Miracle-dz/UniFAR-FTUs huggingface dataset:
MaxMin allocation via degree lower-bounded arborescences

We consider the problem of MaxMin allocation of indivisible goods. There are m items to be distributed among n players. Each player $i$ has a nonnegative valuation pij for an item j, and the goal is to allocate items to players so as to maximize the minimum total valuation received by each player. There is a large gap in our understanding of this problem. The best known positive result is an ~O(√ n)-approximation algorithm, while there is only a factor 2 hardness known. Better algorithms are known for the restricted assignment case where each item has exactly one nonzero value for the players. We study the effect of bounded degree for items: each item has a nonzero value for at most D players. We show that essentially the case D = 3 is equivalent to the general case, and give a 4-approximation algorithm for D = 2. The current algorithmic results for MaxMin Allocation are based on a complicated LP relaxation called the configuration LP. We present a much simpler LP which is equivalent in power to the configuration LP. We focus on a special case of MaxMin Allocation-a family of instances on which this LP has a polynomially large gap. The technical core of our result for this case comes from an algorithm for an interesting new optimization problem on directed graphs, MaxMinDegree Arborescence, where the goal is to produce an arborescence of large outdegree. We develop an nε-approximation for this problem that runs in nO(1/ε) time and obtain a a polylogarithmic approximation that runs in quasipolynomial time, using a lift-and-project inspired LP formulation. In fact, we show that our results imply a rounding algorithm for the relaxations obtained by t rounds of the Sherali-Adams hierarchy applied to a natural LP relaxation of the problem. Roughly speaking, the integrality gap of the relaxation obtained from t rounds of Sherali-Adams is at most n1/t. We are able to extend the latter result to a more general class of instances. Along the way, we prove a result about the existence of a perfect matching in a probabilistically pruned graph which may be of independent interest.
Clitoria ternatea L. as a Potential High Quality Forage Legume

Samples of Clitoria ternatea L. (Cunhã) were harvested at 35, 50, 70, and 90 d after a uniformity harvest in a field study designed as a completely randomized design with a total of 18 experimental plots. The dry matter yield of the whole plant was separated quantitatively into leaves, stems, and pods at each harvesting age. Chemical analyses and in vitro gas production kinetics were performed to assess the quality of the plant parts. Yields, chemical composition, and estimates of gas production parameters were analyzed by fitting a mixed statistical model with two types of covariance structures as follows: variance components and an unrestricted structure with heterogeneous variances. Fast and slow gas yielding pools were detected for both leaves and stems, but only a single pool was detected for pods. The homoscedasticity assumption was more likely for all variables, except for some parameters of the gas production kinetics of leaves and stems. There was no presence of typical pods at 35 and 50 d. In the leaves, the fibrous fractions were affected, whereas the non-fibrous fractions were unaffected by the harvesting age. The harvesting age affected the majority of the chemical constituents and gas kinetic parameters related to the stems. The leaves of this legume were the least affected part by the aging process.
ASOC: a scalable, single-chip communications architecture

As on-chip integration matures, single-chip system designers must not only be concerned with component-level issues such as performance and power, but also with on-chip system-level issues such as adaptability and scalability. Recent trends indicate that next generation systems will require new architectures and compilation tools that effectively deal with these constraints. In this paper, a new single-chip interconnect architecture, adaptive System-On-a-Chip, is described that not only provides scalable data transfer, but also can be easily reconfigured as application-level communication patterns change. An important aspect of the architecture is its support for compile-time, scheduled communication. To illustrate the benefits of the architecture, three DSP benchmarks have been mapped to candidate SoC devices of assorted sizes which contain the new interconnect architecture. The described interconnect architecture is shown to be up to 5 times more efficient than bus-based SoC interconnect architectures via parallel simulation. Additionally, a preliminary layout of our architecture is shown and derived area and performance parameters are presented.
Antagonism for a Highly Anthropomorphic Hand–Arm System

A novel approach to antagonism in robotic systems is introduced and investigated as the basis for an unequalled, highly anthropomorphic hand–arm system currently being developed. This hand–arm system, consisting of a 19-d.o. f. hand and a 7-d.o. f. flexible arm, will be based on antagonistic principles in order to study and mimic the human musculoskeletal system, as well as to advance safety in robotics.
Drawing phylogenetic trees in LATEX and Microsoft Word

