Miracle-dz/UniFAR-FTUs huggingface dataset:
Generic to Specific Recognition Models for Membership Analysis in Group Videos

Automatic understanding and analysis of groups has attracted increasing attention in the vision and multimedia communities in recent years. However, little attention has been paid to the automatic analysis of group membership – i.e., recognizing which group the individual in question is part of. This paper presents a novel two-phase Support Vector Machine (SVM) based specific recognition model that is learned using an optimized generic recognition model. We conduct a set of experiments using a database collected to study group analysis from multimodal cues while each group (i.e., four participants together) were watching a number of long movie segments. Our experimental results show that the proposed specific recognition model (52%) outperforms the generic recognition model trained across all different videos (35%) and the independent recognition model trained directly on each specific video (33%) using linear SVM.
Grammar Induction: An Invitation to Formal Language Theorists

Why should Formal Language specialists get interested and involved in the area of Grammar Induction (GI), likewise known as Grammatical Inference? This is the question we try to answer in this paper. To keep this paper short, we mostly refrain from giving technical details but rather cite according references. So, this is rather a kind of hopefully inspiring (and by no means complete! ) annotated bibliography than a technical paper. However, we hope to present an inviting and inspiring panoramic view on the scene. We believe that there are indeed a number of good reasons, the most obvious being that Grammar Induction, as well as Formal Language Theory, deals with formalisms describing languages, i.e., grammars, automata, expressions, etc. This already implies a lot of interesting issues:
EMOCIONES BASICAS EN DEMENCIA TIPO ALZHEIMER

Hargrave et al, (2002) & Laveneu et al, (2005) hallaron que los pacientes con Demencia tipo Alzheimer (DTA) tienen mas dificultades que sujetos sanos para reconocer emociones,en particular el miedo y la tristeza (Henry et al, 2008). Spoletini et al, (2008) plantean que el deficit de reconocimiento de miedo aparece muy precozmente y podria constituir un marcador profetico. El objetivo es estudiar si los pacientes con DTA presentan alteraciones en el reconocimiento facial de emociones basicas. Se evaluaron 16 pacientes con diagnostico de demencia tipo Alzheimer, comparado con un Grupo Control. Se administraron 3 pruebas de reconocimiento facial de emociones basicas con 60 fotografias del POFA (Ekman y Friesen, 1976) (Tabernero & Politis 2011). Se hallaron diferencias estadisticamente significativas en las 3 tareas con el grupo control (Reconocimiento U de Mann-Whitney=14,500; p=0,000; seleccion U de Mann-W=41,000; p=0,001; apareamiento U de Mann-W=41,000; p=0,001) de emociones. Los pacientes tuvieron mayores alteraciones en el reconocimiento de tristeza (25,71%), miedo (22,76%) y Asco (18,06%). Estos resultados confirman los hallazgos previos que indican alteraciones en el procesamiento facial emocional en pacientes con DTA. Por otro lado nuestros hallazgos coinciden con los autores que encontraron en esta patologia mayor alteracion en reconocer tristeza y miedo. Palabras clave Emocion, Demencia tipo Alzheimer, Tristeza, Miedo Abstract BASIC EMOTIONS IN DEMENTIA OF ALZHEIMER´S TYPE Hargrave et al, (2002) & Laveneu et al, (2005) found that patients to recognize emotions, especially fear and sadness (Henry et al, 2008). Spoletini et al, (2008) suggest that recognition of fear seems appear very early and could be a predictive marker. The aim is to study whether patients with DAT alterations in facial recognition basic emotions.We evaluated 16 patients with a diagnosis of dementia of Alzheimer´s type compared to a control group. 3 tests were administered face recognition with 60 basic emotions POFA photographs (Ekman and Friesen, 1976) (Tabernero & Politis, 2011). Statistically significant differences were found in the 3 tasks with the control group (Recognition Mann-Whitney U = 14,500P = 0.000; Choise Mann-W U = 41,000, p = 0.001; Mating Mann-w = 41,000, P = 0.001). Patients had greater variation in the recognition of sadness (25.71%), fear (22.76%) and disgust (18.06%). These results confirm the findings of previous studies indicating alterations in facial emotional processing in patients with DAT. On the other hand our findings agree with the authors that this pathology found in greater alteration in recognizing sadness and fear. Key words Emotion, Dementia of Alzheimer´s type, Fear, Sadness
Software tool combining fault masking with user-defined recovery strategies

