill back in 2007, resulting in Steve and I publishing a paper which came out in 2008. In January 2009, with the BCTCS looming, I thought it would be fitting to talk about Lucian at BCTCS, due to Bill and Steve being present, and BCTCS being held at Warwick, the crucible of Lucid’s youth. So I revisited Lucian and discovered that there was much more to say than was originally conveyed in the paper. I mulled Lucian over last term and have since revised the language and have had some further thoughts about its semantics.

The Koch Snowflake

This post has been imported from my old blog.

I mentioned a couple of weeks ago I was going to write a post about a certain fractal. Now I have finally gotten round to writing something it has come at a very appropriate time as Britain has seen an unusual amount of snow recently. Sadly all of that snow has melted now. I am going to briefly introduce the Koch Snowflake (also known as the Koch Island, or Koch Star) which is a fractal with a very simple construction. I will first informally describe a geometrical construction of the fractal and will then show some of its properties, particularly the property that the fractal has an infinite length enclosing a finite area.

The base case of the construction is an equilateral triangle. For each successive iteration the construction proceeds as follows:

  • Divide each edge of the polygon (say of length a) into three equal segments of length a/3.
  • Replace the middle segment with an equilateral triangle of side a/3.
  • Remove the base edge of the new equilateral triangle to form a continuous curve with other line segments.

Thus each edge is transformed as such:

The first 5 iterations look like:

Two properties of this fractal may seem paradoxical at first but are easily shown. I will show the derivations here for the interested without skipping too many steps.
For an infinite number of iterations the perimeter of the fractal (the length of all the edges) tends to infinity whilst the area enclosed remains finite.

Infinite Perimeter
First consider the number of edges for an infinite number of iterations. Initially the number of edges is 3, each iteration transforms a single edge into 4 edges (see above), thus the series of the edge count is: 3, 12, 48, …. The general form is:

Starting from an edge length of a each iteration divides the edge length by 3. The following defines the edge length for iteration n and from this calculates the perimeter for iteration n. The limit as n tends to infinity is found, showing that the
perimeter is infinite.

Thus it is easy to see that the perimeter length is infinite through standard results on limits.

Finite Area
The area calculation is a little bit more involved. The result can be seen on Mathworld or Wikipedia but a full derivation isn’t given, so I show my derivation here for the interested.

The area of the n-th iteration of the Koch snowflake is the area of the base triangle + the area of the new, smaller, triangles added to each edge.
From the above length calculations and construction we know that each iteration of the construction divides the length of the edges by three. First consider the relationship between the area of a triangle of edge length a and a triangle of edge length a/3

Unsurprisingly we see that dividing the edge length by 3 divides the area by 9. At each iteration we add new equilateral triangles to each edge, a ninth of the area of the previous iteration’s triangles.
We formulate this as a summation of base case A0 plus the next n-1 iterations where the triangle area at each stage is A0 divided by 32n or 9n (successive divisions of the area by 9). The number of edges is defined by the previous iterations number of edges 3 * 4n-1, thus at the n-th iteration we need to add this number of triangles to the snowflake.

Thus the area is finite at 8/5 times the area of the base equilateral triangle.

So the Koch snowflake construction has been introduced and it has been shown relatively easily that the area of a Koch snowflake tends to a finite limit of 8/5 times the base case area (5) and that the length of perimeter tends to infinity (4). Next time I will probably talk a bit about the fractal dimension of the Koch snowflake and also show an interesting problem that uses the Koch snowflake.

As a last note, following on from the blog post I made about the Python turtle library, a turtle program of the Koch snowflake for Python can be downloaded here.

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The Case for Pre-Funding Social Security

Article excerpt

Why 'personal' or 'private' accounts could save the system.

Social security has been one of the most successful government programs in our nation's history. Unfortunately, the basic financial structure of Social security, designed during the depths of the Great Depression, is not well equipped to handle the substantial demographic changes that are under way in the United States. As a result, Social security simply cannot afford to pay currently scheduled benefits in the coming decades without imposing an ever-larger tax burden on younger workers. In the face of this demographic and financial reality, "doing nothing" is simply not a viable policy option. Social security must change if it is to be made financially secure.

This article outlines the basic reasons that the Social security system is in long-run financial distress and discusses the policy options namely tax increases or benefit cuts-available for closing the financial shortfalls within the confines of the existing system. "Pre-funding" Social security-that is, saving more today in order to reduce the burden on future generations emerges as the most sensible way to proceed, with personal retirement accounts (PRAS) constituting a mechanism for saving that is superior to the current system's reliance on "trust funds." Indeed, much of the current opposition to such accounts is based on misconceptions about PEAS as part of a reformed Social security system.

The U.S. Social security system is not a savings program. Rather, it is an income transfer system that taxes today's workers to pay benefits for today's retirees and other beneficiaries. Economists call such a financial structure a "pay-as-you-go" or "unfunded" system. This is in sharp contrast to die pre-funded nature of most private-sector pension plans in which the money contributed to a worker's pension is invested in real financial assets (e.g., stocks or bonds) that are then used to pay benefits when the worker begins receiving benefits. In economic terms, the primary disadvantage of a "pay-as-you-go" system relative to a pre-funded system is that it reduces national saving, reduces economic growth, and therefore shrinks the size of the economic pie (Feldstein, 1974).

