Miracle-dz/UniFAR-FTUs huggingface dataset:
An algorithm for optimal lambda calculus reduction

We present an algorithm for lambda expression reduction that avoids any copying that could later cause duplication of work. It is optimal in the sense defined by Lévy. The basis of the algorithm is a graphical representation of the kinds of commonality that can arise from substitutions; the idea can be adapted to represent other kinds of expressions besides lambda expressions. The algorithm is also well suited to parallel implementations, consisting of a fixed set of local graph rewrite rules.
Diabetes and its prevention: Pragmatic solutions for people with schizophrenia

Background Patients with schizophrenia have an increased risk of developing diabetes. However, no pragmatic pathway of care has ever been proposed in order to identify individuals at risk and manage that risk effectively. Aims To develop practical recommendations for the screening and management of diabetes in schizophrenia. Method Staged review of evidence for the under recognition of diabetes in people with schizophrenia and of the applicability of current screening strategies to this population. Recommendations for pragmatic pathways of care were developed. Results All patients with schizophrenia should be screened and managed as a high-risk group for the development of diabetes. Psychiatrists should be responsible for screening and diabetes risk management; primary care physicians and/or diabetologists should be responsible for managing diabetes. Choice of antipsychotics should be based on achieving good control of schizophrenia, which may improve compliance with diabetes risk reduction strategies. Conclusions Effective multi-disciplinary team working should reduce the burden of diabetes in schizophrenia.
Optimal control of finite-valued networks

Control of finite-valued networks, including Boolean networks, is currently a hot topic. In this paper the optimization control of the networks with present value performance criterion is discussed. The problem is formulated as a finite strategy game between human and machine. It is firstly proved that the optimal strategy can be found in the set of periodic strategies, which makes the problem finitely computable, though the computational complexity of exhaustion might be a severe problem. Then an efficient numerical method is developed to solve the problem. Some interesting examples are presented to demonstrate the efficiency of our results.
Case-Based Reasoning and User-Generated AI for Real-Time Strategy Games

Creating AI for complex computer games requires a great deal of technical knowledge as well as engineering effort on the part of game developers. This paper focuses on techniques that enable end-users to create AI for games without requiring technical knowledge by using case-based reasoning techniques. AI creation for computer games typically involves two steps: a) generating a first version of the AI, b) debugging and adapting it via experimentation. We will use the domain of real-time strategy games to illustrate how case-based reasoning can address both steps.
Specification of Producer Posted Prices

Minimum economic generation level for the base layer d (l)+ j Maximum capacity of the base layer c (l) j Per unit price for electricity provided through the base layer rj Maximum ramp rate of the base layer sj Shutdown cost that is incurred when base layer generation is below the minimum economic layer d (h)+ j Maximum capacity of the tracking layer c (h) j Per unit price for electricity provided through the tracking layer BCj Base cost function RCj Ramp cost function SCj Shutdown cost function Figure 1: Table of notation for producer cost function for producer j. The problem of deciding the optimal output levels of a group of power generation facilities in order to meet system demand has been studied extensively [1]. If the set of active generation facilities is fixed (i.e., we cannot choose which facilities are active or inactive), the problem is referred to as economic dispatch, whereas it is referred to as unit commitment if the choice of active generation facilities is part of the optimization. The problem of generation scheduling is typically decoupled of the problem of distribution to some extent; however, distribution constraints may be added to the problem, forcing some generators to be active or require extra power to be generated to account for losses. The generation scheduling problem has several internal constraints: 1. Generation facilities have limited ramp rate—the amount of power output change that can be sustained from time period to time period. Ramp rates of different generation facilities vary radically: demand tracking plants such as natural gas can ramp up or down in half an hour, whereas nuclear plants take days. 2. Different kinds of generation have different variable costs—renewables have near zero variable cost and natural gas has quite a high variable cost. 3. For certain kinds of plants (e.g., coal), reducing production below a certain level is expensive—it imposes additional wear on the components. Shutting down these plants also incurs costs. 4. The number of available maintenance crews may be limited, which may limit how many plants can be adjusted at the same time. 5. Plants may have minimum uptime and downtime requirements in order to reduce maintenance costs. 6. Due to the fact that the generation scheduling problem is solved ahead of the realization of demand, it is necessary to keep a reserve of active generation capacity as well as generation capacity that can …
Confessions from a grounded theory PhD: experiences and lessons learnt

Grounded Theory (GT) is used within HCI research, but nuances and more modern interpretations of the method are rarely discussed. This paper has two intentions: to offer guidance on practical issues when applying GT, and to clarify the space of methodological possibilities. We describe an extended GT study on understanding why practitioners choose particular usability evaluation methods. We describe five stages in this study to highlight our experiences and choices made. We draw out seven practical and methodological considerations in applying GT in a CHI context. This challenges the more traditional inductive and objective positions on GT use; it sensitizes novices of GT to these issues; and through the extended case study it provides substance for debate on issues that affect those that use qualitative methods more broadly.
Title : The emergence of cerebral specialisation for the human voice over the first months of life Short title : Cerebral specialisation for human voice To : Social Neuroscience