The voting farm, a tool which implements a distributed software voting mechanism for a number of parallel message passing systems, is described. The tool, developed in the framework of EFTOS (embedded fault tolerant supercomputing), can be used in standalone mode or in conjunction with other EFTOS fault tolerance tools. In the former case, exploitation of the mechanism is described, e.g. to implement restoring organs (N-modular redundancy systems with N-replicated voters); in the latter case, it is shown how it is possible for the user to implement in an easy and effective way a number of different recovery strategies via a custom, high-level language. Combining such strategies with the basic fault masking capabilities of the voting tool makes it possible to set up complex fault tolerant systems such as, for instance, N-and-M-spare systems or gracefully degrading voting farms. The impact that the tool can have on reliability is discussed, and it is shown how, besides structural design goals like fault transparency, the tool achieves replication transparency, a high degree of flexibility and ease-of-use, and good performance.
Interaction Between αCaMKII and GluN2B Controls ERK-Dependent Plasticity

Understanding how brief synaptic events can lead to sustained changes in synaptic structure and strength is a necessary step in solving the rules governing learning and memory. Activation of ERK1/2 (extracellular signal regulated protein kinase 1/2) plays a key role in the control of functional and structural synaptic plasticity. One of the triggering events that activates ERK1/2 cascade is an NMDA receptor (NMDAR)-dependent rise in free intracellular Ca2+ concentration. However the mechanism by which a short-lasting rise in Ca2+ concentration is transduced into long-lasting ERK1/2-dependent plasticity remains unknown. Here we demonstrate that although synaptic activation in mouse cultured cortical neurons induces intracellular Ca2+ elevation via both GluN2A and GluN2B-containing NMDARs, only GluN2B-containing NMDAR activation leads to a long-lasting ERK1/2 phosphorylation. We show that αCaMKII, but not βCaMKII, is critically involved in this GluN2B-dependent activation of ERK1/2 signaling, through a direct interaction between GluN2B and αCaMKII. We then show that interfering with GluN2B/αCaMKII interaction prevents synaptic activity from inducing ERK-dependent increases in synaptic AMPA receptors and spine volume. Thus, in a developing circuit model, the brief activity of synaptic GluN2B-containing receptors and the interaction between GluN2B and αCaMKII have a role in long-term plasticity via the control of ERK1/2 signaling. Our findings suggest that the roles that these major molecular elements have in learning and memory may operate through a common pathway.
An intelligence based model for the prevention of advanced cyber-attacks

The trend and motive of Cyber-attacks have gone beyond traditional damages and challenges to information stealing for political and economic gain. With the recent APT (Advance Persistent Threat), which comprises of Zeroday malware, Polymorphic malware, and Blended threat, the task of protecting vita infrastructures are increasingly becoming difficult. This paper proposes an intelligence based technique that combined the traditional signature based detection with the next generation based detection. The proposed model consists of virtual execution environment, detection, and prevention module. The virtual execution environment is designated to analyze and execute a suspected file contains malware while other module inspect, detect, and prevent malware execution based on the intelligent gathering in the central management system (CMS). The model based on Next Generation Malware Detection of creating threat intelligence for future occurrence prevention. The new model shall take into consideration lapses and benefits of the existing detectors.
A comparison of Gaussian distribution and polynomial classifiers in a hidden Markov model based system for the recognition of cursive script

