Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk and benefits in lifestyle sports: parkour, law and social value

ABSTRACT This paper examines the interrelationship between law and lifestyle sports, viewed through the lens of parkour. We argue that the literature relating to legal approaches to lifestyle sport is currently underdeveloped. Law is viewed as a largely negative presence, seen particularly in terms of the ways in which counter-cultural activities are policed and regulated, where such activities are perceived to be transgressive and undesirable. We argue that this is a somewhat unsophisticated take on how the law can operate, with law constructed as an outcome of constraints to behaviour (where the law authorises or prohibits), distinct from the legal contexts, environments and spaces in which these relationships occur. We examine specifically the interrelationship between risk and benefit and how the law recognises issues of social utility or value, particularly within the context of lifestyle sport. A case study is provided of the employment of claims to social value present in the advancing institutionalisation of parkour in the United Kingdom. Through the case study, the paper seeks to foreground a more nuanced position that moves away from user-centred constructions of law as an imposition toward an appreciation of how the law can be used to support and extend claims to space.
SMURF: A SVM-based Incremental Anti-pattern Detection Approach

In current, typical software development projects, hundreds of developers work asynchronously in space and time and may introduce anti-patterns in their software systems because of time pressure, lack of understanding, communication, and-or skills. Anti-patterns impede development and maintenance activities by making the source code more difficult to understand. Detecting anti-patterns incrementally and on subsets of a system could reduce costs, effort, and resources by allowing practitioners to identify and take into account occurrences of anti-patterns as they find them during their development and maintenance activities. Researchers have proposed approaches to detect occurrences of anti-patterns but these approaches have currently four limitations: (1) they require extensive knowledge of anti-patterns, (2) they have limited precision and recall, (3) they are not incremental, and (4) they cannot be applied on subsets of systems. To overcome these limitations, we introduce SMURF, a novel approach to detect anti-patterns, based on a machine learning technique - support vector machines - and taking into account practitioners' feedback. Indeed, through an empirical study involving three systems and four anti-patterns, we showed that the accuracy of SMURF is greater than that of DETEX and BDTEX when detecting anti-patterns occurrences. We also showed that SMURF can be applied in both intra-system and inter-system configurations. Finally, we reported that SMURF accuracy improves when using practitioners' feedback.
Disruption of Parenting Behaviors in California Mice, a Monogamous Rodent Species, by Endocrine Disrupting Chemicals

The nature and extent of care received by an infant can affect social, emotional and cognitive development, features that endure into adulthood. Here we employed the monogamous, California mouse (Peromyscus californicus), a species, like the human, where both parents invest in offspring care, to determine whether early exposure to endocrine disrupting chemicals (EDC: bisphenol A, BPA; ethinyl estradiol, EE) of one or both parents altered their behaviors towards their pups. Females exposed to either compound spent less time nursing, grooming and being associated with their pups than controls, although there was little consequence on their weight gain. Care of pups by males was less affected by exposure to BPA and EE, but control, non-exposed females appeared able to “sense” a male partner previously exposed to either compound and, as a consequence, reduced their own parental investment in offspring from such pairings. The data emphasize the potential vulnerability of pups born to parents that had been exposed during their own early development to EDC, and that effects on the male, although subtle, also have consequences on overall parental care due to lack of full acceptance of the male by the female partner.
Clustered nested sampling: efficient Bayesian inference for cosmology

Bayesian model selection provides the cosmologist with an e xacting tool to distinguish between competing models based purely on the data, via the Baye sian vidence. Previous methods to calculate this quantity either lacked general applic ability or were computationally demanding. However, nested sampling (Skilling 2004), which w as recently applied successfully to cosmology by Muhkerjee et al. 2006, overcomes both of thes e impediments. Their implementation restricts the parameter space sampled, and thus i mproves the efficiency, using a decreasing ellipsoidal bound in the n-dimensional parameter space centred on the maximum likelihood point. However, if the likelihood function cont ains any multi-modality, separated over a significant portion of the parameter space then the ell ips is prevented from constraining the sampling region by less than the distance between the likelihood peaks. In this paper we introduce a method of clustered nested sampling whereby e llipsoidal clusters can form on any peaks identified –thus improving the efficiency by a facto r which is equal to the ratio of the volumes enclosed by the set of small clustered ellipsoids an the large single ellipse that would necessarily be required without clustering. In addition we have implemented a method for determining the expectation and variance of the final evidence value without the need to use sampling error from repetitions of the algorithm ; this furt her reduces the computational load by at least an order of magnitude. We have applied our algorit hm to a pair of toy models and one cosmological example where we demonstrate that the numb er of likelihood evaluations required is∼ 4% of that necessary for using previous algorithms. We have pro duced a fortran library containing our routines which can be called from any sampling code, in addition for convenience we have incorporated it into the popular C OSMOMC code as COSMOCLUST. Both are available for download at www.mrao. cam.ac. uk/software/cosmoclust.
Molecular Evolution in Collapsing Prestellar Cores. III. Contraction of a Bonnor-Ebert Sphere

