Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the deconstruction of M theory

We argue that there is an equivalence of M-theory on T3 × AN−1 with a four-dimensional non-supersymmetric quiver gauge theory on the Higgs branch. The quiver theory in question has gauge group SU(N)N4N6N8 and is considered in a strong coupling and large N4,6,8 limit. We provide field- and string-theoretical evidence for the equivalence making use of the deconstruction technique. In particular, we find wrapped M2-branes in the mass spectrum of the quiver theory at low energies.
Emerging Concepts in Immune Thrombocytopenia

Immune thrombocytopenia (ITP) is an autoimmune disease defined by low platelet counts which presents with an increased bleeding risk. Several genetic risk factors (e.g., polymorphisms in immunity-related genes) predispose to ITP. Autoantibodies and cytotoxic CD8+ T cells (Tc) mediate the anti-platelet response leading to thrombocytopenia. Both effector arms enhance platelet clearance through phagocytosis by splenic macrophages or dendritic cells and by induction of apoptosis. Meanwhile, platelet production is inhibited by CD8+ Tc targeting megakaryocytes in the bone marrow. CD4+ T helper cells are important for B cell differentiation into autoantibody secreting plasma cells. Regulatory Tc are essential to secure immune tolerance, and reduced levels have been implicated in the development of ITP. Both Fcγ-receptor-dependent and -independent pathways are involved in the etiology of ITP. In this review, we present a simplified model for the pathogenesis of ITP, in which exposure of platelet surface antigens and a loss of tolerance are required for development of chronic anti-platelet responses. We also suggest that infections may comprise an important trigger for the development of auto-immunity against platelets in ITP. Post-translational modification of autoantigens has been firmly implicated in the development of autoimmune disorders like rheumatoid arthritis and type 1 diabetes. Based on these findings, we propose that post-translational modifications of platelet antigens may also contribute to the pathogenesis of ITP.
Psychophysical Chromatic Mechanisms in Macaque Monkey

Chromatic mechanisms have been studied extensively with psychophysical techniques in humans, but the number and nature of the mechanisms are still controversial. Appeals to monkey neurophysiology are often used to sort out the competing claims and to test hypotheses arising from the experiments in humans, but psychophysical chromatic mechanisms have never been assessed in monkeys. Here we address this issue by measuring color-detection thresholds in monkeys before and after chromatic adaptation, employing a standard approach used to determine chromatic mechanisms in humans. We conducted separate experiments using adaptation configured as either flickering full-field colors or heterochromatic gratings. Full-field colors would favor activity within the visual system at or before the arrival of retinal signals to V1, before the spatial transformation of color signals by the cortex. Conversely, gratings would favor activity within the cortex where neurons are often sensitive to spatial chromatic structure. Detection thresholds were selectively elevated for the colors of full-field adaptation when it modulated along either of the two cardinal chromatic axes that define cone-opponent color space [L vs M or S vs (L + M)], providing evidence for two privileged cardinal chromatic mechanisms implemented early in the visual-processing hierarchy. Adaptation with gratings produced elevated thresholds for colors of the adaptation regardless of its chromatic makeup, suggesting a cortical representation comprised of multiple higher-order mechanisms each selective for a different direction in color space. The results suggest that color is represented by two cardinal channels early in the processing hierarchy and many chromatic channels in brain regions closer to perceptual readout.
Maternal body mass index and gestational weight gain and their association with perinatal outcomes in Viet Nam.

OBJECTIVE To examine the association between gestational weight gain and maternal body mass index (BMI) among Vietnamese women and the risk of delivering an infant too small or too large for gestational age. METHODS A prospective health-facility-based study of 2989 pregnant Vietnamese women was conducted in the city of Nha Trang in 2007-2008. Cubic logistic regression was used to investigate the association of interest. Infants were classified into weight-for-gestational-age categories according to weight centiles for the Asian population. Gestational age was based on the date of last menstrual period and adjusted by the results of first-trimester ultrasound. FINDINGS BMI was low (< 18.5), normal (18.5-22.9) and high (≥ 23.0) in 26.1%, 65.4% and 8.5% of the women, respectively. In each of these BMI categories, the percentage of women who delivered infants too small for gestational age was 18.1, 10.0 and 9.4, respectively, and the mean gestational weight gain was 12.5 kg (standard deviation, SD: ± 3.6), 12.2 kg (SD: ± 3.8) and 11.5 kg (SD: ± 4.7), respectively. Among women with low BMI, the risk of delivering an infant too small for gestational age ranged from approximately 40% if the gestational weight gain was < 5 kg to 20% if it was 5-10 kg. CONCLUSION Having a low BMI, commonly found in Viet Nam, puts women at risk of delivering an infant too small for gestational age, especially when total maternal gestational weight gain is < 10 kg.
25C-NBOMe: Preliminary Data on Pharmacology, Psychoactive Effects, and Toxicity of a New Potent and Dangerous Hallucinogenic Drug

