Miracle-dz/UniFAR-FTUs huggingface dataset:
Tangible Visualization Table for Intuitive Data Display

We propose a new tangible visualization table for intuitive and effective visualization of terrain data transferred from a remote server in real time. The shape display approximating the height field of remote terrain data is generated by linear actuators, and the corresponding texture image is projected onto the shape display. To minimize projection distortions, we present a sophisticated technique for projection mapping. Gesture-based user interfaces facilitate intuitive manipulations of visualization results. We demonstrate the effectiveness of our system by displaying and manipulating various terrain data using gesture-based interfaces.
Subjectivity Without Subjects: From Abject Fathers to Desiring Mothers

Chapter 1 Introduction Part 2 Part I: Abject Fathers Chapter 3 The Morality of American Manhood, Responsibility and Virility Chapter 4 Fatherhood and the Promise of Ethics Chapter 5 Abjection in Fassbinder's Dispair and Polanski's The Tenant Part 6 Part II: Desiring Mother Chapter 7 Kristeva's Imaginary Father as a Screen for the Desiring Mother Chapter 8 Recognition, Witnessing, and Identity: Drucilla Cornell on Family Law Chapter 9 Face to Face With the Mother: Alterity in Bergman's Persona Part 10 Part III: Subjectivity Without Subjects Chapter 11 Fractal Politics: How to Use the Subject Chapter 12 Between Soma and Psyche: Kristeva and the Crisis in Meaning Chapter 13 Subjectivity Without Subjects: Circulation from Vision to Visions Chapter 14 Beyond Recognition: Witnessing the Other Otherwise in Varda's Vagabond Chapter 15 Notes Chapter 16 Bibliography Chapter 17 Index
Identification of Two Isoforms of the Kisspeptin-1 Receptor (kiss1r) Generated by Alternative Splicing in a Modern Teleost, the Senegalese Sole (Solea senegalensis)1

Abstract The KISSPEPTIN-1 receptor (KISS1R) and its ligands (KISSPEPTINS) are implicated in the regulation of the onset of puberty. We report the coding region and genomic structure of the kiss1r gene of a modern teleost, the Senegalese sole (Ss). Ss kiss1r cDNA contained an opening frame of 1137 bp, which results in a predicted 378 amino acid protein. Searching genomic databases allowed the identification of kiss1r orthologues in six new species belonging to three vertebrate groups and established the evolutionary relationships of all KISS1R sequences available to date. Analysis of Ss kiss1r revealed for the first time in any vertebrate KISS1R gene the presence of features that are characteristic of a mechanism of alternative splicing. This was confirmed by the identification of two transcripts, Ss kiss1r_v1 and Ss kiss1r_v2. The latter, arising from intron III retention, contained a 27 codons insert in transmembrane region 4 with two stop codons, suggesting it may lead to a truncated protein. The mRNA of the two variants was differently expressed in several tissues. In the brain, levels of the Ss kiss1r_v1 were higher than those of Ss kiss1r_v2. In the gonads, the opposite was observed. Both isoforms exhibited changes depending on sex and maturity stage. The presence of two variants may help to explain some discrepancies observed in past studies regarding KISS1R expression during puberty. Thus, the existence of alternative splicing for the KISS1R gene may contribute to our understanding of the many physiological functions suspected to be mediated by KISSPEPTIN-KISS1R signaling.
Bis{[6-methoxy-2-(4-methylphenyl)iminiomethyl]phenolate-κ2 O,O′}tris(nitrato-κ2 O,O′)europium(III)

The crystal structure of title compound, [Eu(NO3)3(C15H15NO2)2], contains two Schiff base 6-methoxy-2-[(4-methylphenyl)iminomethyl]phenolate (L) ligands and three independent nitrate ions that chelate to the europium(III) ion via the O atoms. The coordination number of the EuIII ion is ten. The L ligands chelate with a strong Eu—O(deprotonated phenolate) bond and a weak Eu—O(methoxy) contact, the latter can be interpreted as the apices of the bicapped square-antiprismatic EuIII polyhedron. Intramolecular N—H⋯O hydrogen bonds occur.
Frontiers in Computational Neuroscience Systematic Analysis of the Contributions of Stochastic Voltage Gated Channels to Neuronal Noise

