Miracle-dz/UniFAR-FTUs huggingface dataset:
DISPARITY MAP GENERATION BASED ON TRAPEZOIDAL CAMERA ARCHITECTURE FOR MULTI -VIEW VIDEO

Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities, the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video remains a huge challenge. This paper presents the mathematical description of trapezoidal camera architecture and relationships which facilitate the determination of camera position for visual content acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera Architecture is that it allows for adaptive camera topology by which points within the scene, especially the occluded ones can be optically and geometrically viewed from several different viewpoints either on the edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate description could very well be used to address the issue of occlusion which continues to be a major problem in computer vision with regards to the generation of depth map.
Agent based task specific team formation for effective distributed decision making

Getting solution of a problem by group discussion is more reliable than getting solution from a single entity. To increase reliability of the solution, efficient group of experts should be formed. Here in this paper we have proposed a methodology for finding efficient team of experts for solution of a given problem collaboratively. The methodology is conceptualized with the notion of Multiagent system. We have considered several factors like Cardinality of team, ability, willingness, trust and reciprocality of an agent in order to construct the team. We have also proposed an optimization function which will be used to choose most eligible agents to form the team of experts.
Gandra-Barta: reconhecimento emocional de faces no envelhecimento normal

This work aims to determine the sensitivity of the base Gandra-BARTA, to alterations in the ability of emotional recognition of faces due to aging. Subsequently, it is intended to recognize the relationship between the capacity of recognition of various emotions, as well as the total time of recognition with the depression level. The test contains of 59 photographs with 6 universal emotions (happiness, sadness, disgust, anger, fear and surprise) and neutral. The sample has 29 participants, 12 young adults (aged 31 to 39 years) and 17 older adults (aged 60 to 82 years). Through the application of MoCA and GDS found that the participants did not have cognitive impairment or severe depression. The results show that older people are slower to perform the test and have a number of hits, the emotions generally quite low compared to young adults. However, we found that the worst emotion identified by the elderly is anger and, to a lesser extent, the neutral expressions. These results they direct future studies to test this behavior in different clinical groups: different types of dementia, traumatic brain injury, depression, among others.
Neoadjuvant chemotherapy: are we barking up the right tree?

editorial Neoadjuvant chemotherapy: are we barking up the right tree? In 2006, Frasci et al. published in Annals of Oncology the final analysis of a Southern Italy Oncology Cooperative Group (SICOG) phase III study that compared weekly cycles of the dose-dense cisplatin–epirubicin–paclitaxel (PET) chemotherapy regimen with triweekly cycles of epirubicin–paclitaxel in locally advanced breast cancer. Pathological complete response (pCR) was designed as the main end point [1]. Four years later, an update of this trial is published in the same journal [2]. This analysis focuses on relapse-free survival (RFS), distant metastasis-free survival (DMFS) and overall survival (OS). These last results merit particular consideration as they present a previously unpublished large and statistically significant improvement of both DMFS and OS in favour of a platinum-containing dose-dense regimen in a (neo)adjuvant setting. However, a major pitfall is that it was neither DMFS nor OS that was the primary end point of this phase III study, but pCR. Did Frasci et al. choose the appropriate end point? High prognostic value of major response to preoperative chemotherapy in breast carcinoma has been described 25 years ago [3]. The high correlation between pCR (mainly both within the breast and within the axillary lymph nodes) and long-term outcome was confirmed by other groups in univariate and multivariate analyses [4, 5]. Coupled with the ease of obtaining information at a fixed and early date after patient inclusion, achievement of pCR has become a widely used end point for clinical research in neoadjuvant settings. Since the introduction of the neoadjuvant strategy in daily practice, at least a dozen pathological response classifications have been proposed. The first ones were primarily on the basis of final pathological assessments of residual disease on post-treatment surgical bed specimens. The strong prognostic value of residual disease in axillary lymph nodes has been highlighted [6], while it has been shown that residual ductal in situ components in tumour beds do not have prognostic significance [7]. During the last 3 years, four new pathological classifications have been described taking into account pretreatment staging, either clinically [8], or using breast contrast-enhanced magnetic resonance imaging and axillary ultrasonography [9] or by bidimensional measurement of the primary bed in the resection specimen [10]. A 'neoadjuvant response index' estimating the degree of downstaging achieved by the neoadjuvant treatment has been developed in order to compare the efficacy of different neoadjuvant regimens and to evaluate the sensitivity of tumour subtypes …
Lipid raft involvement in yeast cell growth and death

