Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Brain Stimulation Frequency—A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators.
ACCURATE MULTIVIEW STEREO RECONSTRUCTION WITH FAST VISIBILITY INTEGRATION AND TIGHT DISPARITY BOUNDING

A novel multi-view stereo reconstruction method is presented. The algorithm is focused on accuracy and it is highly engineered with some parts taking advantage of the graphics processing unit. In addition, it is seamlessly integrated with the output of a structure and motion pipeline. In the first part of the algorithm a depth map is extracted independently for each image. The final depth map is generated from the depth hypothesis using a Markov random field optimization technique over the image grid. An octree data structure accumulates the votes coming from each depth map. A novel procedure to remove rogue points is proposed that takes into account the visibility information and the matching score of each point. Finally a texture map is built by wisely making use of both the visibility and the view angle informations. Several results show the effectiveness of the algorithm under different working scenarios.
Human Activity Recognition System : Using Improved Crossbreed Features and Artificial Neural Network

In this paper, we present an intelligent method of human action recognition based on hybrid features. These features are calculated from the space-time cubes (interest points). The Blocks or cubes are derived from the difference of consecutive frames. These features include average number of blocks per frame, velocity of the blocks i.e. average angle and displacement, some of the kinematic features like divergence and vorticity, and hu features derived from motion energy images (MEI). Principal Component Analysis (PCA) has been used to reduce the dimensionality of the feature vector. For classification, we employ artificial neural networks (ANNs), in which each action video is represented by a bag of features. [Asmatullah Chaudhry, Javed Ullah, M. Arfan Jaffar, Jin Young Kim, Tran Anh Tuan. Human Activity Recognition System: Using Improved Crossbreed Features and Artificial Neural Network. Life Sci J 2012;9(4):5351-5356] (ISSN:1097-8135). http://www.lifesciencesite. com. 795
Incremental Rule Learning and Border Examples Selection from Numerical Data Streams

Mining data streams is a challenging task that requires online systems ba- sed on incremental learning approaches. This paper describes a classification system based on decision rules that may store up-to-date border examples to avoid unneces- sary revisions when virtual drifts are present in data. Consistent rules classify new test examples by covering and inconsistent rules classify them by distance as the nearest neighbour algorithm. In addition, the system provides an implicit forgetting heuristic so that positive and negative examples are removed from a rule when they are not near one another.
Hydrostatic equilibrium equation and Newtonian limit of the singular f(R) gravity

We derive the hydrostatic equilibrium equation of a spherical star for any gravitational Lagrangian density of the form . The Palatini variational principle for the Helmholtz Lagrangian in the Einstein gauge is used to obtain the field equations in this gauge. The equilibrium hydrostatic equation is obtained and is used to study the Newtonian limit for . The same procedure is carried out for the more generally case giving a good Newtonian limit.
Recommender System Incorporating User Personality Profile through Analysis of Written Reviews

In this work we directly incorporate user personality profiles into the task of matrix factorization for predicting user ratings. Unlike previous work using personality in recommender systems, we use only the presence of written reviews by users. Other work that incorporates text directly into the recommendation framework focuses primarily on insights into products/categories, potentially disregarding important traits about the reviewers themselves. By using the reviews to determine the users’ personalities directly, we can acquire key insights into understanding a user’s taste. Our ability to create the personality profile is based on a supervised model trained on the MyPersonality dataset. Leveraging a set of linguistics features, we are able to create a predictive model for all Big 5 personality dimensions and apply it to the task of predicting personality dimensions for users in a different dataset. We use Kernelized Probabilistic Matrix Factorization to integrate the personality profile of the users as side-information. Lastly, we show the empirical effectiveness of using the MyPersonality dataset for predicting user ratings. Our results show that combining the personality model’s raw linguistic features with the predicted personality scores provides the best performance. Furthermore, the personality scores alone outperform a dimensionality reduction of the linguistics features.
Challenges in Climate Science and Contemporary Applied Mathematics

This article discusses the challenges in climate science from the emerging viewpoint of stochastic‐statistical properties of turbulent dynamical systems. The mathematical topics discussed here include empirical information theory, fluctuation‐dissipation theorems, reduced‐order stochastic modeling, and the development of mathematically unambiguous exactly solvable test models for climate science that capture crucial features of vastly more complex scientific problems. The applied mathematics topics include the emerging development of multiscale algorithms for filtering/data assimilation and superparametrization for climate science and other problems in science and engineering, as well as suitable unambiguous mathematical test problems for their behavior. Interesting contemporary research directions and specific open problems are mentioned throughout the article. The perspective here should also be useful for applications to other complex dynamical systems arising in neural science, material science, and environmental/mechanical engineering. © 2011 Wiley Periodicals, Inc.
The kinetics of monazomycin-induced voltage-dependent conductance. I. Proof of the validity of an empirical rate equation