Despite its economic disadvantages, an unfunded, pay-as-you-go system can still work reasonably well when there are a large number of workers paying taxes to support each beneficiary. Back in 1950, for example, there were sixteen workers paying taxes to support each Social security beneficiary. At that time, a payroll tax rate of only 3 percent was sufficient to support the expenditures of the entire Social security program. As the Social security system has expanded and matured, however, the ratio of workers to retirees has fallen substantially, as indicated in Figure i. Today there are only 3.3 workers to support each beneficiary. As a result of population aging, this ratio will fall to just 2 within a generation.1

To put these numbers into perspective, consider the following example. When there are sixteen workers per retiree, as was the case in 1950, then for every $100 that the government pays to the average Social security beneficiary, each worker must pay a tax of $6.25. When the worker-to-beneficiary ratio falls to 3.3, as it stands today, each worker must pay over $30 in taxes to provide a $100 benefit. As this ratio falls to 2, the tax must rise to $50 per worker. Simple mathematics dictates that as the ratio of workers-to-beneficiaries declines, Social security must either raise taxes or reduce benefits in order to keep the system in annual fiscal balance.

While this example is highly stylized, the lesson is very real. Today, employees and employers pay a combined 12.4 percent in Social Security taxes on die first $87,900 in earnings. These taxes, combined with a much smaller amount of revenue obtained from personal income taxation on some Social security benefits, raised approximately $470 billion in 2003. …


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Svenja Kobabe, Dirk Wagner, Eva-Maria Pfeiffer
DOI: http://dx.doi.org/10.1016/j.femsec.2004.05.003 13-23 First published online: 1 October 2004

The bacterial community composition of the active layer (0–45 cm) of a permafrost-affected tundra soil was analysed by fluorescence in situ hybridisation (FISH). Arctic tundra soils contain large amounts of organic carbon, accumulated in thick soil layers and are known as a major sink of atmospheric CO2. These soils are totally frozen throughout the year and only a thin active layer is unfrozen and shows biological activity during the short summer. To improve the understanding of how the carbon fluxes in the active layer are controlled, detailed analysis of composition, functionality and interaction of soil microorganisms was done. The FISH analyses of the active layer showed large variations in absolute cell numbers and in the composition of the active microbial community between the different horizons, which is caused by the different environmental conditions (e.g., soil temperature, amount of organic matter, aeration) in this vertically structured ecosystem. Universal protein stain 5-(4,6-dichlorotriazin-2-yl)aminofluorescein (DTAF) showed an exponential decrease of total cell counts from the top to the bottom of the active layer (2.3 × 109–1.2 × 108 cells per gram dry soil). Using FISH, up to 59% of the DTAF-detected cells could be detected in the surface horizon, and up to 84% of these FISH-detected cells could be affiliated to a known phylogenetic group. The amount of FISH-detectable cells decreased with increasing depth and so did the diversity of ascertained phylogenetic groups.

  • Fluorescence in situ hybridisation
  • Community composition
  • Active layer

1 Introduction

Arctic tundra soils contain large amounts of organic carbon, accumulated in thick layers of soil organic matter [1,2] and are known as a major sink of atmospheric CO2 during the Holocene [3,4]. The reason for the accumulation of organic material is a reduced microbial decomposition of organic matter due to the extreme climatic conditions. Generally, this decomposition is slow and incomplete with high moisture and low temperature [5]. Arctic tundra soils are totally frozen throughout the year and only a thin active layer is non-frozen and shows biological activity during the short summer. In this extreme environment microorganisms have to be capable of withstanding low temperature and repeated freezing–thawing cycles. Due to the underlying ice shield large part of the soils is waterlogged and decomposition of organic matter takes place under anaerobic conditions. The final step in the process of anoxic decomposition of complex organic matter is methanogenesis. Therefore, tundra soils are one of the most important sources in the budget of atmospheric methane (CH4), which is the second significant greenhouse gas after carbon dioxide [6]. Tundra wetlands are estimated to emit between 20 and 40 Tg yr−1 CH4[7]. It accounts for 20% of global methane emission [8].

The large carbon pool in the northern latitudes together with a predicted climate warming [9] leads to speculations about a possible feedback effect on global climate changes by increased decomposition of organic matter and possible increased methane emission [9,10]. For a better prediction of how such changes in environmental conditions may affect the carbon pool, a detailed knowledge of composition, functionality and interaction of microorganisms involved in the carbon cycle is important.

In general, the number, diversity, and activity of soil organisms are influenced by soil organic matter properties (e.g., content, availability), soil texture, pH, moisture, temperature, aeration, and other factors [11]. Soil is a heterogeneous environment and soil aggregates, soil pores, and root environments (rhizosphere) provide numerous niches for different soil microbial communities. Because of the complex vertical structure of the soil and the physical and chemical differences between the horizons it is not possible to deduce a subsurface community structure from analysing surface soils. Deeper layers may contain microbial communities, which are specialised for their environment and differ from surface communities [12,13].

Cultivation-based methods usually fail to give a complete picture of the composition of complex communities [1416]. Molecular, i.e., cultivation-independent techniques could give complementary insight into complex environments. The FISH method is based on the detection of rRNA. Because the rRNA content is associated with the metabolic state of the organism [1719], FISH results are influenced by the activity of the cells [2025]. Although FISH signals cannot directly be translated to cell activity status it is approved that there is a positive relationship between bacterial metabolic rates and the capacity to detect the active cells [26]. In ecological studies it could be an advantage to describe the composition of the more active, and hence ecologically relevant part of the community instead of the total existent population.