The gravitational collapse of a spherical cloud core is investigated by numerical calculations. The initial conditions of the core lie close to the critical Bonnor-Ebert sphere with a central density of ~104 cm-3 in one model (α = 1.1), while gravity overwhelms pressure in the other (α = 4.0), where α is the internal gravity-to-pressure ratio. The α = 1.1 model shows reasonable agreement with the observed velocity field in prestellar cores. Molecular distributions in cores are calculated by solving a chemical reaction network that includes both gas-phase and grain-surface reactions. When the central density of the core reaches 105 cm-3, carbon-bearing species are significantly depleted in the central region of the α = 1.1 model, while the depletion is only marginal in the other model. The two different approaches encompass the observed variations of molecular distributions in different prestellar cores, suggesting that molecular distributions can be probes of contraction or accumulation timescales of cores. The central enhancement of the NH3/N2H+ ratio, which is observed in some prestellar cores, can be reproduced under certain conditions by adopting recently measured branching fractions for N2H+ recombination. Various molecular species, such as CH3OH and CO2, are produced by grain-surface reactions. The ice composition depends sensitively on the assumed temperature. Multideuterated species are included in our most recent gas-grain chemical network. The deuterated isotopomers of H are useful as probes of the central regions of evolved cores, in which gas-phase species with heavy elements are strongly depleted. At 10 K, our model can reproduce the observed abundance ratio of ND3/NH3 but underestimates the isotopic ratios of deuterated to normal methanol.
Ambulatory blood pressure monitoring in patients receiving long, slow home haemodialysis.

BACKGROUND Good blood pressure (BP) control has been reported previously in haemodialysis (HD) patients receiving 8-h dialysis sessions. Home HD allows patients to dialyze for long periods, but there are few data on the BP control achieved by these patients. We studied BP control, using ambulatory blood pressure monitoring (ABPM), in our home-HD patients who were receiving long-hours dialysis. METHODS Twenty-four patients aged 52.7+/-11 years underwent ABPM. They had been on home HD for 52.9+/-39 months and dialysed for 7.2+/-1.1 h thrice weekly. Two patients were taking antihypertensive drugs. Historical data on BP and weight gains were obtained from the patients' own records. Left ventricular (LV) mass was assessed by echocardiography and total body water (TBW) by bioelectrical impedance. RESULTS The mean 24-h BP was 129+/-17 mmHg (systolic) and 83+/-14 mmHg (diastolic). The daytime BP was 131+/-17 mmHg (systolic) and 84+/-14 mmHg (diastolic), while the night-time BP was 126+/-22 mmHg (systolic) and 81+/-17 mmHg (diastolic). Six patients (25%) had a normal circadian BP rhythm, but the rest showed a subnormal fall or an increase in BP at night. Mean 24-h BP did not correlate significantly with time on dialysis, dialysis session length, Kt/V, haemoglobin, interdialytic weight gain, or TBW. Twenty-one patients (87%) had LV hypertrophy and 16 of these had diastolic dysfunction. LV mass index was inversely correlated with nocturnal BP fall (r=-0.54, P=0.03). Non-dippers had been treated longer than dippers (29 vs 59.2 months, P=0.03) but they were similar in respect to age, dialysis session length or Hb concentration. CONCLUSIONS Long, slow haemodialysis at home provides satisfactory daytime BP control in the majority of patients without the need for antihypertensive drugs but abnormal circadian BP rhythm and LV hypertrophy remain common.
Ako: Decentralised Deep Learning with Partial Gradient Exchange

Distributed systems for the training of deep neural networks (DNNs) with large amounts of data have vastly improved the accuracy of machine learning models for image and speech recognition. DNN systems scale to large cluster deployments by having worker nodes train many model replicas in parallel; to ensure model convergence, parameter servers periodically synchronise the replicas. This raises the challenge of how to split resources between workers and parameter servers so that the cluster CPU and network resources are fully utilised without introducing bottlenecks. In practice, this requires manual tuning for each model configuration or hardware type. We describe Ako, a decentralised dataflow-based DNN system without parameter servers that is designed to saturate cluster resources. All nodes execute workers that fully use the CPU resources to update model replicas. To synchronise replicas as often as possible subject to the available network bandwidth, workers exchange partitioned gradient updates directly with each other. The number of partitions is chosen so that the used network bandwidth remains constant, independently of cluster size. Since workers eventually receive all gradient partitions after several rounds, convergence is unaffected. For the ImageNet benchmark on a 64-node cluster, Ako does not require any resource allocation decisions, yet converges faster than deployments with parameter servers.
Comparison of block and event‐related fMRI designs in evaluating the word‐frequency effect