Monazomycin (a positively-charged, polyene-like antibiotic) induces a strongly voltage-dependent conductance in thin lipid membranes when added to one of the bathing solutions. We show here that the kinetics of conductance changes after a step of membrane potential are only superficially similar to the kinetics of the potassium gating system of squid giant axons, in that the beginning of conductance increases are growth functions of the time, as opposed to power functions of the time. We find that the rate constant (reciprocal of the time constant) of the growth varies with the approximately 2.6 power of the monazomycin concentration. The rate constant also varies exponentially with membrane potential such that an e-fold change is associated with a 10-11 mV change of membrane potential. We show that solutions of a simple differential equation are able to reproduce the actual conductance changes almost exactly. In the accompanying paper (Muller and Peskin. 1981. J. Gen. Physiol. 78:201-229), we derive the differential equation from a molecular model and use the theoretical equation so obtained to investigate the gating current of this system and to predict an interesting form of memory.
Assessment of business intelligence maturity in the selected organizations

The main purpose of this paper is to assess the level of Business Intelligence (BI) maturity in organizations. The research questions I ask in this study are: (1) what possibilities offer BI systems for different organizations, (2) how to measure and evaluate the BI maturity in organizations? The study was based on: (1) a critical analysis of literature, (2) a observation of different BI initiatives undertaken in various organizations, as well as on (3) semi-structured interviews conducted in polish organizations in 2012. Some interviews, conducted in 20 polish enterprises, were held with executives, senior members of staff, and ICT specialists. The reminder of my paper is organized as follows. Firstly, the idea of BI is described. Next, the issue of BI maturity models is recognized. Finally, Garter's Maturity Model for Business Intelligence and Performance Management is used to assess the level of BI in surveyed organizations.
Imaginary Engagement, Real-World Effects: Fiction, Emotion, and Social Cognition

Prior research has shown that cumulative written fiction exposure is correlated with (Mar, Oatley, Hirsch, de la Paz, & Peterson, 2006; Mar, Oatley, & Peterson, 2009) and 1-time exposure to literary fiction increases (e.g., Black & Barnes, 2015a; Kidd & Castano, 2013) performance on an emotion-reading task. However, Panero and colleagues (2016) found that although lifetime fiction exposure is a reliable predictor of performance, the causal effects previously observed may be more fragile (see also Samur, Tops, & Koole, 2017). The current article is an exploration of the extent to which the ability of fiction to affect social cognition may depend not only on what is read, but also how one reads. Specifically, an argument is made that the effect of fiction on social cognition may depend on the degree to which the reader contributes imaginatively to the text and that, although drawing meaning from literary fiction may require high levels of imaginative engagement, popular and genre fiction may allow for engaging in this way. This stance is discussed with respect to the role that emotional investment in a story and its characters might play in influencing readers of popular fiction to read in a “literary” way.
A Novel Adaptive Media Access Control Protocol based on the Contention Window in Wireless Sensor Networks

In wireless sensor networks (WNSs), the research on medium access control (Mac) protocol is one of the hot topic for researcher. And also, the MAC protocol is a determined factor for communication performance. In this paper, we analyze the typical existing MAC protocols, and focus on the disadvantage of S-MAC, which is caused by the fixed contention window of carrier sensing, we proposed a novel MAC protocol. The new MAC protocol can adjust the contention window according to the changing of network traffic. In simulation result, we use the OPNET simulation platform to compare the performance with others existing MAC protocol, and show the better performance on network throughput and transmission delay. Furthermore, our MAC protocol can improve the energy consumption rate and prolong the network lifetime.
Suboptimal LMI-Based Solution of Minimum Time Control Problem

The problem of time optimal control design is considered for a chain of integrators. The suboptimal solution based on Implicit Lyapunov Function (ILF) method is presented in the form of continuous stabilizing feedback. The Semi-Definite Programming (SDP) problem with the constraints in the form of Linear Matrix Inequalities (LMI) is obtained for tuning the optimal parameters. The suboptimal solution is compared with the minimum discontinuous feedback on numerical example.
PGC-1α regulates the cell cycle through ATP and ROS in CH1 cells

Peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α) is a transcriptional co-activator involved in mitochondrial biogenesis, respiratory capacity, and oxidative phosphorylation (OXPHOS). PGC-1α plays an important role in cellular metabolism and is associated with tumorigenesis, suggesting an involvement in cell cycle progression. However, the underlying mechanisms mediating its involvement in these processes remain unclear. To elucidate the signaling pathways involved in PGC-1α function, we established a cell line, CH1 PGC-1α, which stably overexpresses PGC-1α. Using this cell line, we found that over-expression of PGC-1α stimulated extra adenosine triphosphate (ATP) and reduced reactive oxygen species (ROS) production. These effects were accompanied by up-regulation of the cell cycle checkpoint regulators CyclinD1 and CyclinB1. We hypothesized that ATP and ROS function as cellular signals to regulate cyclins and control cell cycle progression. Indeed, we found that reduction of ATP levels down-regulated CyclinD1 but not CyclinB1, whereas elevation of ROS levels down-regulated CyclinB1 but not CyclinD1. Furthermore, both low ATP levels and elevated ROS levels inhibited cell growth, but PGC-1α was maintained at a constant level. Together, these results demonstrate that PGC-1α regulates cell cycle progression through modulation of CyclinD1 and CyclinB1 by ATP and ROS. These findings suggest that PGC-1α potentially coordinates energy metabolism together with the cell cycle.
Web–Enabled Classification of SNPs for Genome–Wide Association Studies

Whole genome association studies of the genetic underpinnings of complex phenotypes, and human diseases in particular, have been steadily gaining momentum over the past several years. Yet, the number of polymorphic sites in the human genome, including, but not limited to, single nucleotide polymorphisms (SNPs) is so large that identifying the combination of these few that have a significant effect on the condition of interest remains an overwhelming task. In this manuscript we present a new networked solution, and a program GeneNAB implementing it, to the computational identification and ranking of SNPs likely to be relevant for the phenotype of interest, genome-wide. We expect that the output of this program will be useful to guide further laboratory and clinical studies of these SNPs.
Prevalence of Abnormal Radiological Findings in Health Care Workers with Latent Tuberculosis Infection and Correlations with T Cell Immune Response

Background More than half of all health care workers (HCWs) in high TB-incidence, low and middle income countries are latently infected with tuberculosis (TB). We determined radiological lesions in a cohort of HCWs with latent TB infection (LTBI) in India, and determined their association with demographic, occupational and T-cell immune response variables. Methodology We obtained chest radiographs of HCWs who had undergone tuberculin skin test (TST) and QuantiFERON-TB Gold In Tube (QFT), an interferon-γ release assay, in a previous cross-sectional study, and were diagnosed to have LTBI because they were positive by either TST or QFT, but had no evidence of clinical disease. Two observers independently interpreted these radiographs using a standardized data form and any discordance between them resolved by a third observer. The radiological diagnostic categories (normal, suggestive of inactive TB, and suggestive of active TB) were compared with results of TST, QFT assay, demographic, and occupational covariates. Results A total of 330 HCWs with positive TST or QFT underwent standard chest radiography. Of these 330, 113 radiographs (34.2%) were finally classified as normal, 206 (62.4%) had lesions suggestive of inactive TB, and 11 (3.4%) had features suggestive of active TB. The mean TST indurations and interferon-γ levels in the HCWs in these three categories were not significantly different. None of the demographic or occupational covariates was associated with prevalence of inactive TB lesions on chest radiography. Conclusion/Significance In a high TB incidence setting, nearly two-thirds of HCWs with latent TB infection had abnormal radiographic findings, and these findings had no clear correlation with T cell immune responses. Further studies are needed to verify these findings and to identify the causes and prognosis of radiologic abnormalities in health care workers.
Distinct cellular and subcellular patterns of expression imply distinct functions for the Drosophila homologues of moesin and the neurofibromatosis 2 tumor suppressor, merlin

Interest in members of the protein 4.1 super-family, which includes the ezrin-radixin-moesin (ERM) group, has been stimulated recently by the discovery that the human neurofibromatosis 2 (NF2) tumor suppressor gene encodes an ERM-like protein, merlin. Although many proteins in this family are thought to act by linking the actin-based cytoskeleton to transmembrane proteins, the cellular functions of merlin have not been defined. To investigate the cellular and developmental functions of these proteins, we have identified and characterized Drosophila homologues of moesin (Dmoesin) and of the NF2 tumor suppressor merlin (Dmerlin). Using specific antibodies, we show that although these proteins are frequently coexpressed in developing tissues, they display distinct subcellular localizations. While Dmoesin is observed in continuous association with the plasma membrane, as is typical for an ERM family protein, Dmerlin is found in punctuate structures at the membrane and in the cytoplasm. Investigation of Dmerlin cultured cells demonstrates that it is associated with endocytic compartments. As a result of these studies, we propose that the merlin protein has unique functions in the cell which differ from those of other ERM family members.
Looking westwards: Men in transnational men’s magazine advertising in India