Handwriting recognition systems based on hidden Markov models commonly use a vector quantizer to get the required symbol sequence. In order to get better recognition rates semi-continuous hidden Markov models have been applied. Those recognizers need a soft vector quantizer which superimposes a statistical distribution for symbol generation. In general, Gaussian distributions are applied. A disadvantage of this technique is the assumption of a specific distribution. No proof can be given whether this presupposition holds in practice. Therefore, the application of a method which employs no model of a distribution may achieve some improvements. The paper presents the employment of a polynomial classifier as a replacement of a Gaussian classifier in the handwriting recognition system. The replacement improves the recognition rate significantly, as the results show.
Sparse Multiple Kernel Learning for Hyperspectral Image Classification Using Spatial-Spectral Features

The increase in spatial and spectral resolution of the satellite sensors has provided high-quality data for remote sensing image classification. However, the high-dimensional feature space induced by using many spatial information precludes the use of simple classifiers. This paper proposes to classify the hyperspectral images and simultaneously to learn significant features in such high-dimensional scenarios. Group lasso regularized multiple kernel learning (GLMKL) is used to incorporate extended multi-attribute profile (EMAP) for hyperspectral image classification. We formulate a closed-form solution for optimizing the kernel weights based on the equivalence between group-lasso and MKL, and the derived variant equivalence leads to an efficient algorithm for MKL. Experiments are conducted on three high spatial resolution hyperspectral data sets. The results show that the proposed method achieves better performance for hyperspectral image classification compared to several state-of-the-art algorithms.
Type I and III interferons enhance IL‐10R expression on human monocytes and macrophages, resulting in IL‐10‐mediated suppression of TLR‐induced IL‐12

Currently, only about 30–50% of chronic hepatitis C virus (HCV) and hepatitis B virus (HBV) patients respond to IFN‐based therapy. It has been suggested that IL‐10 is involved in suppressing the activity of type I IFNs on antigen‐presenting cells (APCs). However, the interaction between type I IFNs and IL‐10 is still not clear. Here we report that IFN‐α priming upregulated the expression of IL‐10R1 on monocytes, and subsequently IL‐10 induced a higher level of STAT3 phosphorylation in IFN‐primed cells. This indicates that IFN‐α increased the sensitivity of monocytes to IL‐10, and as a result, TLR‐induced IL‐12p70 by IFN‐pretreated cells was suppressed. Interestingly, both IFN‐β and IL‐29, a member of the type III IFN family, comparably sensitized monocytes and macrophages to IL‐10 stimulation, indicating a general effect of IFN on the activity of IL‐10 in APCs. In summary, we demonstrate that one of the consequences of priming human APCs with IFN is to promote the cells’ sensitivity to IL‐10, which leads to the inhibition of TLR‐induced IL‐12p70 production. Therefore, type I and III IFNs induce a suboptimal activation of immune cells. These findings are relevant for the development of strategies to further improve IFN‐based therapy for patients with multiple sclerosis or viral hepatitis.
LSD1/KDM1A promotes hematopoietic commitment of hemangioblasts through downregulation of Etv2

Significance Epigenetic regulation of cell fate determination is one of the hottest topics today. In this study, we isolated and characterized a zebrafish mutant in histone Lys-specific demethylase 1 (LSD1/KDM1A), and found that LSD1 plays a role in the initiation of hematopoietic differentiation in the hemangioblast, a bipotent cell that can give rise to hematopoietic or endothelial progenitors. In addition, we identified the major function of LSD1 in hemangioblasts to be the down-regulation of Ets variant 2 (Etv2), a critical regulator of hemangioblast development. Our results suggest that the LSD1-dependent shutdown of the Etv2 gene is the significant event required for hemangioblasts to initiate hematopoietic differentiation. The hemangioblast is a progenitor cell with the capacity to give rise to both hematopoietic and endothelial progenitors. Currently, the regulatory mechanisms underlying hemangioblast formation are being elucidated, whereas those controllers for the selection of hematopoietic or endothelial fates still remain a mystery. To answer these questions, we screened for zebrafish mutants that have defects in the hemangioblast expression of Gata1, which is never expressed in endothelial progenitors. One of the isolated mutants, it627, showed not only down-regulation of hematopoietic genes but also up-regulation of endothelial genes. We identified the gene responsible for the it627 mutant as the zebrafish homolog of Lys-specific demethylase 1 (LSD1/KDM1A). Surprisingly, the hematopoietic defects in lsd1it627 embryos were rescued by the gene knockdown of the Ets variant 2 gene (etv2), an essential regulator for vasculogenesis. Our results suggest that the LSD1-dependent shutdown of Etv2 gene expression may be a significant event required for hemangioblasts to initiate hematopoietic differentiation.
An Analysis of the Growth of Computer and Internet Security Breaches

