Miracle-dz/UniFAR-FTUs huggingface dataset:
Work More, Then Feel More: The Influence of Effort on Affective Predictions

Two studies examined how effort invested in a task shapes the affective predictions related to potential success in that task, and the mechanism underlying this relationship. In Study 1, PhD students awaiting an editorial decision about a submitted manuscript estimated the effort they had invested in preparing that manuscript for submission and how happy they would feel if it were accepted. Subjective estimates of effort were positively related to participants' anticipated happiness, an effect mediated by the higher perceived quality of one's work. In other words, the more effort one though having invested, the happier one expected to feel if it were accepted, because one expected a higher quality manuscript. We replicated this effect and its underlying mediation in Study 2, this time using an experimental manipulation of effort in the context of creating an advertising slogan. Study 2 further showed that participants mistakenly thought their extra efforts invested in the task had improved the quality of their work, while independent judges had found no objective differences in quality between the outcomes of the high- and low-effort groups. We discuss the implications of the relationship between effort and anticipated emotions and the conditions under which such relationship might be functional.
Is Music "Colorful"? A Study of the Effects of Age and Musical Literacy on Children's Notational Color Expressions.

This eight-year study represents a pioneering effort to investigate color expression in children’s graphic notations at two stages of development: “Pre-literate” (age: 7.0-8.5), before students received school music instruction, and “Post-literate” (age: 14.0-15.5), three years after students acquired Standard Notation in school, and to consider the effects of age and musical literacy on notational color expressions. Two meetings with Israeli/Jewish schoolchildren were held along a course of eight years: The first meeting with 46 second-graders (1995); the second meeting with 33 ninth-graders (2003). Of these, 17 students participated in two meetings. All participants acquired Standard Notation in their sixth-grade. In each meeting, subjects performed a musical phrase called “Timbre”, represented it graphically and explained their notations. Seventy-nine notations were collected and analyzed by MSC (Morphological, Structural, Conceptual) method of interpretation (Elkoshi, 2000, 2002, 2004a). Based on MSC, notations were classified under four categories: A (Association), P (Pictogram), F (Formal response), and G (Gestalt expression). Results show that the conceptual sub-division of the musical phrase into fragments (G) is color related, whereas the conceptual perception of the chronological sequence (F) is shape rather than color related. Associations (including Is Music “Colorful”? 2 Synesthesia) is probably age related. Post-literate notational color expressions were not affected by musical literacy.
A Brechó-EcoSys extension to support negotiation in the software ecosystems context

The treatment of economic and social issues in Software Engineering was pointed out as a challenge in the coming years. Organizations have opened up their platforms and assets to others, including partners and third-party developers around the world, generating software ecosystems (SECOs). SECOs research can contribute to minimize nontechnical barriers of software reuse in industry because it explores potential relations among companies and stakeholders. However, an inhibitor is the complexity in defining value for reusable assets. This paper presents an extension of the Brechó-EcoSys environment to support components negotiations in reuse repositories. The focus is on complementing the stakeholders' value proposition and realization, as well as incorporating a nontechnical mechanism in components repositories.
Intrinsic Circuits in the Lateral Central Amygdala

Abstract Network activity in the lateral central amygdala (CeL) plays a crucial role in fear learning and emotional processing. However, the local circuits of the CeL are not fully understood and have only recently begun to be explored in detail. Here, we characterized the intrinsic circuits in the CeL using paired whole-call patch-clamp recordings, immunohistochemistry, and optogenetics in C57BL/6J wild-type and somatostatin-cre (SOM-Cre) mice. Our results revealed that throughout the rostrocaudal extent of the CeL, neurons form inhibitory connections at a rate of ∼29% with an average amplitude of 20 ± 3 pA (at −40 mV). Inhibitory input from a single neuron is sufficient to halt firing in the postsynaptic neuron. Post hoc immunostaining for protein kinase Cδ (PKCδ) in wild-type mice and paired recordings in SOM-Cre mice demonstrated that the most common local connections were PKCδ(−) → PKCδ(−) and SOM(+) → SOM(+). Finally, by optogenetically activating either SOM(+) or SOM(−) neurons, we found that almost all neurons in the CeL were innervated by these neuronal populations and that connections between like neurons were stronger than those between different neuronal types. These findings reveal a complex network of connections within the CeL and provide the foundations for future behavior-specific circuit analysis of this complex network.
Cat face detection with two heterogeneous features