The aim of this study was to characterise the population of active microorganisms in the whole active layer of a permafrost-affected soil, by using FISH without previous cultivation.

2 Materials and methods

2.1 Study site and soil conditions

The investigation site is located on Samoylov (N 72°22, E 126°28), a typical island of the central part of the Lena Delta, Siberia. Detailed description of the geomorphologic situation of the island and the whole delta was given previously [2729]. With an area of about 32,000 km2, the Lena Delta is the second largest delta in the world. It is situated in the continuous permafrost zone. The mean annual air temperature in the period 2001–2003, measured by a Russian weather station on Stolb Island, which is approximately 8 km away from Samoylov Island, was −11.9 °C; mean annual precipitation in the same period was about 233 mm [30]. The landscape of the delta is dominated by a microrelief of ice-wedge polygons, which develop due to annual freeze–thaw cycles. The soils are totally frozen for at least eight months every year and only a shallow active layer of about 20–50 cm is unfrozen during the summer months. Predominant landscape formations are low-centred polygons where the flat central parts are surrounded by raised rims. The investigated soils in the polygon centres are characterised by a water level near the soil surface, which, together with the cold climate conditions, leads to an accumulation of organic matter and formation of peat layers. The mainly anaerobic decomposition of soil organic matter generates high CH4 production and emission rates from these sites. Mean flux rates of 53.2 ± 8.7 mg CH4 m−2 d−1 were measured for the polygon centres for the period between the end of May and the beginning of September 1999 [27].

The soil in the centre of a typical polygon was described and sampled in August 2001. At this time the thaw depth of the active layer was up to 45 cm with the water table 18 cm below the surface. The vegetation in the polygon centres site was composed of a moss/lichen layer (total coverage 95%) and a vascular plant layer (total coverage 30%). The latter was dominated by the sedge, Carex aquatilis[31]. For soil description and sampling, a vertical soil profile was dug. Four different peaty, sandy loam textured soil horizons were distinguished. They were covered by a horizon consisting of weakly decomposed organic material. Subsamples for physio-chemical soil characteristics and biological analyses were taken in a horizontal way subsequently after the horizons were identified. Samples for biological analyses were placed into 250 ml Nalgene boxes, which were locked with a seal tape to prevent oxygen contamination of the samples. To ensure detailed investigation of the soil, horizons with a thickness of more than 10 cm were subdivided and subsamples were taken. Soil properties (Table 1, Fig. 1) were described according to Schoeneberger et al. [32] and laboratory analyses were done according to Schlichting et al. [33]. The soil was classified as Typic Historthel according to US Soil Taxonomy [34].

View this table:

Selected soil physico-chemical characteristics of the investigated Typic Historthela

HorizonbDepth (cm)Soil textureb (%)Textural classbMunsell colorcRootsbReducing soil conditionsd
A17–2077158Sandy loam10YR 2/1ManyYes
Bg 120–2376186Sandy loam2,5Y 4/4CommonYes
Bg 223–3069265Sandy loam10YR 3/2FewYes
30–3568275Sandy loam10YR 3/2FewYes
Bg 335–4065296Sandy loam10YR 4/2NoneYes
40–4560337Sandy loam10YR 4/2NoneYes
  • aSoil classification was done according to US Soil Taxonomy Soil Survey Staff [34].

  • bClassifications were done according to Schoeneberger et al. [32].

  • cSoil colour determination was done according to the Munsell soil colour charts [72].

  • dReducing soil conditions were detected by using α–α′-Dipyridil test. Soil Survey Staff [34].

Vertical profile of selected soil properties and EUBmix counts relative to total bacterial cell numbers. (a) Average soil temperature in August, (b) N content, (c) C/N ratio, (d) C content, and (e) fraction of TBC detected with probe EUBmix. C and N contents were measured using Vario EL III elemental analyzer (Elementar Analysensysteme, Germany).

The active layer is subject to great temperature variations between the different horizons. Automatic soil temperature measurements were started in 1998 using Thermistor Soil Temperature Probes 107 (Campbell Scientific Ltd.). The temperature sensors were installed in different depths between soil surface and permafrost table [35]. The average, minimum and maximum temperatures in August for three years are given (Table 2). During summer the upper soil horizons had not only a higher average temperature, compared to the deeper horizons. They were also exposed to a strong diurnal fluctuation, decreasing with depth. The minimum winter temperature measured was −37 °C at a depth of 7 cm and increased up to −29 °C at a depth of 42 cm. The upper soil above 23 cm depth was frozen for 8 months, while the deeper horizons were frozen for 9–10 months in the year.

View this table:

August temperatures in different soil depths of the investigated Typic Historthel

Depth (cm)Temperature (°C) in August (avg. min./max.)
  • –, No temperature was determined due to broken temperature sensor.

