Miracle-dz/UniFAR-FTUs huggingface dataset:
Complementary Interactions between Command-Like Interneurons that Function to Activate and Specify Motor Programs

Motor activity is often initiated by a population of command-like interneurons. Command-like interneurons that reliably drive programs have received the most attention, so little is known about how less reliable command-like interneurons may contribute to program generation. We study two electrically coupled interneurons, cerebral-buccal interneuron-2 (CBI-2) and CBI-11, which activate feeding motor programs in the mollusk Aplysia californica. Earlier work indicated that, in rested preparations, CBI-2, a powerful activator of programs, can trigger ingestive and egestive programs. CBI-2 reliably generated ingestive patterns only when it was repeatedly stimulated. The ability of CBI-2 to trigger motor activity has been attributed to the two program-promoting peptides it contains, FCAP and CP2. Here, we show that CBI-11 differs from CBI-2 in that it contains FCAP but not CP2. Furthermore, it is weak in its ability to drive programs. On its own, CBI-11 is therefore less effective as a program activator. When it is successful, however, CBI-11 is an effective specifier of motor activity; that is, it drives mostly ingestive programs. Importantly, we found that CBI-2 and CBI-11 complement each other's actions. First, prestimulation of CBI-2 enhanced the ability of CBI-11 to drive programs. This effect appears to be partly mediated by CP2. Second, coactivation of CBI-11 with CBI-2 makes CBI-2 programs immediately ingestive. This effect may be mediated by specific actions that CBI-11 exerts on pattern-generating interneurons. Therefore, different classes of command-like neurons in a motor network may make distinct, but potentially complementary, contributions as either activators or specifiers of motor activity.
Hypoxic Preconditioning Improves Survival of Cardiac Progenitor Cells: Role of Stromal Cell Derived Factor-1α–CXCR4 Axis

Background Cardiac progenitor cells (CPCs) have been shown to be suitable in stem cell therapy for resurrecting damaged myocardium, but poor retention of transplanted cells in the ischemic myocardium causes ineffective cell therapy. Hypoxic preconditioning of cells can increase the expression of CXCR4 and pro-survival genes to promote better cell survival; however, it is unknown whether hypoxia preconditioning will influence the survival and retention of CPCs via the SDF-1α/CXCR4 axis. Methods and Results CPCs were isolated from adult mouse hearts and purified by magnetic activated cell sorting using c-kit magnetic beads. These cells were cultured at various times in either normoxic or hypoxic conditions, and cell survival was analyzed using flow cytometry and the expression of hypoxia-inducible factor-1α (HIF-1α), CXCR4, phosphorylated Akt and Bcl-2 were measured by Western blot. Results showed that the expression of pro-survival genes significantly increased after hypoxia treatment, especially in cells cultured in hypoxic conditions for six hours. Upon completion of hypoxia preconditioning from c-kit+ CPCs for six hours, the anti-apoptosis, migration and cardiac repair potential were evaluated. Results showed a significant enhancement in anti-apoptosis and migration in vitro, and better survival and cardiac function after being transplanted into acute myocardial infarction (MI) mice in vivo. The beneficial effects induced by hypoxia preconditioning of c-kit+ CPCs could largely be blocked by the addition of CXCR4 selective antagonist AMD3100. Conclusions Hypoxic preconditioning may improve the survival and retention of c-kit+ CPCs in the ischemic heart tissue through activating the SDF-1α/CXCR4 axis and the downstream anti-apoptosis pathway. Strategies targeting this aspect may enhance the effectiveness of cell-based cardiac regenerative therapy.
Structuring time domain blind source separation algorithms for CASA integration

Most algorithms based on Computational Auditory Scene Analysis (CASA) for binaural speech separation do not have the ability to inhibit already localized and for a long time present sources in the auditory scene. This has the major drawback that the auditory cues of weaker and new sources are subject to interference from already localized and perceived signals and the separation performance is worse if the signals overlap in their processing domain. In this paper we outline how one can build intuitively a separation system that has this inhibition feature. The main block and starting point of our derivation is a simple cross correlation based localization system with two microphones. The inhibition is achieved by feeding back localization results to a filter and sum structure that cancels localized sounds. Interestingly, our intuitive approach leads to a special case of a well known time domain blind source separation algorithm which was derived from a statistical signal processing viewpoint and exhibits good convergence even in reverberant environments. Finally, we discuss how the insights gained from building a blind source separation this way can be used to integrate CASA techniques.
Sparse regression analysis of task-relevant information distribution in the brain

