Miracle-dz/UniFAR-FTUs huggingface dataset:
Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback

Abstract Evidence suggests that the brain uses an operational set of canonical computations like normalization, input filtering, and response gain enhancement via reentrant feedback. Here, we propose a three-stage columnar architecture of cascaded model neurons to describe a core circuit combining signal pathways of feedforward and feedback processing and the inhibitory pooling of neurons to normalize the activity. We present an analytical investigation of such a circuit by first reducing its detail through the lumping of initial feedforward response filtering and reentrant modulating signal amplification. The resulting excitatory-inhibitory pair of neurons is analyzed in a 2D phase-space. The inhibitory pool activation is treated as a separate mechanism exhibiting different effects. We analyze subtractive as well as divisive (shunting) interaction to implement center-surround mechanisms that include normalization effects in the characteristics of real neurons. Different variants of a core model architecture are derived and analyzed—in particular, individual excitatory neurons (without pool inhibition), the interaction with an inhibitory subtractive or divisive (i.e., shunting) pool, and the dynamics of recurrent self-excitation combined with divisive inhibition. The stability and existence properties of these model instances are characterized, which serve as guidelines to adjust these properties through proper model parameterization. The significance of the derived results is demonstrated by theoretical predictions of response behaviors in the case of multiple interacting hypercolumns in a single and in multiple feature dimensions. In numerical simulations, we confirm these predictions and provide some explanations for different neural computational properties. Among those, we consider orientation contrast-dependent response behavior, different forms of attentional modulation, contrast element grouping, and the dynamic adaptation of the silent surround in extraclassical receptive field configurations, using only slight variations of the same core reference model.
HOR 2012 6 th International Workshop on Higher-Order Rewriting

The aim of HOR is to provide an informal forum to discuss all aspects of higher-order rewriting. The topics of the workshop include applications, foundations, frameworks, implementations , and semantics. HOR is a biannual meeting. The present volume provides final versions of six accepted contributed extended abstracts of talks selected for the workshop. HOR 2012 had also a tool session. The following termination checkers for higher-order rewriting systems was presented: • Carsten Fuhs: Haskell termination tool • Rene Thiemann: Isabelle termination tool • Takahito Aoto and Toshiyuki Yamada: Simply-typed TRS termination tool • Cynthia Kop: WANDA, termination tool for Algebraic Functional Systems We are grateful to these authors for accepting to present thier tools at HOR. We are also very grateful to Zhenjiang Hu (National Institute of Informatics, Japan) for kindly accepting to give an invited talk at HOR 2012. Many thanks to the program committee that I had the pleasure to chair, consisting of de Vries. The tasks were the decisions on the invited speakers, a timely refereeing of the submitted abstracts and the final decisions on the program. A heartfelt thank you to the HOR workshop series steering committee , Delia Kesner and Femke van Raamsdonk, who offered me to take this responsibility for the higher-order rewriting community and gave valuable advice throughout. Finally, we would like to thank the organizing committee of RTA 2012, and in particular Naoki Nishida, for all help in the preparation of the workshop. Bidirectional transformations provide a novel mechanism for synchronizing and maintaining the consistency of information between input and output. Despite many promising results on bidirectional transformations, these have been limited to lists and trees. We challenge the problem of bidirectional transformations on graphs, by proposing a formal definition of a well-behaved bidirectional semantics for UnCAL, a graph algebra. Our key idea is to treat graphs as compactable infinite trees and to manipulate trees by structural recursion. Specifically, we carefully refine the existing forward evaluation of structural recursion so that it can produce sufficient trace information for later backward evaluation, and we use the trace information for backward evaluation to reflect updates on the view to the source. We prove our bidirectional evaluation is well-behaved. We extend a framework of program transformation by templates based on first order term rewriting (Chiba et al., 2005) to simply typed term rewriting (Yamada, 2001), which is a framework of higher order term rewriting. A …
Unsupervised social media events clustering using user-centric parallel split-n-merge algorithms