Neuronal stochastic variability: influences on spiking dynamics and network activity ABSTRACT Electrical signaling in neurons is mediated by the opening and closing of large numbers of individual ion channels. The ion channel's state transitions are stochastic and introduce fluctuations in the macroscopic current through ion channel populations. This creates an unavoidable source of intrinsic electrical noise for the neuron, leading to fluctuations in the membrane potential and spontaneous spikes. While this effect is well known, the impact of channel noise on single neuron dynamics remains poorly understood. Most results are based on numerical simulations. There is no agreement, even in theoretical studies, on which ion channel type is the dominant noise source, nor how inclusion of additional ion channel types affects voltage noise. Here we describe a framework to calculate voltage noise directly from an arbitrary set of ion channel models, and discuss how this can be use to estimate spontaneous spike rates.
The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood

It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture-recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and these do not constitute a standard generalized linear model (GLM) family. Modern statistical techniques such as generalized additive models (GAMs), which allow a relaxing of the linearity assumptions on the covariates, are readily available for many standard GLM families. Fortunately, a natural statistical framework for maximizing conditional likelihoods is available in the Vector GLM and Vector GAM classes of models. We present several new R functions (implemented within the VGAM package) specifically developed to allow the incorporation of individual covariates in the analysis of closed population CR data using a GLM/GAM-like approach and the conditional likelihood. As a result, a wide variety of practical tools are now readily available in the VGAM object oriented framework. We discuss and demonstrate their advantages, features and flexibility using the new VGAM CR functions on several examples.
High‐frequency gamma oscillations coexist with low‐frequency gamma oscillations in the rat visual cortex in vitro

Synchronization of neuronal activity in the visual cortex at low (30–70 Hz) and high gamma band frequencies (> 70 Hz) has been associated with distinct visual processes, but mechanisms underlying high‐frequency gamma oscillations remain unknown. In rat visual cortex slices, kainate and carbachol induce high‐frequency gamma oscillations (fast‐γ; peak frequency ∼ 80 Hz at 37°C) that can coexist with low‐frequency gamma oscillations (slow‐γ; peak frequency ∼ 50 Hz at 37°C) in the same column. Current‐source density analysis showed that fast‐γ was associated with rhythmic current sink‐source sequences in layer III and slow‐γ with rhythmic current sink‐source sequences in layer V. Fast‐γ and slow‐γ were not phase‐locked. Slow‐γ power fluctuations were unrelated to fast‐γ power fluctuations, but were modulated by the phase of theta (3–8 Hz) oscillations generated in the deep layers. Fast‐γ was spatially less coherent than slow‐γ. Fast‐γ and slow‐γ were dependent on γ‐aminobutyric acid (GABA)A receptors, α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid (AMPA) receptors and gap‐junctions, their frequencies were reduced by thiopental and were weakly dependent on cycle amplitude. Fast‐γ and slow‐γ power were differentially modulated by thiopental and adenosine A1 receptor blockade, and their frequencies were differentially modulated by N‐methyl‐d‐aspartate (NMDA) receptors, GluK1 subunit‐containing receptors and persistent sodium currents. Our data indicate that fast‐γ and slow‐γ both depend on and are paced by recurrent inhibition, but have distinct pharmacological modulation profiles. The independent co‐existence of fast‐γ and slow‐γ allows parallel processing of distinct aspects of vision and visual perception. The visual cortex slice provides a novel in vitro model to study cortical high‐frequency gamma oscillations.
Indexing high-dimensional data in dual distance spaces: a symmetrical encoding approach

Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-based index structure, which is called EHD-Tree (for symmetrical Encoding-based Hybrid Distance Tree), is proposed to support fast k-Nearest-Neighbor (k-NN) search in high-dimensional spaces. In an EHD-Tree, all data points are first grouped into clusters by a k-Means clustering algorithm. Then the uniform ID number of each data point is obtained by a dual-distance-driven encoding scheme in which each cluster sphere is partitioned twice according to the dual distances of start- and centroid-distance. Finally, the uniform ID number and the centroid-distance of each data point are combined to get a uniform index key, the latter is then indexed through a partition-based B+-tree. Thus, given a query point, its k-NN search in high-dimensional spaces can be transformed into search in a single dimensional space with the aid of the EHD-Tree index. Extensive performance studies are conducted to evaluate the effectiveness and efficiency of our proposed scheme, and the results demonstrate that this method outperforms the state-of-the-art high dimensional search techniques such as the X-Tree, VA-file, iDistance and NB-Tree, especially when the query radius is not very large.
Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis

MOTIVATION Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensional data in a lower dimensional space. RESULTS In this article, we introduce a novel formulation of sparse NMF and show how the new formulation leads to a convergent sparse NMF algorithm via alternating non-negativity-constrained least squares. We apply our sparse NMF algorithm to cancer-class discovery and gene expression data analysis and offer biological analysis of the results obtained. Our experimental results illustrate that the proposed sparse NMF algorithm often achieves better clustering performance with shorter computing time compared to other existing NMF algorithms. AVAILABILITY The software is available as supplementary material.
Appliance scheduling optimization in smart home networks comprising of smart appliances and a photovoltaic panel

In this paper, we propose a solution to the problem of scheduling of smart appliances operations in a given time range. We adopt a photovoltaic (PV) panel as a power producing appliance that acts as micro-grid. Appliance operation is modeled in terms of un-interruptible sequence phases, given in load demand profile. An optimization algorithm, which can provide a schedule for smart home appliances usage is proposed. Simulation results demonstrate the utility of our proposed solution for appliance scheduling. We further show that adding a PV panel in the home results in reduction of electricity bill and export of energy to the national grid.
Determining a Firm's Optimal Outsourcing Rate: A Learning Model Perspective

We present a decision model of a firm's optimal outsourcing rate as an extension of Cha et. al [1]'s previous work on the economic risk of knowledge loss and deskilling in the outsourcing context. Specifically, the model examines the impacts of two critical model parameters--the knowledge transfer rate and the coordination knowledge depreciation rate-on the firm's cost minimizing outsourcing rate. When the knowledge transfer rate is low we find that the optimal decision is either total insourcing or total outsourcing, depending on the coordination knowledge depreciation rate. However, as the knowledge transfer rate increases, the firm's optimal decision becomes a selective outsourcing strategy that creates an interesting bargaining problem.
A Fully Nonparametric Modeling Approach to Binary Regression

© 2015 International Society for Bayesian Analysis. We propose a general nonparametric Bayesian framework for binary regression, which is built from modeling for the joint response-covariate distribution. The observed binary responses are assumed to arise from underlying continuous random variables through discretization, and we model the joint distribution of these latent responses and the covariates using a Dirichlet process mixture of multivariate normals. We show that the kernel of the induced mixture model for the observed data is identifiable upon a restriction on the latent variables. To allow for appropriate dependence structure while facilitating identifiability, we use a square-root-free Cholesky decomposition of the covariance matrix in the normal mixture kernel. In addition to allowing for the necessary restriction, this modeling strategy provides substantial simplifications in implementation of Markov chain Monte Carlo posterior simulation. We present two data examples taken from areas for which the methodology is especially well suited. In particular, the first example involves estimation of relationships between environmental variables, and the second develops inference for natural selection surfaces in evolutionary biology. Finally, we discuss extensions to regression settings with ordinal responses.
Differentially Interconnected Networks of GABAergic Interneurons in the Visual Cortex of the Cat