One of key topics in fMRI analysis is discovery of task-related brain areas. We focus on predictive accuracy as a better relevance measure than traditional univariate voxel activations that miss important multivariate voxel interactions. We use sparse regression (more specifically, the Elastic Net1) to learn predictive models simultaneously with selection of predictive voxel subsets, and to explore transition from task-relevant to task-irrelevant areas. Exploring the space of sparse solutions reveals a much wider spread of task-relevant information in the brain than it is typically suggested by univariate correlations. This happens for several tasks we considered, and is most noticeable in case of complex tasks such as pain rating; however, for certain simpler tasks, a clear separation between a small subset of relevant voxels and the rest of the brain is observed even with multivariate approach to measuring relevance.
Service users’ experiences and views of aggressive situations in mental health care: a systematic review and thematic synthesis of qualitative studies

Background Aggressive situations occurring within mental health services can harm service users, staff, and the therapeutic environment. There is a consensus that the aggression phenomenon is multidimensional, but the picture is still unclear concerning the complex interplay of causal variables and their respective impact. To date, only a small number of empirical studies include users’ views of relevant factors. The main objective of this review is to identify and synthesize evidence relating to service users’ experiences and views of aggressive situations in mental health settings. Methods We included qualitative studies of any design reporting on service users’ own experiences of conditions contributing to aggressive situations in mental health care and their views on preventative strategies. Eligible articles were identified through an electronic database search (PsycINFO, PubMed, Ovid Nursing Database, Embase, and CINAHL), hand search, and cross-referencing. Extracted data were combined and interpreted using aspects of thematic synthesis. Results We reviewed 5,566 records and included 13 studies (ten qualitative and three mixed methods). Service users recognized that both their own mental state and negative aspects of the treatment environment affected the development of aggressive situations. Themes were derived from experiential knowledge and included calls to be involved in questions regarding how to define aggression and relevant triggers, and how to prevent aggressive encounters effectively. The findings suggest that incidents are triggered when users experience staff behavior as custodial rather than caring and when they feel ignored. Conclusion The findings highlight the importance of staffs’ knowledge and skills in communication for developing relationships based on sensitivity, respect, and collaboration with service users in order to prevent aggressive situations. An important factor is a treatment environment with opportunities for meaningful activities and a preponderance of trained staff who work continuously on the development of conditions and skills for collaborative interaction with users.
Development of fire evacuation path selective using adaptive routing algorithms and RFID traffic cone-based observation with shadowing method

In this paper the Radio Frequency Identification (RFID) technology can be applied with the adaptive routings algorithms of fire evacuation paths selection and evaluation to inspect an efficiency of fire building protection system for fire evacuation monitoring report and fire protection system. The suitable path of all available fire evacuation paths in the building when fire explosion occurred is the main importance key not only for an efficiency of fire protection system management, but can be control the congestion situations, shortest evacuation time and safe for more life of all victims. The shortest path of all available fire evacuation paths are the first basically main criteria evaluation and second purposed is the real fire evacuation situation in this selective path that can be guarantee less congestion, safety and available path all time. The shortest path is computed by Dijkstra's algorithm and after that the weight of each connecting paths are updated by RFID traffic cone data based that are installed in each fire exit paths. The user with their RFID tags when passed in the fire evacuation paths are read by RFID traffic cone reader stations and send these data such as name, status, time arrival and other essential data to RFID data based via on Wi-Fi channel. In particular this paper is presented the shadowing model for estimating the indoor localizing with obstructed in building area of the RFID traffic cone stations that can be move to install along the all available fire evacuation paths easily. These RFID techniques can be deal with multi-users, multi-stations of RFID traffic cones and multi- fire evacuation paths. It provides an efficiency time management scheme with correct data reporting and can be work out in real time for fire protection system status. The data based is constructed for supporting to RFID tags of each fire protection product details, fire evacuation paths and can be mapping their localizing into the floor plan of the fire building automatically. Finally, the experiments are presented illustrating that the RFID traffic cone localization techniques may be improve for more accuracy estimation in real situation area while the fire evacuation path selection by shortest path algorithm can work well.
EMERGING AND PROSPERING TRENDS IN CRIME ANALYSIS AND INVESTIGATION SYSTEMS: A LITERATURE REVIEW