Introduction. The use of novel psychoactive substances (NPSs) has rapidly increased as well as their online availability. The aim of this paper is to provide a comprehensive review of the nature and the risks associated with 25C-NBOMe, which has recently appeared in the drug market. Methods. A systematic analysis of the scientific literature and a qualitative assessment of online and media resources (e.g., e-newsgroups, chat-rooms, and e-newsletters) in 10 languages were carried out. Results. 25C-NBOMe is sold online as legal LSD or as research chemical with different designations such as “Boom,” “Pandora,” “Holland film,” or “N-bomb. ” It is a partial agonist of 5-HT2A receptors. It is usually ingested orally/sublingually and, less commonly, nasally, through injection, vaginally, rectally, and smoked. Its effects include sublingual numbing, stimulation, “body high,” hallucinations, dissociation, and anxiety. 25C-NBOMe presents high risk of overdoses; acute toxicity and fatalities have been reported. Conclusions. 25C-NBOMe consumption represents an emerging phenomenon with potential harmful effects. Its use is increased by its online availability at low costs. Health and other professionals should be informed about this new trend of substance use.
Understanding college females' intrinsic motives for physical activity: A qualitative comparison between athletes and non-athletes

The purpose of the current research was to use a qualitative-methodological approach to understand attraction to physical activity in a sample of collegiate females. Attraction to physical activity, or motivation, can be grounded in the self-determination theory (SDT). Based on these results, the secondary purpose was to examine the similarities and differences between collegiate female athletes and non-athletes regarding attraction to physical activity. Participants included eight female athletes and eight female non-athletes. The interviews revealed two overarching themes: attraction and aversion to physical activity, each with subthemes. Understanding motives to engage in physical activity can help program planners create tailored interventions to improve overall exercise adherence. Clinical and collegiate relevance and limitations are discussed as are future research and program implementation suggestions.
A "constrain and move" approach to distributed object manipulation

Studying the system dynamics, this research is an attempt to understand and design the basic robot behavior, information system, and distributed cooperation strategies required by a group of cooperative behavior-based mobile robots for handling an object. A new concept to develop distributed cooperation strategies to carry a load is introduced. In this method, the task of transferring the object is divided into two independent executable subtasks: constraining and moving the load. Each subtask is assigned to a group of distributed mobile robots. Based on this idea (constrain-move concept), two distributed cooperation strategies to turn the object about a fixed point and to move it along a straight line are introduced. The constrain-move concept is generalized for lifting and lowering the object. It is noted that weight of the payload can be used by the robots as a natural constraint on the object. Utilizing this natural constraint, a distributed cooperation strategy and an information system to lift and lower the object are introduced. The coordination protocols are devised in such a way that the robots can control movements of the object using their own sensory information and some static data communicated between the team members. Simulation and experimental results are given to support the proposed approach.
Mixed-integer evolution strategy using multiobjective selection applied to warehouse design optimization

This paper reports about the application of a new variant of multiobjective Mixed-Integer Evolution Strategy to a warehouse design optimization problem. The algorithm is able to deal with real-valued, integer, and discrete nominal input variables in a multiobjective problem, and utilizes a multiobjective selection procedure based on either crowding distance or hypervolume contribution (also called S metric). The warehouse design optimization problem investigated in this study is represented by a warehouse simulator (provided by our collaboration partner) which calculates four warehouse performance measures: total handling time, crate fill rate, order latency, and investment cost. Two of those are treated as objectives, while the other two are represented as constraints. As demonstrated by the results, the algorithm generates solutions which cover the whole Pareto front, as opposed to the expert-generated solutions. Moreover, the algorithm is able to find solutions which improve on the expert-generated solutions with respect to both objectives.
Augmenting sensitivity analysis for embedded applications by program level derivation of process parameters

From the perspective of scheduling the design and development of real-time applications is straightforward. Given the software architecture in terms of a process model and the respective process parameters a variety of methods are available to decide whether the real-time constraints of an application are satisfied or not. However, in practice of application design and development we are unable to follow this straightforward principle. Instead, in the course of a project a lot of pragmatism, experience-based variation and systematic testing finally lead to acceptable solutions. More or less in the last decade those refinement steps have gained scientific interest and emerged towards the so called sensitivity analysis for real-time systems. On one hand we are convinced that sensitivity analysis, as it is applied today, contributes valuable insights into the variation potential of an application-specific software architecture. On the other hand it is obvious that due to the architecture-based approach sensitivity analysis operates at the same level of abstraction as schedulability analysis does. So, both methods neglect lower levels of abstraction which are needed to derive process parameters, first of all execution times and periods. As there already exists a vast stock of methods for the derivation of execution times this paper focusses on the systematic calculation of periods. The approach operates on the abstraction level of programming and follows the objective that programmed actions are responsible for quality criterions in its application environment. To achieve this objective all time-and value-dependent deviations of sensor/actor systems and the computations system have to be formalized to be taken into account.
Cache injection for parallel applications

