Miracle-dz/UniFAR-FTUs huggingface dataset:
INDEFINITE COPOSITIVE MATRICES WITH EXACTLY ONE POSITIVE EIGENVALUE OR EXACTLY ONE NEGATIVE EIGENVALUE

Checking copositivity of a matrix is a co-NP-complete problem. This paper studies copositive matrices with certain spectral properties. It shows that an indefinite matrix with exactly one positive eigenvalue is copositive if and only if the matrix is nonnegative. Moreover, it shows that finding out if a matrix with exactly one negative eigenvalue is strictly copositive or not can be formulated as a combination of two convex quadratic programming problems which can be solved efficiently.
Domain-specific Web search with keyword spices

Domain-specific Web search engines are effective tools for reducing the difficulty experienced when acquiring information from the Web. Existing methods for building domain-specific Web search engines require human expertise or specific facilities. However, we can build a domain-specific search engine simply by adding domain-specific keywords, called "keyword spices," to the user's input query and forwarding it to a general-purpose Web search engine. Keyword spices can be effectively discovered from Web documents using machine learning technologies. The paper describes domain-specific Web search engines that use keyword spices for locating recipes, restaurants, and used cars.
An analysis of elite coaches’ engagement with performance analysis services (match, notational analysis and technique analysis)

Performance analysis has become increasingly more accessible to coaches across many levels of sport (Blaze et al 2004). The primary aim of this study was to investigate how performance analysis tools are used by elite sports coaches. A stratified sample of forty-six elite professional and semi-professional coaches were selected to complete an online-survey relating to their engagement with match, notational and technique analysis. Most coaches (68%) would be provided with a DVD or edited clips after every game, whilst 16% would receive this service following most games. Over 50% of coaches will use performance analysis tools to provide video clips for other coaches and their support staff (64%); provide a video of the opposition (68%); collate quantitative game data (64%); and use as a motivational DVD (55%). Just under half of the coaches (43%) would use some form of live coding and analysis during games, whilst 39% would also receive a written match report including game statistics. Performance analysis information informed the coaches’ short term planning (93%), medium term planning (80%) and long term planning (70%). 91% of coaches identified that their coaching philosophy would impact on their selection of KPI’s, whilst 43% also identified that their ‘gut instinct’ would often impact on their selection. The key findings from this study have provided specific insight relating to how and why elite coaches engage with performance analysts. In particular, these findings inform specifically on how performance analysis impacts on their coaching practices within a number of different contexts.
The Return of Character Education.

I ncreasing numbers of people across the ideological spectrum believe that our society is in deep moral trouble. The disheartening signs are everywhere: the breakdown of the family; the deterioration of civility in everyday life; rampant greed at a time when one in five children is poor; an omnipresent sexual culture that fills our television and movie screens with sleaze, beckoning the young toward sexual activity at ever earlier ages; the enormous betrayal of children through sexual abuse; and the 1992 report of the National Research Council that says the United States is now the most violent of all industrialized nations. As we become more aware of this societal crisis, the feeling grows that schools cannot be ethical bystanders. As a result, character education is making a comeback in American schools.
Cell Expansion-Mediated Organ Growth Is Affected by Mutations in Three EXIGUA Genes

Organ growth depends on two distinct, yet integrated, processes: cell proliferation and post-mitotic cell expansion. Although the regulatory networks of plant cell proliferation during organ growth have begun to be unveiled, the mechanisms regulating post-mitotic cell growth remain mostly unknown. Here, we report the characterization of three EXIGUA (EXI) genes that encode different subunits of the cellulose synthase complex specifically required for secondary cell wall formation. Despite this highly specific role of EXI genes, all the cells within the leaf, even those that do not have secondary walls, display small sizes in the exi mutants. In addition, we found a positive correlation between cell size and the DNA ploidy levels in exi mutant leaves, suggesting that both processes share some regulatory components. Our results are consistent with the hypothesis that the collapsed xylem vessels of the exi mutants hamper water transport throughout the plant, which, in turn, limits the turgor pressure levels required for normal post-mitotic cell expansion during leaf growth.
Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter

The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost. Since this algorithm is tested with long-term scalp EEG, it has the potential to achieve higher performance with intracranial EEG. The clinical value of this algorithm includes providing a pre-judgement to assist the doctor's diagnosis procedure and acting as a reliable warning system in a wearable device for epilepsy patients.
Nomadic pict: correct communication infrastructure for mobile computation