UNLABELLED newicktree is a PSTricks-based LATEX package which enables phylogenetic trees described in the Newick format to be drawn directly into LATEX documents. mswordtree is a macro for producing phylogenetic trees using the drawing elements available in Microsoft Word. AVAILABILITY Both programs are available free from the John Innes Centre's Bioinformatics Research Group website at http://jic-bioinfo.bbsrc. ac.uk/bioinformatics-research/software/index.html. SUPPLEMENTARY INFORMATION A full user-guide for newicktree and installation and usage instructions for mswordtree and available at http://jic-bioinfo.bbsrc. ac.uk/bioinformatics-research/software/index.html
Genomic Control for Association Studies

Summary. A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with case‐control data and yet, like family‐based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly independent; and, by using Bayesian outlier methods, it circumvents the need for Bonferroni correction for multiple tests, leading to better performance in many settings while still constraining risk for false positives. The performance of our genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.
The Communications Skin: Challenges and Dangers for Ubiquitous Data Management 1

The recent technological advances in distributed information gathering from a given location or geographical region by deploying a large number of tiny microsensor nodes, and the progress of wireless communications along with the convergence of Internet technologies and mobile computing have totally reshaped the research and development agenda. This progress has created the anticipation for a communications skin, which will cover significant parts of our planet, and, similar to the human’s skin functionality, will gather information from its surroundings; it will process it, filter it, aggregate it, store it and finally make decisions based on it. The realization of such a vision requires the interplay of several disciplines, like hardware, communications and data management technologies. In this paper, will present the recent developments related to various critical aspects of data management in wireless sensor network environments. The main goal of the paper is to highlight the most important dimensions of the new era for information manipulation, which resulted from this networking paradigm and also to present the specific dangers for the privacy, which come out from the deployment of sensor networks.
Optional linear arrangement of circuit components

We study the problem of arranging circuit components on a straight line so as to minimize the total wire length needed to realize the inter component nets. Branch-and-bound and dynamic programming algorithms that find optimal solutions are presented. In addition, heuristic approaches including some that employ the Monte Carlo method are developed and an experimental evalua-
Using multiple sensor triads for enhanced misalignment estimation for portable and wearable devices

Some existing applications on smartphones and tablets use the accelerometers, gyroscopes, and magnetometers to provide basic indoor positioning solution starting from a known position for short time periods. However, this can be achieved only if the portable device is kept in a fixed orientation, which is unrealistic and inconvenient for the user. In unconstrained portable navigation, the mobile device orientation can be freely changed with respect to the human body without any constraints. In this paper, a novel method is proposed to estimate or enhance the heading misalignment angle between one or more smart device(s) and/or wearable appcessories and the moving platform (person or vehicle). An accurate estimation for heading misalignment angle enables users to change their devices' orientation freely with respect to their bodies without any constraint. Different test scenarios are conducted to assess the performance of the proposed technique including different use cases. The results clearly demonstrated the efficacy of the proposed technique in enabling real-time, continuous and reliable consumer localization indoors and outdoors with mobile device.
G0/G1 switch gene-2 regulates human adipocyte lipolysis by affecting activity and localization of adipose triglyceride lipase

The hydrolysis of triglycerides in adipocytes, termed lipolysis, provides free fatty acids as energy fuel. Murine lipolysis largely depends on the activity of adipose triglyceride lipase (ATGL), which is regulated by two proteins annotated as comparative gene identification-58 (CGI-58) and G0/G1 switch gene-2 (G0S2). CGI-58 activates and G0S2 inhibits ATGL activity. In contrast to mice, the functional role of G0S2 in human adipocyte lipolysis is poorly characterized. Here we show that overexpression or silencing of G0S2 in human SGBS adipocytes decreases and increases lipolysis, respectively. Human G0S2 is upregulated during adipocyte differentiation and inhibits ATGL activity in a dose-dependent manner. Interestingly, C-terminally truncated ATGL mutants, which fail to localize to lipid droplets, translocate to the lipid droplet upon coexpression with G0S2, suggesting that G0S2 anchors ATGL to lipid droplets independent of ATGL's C-terminal lipid binding domain. Taken together, our results indicate that G0S2 also regulates human lipolysis by affecting enzyme activity and intracellular localization of ATGL. Increased lipolysis is known to contribute to the pathogenesis of insulin resistance, and G0S2 expression has been shown to be reduced in poorly controlled type 2 diabetic patients. Our data indicate that downregulation of G0S2 in adipose tissue could represent one of the underlying causes leading to increased lipolysis in the insulin-resistant state.
Memory-Efficient Fully Coupled Filtering Approach for Observational Model Building