In this paper, we propose a generic and efficient object detection framework based on two heterogeneous features and demonstrate effectiveness of our method for a cat face detection problem. Simple Haar-like features with AdaBoost are fast to compute but they are not discriminative enough to deal with complicated shape and texture. Therefore, we cascade joint Haar-like features with AdaBoost and CoHOG descriptors with a linear classifier. Since the CoHOG descriptors are extremely high dimensional pattern descriptors based on gradient orientations, they have a strong classification capability to represent various cat face patterns. The combination of these two distinct classifiers enables fast and accurate cat face detection. The experimental result with about 10,000 cat images shows that our method gives better performance in comparison with the state-of-the-art cat head detection method, although our method does not exploit any cat specific characteristics.
What cognitive intelligence is and what emotional intelligence is not.

My commentary deals with the Mayer, Salovey, and Caruso (this issue) article. I substantially agree with the views of Matthews, Roberts and Zeidner. My commentary considers three issues. First, I indicate that there are fundamental distinction between tests of cognitive intelligence and the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) of emotional intelligence (EI). Second, I sketch a brief outline of some properties of cognitive intelligence construed as a latent trait and I review empirical studies that provide insights into the variable relation between the latent trait for cognitive ability and psychometric measures of intelligence. And, I indicate that the research reported by Mayer et al. does not indicate that MSCEIT assesses a construct that has isomorphic characteristics. Third, I review the studies presented by Mayer et al. purporting to demonstrate that MSCEIT has predictive validity.
Prevalence and Diversity of Bartonella Species in Commensal Rodents and Ectoparasites from Nigeria, West Africa

Background Bartonellae are fastidious bacteria causing persistent bacteremia in humans and a wide variety of animals. In recent years there is an increasing interest in mammalian bartonelloses in general and in rodent bartonelloses in particular. To date, no studies investigating the presence of Bartonella spp. in rodents and ectoparasites from Nigeria were carried out. Methodology/Principal Findings The aim of the current study was to investigate the presence of Bartonella spp. in commensal rodents and their ectoparasites in Nigeria. We report, for the first time, the molecular detection of Bartonella in 26% (46/177) of commensal rodents (Rattus rattus, R. norvegicus and Cricetomys gambianus) and 28% (9/32) of ectoparasite pools (Xenopsylla cheopis, Haemolaelaps spp., Ctenophthalmus spp., Hemimerus talpoides, and Rhipicephalus sanguineus) from Nigeria. Sequence analysis of the citrate synthase gene (gltA) revealed diversity of Bartonella spp. and genotypes in Nigerian rodents and their ectoparasites. Bartonella spp. identical or closely related to Bartonella elizabethae, Bartonella tribocorum and Bartonella grahamii were detected. Conclusions/Significance High prevalence of infection with Bartonella spp. was detected in commensal rodents and ectoparasites from Nigeria. The Bartonella spp. identified were previously associated with human diseases highlighting their importance to public health. Further studies need to be conducted to determine whether the identified Bartonella species could be responsible for human cases of febrile illness in Nigeria.
CCNY-SRI @ TRECVid 2013 intED: a Human Interactive Event Detection System