Social Networks have been developed dramatically just in decades. People now have a convenient way to interact with both social media and other people by making the most of using these social networks. Nevertheless, there is still lack of useful tools that can help users (both consumers and providers) managing such social media under events perspective. In order to meet one of these emerging requirements, a user-centric parallel split-n-merge framework applied for un-supervised clustering social media events is introduced. The purpose of this framework is to cluster social media to events they depict by exploiting and exploring the role of users (who) and the way users interact with data (where, what, when) and others (what, who). The output of the proposed framework can be used for event organization/summarization, and as pre-processing stage for event detection and tracking. Major advantages of the proposed framework are (1) low computational solution w.r. t large-scale data, (2) parallel running, and (3) unsupervised clustering with no training data and third-party information requirements. The comparison between the proposed framework and up-to-date methods with MediaEval20131 test-bed and evaluation tools shows a very competitive result.
FACE APPEARANCE FACTORIZATION FOR EXPRESSION ANALYSIS AND SYNTHESIS

Facial expression interpretation, recognition and analysis is a key issue in visual communication and man to machine interaction. In this paper, we present a factorization technique which decomposes the appearance parameters coding a natural image. This technique is then used to perform facial expression synthesis on unseen faces showing any undetermined facial expression, as well as facial expression recognition.
On a relationship between non-deterministic communication complexity and instance complexity

We study the relationship between non-deterministic communication complexity of uniform functions [8, 9, 4] and instance complexity [7] (see the definitions in 2.1 and 2.2 respectively). For that purpose, the witness of the non-deterministic communication protocol executed by Alice and Bob is interpreted by Alice as a program p that, for t sufficiently large, “corresponds exactly” (see Definition 4) to the instance complexity ic(y : Y1(x)); in the previous expression x and y are the parts of the input known by Alice and Bob respectively and Y1(x) is the set of all values of y such that f(x, y) = 1. The main results of this paper are max|x|=|y|=n{ict(n) yes (y : Y1(x))} = N(f) and max|x|=|y|=n{ic(y : Y1(x))} = N(f) where icyes(a : S) is a variant of instance complexity (see Definition 5) and the non-deterministic communication complexities N(f) and N(f) are defined in [4], Chap. 2. We also present in Sec. 5 a simple inequality relating individual communication complexity with instance complexity.
Interleukin-32 Increases Human Gastric Cancer Cell Invasion Associated with Tumor Progression and Metastasis

Purpose: The proinflammatory cytokine interleukin-32 (IL-32) is a novel tumor marker highly expressed in various human carcinomas, including gastric cancer. However, its effects on prognosis of patients with gastric cancer and cancer metastasis are virtually unknown at present. The main aim of this study was to explore the clinical significance of IL-32 in gastric cancer and further elucidate the molecular mechanisms underlying IL-32–mediated migration and invasion. Experimental Design: Gastric cancer cells with ectopic expression or silencing of IL-32 were examined to identify downstream molecules and establish their effects on cell motility, invasion, and lung metastasis in vivo. Results: IL-32 was significantly upregulated in gastric cancer and positively correlated with aggressiveness of cancer and poor prognosis. Ectopic expression of IL-32 induced elongated morphology and increased cell migration and invasion via induction of IL-8, VEGF, matrix metalloproteinase 2 (MMP2), and MMP9 expression via phosphor-AKT/phospho-glycogen synthase kinase 3β/active β-catenin as well as hypoxia-inducible factor 1α (HIF-1α) signaling pathways. Conversely, depletion of IL-32 in gastric cancer cells reversed these effects and decreased lung colonization in vivo. Examination of gene expression datasets in oncomine and staining of gastric cancer specimens demonstrated the clinical significance of IL-32 and its downstream molecules by providing information on their coexpression patterns. Conclusions: IL-32 contributes to gastric cancer progression by increasing the metastatic potential resulting from AKT, β-catenin, and HIF-1α activation. Our results clearly suggest that IL-32 is an important mediator for gastric cancer metastasis and independent prognostic predictor of gastric cancer. Clin Cancer Res; 20(9); 2276–88. ©2014 AACR.
Conformational Stability Is a Determinant of Ribonuclease A Cytotoxicity*