Generally, training neural networks with the global extended Kalman filter (GEKF) technique exhibits excellent performance at the expense of a large increase in computational costs which can become prohibitive even for networks of moderate size. This drawback was previously addressed by heuristically decoupling some of the weights of the networks. Inevitably, ad hoc decoupling leads to a degradation in the quality (accuracy) of the resultant neural networks. In this paper, we present an algorithm that emulates the accuracy of GEKF, but avoids the construction of the state covariance matrix-the source of the computational bottleneck in GEKF. In the proposed algorithm, all the synaptic weights remain connected while the amount of computer memory required is similar to (or cheaper than) the memory requirements in the decoupling schemes. We also point out that the new method can be extended to derivative-free nonlinear Kalman filters, such as the unscented Kalman filter and ensemble Kalman filters.
StubDroid: Automatic Inference of Precise Data-Flow Summaries for the Android Framework

Smartphone users suffer from insucient information on how commercial as well as malicious apps handle sensitive data stored on their phones. Automated taint analyses address this problem by allowing users to detect and investigate how applications access and handle this data. A current problem with virtually all those analysis approaches is, though, that they rely on explicit models of the Android runtime library. In most cases, the existence of those models is taken for granted, despite the fact that the models are hard to come by: Given the size and evolution speed of a modern smartphone operating system it is prohibitively expensive to derive models manually from code or documentation. In this work, we therefore present StubDroid, the first fully automated approach for inferring precise and efficient library models for taint-analysis problems. StubDroid automatically constructs these summaries from a binary distribution of the library. In our experiments, we use StubDroid-inferred models to prevent the static taint analysis FlowDroid from having to re-analyze the Android runtime library over and over again for each analyzed app. As the results show, the models make it possible to analyze apps in seconds whereas most complete re-analyses would time out after 30 minutes. Yet, StubDroid yields comparable precision. In comparison to manually crafted summaries, StubDroid's cause the analysis to be more precise and to use less time and memory.
Virtual Thread: Maximizing Thread-Level Parallelism beyond GPU Scheduling Limit

Modern GPUs require tens of thousands of concurrent threads to fully utilize the massive amount of processing resources. However, thread concurrency in GPUs can be diminished either due to shortage of thread scheduling structures (scheduling limit), such as available program counters and single instruction multiple thread stacks, or due to shortage of on-chip memory (capacity limit), such as register file and shared memory. Our evaluations show that in practice concurrency in many general purpose applications running on GPUs is curtailed by the scheduling limit rather than the capacity limit. Maximizing the utilization of on-chip memory resources without unduly increasing the scheduling complexity is a key goal of this paper. This paper proposes a Virtual Thread (VT) architecture which assigns Cooperative Thread Arrays (CTAs) up to the capacity limit, while ignoring the scheduling limit. However, to reduce the logic complexity of managing more threads concurrently, we propose to place CTAs into active and inactive states, such that the number of active CTAs still respects the scheduling limit. When all the warps in an active CTA hit a long latency stall, the active CTA is context switched out and the next ready CTA takes its place. We exploit the fact that both active and inactive CTAs still fit within the capacity limit which obviates the need to save and restore large amounts of CTA state. Thus VT significantly reduces performance penalties of CTA swapping. By swapping between active and inactive states, VT can exploit higher degree of thread level parallelism without increasing logic complexity. Our simulation results show that VT improves performance by 23.9% on average.
CVXPY: A Python-Embedded Modeling Language for Convex Optimization

CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy. org/ under the GPL license, along with documentation and examples.
Outcomes of an Agency-Developed Treatment Foster Care Model for Adolescents

Adolescents constitute a large proportion of youth in foster care, but few foster care models specifically concentrate on their developmental or treatment needs. This study examined outcomes for an agency-developed, theoretically based treatment foster care (TFC) model using de-identified administrative data from 612 youth discharged from care over a 3-year period using a structural equation modeling path analysis. Results indicate that youth enrolled in Pressley Ridge Treatment Foster Care (PR-TFC) improve in functioning from entry to discharge and that, overall, youth in PR-TFC treatment typically improve in day-to-day functioning as they age, and youth who enter the PR-TFC homes at an older age generally function better at discharge than younger youth who stayed comparable amounts of time. Additional results indicate that older youth, youth with a greater number of clinical diagnoses, youth with a lower pre-test Child and Adolescent Functional Assessment Scale (CAFAS) score, and youth of color spent more time in care, while older youth, youth with fewer clinical diagnoses, youth with lower pre-test CAFAS scores, and European American youth had lower post-test CAFAS scores, indicating better functioning at discharge. This article also provides an example of how administrative data can be used to develop practice-based evidence for a treatment model.
ININ Submission to Zero Cost ASR Task at MediaEval 2016