Crime analysis and investigation systems play a critical role in battling crime and war against terrorism. This paper is a detailed literature review on current crime analysis and investigation systems developed to date. The reviewed literature is divided into two broad categories, "ontologies" and "clustering and classification". The paper encompasses a detailed discussion on systems belonging to both categories. During literature review, it was discovered that over the years evolving crime systems took inspiration from their predecessors, in terms of functionality and features. Therefore, some interesting trends were identified. These trends gradually prospered with the passage of time, strengthening the capabilities of the evolving systems. This paper discusses these trends in detail, and also anticipates the key features and design for the future generation of crime systems.
Trace: Tennessee Research and CreativeExchange

Abstmct-In a field as rapidly growing as software engineering, the education problem splits into two mPjor parts-university education and industrid education. (Some of which is given at university locations, as short courses, but considered industrial education here.) Both parts draw on the same underlying disciplines and methoddogies. But the people involved-both teachers and students-have different objectives and characteristics. At the university level students are young, inexperienced, and datively homogeneous in background and abilities. At the industrial level, students are older, more experienced, and vary considerably in background and abilities. In this paper, we discuss the underlying commonalities and the overlaid differences of university and industrial education in soft-wpre engineering The commonalities in discipline and methodd-ogies invdve the study and understanding of the Software Process, as discussed in Section II of this special issue, and of the “Tods” and “Know How” discussed in Section HI. The differences are due to the characteristics and objectives of students, and show up on curricula content and structure and in course definition.
In the Pursuit of Effective Affective Computing: The Relationship Between Features and Registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a “dense” form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a “coarse” form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.
Identification of an ADAM17 Cleavage Region in Human CD16 (FcγRIII) and the Engineering of a Non-Cleavable Version of the Receptor in NK Cells

CD16a and CD16b are IgG Fc receptors expressed by human natural killer (NK) cells and neutrophils, respectively. Both CD16 isoforms undergo a rapid down-regulation in expression by ADAM17-mediated proteolytic cleavage upon cell activation by various stimuli. We examined soluble CD16 released from activated NK cells and neutrophils by mass spectrometric analysis, and identified three separate cleavage sites in close proximity at P1/P1′ positions alanine195/valine196, valine196/serine197, and threonine198/isoleucine199, revealing a membrane proximal cleavage region in CD16. Substitution of the serine at position 197 in the middle of the cleavage region for a proline (S197P) effectively blocked CD16a and CD16b cleavage in cell-based assays. We also show that CD16a/S197P was resistant to cleavage when expressed in the human NK cell line NK92 and primary NK cells derived from genetically-engineered human induced pluripotent stem cells. CD16a is a potent activating receptor and despite blocking CD16a shedding, the S197P mutation did not disrupt IgG binding by the receptor or its activation of NK92 cells by antibody-treated tumor cells. Our findings provide further characterization of CD16 cleavage by ADAM17 and they demonstrate that a non-cleavable version of CD16a can be expressed in engineered NK cells.
Learning to Rank : A Machine Learning Approach to Static Ranking

Over the last decade, the Web has grown exponentially in size. Unfortunately, the number of incorrect, spamming, and malicious sites has also grown rapidly. Despite of that, users continue to rely on the search engines to separate the good from the bad, and rank results in such a way the best pages are suggested first. The probably most prominent ranking methods is PageRank [4]. Although Google, the most popular search engine, ranking algorithm originally based on the PageRank algorithm, there has recently been work showing that PageRank may not perform any better than other simple measures on certain tasks. For example Amento et al. [1] found that simple features, such as the number of pages on a site, performed as well as PageRank. We will introduce and discuss two solutions, RankNet [2] and fRank [5], which follow a line of research completely different from PageRank, Hits [3] or other similar ranking algorithms which are based on link analysis. In [2] Burges et al. proposed RankNet, a probabilistic cost for training systems to learn ranking functions using pairs of training examples. In [5] Brill et al. combined all kinds of Web page’s features using RankNet to achieve a ranking system, called fRank (feature Rank), that according to their experiments, is significantly better than PageRank.
Infrastructure for poor people : public policy for private provision