For two decades, the memory wall has affected many applications in their ability to benefit from improvements in processor speed. Cache injection addresses this disparity for I/O by writing data into a processor's cache directly from the I/O bus. This technique reduces data latency and, unlike data prefetching, improves memory bandwidth utilization. These improvements are significant for data-intensive applications whose performance is dominated by compulsory cache misses. We present an empirical evaluation of three injection policies and their effect on the performance of two parallel applications and several collective micro-benchmarks. We demonstrate that the effectiveness of cache injection on performance is a function of the communication characteristics of applications, the injection policy, the target cache, and the severity of the memory wall. For example, we show that injecting message payloads to the L3 cache can improve the performance of network-bandwidth limited applications. In addition, we show that cache injection improves the performance of several collective operations, but not all-to-all operations (implementation dependent). Our study shows negligible pollution to the target caches.
Indexing Uncertain Data in General Metric Spaces

In this study, we deal with the problem of efficiently answering range queries over uncertain objects in a general metric space. In this study, an uncertain object is an object that always exists but its actual value is uncertain and modeled by a multivariate probability density function. As a major contribution, this is the first work providing an effective technique for indexing uncertain objects coming from general metric spaces. We generalize the reverse triangle inequality to the probabilistic setting in order to exploit it as a discard condition. Then, we introduce a novel pivot-based indexing technique, called UP-index, and show how it can be employed to speed up range query computation. Importantly, the candidate selection phase of our technique is able to noticeably reduce the set of candidates with little time requirements. Finally, we provide a criterion to measure the quality of a set of pivots and study the problem of selecting a good set of pivots according to the introduced criterion. We report some intractability results and then design an approximate algorithm with statistical guarantees for selecting pivots. Experimental results validate the effectiveness of the proposed approach and reveal that the introduced technique may be even preferable to indexing techniques specifically designed for the euclidean space.
Adaptive Motion Detectors Inspired By Insect Vision

Introduction Inventions such as miniature unmanned aerial vehicles would extend our capabilities in a variety of areas and are a major focus of active research. Before their promise can be reached, however, significant challenges in guidance and control, flight mechanisms, and energy storage must be overcome. Engineers and scientists are turning to animals, particularly insects, for inspiration about how evolution has solved these problems. Our group believes that understanding the visual system of the fly will provide solutions for building a small and efficient visual system suited for real-time flight control. We are therefore investigating the algorithms used in visual motion detection and course stabilization implemented in neural hardware by the fly and translating the concepts into software and analog, “neuromorphic” VLSI electronic implementations. The present work shows that flies implement an adaptive contrast gain control on visual signals before performing motion detection, resulting in neural responses that signal velocity largely independently of overall contrast in the visual input. Additionally, we describe a circuit that implements a proposed mechanism of adaptive contrast gain control based on our neurobiological findings.
Detecting and Locating of Brain Abnormality in MR Images Using Texture Feature Analysis and Improved Probabilistic Relaxation Methods

Medical imaging has become a major tool in clinical trials since it enables rapid diagnosis with visualization and quantitative assessment. In the study, a detecting method of brain abnormality is proposed through magnetic resonance imaging. The proposed method is composed of four procedures. First the preprocessing is employed to remove noises and enhance the homogeneity of soft tissues. After preprocessing, we adopt the spatial gray level dependence method to compute four texture features of each image. Then, the improved probability relaxation method is applied to discriminate the brain abnormality with extracted texture information. The isolated noises are removed by using neighborhood processing. Final the performance of the improved method has been evaluated and compared to the original method. This proposed method performs better results than the other one, which can be used in further processing stages. We have developed a computer-aided detection system to distinguish the tumor and find the location and coarse contour from brain MRIs. The system can assist doctors to diagnose whether the brain has abnormal and train inexperienced doctors. The proposed algorithm can play a useful role for storage, filtering and indexing of mass MRI data, and furthermore it provides an initial step to find accurate tumor boundaries. Key-Words: Computer-Aided Detection System, Texture Feature Analysis, Spatial Gray Level Dependence, Probability Relaxation Method, Magnetic Resonance Image, Brain Tumor
Review of Combinatorial Optimization - Theory and Algorithms