In this paper, we present a interactive Event Detection (interactiveED) system evaluated in TRECVID 2013 competition. The proposed system is evaluated on all the seven event categories. Two channels of raw features: STIP-HOG/HOF and SURF/MHI-HOG ‐ are extracted from down-sampled surveillance video frames. A Bag Of Words model is used to generate representations of segments of surveillance videos. Segments of videos are sampled using sliding windows. Spatial priors are utilized in two channels: Hot Region and Human Tracking Masks. Spatial priors are used for filtering noisy feature responses. Feature mapping technique is employed to generate more features, which potentially increase the separability of sample set in feature space. A cascade of SVMs are learned to tackle the classification task, with respect to different camera views. Human interaction is utilized as a post-processing layer to filter out false alarms. A Graphical User Interface (GUI) is developed to help an expert user to accomplish the task efficiently and conveniently.
Consumer choice in competitive location models: Formulations and heuristics

A new direction of research in Competitive Location theory incorporates theories of Consumer Choice Behavior in its models. Following this direction, this paper studies the importance of consumer behavior with respect to distance or transportation costs in the optimality of locations obtained by traditional Competitive Location models. To do this, it considers different ways of defining a key parameter in the basic Maximum Capture model (MAXCAP). This parameter will reflect various ways of taking into account distance based on several Consumer Choice Behavior theories. The optimal locations and the deviation in demand captured when the optimal locations of the other models are used instead of the true ones, are computed for each model. A metaheuristic based on GRASP and Tabu search procedure is presented to solve all the models. Computational experience and an application to 55-node network are also presented.
Dynamic Implicit Surfaces for Fast Proximity Queries in Physically Based Modeling

In this paper we deal with the problem of distance computation between static or dynamic objects, which is an important problem when dealing with the effects of collisions in the context of physically based modeling to obtain a fast numerical integration of the underlying ordinary differential equation. We use an implicit formulation of the (potential) collisions already in the physical laws of the simulated system. The new idea of our approach for distance computation is to use a special implicit representation recently used by Raviv and Elber (in the context of free-form sculpting). In the context of proximity queries this implicit representation has two main advantages: First, any given boundary representation can be approximated quite easily, no high-degree polynomials and complicated approximation algorithms are needed. Second, the evaluation of the corresponding implicit trivariate tensor product B-spline function is very fast and independent of the size of the object. In the paper we first describe the approach in detail and discuss its space and time complexity. Examples from different areas show the advantages of the approach even for dynamic scenes and objects in practice. Our method is fast enough to maintain a 1000 Hz refresh rate, as is commonly required by haptic rendering, for small objects in very complex environments on standard PC hardware.
New Delhi Metallo-β-Lactamase 1(NDM-1), the Dominant Carbapenemase Detected in Carbapenem-Resistant Enterobacter cloacae from Henan Province, China

The emergence of New Delhi metallo-β-lactamase 1 (NDM-1) has become established as a major public health threat and represents a new challenge in the treatment of infectious diseases. In this study, we report a high incidence and endemic spread of NDM-1-producing carbapenem-resistant Enterobacter cloacae isolates in Henan province, China. Eight (72.7%) out of eleven non-duplicated carbapenem-resistant E. cloacae isolates collected between June 2011 and May 2013 were identified as NDM-1 positive. The bla NDM-1 gene surrounded by an entire ISAba125 element and a bleomycin resistance gene ble MBL in these isolates were carried by diverse conjugatable plasmids (IncA/C, IncN, IncHI2 and untypeable) ranging from ~55 to ~360 kb. Molecular epidemiology analysis revealed that three NDM-1-producing E. cloacae belonged to the same multilocus sequence type (ST), ST120, two of which were classified as extensively drug-resistant (XDR) isolates susceptible only to tigecycline and colistin. The two XDR ST120 E. cloacae isolates co-harbored bla NDM-1, armA and fosA3 genes and could transfer resistance to carbapenems, fosfomycin and aminoglycosides simultaneously via a conjugation experiment. Our study demonstrated NDM-1 was the most prevalent metallo-β-lactamase (MBL) among carbapenem-resistant E.cloacae isolates and identified a potential endemic clone of ST120 in Henan province. These findings highlight the need for enhanced efforts to monitor the further spread of NDM-1 and XDR ST120 E. cloacae in this region.
An overview of free software tools for general data mining