The chapters in this book examine the data on infrastructure and the poor in developing countries and consider how policies centered on private provision can address their needs. Many of the chapters focus on the extent to which the poor have access to infrastructure services of reasonable quality, for example, to water that is safe to drink, to a reliable source of electricity, and to a nearby telephone. Access to such services is, of course, not the only infrastructure issue that matters to the poor; the poor who already have access to modern services care, for instance, about the price and reliability of those services. However, in most developing countries access is the key issue. In these countries most of the poor have no access to standard infrastructure services provided by utilities. Instead they often pay high prices for lower-quality substitutes: they might buy water by the bucket from a private vendor and use candles instead of electricity for lighting. They would rarely make a telephone call. The lack of ready access to good basic infrastructure services can directly reduce the well-being of the poor.
Theorem-Proving for Computers: Some Results on Resolution and Renaming

A considerable step forward in the development of theorem-proving by machine was taken by Robinson (1965) with the introduction of the resolution method. In this method the conjunction of the axioms and the negation of the theorem to be proved are in the usual way (cf. Davis, 1963) converted into a conjunction of so-called clauses, each clause being a disjunction of atoms (i.e. atomic predicates) which may or may not be negated. The arguments of these predicates are variables or constants or functions of these. For the theorem to be valid the conjunction of this set of clauses must be shown to be unsatisfiable. Previous methods (cf. Davis, 1963) used Herbrand's theorem directly by explicitly instantiating these clauses over a finite subset of the Herbrand universe of constants, and then attempting to show that the conjunction of the resulting set of clauses, the so-called ground clauses, led to a truth-functional contradiction. (A ground clause is any clause in which each variable has been replaced by a constant belonging to the Herbrand universe.) In Robinson's method, the test for unsatisfiability is carried out directly on the clauses, and not on their instantiated or ground versions. This is effected by the iteration of a single operation termed resolution. To describe this operation, let us—as is customary—term any atom or any negated atom a literal, and term two literals which are negations of each other complements. Resolution operates on two clauses, when one of them contains at least one literal whose complement is either contained in the other or can be generated in the other by some substitution for its arguments. When this is the case, a new clause known as the resolvent is formed from the two parent clauses, which consists of all the literals in the parents except the matched complementary pairs. (The arguments in some of the literals may, of course, have been changed if a substitution had been required for the matching.) Robinson's basic result is that if resolutions are carried out on the original set of clauses and the ones generated by these operations, then the original set is unsatisfiable if and only if an empty clause can be generated. So the theorem is proved when an empty clause has been generated.
Genetic rescue, the greater prairie chicken and the problem of conservation reliance in the Anthropocene

A central question in conservation is how best to manage biodiversity, despite human domination of global processes (= Anthropocene). Common responses (i.e. translocations, genetic rescue) forestall potential extirpations, yet have an uncertain duration. A textbook example is the greater prairie chicken (GRPC: Tympanuchus cupido pinnatus), where translocations (1992–1998) seemingly rescued genetically depauperate Illinois populations. We re-evaluated this situation after two decades by genotyping 21 microsatellite loci from 1831 shed feathers across six leks in two counties over 4 years (2010–2013). Low migration rates (less than 1%) established each county as demographically independent, but with declining-population estimates (4 year average N = 79). Leks were genetically similar and significantly bottlenecked, with low effective population sizes (average Ne = 13.1; 4 year Ne/N = 0.166). Genetic structure was defined by 12 significantly different family groups, with relatedness r = 0.31 > half-sib r = 0.25. Average heterozygosity, indicating short-term survival, did not differ among contemporary, pre- and post-translocated populations, whereas allelic diversity did. Our results, the natural history of GRPC (i.e. few leks, male dominance hierarchies) and its controlled immigration suggest demographic expansion rather than genetic rescue. Legal protection under the endangered species act (ESA) may enhance recovery, but could exacerbate political–economic concerns on how best to manage ‘conservation-reliant’ species, for which GRPC is now an exemplar.
Convergence of Gradient Descent for Low-Rank Matrix Approximation

This paper provides a proof of global convergence of gradient search for low-rank matrix approximation. Such approximations have recently been of interest for large-scale problems, as well as for dictionary learning for sparse signal representations and matrix completion. The proof is based on the interpretation of the problem as an optimization on the Grassmann manifold and Fubiny-Study distance on this space.
AN ARCHITECTURE FOR AN ADAPTIVE WEB-BASED LEARNING ENVIRONMENT

Adaptive web based systems are believed to be a promising challenge for efficient curricula. In this paper we present the architecture of a system designed and implemented. A part of the paper presents the mining techniques that are used to extract students’ preferences and the way their profile is created. The personalization processes used are briefly presented.