Rarely do mathematical disciplines have so direct practical relevance as combinatorial optimizations, which is why it is one of the most active areas of discrete mathematics. It became a subject in its own right only about 50 years ago, which makes it one of the youngest also.This book covers most of the important results and algorithms achieved in the field to date. Most of the problems are formulated in terms of graphs and linear programs. The book starts with reviewing basic graph theory and linear and integer programming. Next, the classical topics in the field are studied: minimum spanning trees, shortest paths, network flows, matching and matroids.Most of the problems in Chapters 6-14 have polynomial time (efficient) algorithms, while most of the problems studied in Chapters 15-21 are NP-hard, i.e. polynomial time algorithm is unlikely to exist. Although in many cases approximation algorithms are offered which at least have guaranteed performance.Some of the topics include areas which have developed very recently, and which have not appeared in a book before. Examples are algorithms for multicommodity flows, network design problems and the traveling salesman problem. The book also contains some new results and new proofs for previously known results.The authors have an unique approach in the presentation of the topics. They provided detailed proofs for almost all results, including deep classical theorems (e.g. weighted matching algorithm and Karmarkar-Karp bin-packing algorithm) whose proofs are usually sketched in previous works.
Combining dynamic data with physical biometric verification to counteract spoofing

Current physical biometric verification systems are hampered by a major vulnerability: spoofing. Keepi ng biological information, such as the face, fingerpri nts, and irises, concealed from others in daily lif e is difficult, and therefore theft and counterfeit of exposed biologic al nformation can be relatively easily accomplishe d by first capturing an individual’s targeted information as an image an d then using the data to reproduce a model. Here, I propose a new method of physical biometric verification that uses dynamic data which are difficult to spoof. This ba sic concept can be applied to several types of biometric verification, such as those based on finger geometry, finger vei ns, irises, and the contour of the eyelid. I also propose an algorithm for this new verification method and provide experi mental examples of its application.
Tax Incidence

This chapter reviews the concepts, methods, and results of studies that analyze the incidence of taxes. The purpose of such studies is to determine how the burden of a particular tax is allocated among consumers through higher product prices, workers through a lower wage rate, or other factors of production through lower rates of return to those factors. The methods might involve simple partial equilibrium models, analytical general equilibrium models, or computable general equilibrium models. We review partial equilibrium models, where the burden of a tax is shown to depend on the elasticity of supply relative to the elasticity of demand. In particular, we consider partial equilibrium models with imperfect competition. Turning to a general equilibrium setting, we review the classic model of Harberger (1962) and illustrate its generality by applying it to a number of different contexts. We also use this model to demonstrate the practicality of analytical general equilibrium modeling through the use of log linearization techniques. We then turn to dynamic models to show how a tax on capital affects capital accumulation, future wage rates, and overall burdens. Such models might also provide analytical results or computational results. We also focus on relatively recent models that calculate the lifetime incidence of taxes, with both intratemporal and intertemporal redistribution. Finally, the chapter reviews the use of incidence methods and results in the policy process.
Use of Grounded Theory in Information Systems Area: An Exploratory Analysis

Lately, Grounded Theory method is gaining importance as a method for theory building. However, its application is not free of criticism due to lack of rigour and formality in research procedures and description of results. We analysed four cases were Grounded Theory method was used and, for each case, we identified several issues to the use of this research method. A number of recommendations and a list of critical success factors for practitioners has been generated as a result of the findings of this study. We think that this information might be useful for people that is starting a research project and want to use Grounded Theory method.
Difficulty in advancing a tracheal tube over a fibreoptic bronchoscope: incidence, causes and solutions.

Fibreoptic tracheal intubation is a useful technique in patients whose tracheas are dif®cult to intubate. 69 However, there are two major dif®culties with this technique. The ®rst is location of the glottis and insertion of a ®brescope into the trachea. Induction of general anaesthesia (with or without neuromuscular block) causes the soft palate, tongue and epiglottis to approximate to the posterior pharyngeal wall, and thus little air space is left in the oropharynx for manoeuvring the tip of the ®brescope to locate the glottis. The second dif®culty is insertion of a tube over the ®brescope into the trachea. There have been reports of failed tracheal intubation despite successful insertion of a ®brescope into the trachea. 89 To solve the ®rst dif®culty, several manoeuvres (such as thrusting the jaw forward, extension of the head, or traction of the tongue) have been proposed, and airway intubators (such as the Berman, Ovassapian and Williams) have been developed. In addition, there have been comprehensive articles discussing effective ways of teaching ®brescopy. 66 69 85 In contrast, there have been no textbooks or reviews which comprehensively deal with the second dif®culty, of advancing a tracheal tube over a ®brescope. Therefore, the main aim of this review article is to analyse the incidence of, causes of and possible solution to, the dif®culty in advancing a tube over a ®brescope into the trachea.