Networks of GABAergic neurons have been implicated in neuronal population synchronization. To define the extent of cellular interconnections, we determined the effect, number, and subcellular distribution of synapses between putative GABAergic neurons in layers II–IV of the cat visual cortex using paired intracellular recordingsin vitro followed by correlated light and electron microscopy. All neurons having interneuronal electrophysiological properties were classified by their postsynaptic target profile and were identified as basket (BC; n = 6), dendrite-targeting (DTC; n = 1), and double bouquet (DBC; n = 2) cells. In four out of five anatomically fully recovered and reconstructed cell pairs, synaptic connections were found to be reciprocal. Generally BCs established synaptic junctions closer (21 ± 20 μm) to postsynaptic somata than did DBCs (43 ± 19 μm; p < 0.01). The unitary number of synapses (n values, 10, 7, and 20) in each of three BC-to-BC pairs was higher than that in three BC-to-DBC (n values, 1, 2, and 2) and three DBC-to-BC (n values, 1, 4, and 4) connections (p < 0.05). A BC innervated a DTC through two synaptic junctions. Unitary postsynaptic effects mediated by five BCs could be recorded in two BCs, two DBCs, and a DTC. The BCs elicited short-duration fast IPSPs, similar to those mediated by GABAA receptors. At a membrane potential of −55.0 ± 6.4 mV, unitary IPSPs (n = 5) had a mean amplitude of 919 ± 863 μV. Postsynaptic response failures were absent when an IPSP was mediated by several release sites. Thus, distinct GABAergic interneurons form reciprocally interconnected networks. The strength of innervation and the proximal placement of synapses suggest a prominent role for BCs in governing the activity of intracortical GABAergic networks in layers II–IV.
Dynamic tuning of the IEEE 802.11 protocol to achieve a theoretical throughput limit

In wireless LANs (WLANs), the medium access control (MAC) protocol is the main element that determines the efficiency in sharing the limited communication bandwidth of the wireless channel. In this paper we focus on the efficiency of the IEEE 802.11 standard for WLANs. Specifically, we analytically derive the average size of the contention window that maximizes the throughput, hereafter theoretical throughput limit, and we show that: 1) depending on the network configuration, the standard can operate very far from the theoretical throughput limit; and 2) an appropriate tuning of the backoff algorithm can drive the IEEE 802.11 protocol close to the theoretical throughput limit. Hence we propose a distributed algorithm that enables each station to tune its backoff algorithm at run-time. The performances of the IEEE 802.11 protocol, enhanced with our algorithm, are extensively investigated by simulation. Specifically, we investigate the sensitiveness of our algorithm to some network configuration parameters (number of active stations, presence of hidden terminals). Our results indicate that the capacity of the enhanced protocol is very close to the theoretical upper bound in all the configurations analyzed.
Challenges in Using Mix Methods in Evaluation

This article explores the debates between quantitative and qualitative methods in the evaluation process, analyzes the challenges about methodological mix in terms of credibility and validity of data and tools, and the evaluation findings. Beyond the epistemological contradictions, it seems that, in terms of usefulness, the mixing of methods is a practical solution, along with hybrids theories, able to provide information to improve the sufficiency of the program. Mixing methods is also a way to reduce conflict between positivism and constructivism and an opportunity for increasing flexibility that the evaluator has in choosing the most appropriate methods for obtaining information in the assessment process.
Antimicrobial Resistance in Invasive Non-typhoid Salmonella from the Democratic Republic of the Congo: Emergence of Decreased Fluoroquinolone Susceptibility and Extended-spectrum Beta Lactamases