This paper addresses the design and verification of infrastructure for mobile computation. In particular, we study language primitives for communication between mobile agents. They can be classi ed into two groups. At a low level there are location dependent primitives that require a programmer to know the current site of a mobile agent in order to communicate with it. At a high level there are location independent primitives that allow communication with a mobile agent irrespective of any migrations. Implementation of the high level requires delicate distributed infrastructure algorithms. In earlier work with Wojciechowski and Pierce we made the two levels precise as process calculi, allowing such algorithms to be expressed as encodings of the high level into the low level; we built NOMADIC PICT, a distributed programming language for experimenting with such encodings. In this paper we turn to semantics, giving a de nition of the core language and proving correctness of an example infrastructure. This requires novel techniques: we develop equivalences that take migration into account, and reasoning principles for agents that are temporarily immobile (eg. waiting on a lock elsewhere in the system).
Assessing completion rates of EMT-Basic students using the Self-Directed Search

Assessing Completion Rates of EMT-Basic Students Using the Self-Directed Search by Rod Hackwith Dr. Cecilia Maldonado-Daniels, Committee Chair Associate Professor of Workforce Education and Development University of Nevada, Las Vegas With shrinking budgets and a need to demonstrate accountability to legislatures and boards of higher education, retention rates of students have been utilized by institutions of higher education to demonstrate their effectiveness and value. The purpose of this descriptive, exploratory study was to determine if specific personality types as identified by the Self-Directed Search (SDS) were more successful in completing an EMT-Basic course at the local community. Secondary data, collected as a pilot for the purpose of improving program retention, was based on information gathered from students (n=47) enrolled in an EMT-Basic class over the course of one semester where success rates were tracked in accordance with each students' occupational code as determined by the SDS. Social (S) and Realistic (R) types were the most predominant Holland code pairing and this group of students had a significantly higher pass rate than other codes of this group.
Syntactic Surprisal Affects Spoken Word Duration in Conversational Contexts

We present results of a novel experiment to investigate speech production in conversational data that links speech rate to information density. We provide the first evidence for an association between syntactic surprisal and word duration in recorded speech. Using the AMI corpus which contains transcriptions of focus group meetings with precise word durations, we show that word durations correlate with syntactic surprisal estimated from the incremental Roark parser over and above simpler measures, such as word duration estimated from a state-of-the-art text-to-speech system and word frequencies, and that the syntactic surprisal estimates are better predictors of word durations than a simpler version of surprisal based on trigram probabilities. This result supports the uniform information density (UID) hypothesis and points a way to more realistic artificial speech generation.
90° hybrid-coupler based phase-interpolation phase-shifter for phased-array applications at W-band and beyond

This paper presents a 90° hybrid-coupler based passive phase interpolator that is utilized to design a W-band 5-bit phase shifter in 0.13 μm SiGe BiCMOS process. In the proposed phase shifter, amplitude weighting is made first by VGAs. Then, a 90°-hybrid performs I/Q phase splitting and phase interpolation to synthesize all four quadrant phases. In this way, the accuracy of the phase synthesis is less vulnerable to an amplifier loading effect. Further, by cascading all building blocks with a low matched impedance the phase shifter will be less sensitive to parasitic capacitance, suitable for mm-Wave applications. The phase shifter is optimized for a transmitter application and the measured peak-to-peak gain variation for all 5-bit phase states is 4.8-9.7 dB at 94 GHz. The measured rms gain error is <; 1.6 dB over 93-108 GHz. The measured RMS phase error is <; 1.5° at 94 GHz. The input and output P-1dB is -13 dBm and -4.7 dBm, respectively, at 94 GHz. The chip consumes 37 mW from 2.2 V supply voltage. The chip size is 1.87×0.75 mm2.
Individualism, acceptance and differentiation as attitude traits in the public’s response to vaccination

The attitude of the general public to vaccination was evaluated through a survey conducted on a representative sample of the Israeli population (n = 2,018), in which interviewees were requested to express their standpoints regarding five different vaccination programs. These included: pandemic influenza vaccination, seasonal influenza vaccination, travel vaccines, Human Papilloma Virus vaccine and childhood vaccinations. Analysis of the responses reveal three major attitude traits: a) acceptance, characterized by the opinion that targets should be vaccinated; b) individualism, characterized by the opinion that vaccination should be left to personal choice; and c) differentiation, characterized by the tendency to express different attitudes when addressing different vaccination programs. Interestingly, direct opposition to vaccination was found to be a minor attitude trait in this survey. Groups within the population could be defined according to their tendency to assume these different attitudes as Acceptors, Judicious-acceptors, Differentiators, Soft-individualists, and Hard-individualists. These groups expressed different standpoints on all five vaccination programs as well as on other health recommendations, such as screening for early detection of cancer. Attitude traits could be also correlated, to a certain extent, with actual compliance with vaccination programs. Interestingly, attitudes to vaccination were not correlated with social profiles related to income or education, although younger individuals exhibited higher degrees of individualism and differentiation. Taken together, all this is in accordance with the current social settings, underlining the individual's tendency for critical evaluation and self-stirring. This should be taken into consideration by health authorities involved in vaccination programs.
Retrovirus-mediated gene transfer of human adenosine deaminase: expression of functional enzyme in murine hematopoietic stem cells in vivo