The notion that cellular membranes contain distinct microdomains, acting as scaffolds for signal transduction processes, has gained considerable momentum. In particular, a class of such domains that is rich in sphingolipids and cholesterol, termed as lipid rafts, is thought to compartmentalize the plasma membrane, and to have important roles in survival and cell death signaling in mammalian cells. Likewise, yeast lipid rafts are membrane domains enriched in sphingolipids and ergosterol, the yeast counterpart of mammalian cholesterol. Sterol-rich membrane domains have been identified in several fungal species, including the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe as well as the pathogens Candida albicans and Cryptococcus neoformans. Yeast rafts have been mainly involved in membrane trafficking, but increasing evidence implicates rafts in a wide range of additional cellular processes. Yeast lipid rafts house biologically important proteins involved in the proper function of yeast, such as proteins that control Na+, K+, and pH homeostasis, which influence many cellular processes, including cell growth and death. Membrane raft constituents affect drug susceptibility, and drugs interacting with sterols alter raft composition and membrane integrity, leading to yeast cell death. Because of the genetic tractability of yeast, analysis of yeast rafts could be an excellent model to approach unanswered questions of mammalian raft biology, and to understand the role of lipid rafts in the regulation of cell death and survival in human cells. A better insight in raft biology might lead to envisage new raft-mediated approaches to the treatment of human diseases where regulation of cell death and survival is critical, such as cancer and neurodegenerative diseases.
Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Random number generation is a very important operation in computational science e.g. in Monte Carlo simulations methods. It is also a computationally intensive operation especially for high quality random number generation. In this paper, we present the design and implementation of a parallel implementation of one of the most widely used random number generators, namely the Mersenne Twister. The latter is very widely used in high performance computing applications such as financial computing. Implementations of our parallel Mersenne Twister number generator core on Xilinx Virtex4 FPGAs achieve a throughput of 26.13 billion random samples per second. The paper also reports equivalent parallel software implementations running on an Intel Core 2 Quad Q9300 CPU with 8 GB RAM, using multi-threading technology and the Intel® Math Kernel Library (MKL), as well as on an NVIDIA 8800 GTX GPU. Comparative results show that our FPGA-based implementation outperforms equivalent CPU and GPU implementations by ~25x and ~9x respectively. Moreover, when using the same amount of energy, the FPGA can generate 37x and 35x more Mersenne Twister random samples than the CPU and the GPU, respectively.
NMDA receptors are essential for the acquisition, but not expression, of conditional fear and associative spike firing in the lateral amygdala

We examined the contribution of N‐methyl‐D‐aspartate (NMDA) receptors (NMDARs) to the acquisition and expression of amygdaloid plasticity and Pavlovian fear conditioning using single‐unit recording techniques in behaving rats. We demonstrate that NMDARs are essential for the acquisition of both behavioral and neuronal correlates of conditional fear, but play a comparatively limited role in their expression. Administration of the competitive NMDAR antagonist ±‐3‐(2‐carboxypiperazin‐4‐yl) propyl‐1‐phosphonic acid (CPP) prior to auditory fear conditioning completely abolished the acquisition of conditional freezing and conditional single‐unit activity in the lateral amygdala (LA). In contrast, CPP given prior to extinction testing did not affect the expression of conditional single‐unit activity in LA, despite producing deficits in conditional freezing. Administration of CPP also blocked the induction of long‐term potentiation in the amygdala. Together, these data suggest that NMDARs are essential for the acquisition of conditioning‐related plasticity in the amygdala, and that NMDARs are more critical for regulating synaptic plasticity and learning than routine synaptic transmission in the circuitry supporting fear conditioning.
Novel Evaluation Index for Image Quality