To: Social Neuroscience Lloyd-Fox, S. , Blasi, A. , Mercure, E. , Elwell, C.E. & Johnson, M.H. 1 Centre for Brain and Cognitive Development, Birkbeck, University of London. 2 Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Kings College London, UK. Institute of Cognitive Neuroscience, University College London, UK. 4 Department of Medical Physics and Bioengineering, University College London, UK.
Fixed length semiorder preserving code for field level data file compression

An encoding scheme (FLSOPC) is presented as a new data compression method. The generated fixed-length codes are preserving the order on the original data representations in the sense of semiorder preservation as defined in this paper. The FLSOPC employing binary sectioning assignment algorithm requires the code size that is linear to logarithm of the data cardinality. It is about 2.8 times that required by FLMB (fixed-length minimum bit) encoding when no knowledge about data is given a priori. This factor can be reduced to 2.1 if a half of data has been available as the initial load and approaches 1 when even more data is known.
Light Variability Illuminates Niche-Partitioning among Marine Picocyanobacteria

Prochlorococcus and Synechococcus picocyanobacteria are dominant contributors to marine primary production over large areas of the ocean. Phytoplankton cells are entrained in the water column and are thus often exposed to rapid changes in irradiance within the upper mixed layer of the ocean. An upward fluctuation in irradiance can result in photosystem II photoinactivation exceeding counteracting repair rates through protein turnover, thereby leading to net photoinhibition of primary productivity, and potentially cell death. Here we show that the effective cross-section for photosystem II photoinactivation is conserved across the picocyanobacteria, but that their photosystem II repair capacity and protein-specific photosystem II light capture are negatively correlated and vary widely across the strains. The differences in repair rate correspond to the light and nutrient conditions that characterize the site of origin of the Prochlorococcus and Synechococcus isolates, and determine the upward fluctuation in irradiance they can tolerate, indicating that photoinhibition due to transient high-light exposure influences their distribution in the ocean.
On data skewness, stragglers, and MapReduce progress indicators

We tackle the problem of predicting the performance of MapReduce applications designing accurate progress indicators, which keep programmers informed on the percentage of completed computation time during the execution of a job. This is especially important in pay-as-you-go cloud environments, where slow jobs can be aborted in order to avoid excessive costs. Performance predictions can also serve as a building block for several profile-guided optimizations. By assuming that the running time depends linearly on the input size, state-of-the-art techniques can be seriously harmed by data skewness, load unbalancing, and straggling tasks. We thus design a novel profile-guided progress indicator, called NearestFit, that operates without the linear hypothesis assumption in a fully online way (i.e., without resorting to profile data collected from previous executions). NearestFit exploits a careful combination of nearest neighbor regression and statistical curve fitting techniques. Fine-grained profiles required by our theoretical progress model are approximated through space- and time-efficient data streaming algorithms. We implemented NearestFit on top of Hadoop 2.6. 0. An extensive empirical assessment over the Amazon EC2 platform on a variety of benchmarks shows that its accuracy is very good, even when competitors incur non-negligible errors and wide prediction fluctuations.
Metaphor and the ‘emergent property’ problem: A relevance-theoretic treatment.

The interpretation of metaphorical utterances often results in the attribution of emergent properties; these are properties which are neither standardly associated with the individual constituents of the utterance in isolation nor derivable by standard rules of semantic composition. For example, an utterance of ‘Robert is a bulldozer’ may be understood as attributing to Robert such properties as single-mindedness, insistence on having things done in his way, and insensitivity to the opinions/feelings of others, although none of these is included in the encyclopaedic information associated with bulldozers (earth-clearing machines). An adequate pragmatic account of metaphor interpretation must provide an explanation of the processes through which emergent properties are derived. In this paper, we attempt to develop an explicit account of the derivation process couched within the framework of relevance theory. The key features of our account are: (a) metaphorical language use is taken to lie on a continuum with other cases of loose use, including hyperbole; (b) metaphor interpretation is a wholly inferential process, which does not require associative mappings from one domain (e.g. machines) to another (e.g. human beings); (c) the derivation of emergent properties involves no special interpretive mechanisms not required for the interpretation of ordinary, literal utterances.
The power of blazar jets

We estimate the power of relativistic, extragalactic jets by modelling the spectral energy distribution of a large number of blazars. We adopt a simple one-zone, homogeneous, leptonic synchrotron and inverse Compton model, taking into account seed photons originating both locally in the jet and externally. The blazars under study have an often dominant high-energy component which, if interpreted as due to inverse Compton radiation, limits the value of the magnetic field within the emission region. As a consequence, the corresponding Poynting flux cannot be energetically dominant. Also the bulk kinetic power in relativistic leptons is often smaller than the dissipated luminosity. This suggests that the typical jet should comprise an energetically dominant proton component. If there is one proton per relativistic electrons, jets radiate around 2‐10 per cent of their power in high-power blazars and 3‐30 per cent in less powerful BL Lacs.
Demonstration of in vivo DNA repair synthesis in mouse skin exposed to various chemical carcinogens.