Onconase™, a homolog of bovine pancreatic ribonuclease A (RNase A) with high conformational stability, is cytotoxic and has efficacy as a cancer chemotherapeutic agent. Unlike wild-type RNase A, the G88R variant is toxic to cancer cells. Here, variants in which disulfide bonds were removed from or added to G88R RNase A were used to probe the relationship between conformational stability and cytotoxicity in a methodical manner. The conformational stability of the C40A/G88R/C95A and C65A/C72A/G88R variants is less than that of G88R RNase A. In contrast, a new disulfide bond that links the N and C termini (residues 4 and 118) increases the conformational stability of G88R RNase A and C65A/C72A/G88R RNase A. These changes have little effect on the ribonucleolytic activity of the enzyme or on its ability to evade the cytosolic ribonuclease inhibitor protein. The changes do, however, have a substantial effect on toxicity toward human erythroleukemia cells. Specifically, conformational stability correlates directly with cytotoxicity as well as with resistance to proteolysis. These data indicate that conformational stability is a key determinant of RNase A cytotoxicity and suggest that cytotoxicity relies on avoiding proteolysis. This finding suggests a means to produce new cancer chemotherapeutic agents based on mammalian ribonucleases.
Capsaicin extraction from hot pepper of Capsicum genus

of extraction of capsaicin were studied. Liquid extraction of capsaicin was carried out from the dried hot pepper with constant stirring and the ratio of plant material and the extractant from 20:1 to 50:1. Methanol, ethanol, and their aqueous solutions were used as extractants. The extraction efficiency was assessed by the content of total extractives and capsaicin. Analysis of the extracts was carried out by the methods of spectrophotometry and by high performance thin layer and liquid chromatography. The study of the extraction kinetics showed that the time to establish the equilibrium concentration of capsaicin does not depend on the type of extractant, and the ratio of plant material and extractant. Grinding the raw material to a particle size of less than 2 mm reduces the equilibrium time to 60 minutes. To achieve 99% yield of capsaicin five extraction steps are necessary. Grinding of raw materials to a particle size of less than 1 mm is not advisable. It does not reduce the extraction time and makes it difficult to filter the extracts. P re-maceration of raw materials in water with ultrasonic exposure for 1 hour at the hydro-module of 1:5 and with the ultrasound power of 128 W reduces the time to establish equilibrium to 30 minutes and the number of extraction stages to three. If these parameters are observed the yield of capsaicin exceeds 99%, and the total extraction time is 2.5 hours, which makes it possible to choose extraction as a method for preparing samples of hot pepper for analyzing capsaicin by high performance liquid chromatography .
SOCIAL WORK STUDENTS’ ATTITUDES AND BELIEFS ABOUT MENTAL HEALTH COURTS

iii ACKNOWLEDGEMENTS . iv LIST OF TABLES . vii CHAPTER ONE: INTRODUCTION Problem Formulation. 1 Purpose of the Study . 3 Significance of the Projects for Social Work Practice . 5 CHAPTER TWO: LITERATURE REVIEW Introduction . 6 Prevalence of the Problem . 6 Receidivism Rates of Mentally Ill Offenders . 7 MHC Program Components . 8 Evaluation of MHC’s Effectiveness . 11 Professional Views Towards MHCs . 13 Theories Guiding Conceptualization . 15 CHAPTER THREE: METHODS Introduction . 19 Study Design . 19 Sampling . 20 Data Collection and Instruments . 21 Procedures . 22 Protection of Human Subjects . 22
The Bacillus subtilis GTP Binding Protein Obg and Regulators of the ςB Stress Response Transcription Factor Cofractionate with Ribosomes

ABSTRACT Obg, an essential GTP binding protein of Bacillus subtilis, is necessary for stress activation of the ςB transcription factor. We investigated Obg's cellular associations by differential centrifugation of crude B. subtilis extracts, using an anti-Obg antibody as a probe to monitor Obg during the fractionation, and by fluorescent microscopy of a B. subtilis strain in which Obg was fused to green fluorescent protein. The results indicated that Obg is part of a large cytoplasmic complex. In subsequent analyses, Obg coeluted with ribosomal subunits during gel filtration of B. subtilislysates on Sephacryl S-400 and specifically bound to ribosomal protein L13 in an affinity blot assay. Probing the gel filtration fractions with antibodies specific for ςB and its coexpressed regulators (Rsb proteins) revealed coincident elution of the upstream components of the ςB stress activation pathway (RsbR, -S, and -T) with Obg and the ribosomal subunits. The data implicate ribosome function as a possible mediator of the activity of Obg and the stress induction of ςB.
Model-based least squares optimal interpolation