Background Co-resistance against the first-line antibiotics ampicillin, chloramphenicol and trimethoprim/sulphamethoxazole or multidrug resistance (MDR) is common in non typhoid Salmonella (NTS). Use of alternative antibiotics, such as fluoroquinolones or third generation cephalosporins is threatened by increasing resistance, but remains poorly documented in Central-Africa. Methodology/Principal findings As part of a microbiological surveillance study in DR Congo, blood cultures were collected between 2007 and 2011. Isolated NTS were assessed for serotype and antimicrobial resistance including decreased ciprofloxacin susceptibility and extended-spectrum beta-lactamase (ESBL) production. In total, 233 NTS isolates (representing 23.6% of clinically significant organisms) were collected, mainly consisting of Salmonella Typhimurium (79%) and Salmonella Enteritidis (18%). The majority of NTS were isolated in the rainy season, and recovered from children ≤2 years old. MDR, decreased ciprofloxacin susceptibility, azithromycin and cefotaxime resistance were 80.7%, 4.3%, 3.0% and 2.1% respectively. ESBL production was noted in three (1.3%) isolates. Decreased ciprofloxacin susceptibility was associated with mutations in codon 87 of the gyrA gene, while ESBLs all belonged to the SHV-2a type. Conclusions/Significance Presence of almost full MDR among NTS isolates from blood cultures in Central Africa was confirmed. Resistance to fluoroquinolones, azithromycin and third generation cephalosporins is still low, but emerging. Increased microbiological surveillance in DR Congo is crucial for adapted antibiotic therapy and the development of treatment guidelines.
Is there a connection between face symmetry and face recognition?

Recent research in the area of automatic machine recognition of human faces has shown that there may be an advantage in utilizing face symmetry to improve recognition accuracy. While promising, this work has led to several open questions. What is a good feature description or score of the symmetry of the face? Is there a statistical significance between face symmetry and face recognition? We present new symmetry scores of the face and use the scores to compare the symmetry in several subgroups of a face database. A 3D face database is used to remove the effects of illumination which should improve the reliability of the symmetry score. We find a significant difference in face symmetry between the men and women subjects in the database. The database is then partitioned into most symmetric and least symmetric subjects based on the symmetry scores. The average-half-face is utilized in our face recognition experiments to take into account the symmetry of the face. Face recognition with eigenfaces using the average-half-face is significantly higher than using the full face in all subgroups regardless of symmetry score. However, face recognition using the full face does depend on the symmetry score and generally favors the least symmetric subjects.
Popular press and forensic genetics in Portugal: Expectations and disappointments regarding two cases of missing children

Two cases of missing children in Portugal (Joana and Maddie) have recently highlighted the dilemmas and contingencies associated with the technology of “genetic fingerprinting” for forensic purposes in the context of criminal investigations. The purpose of this article is to analyze the popular press’s discourses and representations around forensic genetics in the context of those two highly mediatized criminal investigation cases. The symbolical construction and representation of forensic genetics by the media presents a form of public exposure to beliefs on forensic genetics’ characteristics and potential. These are blended with popular cultural contexts that are constructed with reference to images of a super-science which may carry consequences in the public understanding of forensic science. The media coverage of both cases and their actual disclosure resembles the patterns of a CSI effect, insofar as real science’s capabilities and limitations are placed against fictionalized representations of forensic science.
Importance of psychiatric examination in predictive genetic testing for Huntington disease.

BACKGROUND AND PURPOSE Huntington disease (HD) is an au-tosomal dominant hereditary neurodegenerative disease with multiplication of CAG triplet in the short arm of chromoso-me 4, manifested by motor symptoms, cognitive dysfunction progressing to dementia, and various types of neuropsychiat-ric disorders. The diagnosis of HD is confirmed by a gene-tic test, which may also be carried out presymptomatically. MATERIAL AND METHODS We studied differences in psychiatric examination and psychometric measures among the 52 people at risk of HD, who were recommended to postpone or to continue in the predictive protocol. In addition to the psychiatric examination, we administered the Eysenck Personality Questionnaire (EPQ-A), the Symptom Checklist 90 (SCL-90), and quality of life questionnaire (MANSA). RESULTS People at risk of HD with the recommended test postponement showed lower rate of neuroticism and EPQ-A lie score, higher values on the phobia and the so-called 'positive symptom distress index' in SCL-90 and lower quality of life than people at risk of HD with the recommendation to continue. CONCLUSIONS Our results indicate that the formalized testing does not bring significant information whereas the clinical psychiatric examination remains the main decisive factor in the recommendation to perform a predictive genetic test. The motivation of applicants is considered as the most important factor in the decision-making process.