Chemical carcinogen-induced unscheduled DNA synthesis in mouse skin in vivo was demonstrated with the aid of a mechanical device. An isotonic aqueous solution containing a carcinogen and [methyl-3H]thymidine was injected s.c. into an isolated portion of the skin clamped off with ring-shaped forceps. Dose-dependent unscheduled DNA synthesis was clearly demonstrated as silver grains on the nuclei of both epithelial and dermal fibroblastic cells in this portion of skin in response to treatment with methyl methanesulfonate, 1-methyl-1-nitrosourea, 4-nitroquinoline 1-oxide, and 4-hydroxyaminoquinoline 1-oxide. The range of variability was small among animals and within a single area of skin. These findings suggest that this system should be useful for quantitative measurement of unscheduled DNA synthesis in individual cells of the skin in vivo. Unscheduled DNA synthesis in response to various carcinogens was 3- to 5-fold more active in epithelial cells than in dermal fibroblastic cells. A time course study showed that active unscheduled DNA synthesis could be detected after 10 min, implying that adduct removal with resulting synthesis had occurred by this time.
Measuring leadership and management and their linkages with literacy in rural and township primary schools in South Africa

This paper describes a rigorous process to develop and trial new metrics for measuring and codifying school leadership and management practices and processes that are considered theoretically related to literacy outcomes. The predictive validity of these measures is assessed in challenging contexts including 60 township and rural primary schools in South Africa. We observe a randomness to how better leadership and management practices are distributed across better and worse performing schools. Regression analyses confirm weak and inconsistent linkages between measured leadership and management dimensions and literacy outcomes across the sample. However, we find evidence of stronger linkages with intermediate outcomes, including evidence of curriculum coverage. This research contributes to a burgeoning, yet underdeveloped literature on educational management and leadership in Africa and the challenges of measurement in this context.
The role of the novel adipocyte-derived hormone adiponectin in human disease.

Adiponectin, also called GBP-28, apM1, AdipoQ and Acrp30, is a novel adipose tIssue-specific protein that has structural homology to collagen VIII and X and complement factor C1q, and that circulates in human plasma at high levels. It is one of the physiologically active polypeptides secreted by adipose tIssue, whose multiple functions have started to be understood in the last few Years.A reduction in adiponectin expression is associated with insulin resistance in some animal models. Administration of adiponectin has been accompanied by a reduction in plasma glucose and an increase in insulin sensitivity. In addition, thiazolidinediones, drugs that enhance insulin sensitivity through stimulation of the peroxisome proliferator-activated receptor-gamma, increase plasma adiponectin and mRNA levels in mice. On the other hand, this adipocyte protein seems to play a protective role in experimental models of vascular injury. In humans, adiponectin levels are inversely related to the degree of adiposity and positively associated with insulin sensitivity both in healthy subjects and in diabetic patients. Plasma adiponectin levels have been reported to be decreased in some insulin-resistant states, such as obesity and type 2 diabetes mellitus, and also in patients with coronary artery disease. On the contrary, chronic renal failure, type 1 diabetes and anorexia nervosa are associated with increased plasma adiponectin levels. Concentrations of plasma adiponectin have been shown to correlate negatively with glucose, insulin, triglyceride levels and body mass index, and positively with high-density lipoprotein-cholesterol levels and insulin-stimulated glucose disposal. Weight loss and therapy with thiazolidinediones increased endogenous adiponectin production in humans. Adiponectin increases insulin sensitivity by increasing tIssue fat oxidation, resulting in reduced circulating fatty acid levels and reduced intracellular triglyceride contents in liver and muscle. This protein also suppresses the expression of adhesion molecules in vascular endothelial cells and cytokine production from macrophages, thus inhibiting the inflammatory processes that occur during the early phases of atherosclerosis. In view of these data, it is possible that hypoadiponectinemia may play a role in the development of atherosclerotic vascular disease. In summary, the ability of adiponectin to increase insulin sensitivity in conjunction with its anti-inflammatory and anti-atherogenic properties have made this novel adipocytokine a promising therapeutic tool for the future, with potential applications in states associated with low plasma adiponectin levels.
Betti numbers of graded modules and the Multiplicity Conjecture in the non-Cohen-Macaulay case