This expert paper describes the characteristics of six most used free software tools for general data mining that are available today: RapidMiner, R, Weka, KNIME, Orange, and scikit-learn. The goal is to provide the interested researcher with all the important pros and cons regarding the use of a particular tool. A comparison of the implemented algorithms covering all areas of data mining (classification, regression, clustering, associative rules, feature selection, evaluation criteria, visualization, etc.) is provided. In addition, the tools' support for the more advanced and specialized research topics (big data, data streams, text mining, etc.) is outlined, where applicable. The tools are also compared with respect to the community support, based on the available sources. This multidimensional overview in the form of expert paper on data mining tools emphasizes the quality of RapidMiner, R, Weka, and KNIME platforms, but also acknowledges the significant advancements made in the other tools.
Oligodendroglial cell death in jimpy mice: an explanation for the myelin deficit

Neuroglial cell death was investigated in 3 white matter tracts of jimpy and normal mice. In normal animals, glial death during development ranged from 0.5 to 2.7% of the total glial population. The number of dying glial cells was significantly higher in jimpy animals at times corresponding with oligodendroglial proliferation and the onset of myelination in each tract. At certain ages, over 10% of the glial population were pyknotic at the light-microscopic level. Dying glial cells that were identified ultrastructurally presented the characteristics of oligodendrocytes. Premature death of oligodendrocytes presents a simple explanation for the gross deficits of myelin in jimpy animals. The shortened life span of the jimpy oligodendrocyte may preclude the elaboration of a normal myelin sheath. The jimpy model may prove to be a valuable tool in delineating a role for normal neuroglial cell death during the development of the nervous system.
HF-rTMS Treatment in Medication-Resistant Melancholic Depression: Results from 18FDG-PET Brain Imaging

ABSTRACT Introduction: High frequency repetitive transcranial magnetic stimulation (HF-rTMS) of the left dorsolateral prefrontal cortex (DLPFC) might be a promising strategy to treat depression, but not all patients show a positive outcome. Objective: In this open study, we evaluate whether a favorable HF-rTMS treatment outcome could be predicted by baseline prefrontal brain glucose metabolism (CMRglc), measured by 18fluorodeoxyglucose positron emission tomography (18FDG-PET). Methods: A sample of 21 antidepressant-free, treatment-resistant depression (TRD) patients of the melancholic subtype received 10 sessions of HF-rTMS delivered on the left DLPFC. Patients underwent a static 18FDG-PET before and after HF-rTMS treatment. Results: Forty-three percent of the patients showed a reduction of at least 50% on their Hamilton Rating Scale for Depression scores. Higher baseline metabolic activities in the DLPFC and the anterior cingulate cortex (ACC) were associated with better clinical outcome. Successful HF-rTMS treatment was related to metabolic changes in subdivisions of the ACC (Brodmann areas 24 and 32). Conclusion: This biological impact of HF-rTMS on regional brain CMRglc explains to some extent how HF-rTMS may improve moods in TRD patients. Larger sham-controlled HF-rTMS treatment studies are needed to confirm these results.
Following Temperature Stress, Export of Heat Shock mRNA Occurs Efficiently in Cells with Mutations in Genes Normally Important for mRNA Export