The traditional approach to image interpolation is by synthesis using basis functions because of its computational simplicity and experience-proven quality of the result. We offer an alternative approach to designing the basis (interpolation kernels), using least-squares optimisation and image models that encompass the prior knowledge. In this paper we consider and derive a finite-support interpolation kernel based on a step-edge model and show that this results in a piece-wise cubic polynomial similar to Keys' cubic convolution. We offer an experimental comparison of the proposed kernel to a number of common methods and show that it performs similar to, or better than, the existing methods with similar extent of spatial support.
Precursors of the El Nio/La Nia onset and their interrelationship

[1] In this study, the equatorial sea level, western Pacific zonal wind, and high-frequency (2∼90 day) wind variability are investigated as precursors of the onset of El Nino/La Nina. To a large extent, it is shown that each variable is a good indicator of El Nino–Southern Oscillation (ENSO) onset by exhibiting significant correlation to the ENSO index with 9 month lag. However, it is demonstrated here that the three precursors are remarkably correlated with each other. Based on the statistical analysis, we suggest here that the three precursors are governed by strong coupling processes: (1) scale interaction within the atmosphere between the low-frequency (LF, i.e., interannual) and high-frequency (HF, i.e., intraseasonal) winds and (2) positive air-sea coupled feedback among the western Pacific westerly, SST, and zonal mean thermocline. Our observational analysis and statistical prediction experiments suggest that the three precursors are not independent and they reflect the different aspects of the same coupling process during the ENSO onset phase.
Software architecture reliability prediction models: An overview

The ability to predict reliability of the software during its architectural design not only helps in saving cost but also helps to improve its reliability. With the growing size and complexity of software applications researchers have focused that how to get software reliability through its architecture. Architectural design phase is the stage where one can evaluate either the developed software will fulfill the requirements or not; that's why a highly reliable method is required to analyze and predict the software's architectural reliability. Reliability prediction at architecture level is a challenging task because the architecture reliability depends on the reliability of the individual component, their size, complexity, implemented technology and the interaction among the components. In this paper we have compared the existing reliability prediction models based on our criteria. The purpose is to discover that which one is the best and what is the shortcoming of these models. We also have suggested the research activities needed to overcome these shortcomings.
A Structural Model of Segregation in Social Networks

In this paper, I develop and estimate a dynamic model of strategic network formation with heterogeneous agents. While existing models have multiple equilibria, I prove the existence of a unique stationary equilibrium, which characterizes the likelihood of observing a specific network in the data. As a consequence, the structural parameters can be estimated using only one observation of the network at a single point in time. The estimation is challenging because the exact evaluation of the likelihood is computationally infeasible. To circumvent this problem, I propose a Bayesian Markov Chain Monte Carlo algorithm that avoids direct evaluation of the likelihood. This method drastically reduces the computational burden of estimating the posterior distribution and allows inference in high dimensional models. I present an application to the study of segregation in school friendship networks, using data from Add Health containing the actual social networks of students in a representative sample of US schools. My results suggest that for white students, the value of a same-race friend decreases with the fraction of whites in the school. The opposite is true for African American students. The model is used to study how different desegregation policies may affect the structure of the network in equilibrium. I find an inverted u-shaped relationship between the fraction of students belonging to a racial group and the expected equilibrium segregation levels. These results suggest that desegregation programs may decrease the degree of interracial interaction within schools.
Role of serotonin in cocaine effects in mice with reduced dopamine transporter function