We use the results by Eisenbud and Schreyer to prove that any Betti diagram of a graded module over a standard graded polynomial ring is a positive linear combination Betti diagrams of modules with a pure resolution. This implies the Multiplicity Conjecture of Herzog, Huneke and Srinivasan for modules that are not necessarily Cohen-Macaulay. We give a combinatorial proof of the convexity of the simplicial fan spanned by the pure diagrams.
Two Flavonolignans from Milk Thistle (Silybum marianum) Inhibit CYP2C9-Mediated Warfarin Metabolism at Clinically Achievable Concentrations

Milk thistle (Silybum marianum) is a popular herbal product used for hepatoprotection and chemoprevention. Two commercially available formulations are the crude extract, silymarin, and the semipurified product, silibinin. Silymarin consists of at least seven flavonolignans, of which the most prevalent are the diastereoisomers silybin A and silybin B; silibinin consists only of silybin A and silybin B. Based on a recent clinical study showing an interaction between a silymarin product and the CYP2C9 substrate losartan, the CYP2C9 inhibition properties of silybin A and silybin B and corresponding regioisomers, isosilybin A and isosilybin B, were evaluated using human liver microsomes (HLMs), recombinant CYP2C9 (rCYP2C9) enzymes, and the clinically relevant probe, (S)-warfarin. Silybin B was the most potent inhibitor in HLMs, followed by silybin A, isosilybin B, and isosilybin A (IC50 of 8.2, 18, 74, and >100 μM, respectively). Next, silybin A and silybin B were selected for further characterization. As with HLMs, silybin B was more potent than silybin A toward rCYP2C9*1 (6.7 versus 12 μM), rCYP2C9*2 (9.3 versus 19 μM), and rCYP2C9*3 (2.4 versus 9.3 μM). Using a matrix of five substrate (1–15 μM) and six inhibitor (1–80 μM) concentrations and HLMs, both diastereoisomers inhibited (S)-warfarin 7-hydroxylation in a manner described best by a mixed-type inhibition model (Ki values of 4.8 and 10 μM for silybin B and silybin A, respectively). These observations, combined with the high systemic silibinin concentrations (>5–75 μM) achieved in a phase I study involving prostate cancer patients, prompt clinical evaluation of a potential warfarin-milk thistle interaction.
Generalized additive distributed lag models: quantifying mortality displacement.

There are a number of applied settings where a response is measured repeatedly over time, and the impact of a stimulus at one time is distributed over several subsequent response measures. In the motivating application the stimulus is an air pollutant such as airborne particulate matter and the response is mortality. However, several other variables (e.g. daily temperature) impact the response in a possibly non-linear fashion. To quantify the effect of the stimulus in the presence of covariate data we combine two established regression techniques: generalized additive models and distributed lag models. Generalized additive models extend multiple linear regression by allowing for continuous covariates to be modeled as smooth, but otherwise unspecified, functions. Distributed lag models aim to relate the outcome variable to lagged values of a time-dependent predictor in a parsimonious fashion. The resultant, which we call generalized additive distributed lag models, are seen to effectively quantify the so-called 'mortality displacement effect' in environmental epidemiology, as illustrated through air pollution/mortality data from Milan, Italy.
Anytime RRBT for handling uncertainty and dynamic objects

We present an efficient anytime motion planner for mobile robots that considers both other dynamic obstacles and uncertainty caused by various sensors and low-level controllers. Our planning algorithm, which is an anytime extension of the Rapidly-exploring Random Belief Tree (RRBT), maintains the best possible path throughout the robot execution, and the generated path gets closer to the optimal one as more computation resources are allocated. We propose a branch-and-bound method to cull out unpromising areas by considering path lengths and uncertainty. We also propose an uncertainty-aware velocity obstacle as a simple local analysis to avoid dynamic obstacles efficiently by finding a collision-free velocity. We have tested our method with three benchmarks that have non-linear measurement regions or potential collisions with dynamic obstacles. By using the proposed methods, we achieve up to five times faster performance given a fixed path cost.
AMIRAS—An Airborne MIRAS Demonstrator

This paper describes AMIRAS, an airborne demonstrator of the Microwave Imaging Radiometer with Aperture Synthesis, which is the instrument onboard ESA's Soil Moisture and Ocean Salinity (SMOS) mission. The main electrical, mechanical, thermal, and control elements of the demonstrator are shown, together with its capabilities and performances as demonstrator of the spaceborne instrument. AMIRAS main tests inside an anechoic chamber, field ground experiments, and its first two maiden flights are reported, and some results of these tests are highlighted. AMIRAS will further be used in some calibration and validation campaigns of the SMOS mission.