This study uses the modified Gompertz model and sparse data to analyze the growth rates of different types of computer and Internet-related crimes. The Gompertz model is an appropriate diffusion model because it is capable of modeling two opposite behaviors: (1) acts of attacks and imitation of attacks and (2) deterrence acts to prevent such attacks. In addition, this model can handle sparse data adequately. The model was used to analyze various types of attacks. The results indicated that growth patterns of computer and Internet crimes differ in growth patterns and that a relationship exists between occurrences of such security breaches and uses of certain security technologies. Thus, for example, financial fraud and denial of service are growing at a faster pace. The study also found, for example, that an increase in virus-related incidents does not necessarily increase anti-virus software use.
Peripheral scholarship and the context of foreign paid publishing in Nigeria

Lately, a phenomenal dimension of peripheral scholarship, compulsorily demanding the ‘foreign’, has evolved into the practice of paid publishing in ‘foreign’ journals among Nigerian academics. These ‘foreign’ journals afford speedy publishing at a fee with little or no peer review. This study is a descriptive research which collected qualitative data through 30 in-depth interviews conducted with academics in two federal universities in Nigeria. The findings established that though some universities are beginning to question their intellectual validity and propriety, predatory paid-for foreign journals remain popular among academics desirous to satisfy the ‘international publishing rule’ for promotion at all costs. Lacking international scholarly credibility, predatory journals will not advance Nigerian scholarship into the global scholarly mainstream which the ‘international rule’ ultimately seeks.
Mesh Massage : A Versatile Mesh Optimization Framework

We present a general framework for post-processing and optimizing surface meshes with respect to various target criteria. On the one hand, the framework allows us to control the shapes of the mesh triangles by applying simple averaging operations, on the other we can control the Hausdorff distance to some reference geometry by minimizing a quadratic energy. Due to the simplicity of this setup, the framework is efficient and easy to implement. Yet it constitutes an effective and versatile tool with a variety of possible applications. In particular, we use it to reduce the texture distortion in animated mesh sequences, to improve the results of cross-parameterizations, and to minimize the distance between meshes and their remeshes.
Design issues for permanent magnet machine sensorless drive combining saliency-based and back-EMF-based control in the entire speed range

This paper addresses design issues on a position sensorless drive for permanent magnet (PM) synchronous machines in the entire speed range. At initial state, the rotor magnetic polarity is identified based on the flux saturation through a square-wave voltage injection. For low speed operation, the spatial information in the saliency is tracked for the closed-loop sensorless drive. The square-wave voltage is persistently injected to measure the saliency reflected current ripples for the position estimation. For high speed operation, the back-electromagnetic-force (EMF) voltage is estimated for the spatial saliency replacement to achieve the maximum speed under the same DC bus voltage. The rotor position is estimated from the spatial information in back-EMF through a sliding-mode observer (SMO). A transition algorithm based on a multi-input phase-lock loop by blending these two estimated position signals is proposed for a smooth dynamic operation. In this paper, all the design methods are verified on an interior PM motor with a saliency ratio of 1.37 (Lq/Ld = 1.37).
Short communication: the effect of social media on customer behaviour