2.2 Sample preparation for cell counts

Subsamples for cell counts by 5-(4,6-dichlorotriazin-2-yl)aminofluorescein (DTAF) staining and FISH were frozen immediately after sampling and were transported to Germany. After transportation they were thawed at 3 °C. Immediately after thawing subsamples of 1gram were either fixed directly in ethanol (96%) or in a freshly prepared, 4% paraformaldehyde/phosphate-buffered saline (PBS) solution (pH 7.2) for 4 h at 5 °C. The paraformaldehyde-fixed samples were then washed with PBS and stored in ethanol–PBS (1:3) at −20 °C. Before application to slides, we diluted the samples with 0.1% sodium pyrophosphate in distilled water to obtain 100–200 cells per microscopic field of view. The dilution was dispersed by mild sonication with an MS73 probe (Sonopuls HD70; Bandelin, Berlin, Germany) at a setting of 20 for 30 s. Dispersed soil samples were spotted on gelatin-coated (0.1% gelatine, 0.01% KCr(SO4)2) Teflon-laminated slides with ten wells. Twenty μl of fixed and dispersed soil sample were dropped onto each well, allowed to air dry, and dehydrated by serial immersion of the slides in 50%, 80%, and 96% ethanol. The FISH method was used directly in soil smears because extraction of bacterial cells from soil is difficult to perform due to the exclusion of bacteria associated with soil particles [25].

2.3 Non-selective staining of all cells (DTAF staining)

Before the slides were prepared for FISH, they were stained with the universal protein stain DTAF. Freshly prepared stain solution consisted of 2 mg of DTAF dissolved in 10 ml of phosphate buffer (0.05M Na2HPO4 with 0.85% NaCl, pH 9 [36]). The staining procedure was done as described by Bloem et al. [37]. A drop of stain solution was given on each well with dried soil film and incubated for 30 min at room temperature. After staining the slides were washed three times for 20 min each with phosphate buffer (pH 9). Finally they were passed through four water bathes each for a few seconds and air-dried.

2.4 Fluorescence in situ hybridisations and probe description

All oligonucleotide probes used in this study were purchased from Interactiva (Ulm, Germany). They were labelled with the cyanine dyes Cy3 or Cy5. Probes for the domains Bacteria and Archaea and specific probes for different phylogenetic groups of Bacteria were used. All probe sequences, formamide concentrations in hybridisation buffer, NaCl concentrations in washing buffer, and references are summarised in Table 3. For each hybridisation the bacterial probe EUBmix was used together with one specific probe marked with a different dye. Therefore, the target cells of the group specific probes were marked with three different dyes.

View this table:

rRNA-targeted oligonucleotide probes used for hybridisation

ProbeTarget groupSequence (5′–3′) of probeTarget siteaFAb (%)NaClc (mM)Reference
EUB338*Domain BacteriaGCTGCCTCCCGTAGGAGT16S (338)0–3580–900[73]
EUB338 II*Domain BacteriaGCAGCCACCCGTAGGTGT16S (338)0–3580–900[74]
EUB338 III*Domain BacteriaGCTGCCACCCGTAGGTGT16S (338)0–3580–900[74]
NON338Control probe complementary to EUB338ACTCCTACGGGAGGCAGC16S0–3580–900[75]
ARC915Domain ArchaeaGTGCTCCCCCGCCAATTCCT16S (915)20225[39]
ALF968α-subclass of ProteobacteriaGGTAAGGTTCTGCGCGTT16S (968)3580[76]
BET42aβ-subclass of ProteobacteriaGCCTTCCCACTTCGTTT23S (1027)3580[77]
GAM42aγ-subclass of ProteobacteriaGCCTTCCCACATCGTTT23S (1027)3580[77]
CF319A**Cytophaga–Flavobacterium cluster of CFB-phylumTGGTCCGTGTCTCAGTAC16S (319)3580[77]
CF319B**Same as CF319ATGGTCCGTATCTCAGTAC16S (319)3580[77]
HGC69aGram-positive bacteria with high GC contentTATAGTTACCACCGCCGT23S (1901)25159[78]
LGC354A***Gram-positive bacteria with low GC contentTGGAAGATTCCCTACTGC16S (354)3580[79]
LGC354B***Same as LGC354ATGGAAGATTCCCTACTGC16S (354)3580[79]
LGC354C***Same as LGC354ATGGAAGATTCCCTACTGC16S (354)3580[79]
  • ****, Probes marked with the same amount of * are applied in equimolar mixtures.

  • aEscherichia coli numbering.

  • bPercentage (vol/vol) of formamide in the hybridisation buffer.

  • cPercentage (vol/vol) of NaCl in the washing buffer.

In situ hybridisations with probes HGC69a and LGCmix were done on ethanol-fixed samples, while paraformaldehyde-fixed soil samples were used for probing gram-negative bacteria. Probe NON338 was used as a negative control for the ethanol-fixed as well as the paraformaldehyde-fixed samples. In situ hybridisations were performed similarly as described elsewhere [38,39]. A 10 μl aliquot of hybridisation buffer (0.9 M NaCl, 20 mM Tris–HCl; pH 8.0), 0.02% sodium dodecyl sulfate (SDS), formamide in concentrations as given in Table 3, and 30 ng/μl of probe was placed on each well. The slides were transferred to an equilibrated 50 ml polypropylene top tube [24] and incubated at 46 °C for 90 min. Slides were then washed at 48 °C for 10 min in washing buffer (20 mM Tris–HCl, pH 8.0), 5 mM EDTA, 0,01% SDS w/v, NaCl concentration as given in Table 3. Afterwards they were washed in ice-cold double-distilled water for a few seconds and quickly dried in an air stream. Finally slides were mounted in Citifluor AF1 antifadent (Plano; Wetzlar, Germany) and covered with a coverslip.