Simplified Moloney murine leukemia virus-based recombinant retrovirus vectors have been constructed which transduce human adenosine deaminase (ADA) cDNA. ADA transcription is under the control of the constitutive promoter for the human X chromosome phosphoglycerate kinase (pgk) gene. In these simplified vectors, dominant selectable markers are not included and selection is dependent on overproduction of functional ADA enzyme. Primary murine hematopoietic cells were infected with helper-free recombinant ADA virus generated from Psi-2 packaging cells. Protein analysis revealed that human ADA enzyme was expressed in progenitor-derived hematopoietic colonies in vitro and CFU-S-derived spleen colonies in vivo. Enzyme expression was dependent on transcription from the pgk promoter. ADA expression in primary murine hematopoietic cells directed by the internal promoter was not adversely affected by the presence of the Moloney virus long terminal repeat enhancer sequence. Use of these vectors allows systematic evaluation of the effects of specific sequences in recombinant retrovirus vectors on expression in primary murine hematopoietic cells in vivo.
Analyzing the impact of power infrastructure failures on cloud application availability

The widespread adoption of cloud computing has been driven by perceived advantages in agility and scalability inherent in cloud computing. For hyperscale cloud service providers, managing the high expectations of customers and the damage resulting from service outages is an increasing and critical challenge. Data power failure is a significant risk to cloud service availability. This paper examines the relationship between power infrastructure architectures and software application availability in a hyperscale data center. Using sensitivity analysis, we define four power infrastructure architectures and analyse the impact of power infrastructure failures on applications hosted in a hyperscale data center. We use Stochastic Petri Net (SPN) models to represent the power infrastructure behavior, and Reliability Block Diagrams (RBD) to represent application availability. Results from stationary analysis suggest that the availability gain on a highly redundant architecture varies depending on the application type.
Implicit Privatization Using Private Transactions

In software transactional memory (STM) systems, it is useful to isolate a memory region accessed by one thread from all others, so that it can then operate on it “privately”, that is, without the instrumentation overhead of inter-transactional synchronization. Allowing transactions to implicitly privatize memory is a source of major performance degradation in state-of-the-art STMs. The alternative, to explicitly declare and guarantee privacy only when needed, has been argued to be too tricky to be useful for general programming. This paper proposes private transactions, a simple intermediate that combines the ease of use of implicit privatization, with the efficiency that can be obtained from explicitly knowing which regions are private. We present a new scalable quiescing algorithm for implicit privatization using private transactions, applicable to virtually any STM algorithm, including the best performing TL2/LSA-style STMs. The new algorithm delivers virtually unhindered performance at all privatization levels when private transactions involve work, and even under the extreme case of empty private transactions, allows for a scalable “pay as you go” privatization overhead depending on the privatization level.
Universal conditions for nonlinear refractive index n/sub 2/ estimation of dispersion compensating fibers by CW-SPM method

Universal conditions for nonlinear refractive index n/sub 2/ estimation of dispersion compensating fibers by continuous wave (CW)-SPM method are investigated theoretically and experimentally. It is clarified that the required fiber length and the minimum power for n/sub 2/ estimation can be expressed as simple functions in terms of chromatic dispersion D. Moreover, it is experimentally confirmed that the present conditions for n/sub 2/ estimation are reasonable and that the n/sub 2/ value of DCF longer than the required fiber length is underestimated.
Extraction of key postures using shape contexts

There has been steady effort to modelize or recognize human action in fields of computer visions or mechanical learning, which should lead to fruitful results. This study presents how to extract key postures that can explain human actions within video sequence. To detect key postures that can differentiate human actions significantly, we select key posture candidates using information entropy which is a global feature, and then during key posture matching using shape context, we can select critical key postures. The method proposed shows efficiency in the experimental results and will contribute to development of research by inferring human action through connection of key postures with respect to human action.
Towards Component-Based Design of Safety-Critical Cyber-Physical Applications