This paper details the experiments conducted to train an as good performing Vietnamese speech recognition system as possible using public domain data only, as a part of the Zero Cost task at MediEval 2016. We explored techniques related to audio preprocessing, use of speaker’s pitch information, data perturbation, for building subspace Gaussian mixture acoustic model which is known for estimating robust parameters when the amount of data is less, and also unsupervised adaptation, RNN language model based lattice rescoring and system combination using ROVER tec hnique.
Smart antennas and their impact on network and communication systems performance

This paper focuses on the interaction and integration of several critical components of a MANET using smart antenna systems. A MANET is a wireless network where the communicating nodes are mobile, and the network topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of adaptive antenna systems and their underlying signal processing algorithms. In fact, a major objective of this work is to study and document the overall efficiency of networks in terms of the antenna pattern and the length of the training sequence used by the beamforming algorithms. Furthermore, the paper presents strategies and algorithms to combat the effects of fading channels on the overall system performance.
Quasi-succinct indices

Compressed inverted indices in use today are based on the idea of gap compression: documents pointers are stored in increasing order, and the gaps between successive document pointers are stored using suitable codes which represent smaller gaps using less bits. Additional data such as counts and positions is stored using similar techniques. A large body of research has been built in the last 30 years around gap compression, including theoretical modeling of the gap distribution, specialized instantaneous codes suitable for gap encoding, and ad hoc document reorderings which increase the efficiency of instantaneous codes. This paper proposes to represent an index using a different architecture based on quasi-succinct representation of monotone sequences. We show that, besides being theoretically elegant and simple, the new index provides expected constant-time operations, space savings, and, in practice, significant performance improvements on conjunctive, phrasal and proximity queries.
Consultants in NHS Scotland: A Survey of Work Commitments, Remuneration, Job Satisfaction and Retirement Plans

Abstract Background and Aims: UK consultants have reported working long hours, increased stress and reduced morale. This study set out to elicit consultants' views on flexible working and to gather data on consultants' workloads, remuneration, job satisfaction and retirement plans. As such it is the first comprehensive study of consultants in NHS Scotland. Methods. The Information and Statistics Division of the Scottish Executive Health Dept provided a list of consultants working in NHS Scotland. Focus groups and interviews informed the design of a postal, self-completion, questionnaire. Results: The response rate was 61%. Almost two-thirds (65%) of respondents felt their workloads were unreasonable and unsustainable and 67% were unable to provide their desired standards of patient care. Two-thirds (67%) did not normally take meal breaks, 63% had insufficient time for outside interests, whilst 44% felt their health was being adversely affected. Many (84%) believed that some of their work could be delegated to someone less qualified but 79% agreed that there were insufficient staff to make this possible. The average planned retirement age was 60 years, with 23% describing their plans as definite and 70% as quite or very likely. When asked what might induce them to postpone retirement, 50% cited reduced workload/work intensity. Conclusions: In 2003, a majority of consultants in the UK voted in favour of the new consultant contract. This will improve consultant pay and introduce a standard 40-hour working week, including worked on-call. This should address tow of the main areas of consultant dissatisfaction in NHS Scotland. However, staff shortages will require to be addressed if the contract is to be successfully implemented.
Genetic algorithm for seismic velocity picking

We adopt genetic algorithm (GA) for velocity picking in reflection seismic data. Conventional seismic velocity picking was to pick a series of peaks in a seismic semblance image (stacking energy) by geophysicists. However, it took human efforts and time. Here, we transfer the velocity picking to a combinatorial optimization problem. The local peaks in time-velocity seismic semblance image are ordered in a sequence with time first, then velocity. We define a fitness function including the total semblance of picked points, and constraints on the number of picked points, interval velocity, and velocity slope. GA can find an individual with the highest fitness value, and the picked points form the best polyline. We use simulation data and Nankai real seismic data in the experiments. We sequentially find the best parameter settings of GA. The picking result by GA is good and close to the human picking result. The result of velocity picking by GA is used for the normal move-out (NMO) correction and stacking. The stacking result shows that the signal is enhanced. This method can improve the seismic data processing and interpretation.