2.5 Microscopy and quantification

A Zeiss LSM 510 scanning confocal microscope equipped with an Ar ion laser (488 nm), and two HeNe lasers (543 and 633 nm) was used to record optical sections. Image handling was done with the LSM510 software (version 2.3). Small fluorescent pieces of the soil matrix hindered an automatic detection with our equipment, as was described, e.g., by Daims et al. [40], therefore the counting was done manually. For each hybridisation approach at least 1000 DTAF-stained cells were counted on at least 10 randomly chosen fields. For each horizon the rate of bacteria detectable by FISH (cells containing a sufficient number of ribosomes [16]) was calculated by counting EUBmix-positive signals relative to DTAF-counts on PFA-fixed samples. These calculations were corrected for samples with high proportions of gram-positive bacteria, according to Friedrich et al. [41]. This was done by adding the amount of bacteria detected by probes HGC69a and LGCmix in the ethanol-fixed samples to the EUBmix counts.

Group-specific cell counts were performed with DTAF-stained soil samples simultaneously hybridised with Cy5-labelled EUBmix and the respective group-specific Cy3-labelled probe. This procedure enabled a threefold staining of the target-cells. This was important because background signals of non-bacterial soil particles often hinder clearly convincing results in soil samples, when using a single fluorescent probe [42]. Quantification of specific cells was done relative to the number of EUBmix-hybridised cells. Counting results were always corrected by subtracting signals obtained with the probe NON338.

For calculating the number of cells per gram of soil (BC), the mean count of bacteria per counting area (B), the microscope factor (area of the sample spot/area of counting field), (M) the dilution factor (D) and the weight of fixed sample used for hybridisation (W) were determined and arranged in the equation BC=B×M×D×W−1.

3 Results and discussion

Total bacterial cell numbers (TBC) in the soil, determined by DTAF staining, ranged from 1.2 to 23.0 × 108 cells g−1. These numbers were comparable to TBCs found in other arctic soils [43], and peat [44] and soils of other regions [45]. As shown in Table 4 and Fig. 1, TBC were highest (23.0 × 108 cells g−1) in the uppermost 5 cm layer of the soil and decreased with depth. In the deepest investigated horizon (40–45 cm) 1.2 × 108 cells g−1 were detected. It corresponds to 10% of the TBC detected in the surface horizon. TBC decreased exponentially with increasing depth (r2= 0.9711), with the exception in the horizon between 17 and 20 cm soil depth, where cell counts in the same order as in the layer above were retrieved (Table 4). Total cell counts for the deepest sample of the active layer were in the same range as other studies found below the permafrost table in continuously frozen sediments in Russia using acridine orange [46], DTAF staining [47], or direct visual microscopic counting [48].

View this table:

Total bacterial numbers in different horizons of the soil analysed after DTAF staining and relative percentage of hybridised cells with specific probes

Sample depth (cm)Total cell counts (cells/g [108]) (mean ± SD)% of DTAF cells (mean ± SD) detected with specific probesa% Affiliated Eubacteriab
EUBmixALF968BET42aCF mixGAM42aHGC69aLGCmixARC915
0–523.0 ± 7.859 ± 121.3 ± 1.211.7 ± 3.28.4 ± 5.63.3 ± 0.74.3 ± 2.35.7 ± 2.00.5 ± 0.734.7
5–1013.8 ± 3.352 ± 70.5 ± 0.96.3 ± 1.23.4 ± 3.29.8 ± 2.17.5 ± 2.31.0 ± 1.022.4 ± 30.029.0
10–179.2 ± 2.952 ± 105.5 ± 2.211.9 ± 2.45.1 ± 5.13.2 ± 1.210.0 ± 4.47.7 ± 7.19.9 ± 23.344.0
17–2010.4 ± 3.247 ± 161.1 ± 1.39.5 ± 0.80.4 ± 1.02.9 ± 0.812.6 ± 3.23.1 ± 2.65.2 ± 11.131.9
20–235.5 ± 2.134 ± 62.1 ± 1.54.7 ± 1.00.0 ± 0.05.6 ± 2.510.8 ± 5.83.2 ± 2.27.2 ± 16.628.5
23–303.7 ± 1.528 ± 62.8 ± 3.53.4 ± 1.01.1 ± 1.10.0 ± 0.04.7 ± 3.30.4 ± 0.82.6 ± 5.812.2
30–352.6 ± 0.727 ± 100.4 ± 0.95.2 ± 0.40.0 ± 0.00.1 ± 0.90.1 ± 0.10.4 ± 0.80.9 ± 2.417.2
35–402.0 ± 0.728 ± 50.2 ± 0.65.5 ± 0.80.0 ± 0.00.2 ± 0.52.2 ± 1.21.2 ± 1.88.1 ± 19.315.2
40–451.2 ± 0.533 ± 83.8 ± 1.82.9 ± 2.00.0 ± 0.00.0 ± 0.04.9 ± 2.40.1 ± 0.41.0 ± 1.812.2
  • aPercent detection compared to DTAF. Numbers have been corrected by subtracting NON338 counts. Probe names are abbreviations of those shown in Table 1.