One of the most important marketplace for the transactions of goods and services is the internet. The internet usage has been increasing and so does the transactions through internet. It is important to consider, that the internet buyers have different approaches to buying and their responses to marketing from the traditional offline consumersIn fact, in these digital era days marketing needs to change. It needs to adapt in developing brands and improving customer relationship through online marketing channels. The firms need to engage more in social media, since, more customers are engaging in social media. Thus, in this paper we want to demonstrate the effect of social media on consumer behavior. This outcome of the study can be utilized by the firms to enhance their output.
Concepts of Connectivity and Human Epileptic Activity

This review attempts to place the concept of connectivity from increasingly sophisticated neuroimaging data analysis methodologies within the field of epilepsy research. We introduce the more principled connectivity terminology developed recently in neuroimaging and review some of the key concepts related to the characterization of propagation of epileptic activity using what may be called traditional correlation-based studies based on EEG. We then show how essentially similar methodologies, and more recently models addressing causality, have been used to characterize whole-brain and regional networks using functional MRI data. Following a discussion of our current understanding of the neuronal system aspects of the onset and propagation of epileptic discharges and seizures, we discuss the most advanced and ambitious framework to attempt to fully characterize epileptic networks based on neuroimaging data.
Pediatric defibrillation: current flow is improved by using "adult" electrode paddles.

OBJECTIVE Current flow, the major determinant of defibrillation success, depends on delivered energy and transthoracic impedance. Previous experimental data suggest that transthoracic impedance is higher using "pediatric" electrode paddles compared to the larger "adult" electrode paddles. There are few data from actual shocks to support the experimental studies. The purpose of this study was to measure transthoracic impedance during actual shock delivery and to determine the optimal electrode paddle size for pediatric defibrillation and cardioversion. METHODS We prospectively evaluated all shocks of < or = 20 joules given to pediatric patients at the University of Iowa from 1988 to 1992. Data collected included energy selected by the operator, energy delivered by the defibrillator, peak current flow and transthoracic impedance. Data were analyzed by unpaired t test and linear regression. RESULTS Fifty-five shocks were delivered to 20 patients, age newborn to 8 years. Thirty-seven shocks were given with "pediatric" electrode paddles (surface area 21 cm2) and 18 with "adult" electrode paddles (surface area 83 cm2). Selected energy correlated well with delivered energy (r = .98, P < .0001). Delivered energy using "pediatric" electrodes did not differ from that delivered with "adult" electrodes (8.0 +/- 0.9 joules vs 10.5 +/- 1.2 joules P > .1). However transthoracic impedance was significantly higher with "pediatric" electrodes (78.1 +/- 4.4 ohms vs 54.6 +/- 2.7 ohms P < .0008), resulting in lower peak current flow through "pediatric" electrode paddles (6.2 +/- 0.5 amps vs 8.7 +/- 0.5 amps P < .002). There was no correlation between joules/kg and peak current flow (r = .26, P > .05). CONCLUSION Use of "pediatric" electrode paddles results in higher transthoracic impedance and thus lower peak current flow. In pediatric defibrillation, larger "adult" electrode paddles should be used as soon as chest size permits (approximately 10 kg). Lower transthoracic impedance results in higher current flow that facilitates cardioversion and defibrillation.
ESTUDIO EXPLORATORIO DEL SINDROME DE BURNOUT EN UNA INSTITUCION DE EDUCACION SUPERIOR MEXICANA USANDO LA ESCALA DE MASLACH

This research is an exploratory study to measure burnout syndrome levels in 70 employees working at a Mexican Public University. The measuring instrument used was the Maslach Burnout Inventory (MBI, 1986). The questionnaire has 22 items with a likert scale of 6 options that go fromnever to dailyto explain how often the employee perceives any of the situations described in the items. Factor analysis of the 22 items shows that the main variables of emotional exhaustion, depersonalization and personal accomplishment at work are grouped. Findings show that employees burnout syndrome has made them lower their productivity and performance and some of them show physical signs of sickness that cause absenteeism and apathy towards their job.