Printed word frequency can modulate retrieval effort in a task requiring associative semantic judgment. Event‐related fMRI, while avoiding stimulus order predictability, is in theory statistically less powerful than block designs. We compared one event‐related and two block designs that evaluated the same semantic judgment task and found that similar brain regions demonstrated the word frequency effect. Although the responses were lower in amplitude, event‐related fMRI was able to detect the word frequency effect to a comparable degree compared to the block designs. The detection of a frequency effect with the event‐related design also suggests that stimulus–order predictability may not be as serious a concern in block designs as might be supposed. Hum. Brain Mapping 18:186–193, 2003. © 2003 Wiley‐Liss, Inc.
The Operational Global Icosahedral-Hexagonal Gridpoint Model GME: Description and High-Resolution Tests

The German Weather Service (Deutscher Wetterdienst) has recently developed a new operational global numerical weather prediction model, named GME, based on an almost uniform icosahedral‐hexagonal grid. The GME gridpoint approach avoids the disadvantages of spectral techniques as well as the pole problem in latitude‐ longitude grids and provides a data structure extremely well suited to high efficiency on distributed memory parallel computers. The formulation of the discrete operators for this grid is described and evaluations that demonstrate their second-order accuracy are provided. These operators are derived for local basis functions that are orthogonal and conform perfectly to the spherical surface. The local basis functions, unique for each grid point, are the latitude and longitude of a spherical coordinate system whose equator and zero meridian intersect at the grid point. The prognostic equations for horizontal velocities, temperature, and surface pressure are solved using a semi-implicit Eulerian approach and for two moisture fields using a semi-Lagrangian scheme to ensure monotonicity and positivity. In the vertical direction, finite differences are applied in a hybrid (sigma pressure) coordinate system to all prognostic variables. The semi-implicit treatment of gravity waves presented here leads to a 3D Helmholtz equation that is diagonalized into a set of 2D Helmholtz equations that are solved by successive relaxation. Most of the same physical parameterizations used in the authors’ previous operational regional model, named EM, are employed in GME. Some results from the verification process for GME are provided and GME performance statistics on a Cray T3E1200 as well as on the ECMWF Fujitsu VPP5000 systems are summarized. For the case of the severe Christmas 1999 storm over France and Germany the pronounced sensitivity of the model with respect to the initial state is discussed. Finally, a test case is shown where it is currently possible, though not yet operationally practical, to run GME at 15-km resolution on the VPP5000.
CMOS Leakage and Power Reduction in Transistors and Circuits: Process and Layout Considerations

Power reduction in CMOS platforms is essential for any application technology. This is a direct result of both lateral scaling—smaller features at higher density, and vertical scaling—shallower junctions and thinner layers. For achieving this power reduction, solutions based on process-device and process-integration improvements, on careful layout modification as well as on circuit design are in use. However, the drawbacks of these solutions, in terms of greater manufacturing complexity (and higher cost) and speed degradation, call for “optimized” solutions. This paper reviews the issues associated with transistor scaling and related solutions for leakage and power reduction in terms of topological design rules and layout optimization for digital and analog transistors. For standard cells and SRAMs cells, leakage aware layout optimization techniques considering transistor configuration, stressors, line-edge-roughness and more are presented. Finally, different techniques for leakage and power reduction at the circuit level are discussed.
The Intersexual Genetic Correlation for Lifetime Fitness in the Wild and Its Implications for Sexual Selection

Background The genetic benefits of mate choice are limited by the degree to which male and female fitness are genetically correlated. If the intersexual correlation for fitness is small or negative, choosing a highly fit mate does not necessarily result in high fitness offspring. Methodology/Principal Finding Using an animal-model approach on data from a pedigreed population of over 7,000 collared flycatchers (Ficedula albicollis), we estimate the intersexual genetic correlation in Lifetime Reproductive Success (LRS) in a natural population to be negative in sign (−0.85±0.6). Simulations show this estimate to be robust in sign to the effects of extra-pair parentage. The genetic benefits in this population are further limited by a low level of genetic variation for fitness in males. Conclusions/Significance The potential for indirect sexual selection is nullified by sexual antagonistic fitness effects in this natural population. Our findings and the scarce evidence from other studies suggest that the intersexual genetic correlation for lifetime fitness may be very low in nature. We argue that this form of conflict can, in general, both constrain and maintain sexual selection, depending on the sex-specific additive genetic variances in lifetime fitness.
The organization of behavior into temporal and spatial neighborhoods