  • bResults obtained from the addition of counts with all above named specific probes without probe ARC 915.

Not only the total cell numbers, but also the fraction of cells detectable with probe EUBmix, which identified members of the domain Bacteria, decreased by depth from 59% to around 30% (Table 4). This decrease in the fraction of detectable bacteria was due to a strong exponential decrease (r2= 0.963) of absolute EUBmix counts from 13.6 to 0.4 × 108 cells g−1 (Fig. 2). There were only a few studies to compare our data. The soil samples in which Zarda et al. [49] and Christensen et al. [25] found 41% or only 5% of the TBC with probe EUB338, were from the upper 10 cm of soils located in the temperate zone. A more comparable environment could be the Siberian peat samples investigated by Dedysh et al. [44], in which up to 65% of TBC were found with EUB 338. These results indicate that the extreme low temperatures in the investigated tundra soil did not lead to lower amounts of active bacteria than that from other soils. The high amounts of active bacteria found in our investigation of tundra soil as well as by Dedysh in the peat samples could be attributed to the very high content of organic matter, especially in the upper horizons. It is accepted and shown in other studies that carbon availability is the most important limiting factor for microbial growth in soil [5053]. Its possible influence on the activity of cells and hence on their ribosome content enhanced the detectability by FISH. Therefore the decreased EUB detection found in the deeper soil horizons could be attributed to the lower C content in these horizons. The EUB detection rates throughout the soil profile showed a very strong correlation to Corg content (R2= 0.951, p= < 0.0001, n= 9) (Fig. 1(d) and (e)). Considering the low temperatures, at which mesophilic organisms show a drastic decrease of metabolic activity, the EUBmix amounting of the TBC number in the deeper horizons indicated the existence of psychrophilic or at least psychrotrophic organisms.

Vertical profile of absolute numbers of bacteria detected with different probes in the investigated Typic Historthel. All data correspond to 1 g soil (dry weight). Probe names and target groups are explained in Table 3. Note the different x-axis range of the first diagram. Classification of the soil profile in different horizons is given on the left of the DTAF/EUBmix profile.

In contrast to the distribution observed for the domain Bacteria, none of the individual major phylogenetic groups showed a clear exponential decrease of cell numbers with depth. Notably, the highest abundance of the gram-positive Bacteria with a high G + C content, the α-Proteobacteria, and the γ-Proteobacteria was found in horizons below the top 5 cm. However, all groups showed much higher abundances in the upper part of the profile and a significant reduction in cell numbers in depths below 23 cm. Apparent differences among the individual bacterial groups were the amount of cell numbers and their distribution in soil profile (Fig. 2). This can be explained by different habitat requirements for the bacterial groups as well as positive and negative influences among bacterial species.

For example, the Cytophaga–Flavobacterium cluster (CF group) of CFB phylum (Cytophaga–Flavobacterium–Bacteroides phylum) was found in the amount between 2.0 × 108 and 0.5 × 108 cells g−1 in the upper 17 cm of soil. Most of the known members of this group are organotrophic, aerobic bacteria that are specialised in the degradation of complex macromolecules like proteins, pectin or cellulose [54,55]. The influence of water level and organic matter on the abundance of the Cytophaga–Flavobacterium group was obvious. In the aerobic upper 17cm layer of the soil, the top 5 cm layer containing the highest amount of organic matter had the highest amount of cells of Cytophaga–Flavobacterium group whereas in the anaerobic zone, below the water table at 18 cm, nearly no cells were detected. This major difference in cell abundance between the aerobic and anaerobic horizons was not found for the other phylogenetic groups. For the high G + C group, cell counts were nearly equal (approximately 1 × 108 cells g−1) in the horizons between 0 and 20 cm whereas the gram-positive Bacteria with low G + C content showed a more varying distribution in the upper 20 cm layer with cell numbers between 1.3 and 0.3 × 108 g−1.

The abundances of the phylogenetic groups as illustrated in Fig. 2 led to the different compositions of active Bacteria in the horizons as shown in Fig. 3. With our set of probes for major phyla within the domain Bacteria we could affiliate between 12.2% and 44.0% of the total DTAF counts (Table 4). In the upper 23 cm layer this ratio was between 28.5% and 44%, which means that at least in the upper horizons the majority (55–84%) of the FISH-detectable Bacteria could be affiliated to a known phylogenetic group. In the upper part of the soil, a more diverse composition of active Bacteria than in the lower horizons was found. Two dominant groups and at least two other groups with relevant cell numbers were found in each horizon. For example, in the upper 5 cm the β-Proteobacteria group was dominant (20% of all EUB-counts could be assigned to this phylogenetic group), followed by the Cytophaga–Flavobacterium group (14%). Three other groups were found in ratios between 6% and 10%. The β-Proteobacteria and high G + C groups were the dominant throughout the soil profile. A direct comparison of the data with other studies was not possible due to the above-mentioned restriction of other FISH studies to the surface layer. Significant decrease in the diversity of the soil microbial communities with depth were also detected in other studies by using phospholipids fatty acid (PFLA) analysis or terminal restriction fragment length polymorphism (TRFLP) analysis [13,53,56]. The decrease of the amount of EUB-detected cells detectable by specific probes in depths below 23 cm suggested that a larger portion of species did not fit into the phylogenetic groups detected with our probes. However, the reason is most likely a lower activity of cells in deeper horizons and hence a lower rRNA content, which is not high enough for a detectable signal of the phylogenetic group probes. This assumption is supported by the observation that the signal intensity of the EUBmix probe decreased in deeper soil horizons.