Cyber-physical systems typically involve a large number of mobile autonomous devices that closely interact with each other and their environment. Standard design and development techniques from the embedded domain fail to accurately model the dynamics of such systems and, hence, there is an increasing need for new programming models and abstractions. Component-based design approaches are a promising solution to manage the complexity of large-scale dynamic systems. However, existing such approaches either do not accurately model transitory interactions between components -- which are typical of cyber-physical systems -- or do not provide guarantees for real-time behavior which is essential in many safety-critical applications. To overcome this problem, in this paper, we present a component-based design technique based on DEECo (Dependable Emergent Ensembles of Components). The DEECo framework allows modeling large-scale dynamic systems by a set of interacting components. In contrast to other component-based design approaches from the literature, DEECo provides mechanisms to describe transitory interactions between components. We introduce necessary extensions to the DEECo design flow and integrate it with real-time analysis techniques that allow reasoning about timing behavior at the component-description level. Finally, we illustrate the simplicity and usefulness of our approach on a case study consisting of an intelligent crossroad system.
Multistability in perception: binding sensory modalities, an overview

This special issue presents research concerning multistable perception in different sensory modalities. Multistability occurs when a single physical stimulus produces alternations between different subjective percepts. Multistability was first described for vision, where it occurs, for example, when different stimuli are presented to the two eyes or for certain ambiguous figures. It has since been described for other sensory modalities, including audition, touch and olfaction. The key features of multistability are: (i) stimuli have more than one plausible perceptual organization; (ii) these organizations are not compatible with each other. We argue here that most if not all cases of multistability are based on competition in selecting and binding stimulus information. Binding refers to the process whereby the different attributes of objects in the environment, as represented in the sensory array, are bound together within our perceptual systems, to provide a coherent interpretation of the world around us. We argue that multistability can be used as a method for studying binding processes within and across sensory modalities. We emphasize this theme while presenting an outline of the papers in this issue. We end with some thoughts about open directions and avenues for further research.
WHITE MATTER SEGMENTATION OF BRAIN MRI DURING INFANCY

The objective of this study is the development of an automatic segmentation framework to measure the volume changes in white matter tissue from premature infant MRI data. Due to the early stage of the developing brain which results in a high water content in brain tissue, several major computational challenges arise including artefacts, intensity variations and partial volume effect. The first component of the framework is the development of a novel brain extraction method [1] [2]. Due to the overlapping of intensity values across different brain tissues, a primary challenge is the removal of non-brain tissue such as skull, fluid, fat and body parts. The second component involves the intensity inhomogeneities called bias field and has a significant effect on the segmentation. The intensity variations described as a low-frequency multiplicative artefact is a result of the inhomogeneity in the magnetic field during the MRI acquisition. The last component is a novel probabilistic model which segments and measures the white matter volume. The key element is the classification of the partial volume voxels which is achieved by an expectation-maximization algorithm combined with a probabilistic segmentation scheme. Examples of each step of this framework are presented in Fig. 1. Figure 1: Some results of the three steps of the framework are presented; (A) and (E) are original images of two different premature infants, (B) and (F) show the results of the brain extraction algorithm, (C) and (G) demontrate the correction of the corrupted bias field; (D) and (H) demontrate final results in which the contours of the white matter are marked in red.
Distributed Optimal Lexicographic Max-Min Rate Allocation in Solar-Powered Wireless Sensor Networks

Understanding the optimal usage of fluctuating renewable energy in wireless sensor networks (WSNs) is complex. Lexicographic max-min (LM) rate allocation is a good solution but is nontrivial for multihop WSNs, as both fairness and sensing rates have to be optimized through the exploration of all possible forwarding routes in the network. All current optimal approaches to this problem are centralized and offline, suffering from low scalability and large computational complexity—typically solving O(N2) linear programming problems for N-node WSNs. This article presents the first optimal distributed solution to this problem with much lower complexity. We apply it to solar-powered wireless sensor networks (SP-WSNs) to achieve both LM optimality and sustainable operation. Based on realistic models of both time-varying solar power and photovoltaic-battery hardware, we propose an optimization framework that integrates a local power management algorithm with a global distributed LM rate allocation scheme. The optimality, convergence, and efficiency of our approaches are formally proven. We also evaluate our algorithms via experiments on both solar-powered MICAz motes and extensive simulations using real solar energy data and practical power parameter settings. The results verify our theoretical analysis and demonstrate how our approach outperforms both the state-of-the-art centralized optimal and distributed heuristic solutions.