The mot1 framework [1] is a system for learning behaviors while organizing them across a two-dimensional, topological map such that similar behaviors are represented in nearby regions of the map. The current paper introduces temporal coherence into the framework, whereby temporally extended behaviors are more likely to be represented within a small, local region of the map. In previous work, the regions of the map represented arbitrary parts of a single global policy. This paper introduces and examines several different methods for achieving temporal coherence, each applying updates to the map using both spatial and temporal neighborhoods, thus encouraging parts of the policy that commonly occur together in time to reside within a common region. These methods are analyzed experimentally in a setting modeled after a human behavior-switching game, in which players are rewarded for producing a series of short but specific behavior sequences. The new methods achieve varying degrees-in some cases high degrees-of temporal coherence. An important byproduct of these methods is the automatic decomposition of behavior sequences into cohesive groupings, each represented individually in local regions.
Rateless Erasure Code Based Secure Storage in Cloud Computing

--Cloud computing is a promising computing model that enables convenient and on-demand network access to a shared pool of configurable computing resources. The first offered cloud service is moving data into the cloud: data owners let cloud service providers host their data on cloud servers and data consumers can access the data from the cloud servers. This new paradigm of data storage service also introduces new security challenges, because data owners and data servers have different identities and different business interests. In this paper, to ensure the correctness of users’ data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of raptor coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). The proposed design further support secure and efficient dynamic operations on data block. Our result shows that, our proposed model provides a secure storage for data in cloud.
UV resonance Raman spectroscopy : a process analytical tool for host cell DNA and RNA dynamics in mammalian cell lines

BACKGROUND Recent advances in Raman spectroscopy have resulted in the development of rapid, in situ Raman probes that can identify and allow the assessment of the quality of complex constituents in mammalian cell culture. One specific Raman technique, UV resonance Raman (UVRR) spectroscopy, has potential as a probe for residual cellular DNA and RNA in mammalian cell culture medium. RESULTS Variations in DNA and RNA UVRR spectral profiles of medium-cellular footprint samples were identified and related to time of harvest and increased cell lysis that is associated with a loss in cell viability. Increased DNA and RNA were also observed in the cell culture supernatant in response to sodium butyrate treatment. Variation in DNA and RNA profiles as a result of both primary and secondary clarification methods during downstream bioprocessing could also be determined with UVRR spectroscopy. CONCLUSIONS This study has demonstrated the utility of UVRR spectroscopy as a tool to monitor variations in residual DNA and RNA that may contaminate cell culture medium. Application of this technique has the potential for both improvement of recovery techniques and assurance of reliable clearance of DNA/RNA to acceptable safety levels
Quantifying Tropical Dry Forest Type and Succession: Substantial Improvement with LiDAR

Improved technologies are needed to advance our knowledge of the biophysical and human factors influencing tropical dry forests, one of the world's most threatened ecosystems. We evaluated the use of light detection and ranging (LiDAR) data to address two major needs in remote sensing of tropical dry forests, i.e., classification of forest types and delineation of forest successional status. We evaluated LiDAR‐derived measures of three‐dimensional canopy structure and subcanopy topography using classification‐tree techniques to separate different dry forest types and successional stages in the Guánica Biosphere Reserve in Puerto Rico. We compared the LiDAR‐based results with classifications made from commonly used remote sensing data, including Landsat satellite imagery and radar‐based topographic data. The accuracy of the LiDAR‐based forest type classification (including native‐ and exotic‐dominated forest classes) was substantially higher than those from previously available data (kappa = 0.90 and 0.63, respectively). The best result was obtained when combining LiDAR‐derived metrics of canopy structure and topography, and adding Landsat spectral data did not improve the classification. For the second objective, we observed that LiDAR‐derived variables of vegetation structure were better predictors of forest successional status (i.e., mid‐secondary, late‐secondary, and primary forests) than was spectral information from Landsat. Importantly, the key LiDAR predictors identified within each classification‐tree model agreed with previous ecological knowledge of these forests. Our study highlights the value of LiDAR remote sensing for assessing tropical dry forests, reinforcing the potential for this novel technology to advance research and management of tropical forests in general.
Privacy Frost: A User-Oriented Data Anonymization Tool

A challenging task in privacy protection for public data is to realize an algorithm that generalizes a table according to requirements of a data user. In this paper, we propose an anonymization scheme for generating a k-anonymous and l-diverse table, and show evaluation results using three different tables. Our scheme is based on both top-down and bottom-up approaches for full-domain and partial-domain generalization, and the requirements are automatically incorporated into the generated table. The generated table meets user's requirements and can be employed in the services provided by users without any modification or evaluation.