Vertical profile of probe-specific counts relative to EUB-counts (percentages) in the Typic Historthel. Probe names are abbreviations of those shown in Table 3.

The greater diversity and activity of cells in the upper horizons can be explained by higher temperatures and better substrate supply. In the upper layers the high root density may contribute, in addition to the high C content, to higher activity. While the upper 23 cm showed a high root density, only few roots were found between 23 and 35 cm, and none below 35 cm. The rhizosphere is known as a highly active soil compartment. Microbial activity and growth are stimulated through the release of compounds such as amino acids and sugars in plant root exudates [57]. Therefore microbial communities associated with the rhizosphere are often more active in relation to the microorganisms in bulk soil [58]. In addition to better substrate provision in the rhizosphere, another effect, which could influence bacterial composition in the rhizosphere, is the transport of oxygen from the atmosphere to the roots through the aerenchyma. This transport is described for many wetland plants as adaptation to anaerobic soil conditions [5961]. At the investigated soil site the large aerenchyma of Carex aquatilis serve as pathways for gas transport [31]. The presence of oxygen in the rhizosphere could enable the existence of aerobic species in an environment, which is anaerobic on the macroscopic scale. Altogether, the decrease of temperature, aeration, and substrate supply with depth leads to reduced activity of cells and eliminates those unable to withstand these harsher conditions.

Quantification of the domain Archaea was more difficult and showed higher standard deviations than that of the domain Bacteria. This was due to a strong formation of aggregates, as shown in Fig. 3. The basic requirement for the counting method is a homogeneous distribution of cells on each well. Cell counts are illustrated in Fig. 2, but one should keep in mind the statistical problems related with these data. Most Archaea were found in the Oi-horizon between 5 and 10 cm. The number of approximately 3.0 × 108 cells g−1 means that 22% of all DTAF cell counts could be assigned to the domain Archaea (Table 3). Also, the cell numbers from 10 to 23 cm were higher than in the upper 5 cm.

In the following, the cell counts retrieved by Arc915 were discussed as cell counts of methanogens. For justification, the subsamples of the upper 17 cm, where high amounts of cells were detected by probe Arc915, were additionally hybridised with probe MER 1, which is specific for 16SrRNA of methanogens [62]. Nearly the same number of cells hybridised with Arc915 as with MER1. Additionally, methane activity measurements (unpublished data) show a high methane production in the depth of 5–17 cm, where high numbers of Arc915 cells were found.

Soil depth, at which most methanogens were found, was a zone with changing oxygen conditions, which was above the water level during sampling time and not in the anaerobic zone of the profile. Oxygen content in this horizon is not optimal for methane production since methanogens are regarded as strictly anaerobic organisms [63] and can only survive in anaerobic microhabitats of this horizon. Other soil investigations also found methanogens in oxic soil horizons [6466]. Wagner and Pfeiffer [64] demonstrated that aerobic and facultative anaerobic microflora in soil enable methane activity in the presence of oxygen in microscale anoxia. The reason why the methanogens seem to favour the upper horizons despite the suboptimal oxygen rates could be related to the better substrate provision in these horizons. The upper horizons of the Typic Historthel provide a high content of organic carbon and high cell numbers of Eubacteria, which convert high-weight macromolecules to the substrates that can be used by the methanogens. Other studies also found a strong influence of the amount [67] and the quality [68] of fresh organic carbon in soil on the amount and activity of methanogens. Despite its high amount of organic matter, nearly no Archaea were found in the uppermost 5 cm. This upper layer is less compact and therefore better vented than the layers below and did not provide enough anaerobic microhabitats.

It should be noted that soils are spatiotemporal heterogeneous environments. Therefore the results of this study reflect the situation at the sampling point in the low-centred polygon at the time of sampling. In order to draw broader conclusions about the ecological situation in low-centred polygons further samplings at different times are necessary. Due to the time-consuming analysis only one profile was examined but attention was paid to that the characteristics of this polygon were typical for the surrounding landscape. This study can thus provide only an early insight into community structure in polygonal tundra soils.

4 Conclusions

This study reveals the first analysis of the composition of an active community from tundra soil. By use of FISH we have shown that differences in soil parameters, like C content, water content, and root existence, caused differences in the composition of bacterial communities among the horizons of the Typic Historthel. For some phylogenetic groups such as the Cytophaga–Flavobacterium group, the most influential parameters were identified. Despite all differences in the requirements of the specific groups, which influence their abundances in soil, the total diversity and quantity of active cells was strongly related to the content of organic matter, an effect that was noted in soils of polygonal tundra also by other researchers [69,70]. Nevertheless, despite the harsh environmental conditions in the deeper horizons directly above the permafrost, there is evidence for high amount of cells (4 × 107 cells g−1) with at least minimal activity. Even in the deeper parts of the active layer at least a minimal turnover of organic matter, by probably psychrophilic organisms, can therefore be expected.