The mesolimbic dopaminergic system, especially the nucleus accumbens, has received attention for its involvement in the reinforcing and addictive properties of cocaine and other drugs of abuse. It is generally accepted that the ability of cocaine to inhibit the dopamine transporter (DAT) is directly related to its reinforcing actions. However, mice with a genetic deletion of the DAT (DAT-KO mice) still experience the rewarding effects of cocaine. These behavioral findings suggest that there is an alternate site for cocaine reinforcement. We demonstrate here that modulation of the serotonergic system in the ventral tegmental area, where the mesolimbic dopamine system originates, is a target of cocaine action. The ultimate effect of this serotonin mechanism in animal models with sustained elevations of dopamine may be a feed-forward enhancement of dopamine levels in the nucleus accumbens.
Antigen-Based Immune Therapeutics for Type 1 Diabetes: Magic Bullets or Ordinary Blanks?

The ideal drug of modern medicine is the one that achieves its therapeutic target with minimal adverse effects. Immune therapy of Type 1 diabetes (T1D) is no exception, and knowledge of the antigens targeted by pathogenic T cells offers a unique opportunity towards this goal. Different antigen formulations are being considered, such as proteins or peptides, either in their native form or modified ad hoc, DNA plasmids, and cell-based agents. Translation from mouse to human should take into account important differences, particularly in the time scale of autoimmune progression, and intervention. Critical parameters such as administration route, dosing and interval remain largely empirical and need to be further dissected. T1D staging through immune surrogate markers before and after treatment will be key in understanding therapeutic actions and to finally turn ordinary blanks into magic bullets.
A Reformative Gradient Vector Flow Based on Beltrami Flow

The gradient vector flow (GVF) snake shows high performance at concavity convergence and initialization insensitivity, but the two components of GVF field are treated isolatedly during diffusion, this leads to the failure of GVF snake at deep and narrow concavity convergence and weak edge preserving. In this study, a novel external force for active contours is proposed that couples the two components during diffusion by generalizing the Laplacian operator from flat space to manifold. The specific operator is Beltrami operator. This proposed method has been assessed on synthetic and real images; experimental results show that the new method behaves similarly to the GVF snake in terms of capture range enlarging, initialization insensitivity, Ushape concavity convergence, while provides much better results than GVF snake for noise robustness, narrow and deep concavity convergence and weak edge preserving.
Effects of Aripiprazole and Haloperidol on Fos-like Immunoreactivity in the Prefrontal Cortex and Amygdala

Objective Aripiprazole, a dopamine system stabilizer, shows efficacy against both negative symptoms and positive symptoms in patients with schizophrenia. The aim of this study was to investigate the effects of aripiprazole and haloperidol on c-FOS expression in rat brain. Methods Aripiprazole (1, 10 and 30 mg/kg, i.p.) and haloperidol (0.1 and 1 mg/kg, i.p.) were administered to adult Male Sprague-Dawley rats. After 2 h of drug or vehicle administration, the rats were killed and their brains were removed and perfused with fixative, then cut into 40 µm slices on a freezing microtome. Brain regions of interest were the medial prefrontal cortex (mPFC), the nucleus accumbens core and shell (NAC-C and NAC-S), the hippocampus (CA1, CA3 and DG), the central amygdala (Ce), the basolateral amygdala (BL) and the temporal cortex (Tc). Immunohistochemistry was performed to label cell bodies containing c-FOS. Results The administration of aripiprazole at all doses (1, 10 or 30 mg/kg) resulted in greater Fos-like immunoreactivity (FLI) in the investigated brain areas, as compared to the vehicle. Comparable increases in FLI were demonstrated in the NAC-C and NAC-S in response to both aripiprazole and haloperidol treatment. The administration of haloperidol (0.1 or 1 mg/kg) also resulted in greater FLI in the investigated brain areas, except the mPFC, where no changes were observed. In the Ce and BL, a significant increase in Fos-positive neurons was observed only with 0.1 mg/kg of haloperidol. Conclusion Both aripiprazole and haloperidol increased FLI in limbic areas, which are considered important targets of antipsychotic drugs. The differential action of aripiprazole on FLI in the amygdala and mPFC as compared to haloperidol may be a good way to differentiate atypical from typical antipsychotics.