This study examines advertising content of four top-selling Indian editions of transnational men’s lifestyle magazines (Men’s Health India, GQ India, FHM India and Maxim India) to understand how it constructs masculinity for upper-class urban Indian men. Through content analysis of advertisements, the study finds greater presence of international brands and Caucasian models than domestic Indian brands and Indian models. Male models often appear alone and in decorative roles as opposed to professional roles. The study discusses the emergence of class-based glocal masculinity that helps assimilate upper-class Indian men into the global consumer base through shared ideals, goals and values.
Evaluations of the Lightweight Grid CIGRI upon the Grid5000 Platform

A widely used method for large scale experiment execution upon P2P or cluster computing platforms, is the exploitation of idle resources. Specifically in the case of clusters, administrators share their cluster's idle cycles into computational grids, for the execution of the so called bag-of-tasks applications. Fault-tolerance and scheduling are some of the important challenges that have arisen on the specific research field. On this paper, we present a simple, scalable, fault tolerant and user-transparent approach of harnessing idle cluster resources for executing grid bag-of-tasks applications. Our main interest lies on the large-scale deployment and evaluation of our lightweight grid computing approach, under real-life parameters. Under this context, we experiment with CIGRI and a fully transparent system-level checkpointing feature for scheduling and turnaround-time optimisation. We discuss the value of experimentation on computer science, we propose reproducible experiments based on real workload traces and we explain how our experimental methodology contributes on the development and evaluation of our grid platform.
Eliminative Argumentation: A Basis for Arguing Confidence in System Properties

Abstract : Assurance cases provide a structured method of explaining why a system has some desired property, for exam-ple, that the system is safe. But there is no agreed approach for explaining what degree of confidence one should have in the conclusions of such a case. This report defines a new concept, eliminative argumentation, that provides a philosophically grounded basis for assessing how much confidence one should have in an as-surance case argument. This report will be of interest mainly to those familiar with assurance case concepts and who want to know why one argument rather than another provides more confidence in a claim. The report is also potentially of value to those interested more generally in argumentation theory.
Modular architecture for multiple transforms in modern video standards

Modern video standards such as H.264 and HEVC introduce new simplified transform functions that allow for simple hardware implementation, different block sizes and enhanced coding efficiency. However, the number of different transforms to implement has increased, leading to the need of shared architectures able to process several transforms with minimum hardware overhead. This trend started with H.264, and continued with the new transforms in HEVC. Additionally, other video codecs such as VC1 and AVS should also be supported, together with the new ones still to appear. Therefore, it seems that new architectures will be necessary for each new generation of codecs, and that hardware sharing will continue to be a must. In this work, we propose a modular architecture that implements great flexibility and that permits extending to larger transform sides and scaling to higher levels of performance by just enabling or implementing more instances. The basic programmable module is introduced, together with techniques to support different transform sizes. Then, an evaluation of the performance for different transform functions is presented.
Davies' method for anomalous diffusions

Davies' method of perturbed semigroups is a classical technique to obtain off-diagonal upper bounds on the heat kernel. However Davies' method does not apply to anomalous diffusions due to the singularity of energy measures. In this note, we overcome the difficulty by modifying the Davies' perturbation method to obtain sub-Gaussian upper bounds on the heat kernel. Our computations closely follow the seminal work of Carlen, Kusuoka and Stroock \cite{CKS}. However, a cutoff Sobolev inequality due to Andres and Barlow \cite{AB} is used to bound the energy measure.
Combining Active and Reactive Behavior in Concurrent Objects

A distributed system can be modeled by objects that run concurrently, each with its own processor, and communicate by remote method calls. However objects may have to wait for response to external calls; at best resulting in inefficient use of processor capacity, at worst resulting in deadlock. Furthermore, it is difficult to combine active and passive object behavior without defining explicit control loops. This paper proposes a solution to these problems by means of asynchronous method calls and conditional processor release points in program code. Although at the cost of additional internal non-determinism in the objects, this approach seems attractive in asynchronous or unreliable distributed environments. The concepts are illustrated by the small object-oriented language Creol and its operational semantics.