ABSTRACT Heat shock leads to accumulation of polyadenylated RNA in nuclei of Saccharomyces cerevisiae cells, transcriptional induction of heat shock genes, and efficient export of polyadenylated heat shock mRNAs. These studies were conducted to examine the requirements for export of mRNA following heat shock. We used in situ hybridization to detect SSA4 mRNA (encoding Hsp70) and flow cytometry to measure the amount of Ssa4p-green fluorescent protein (GFP) produced following heat shock. Npl3p and Yra1p are mRNA-binding proteins recruited to nascent mRNAs and are essential for proper mRNA biogenesis and export. Heat shock mRNA was exported efficiently in temperature-sensitive npl3, yra1, and npl3 yra1 mutant strains. Nevertheless, Yra1p was recruited to heat shock mRNA, as were Nab2p and Npl3p. Interestingly, Yra1p was not recruited to heat shock mRNA in yra1-1 cells, suggesting that Npl3p is required for recruitment of Yra1p. The THO complex, which functions in transcription elongation and in recruitment of Yra1p, was not required for heat shock mRNA export, although normal mRNA export is impaired in growing cells lacking THO complex proteins. Taken together, these studies indicate that export following heat shock depends upon fewer factors than does mRNA export in growing cells. Furthermore, even though some mRNA-binding proteins are dispensable for efficient export of heat shock mRNA, those that are present in nuclei of heat shocked cells were recruited to heat shock mRNA.
Isprs Journal of Photogrammetry and Remote Sensing Automatic Detection of Residential Buildings Using Lidar Data and Multispectral Imagery

This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a 'primary building mask' and a 'secondary building mask'. The primary building mask indicates the void areas where the laser does not reach below a certain height threshold. The secondary building mask indicates the filled areas, from where the laser reflects, above the same threshold. Line segments are extracted from around the void areas in the primary building mask. Line segments around trees are removed using the normalized difference vegetation index derived from the orthorectified multispectral images. The initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. It is experimentally shown that the proposed technique can successfully detect urban residential buildings, when assessed in terms of 15 indices including completeness, correctness and quality.
MULTI-CARRIER PAs Inverse Modeling Estimation Algorithm for Multi-Carrier High Power Amplifiers

Many predistortion schemes use a memoryless approach [1, 2], but with broadband systems, where the bandwidth is typically larger than five MHz, the PA typically can no longer be considered a memory-less system. With this, the inverse transfer function of the PA—which describes the forward transfer function of the required pre-distorter function—can no longer be obtained using memory-less approaches. The reason for this is that, for any given input envelope value, there are an infinite number of possible values for the inverse function. To overcome this, the PA output and the pre-distorter can be modeled as the summation of a number of non-linear Pth order polynomials operating on the current sample, as well as other past input samples [3]. For the PA, this is given by,
Face synthesis from a frontal pose image using partial least squares and b-splines

This paper investigates the effect of b-splines as a representation for dense 3D facial shape estimation under the partial least squares regression scheme. To this end, a frontal grayscale image is first used for predicting a texture map expressed in cylindrical coordinates. The texture map is then used for estimating a sparse grid of control points from which a b-spline surface is constructed. The prediction steps are carried out through a regression matrix built from the partial least squares technique. Experimental results demonstrate that using b-splines considerably reduces the information contained in a dense 3D cylindrical map, while efficiently preserving the accuracy provided by cylindrical dense maps for the purposes of statistical 3D shape estimation.
Local Weighted Dissimilarity Measure Based Multiscale 3D Keypoint Detection

This paper proposes a multiscale 3D keypoint detection method based on local weighted dissimilarity measure. At first, compute the local weighted dissimilarity measure of each vertex at different scale. Then determine the detecting scale of each vertex. Finally compare the local weighted dissimilarity measure of each vertex with those of its neighboring surface points at its detecting scale. The keypoint is defined as the vertex that has highest local weighted dissimilarity measure in its neighborhood. The contribution of this paper includes that we propose a novel local weighted dissimilarity measure and the frame of multiscale keypoint detection method. The proposed local weighted dissimilarity measure is computed from the shape index value, and it is invariable to rotation and translation transformation. The multiscale algorithm frame enable the detected key points are robust to noise, especially to high level noise. Extensive experiments have performed to testify the effectiveness of the proposed method.