Using the described protocol for FISH, this technique was successfully used to describe the composition of active bacterial community of arctic soil. By applying three different dyes, every positive target cell was stained at least with two different dyes, which enabled a clear discrimination between bacterial cells and non-bacterial soil particles (Fig. 4). The relatively high standard deviation of cell counts obtained for some groups is attributed to the heterogeneity of soil. However, the deviations were in the same order as in other studies of sediment [71] and soil [49]. To better resolve the effect of different community compositions on the carbon conversion, future investigations will combine community analyses with investigations of substrate conversion in different soil horizons.

Confocal laser scanning microscope (CLSM) images showing DTAF staining and in situ hybridisation of bacteria in a soil sample from the top 5 cm. Both pictures show identical microscopic fields, displayed in different artificial colours. (a) Hybridisation with probe EUBmix-Cy5 (red), additional all cells were stained with DTAF (blue). Due to double staining the target Bacteria cells appear purple. (b) Additional hybridisation with probe CFmix-Cy3 (green). Target Cytophaga–Flavobacterium cells appear yellow, due to threefold staining. Some of them were marked with yellow circles. The scale bars represent 10 μm.

We thank the Russian–German field parties during the expedition 2001 for the enjoyable cooperation in the field. We thank Ute Bastian, Christine Flemming (Alfred Wegener Institute, Research Unit Potsdam), and Susanne Kopelke (Institute of Soil Science, University of Hamburg) for providing laboratory assistance. We also thank Dr. Otto Baumann (Department of Zoophysiology, University of Potsdam) for extensive introduction into CLSM handling and providing microscope time. Special thanks to Lars Kutzbach for many fruitful discussions and to Christian Wille for critical reading of the manuscript.

This study is part of the German–Russian project The Laptev Sea System (03G0534G), which was supported by the German Ministry of Education and Research (BMBF) and the Russian Ministry of Research and Technology.

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View Abstract


9to5 Mac has received what appears to be a leaked confidential AppleCare document Apple acknowledges that they are investigating reports of Wi-Fi issues with the new iPad. And that repair centers and Apple stores should replace the 3rd generation units if they exhibit specific symptoms.

Symptoms can include, but are not limited to:

- Intermittent connectivity
- Slow Wi-Fi speeds
- Wi-Fi network not seen


248 Wilmslow Rd, M14 6LD

South, Manchester

Cuisine: Traditional

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About Kosmos

Greek food in Fallowfield

Kosmos is a family restaurant run by married couple Stewart and Loulla Astin. Born in a small traditional village in Cyprus, Loulla learned about generations old Greek and Cypriot cuisine from her grandmother. She moved to Manchester aged fifteen where her father Solomon Solominides was the first person to bring kebabs to the city. Loulla opened Kosmos in 1981 and it has been popular ever since, winning awards and recognition for its Greek and Cypriot food. Loulla has appeared on television many times and meet the Queen at a reception for services to the hospitality industry in the UK.


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Cherry not too far from KVD

Hank Cherry is fishing just a few hundred yards from KVD. We never saw him yesterday, but we were told he was nearby. None of this is meant to imply that either is infringing on the other, just that the best in the world are all likely to find the same sweet spots.


Massachusetts Senate advances minimum wage legislation - again

Minimum wage 61113.jpg
Victoria Entzminger, 54, and Ruthella Logan, 51, both personal care attendants from Brockton and members of the Service Employees International Union, hold signs to show where they stand on increasing the minimum wage during a hearing at the Statehouse. (The Republican file photo)

BOSTON - The Massachusetts Senate passed – again – a bill raising the state’s minimum wage and reforming unemployment insurance.

The move was a largely procedural step which allows the bill to proceed to a committee of conference.

The Senate had passed in a bill in November raising the state’s $8 an hour minimum wage to $11 an hour. It passed a bill in February reforming the state’s unemployment insurance system.

The House combined the two policies into a single bill, a strategic move since businesses typically oppose the minimum wage hike but support the unemployment insurance reforms, which would lower their costs.

There were, however, significant differences between the House and Senate bills.

For example, the House would raise the hourly wage to $10.50, while the Senate would raise it to $11. Only the Senate bill includes an economic indexing provision so that after 2016 the minimum wage would rise each year at the same rate as the consumer price index for the Northeast. Political maneuvering had blocked the bills from legislative action.

The Senate on Thursday voted on the House bill, but replaced the portions dealing with both minimum wage and unemployment insurance with the Senate's language.

State Sen. Dan Wolf, a Harwich Democrat and chairman of the Joint Committee on Labor and Workforce Development, urged senators not to take too long to debate the bill.

"The task before us is not to rehash the substance of those bills we passed in November and again in February, which were balanced and well delivered and well thought out," Wolf said. "The task is to get a vehicle we can get to the governor's desk."

Wolf said legislators were there to discuss "process, process, process."

Senate Minority Leader Bruce Tarr, a Gloucester Republican, said debate was important to send "the right bill" to committee. "Not to merely say these questions have been asked and answered but to say these continue to be asked and need to be answered appropriately," Tarr said.

There have been passionate debates in the legislature regarding both the impact of the minimum wage hike on businesses and the best way to reform unemployment insurance. However, after several hours of discussion regarding a variety of amendments, none of which passed, the Senate passed the bill as proposed.

The Senate’s vote sends the bill on to a committee of legislators from both bodies who will try to iron out their differences.