Indexes used for image quality evaluation are provided as computational models to measure the quality of images in a perceptually consistent manner. This paper presents a novel evaluation index for assessing image qualities. The index is a modification of the existing traditional Structural Similarity Index Measure (SSIM) by adding another factor to reflect the shape of the brightness histogram of the assessed image. The proposed index therefore is a combination of four major factors luminance, contrast, structure and shape of histogram. This index is mathematically simple and applicable in various image processing. For demonstration a new image de-noising approach using an adaptive shrinkage threshold in the shearlet domain is used. Experimental results show that the new image quality indexes give better prediction accuracy, better prediction monotonicity than PSNR, HQI, UIQI and SSIM.
Reference-Based Transitions in Short-Run Price Elasticity

Marketing literature has long recognized that price response need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on reference price type, asymmetric thresholds and sign and magnitude of elasticity transitions. In this paper, we introduce smooth transition models to study reference-based price response across 25 fast moving consumer good categories. Our application to 100 brands shows that 77% demonstrate reference-based price response, of which 36% reflects historical reference prices, 31% reflects competitive reference prices, and 33% reflects both types of reference prices. This reference-based price response shows asymmetry for gains versus losses on three levels: the threshold size, the sign and the magnitude of the elasticity difference. For historical reference prices, the threshold size is larger for gains (20%) than for losses (12%) and the assimilation/contrast effects for gains (-0.41) are smaller than the saturation effects for losses (0.81). For competitive reference prices, the threshold size is smaller for gains (3%) than for losses (16%), and the saturation effects are larger for gains (0.33) than for losses (0.15). These results are moderated by both brand and category characteristics that affect reference price accessibility and diagnosticity. Historical reference prices more often play a role for national brands, for planned purchases and in inexpensive categories with low price volatility and high purchase frequency. When price discounting, high-share brands face larger latitudes of acceptance. When raising prices, saturation effects set in later for brands with high price volatility and for categories with high price spread and for planned purchases. As for competitive reference prices, saturation effects set in later for expensive brands with high price volatility and in categories with lower price volatility, higher price spread and higher concentration. Sales, revenue and margin implications are illustrated for price changes typically observed in consumer markets.
The Role of Self-efficacy and Social Support in Emerging Adults' Physical Activity

The Role of Self-efficacy and Social Support in Emerging Adults’ Physical Activity Nicole M. Silva Emerging adulthood is a time where emerging adults develop health behaviors that persist throughout the life span (Barnett et al., 2014). However, only 55.4% of emerging adults engage in the recommended amount of physical activity each week (U.S. Department for Health and Human Services, 2013). The current study examined two factors that are associated with physical activity, specifically self-efficacy and social support, in 403 (M age = 19.25, SD = 1.12) emerging adults. Linear regressions indicated that emerging adults who reported higher levels of general self-efficacy (β = .13, p < .05), domain self-efficacy (β = .33, p < .05), and support from the entire social network (β = .50, p < .001) engaged in more physical activity. Support from the entire social network still accounted for a significant portion of the variance in physical activity when accounting for general or domain self-efficacy (β for support = .48, p < .001 and .30, p < .05, respectively). The differential effects of source of support (i.e., family and friends) and type of support (i.e., esteem support, informational support, and companionship support) were also examined. Emerging adults who reported higher levels of support from family (β = .22, p < .001) and friends (β = .33, p < .001) engaged in more physical activity. Although emerging adults reported receiving more esteem support from family (M = 2.95, SD = 1.23) compared to friends (M = 2.74, SD = 1.15), esteem support from friends (β = .33, p < .001) had a larger effect on physical activity than esteem support from family (β = .21, p < .05).
Explaining Evolutionary Shifts between Bee and Hummingbird Pollination: Convergence, Divergence, and Directionality

In certain angiosperm genera, closely related species have diverged from one another to converge on different pollination syndromes, whereas species with intermediate phenotypes are rare or absent. Convergent conformity to syndromes implies the existence of “evolutionary attractors” toward which phenotypes are drawn; divergent breaks from conformity show that populations can escape one attractor and be drawn to another. We discuss how these two opposed processes can be reconciled for the special case of evolutionary transitions between bee pollination and hummingbird pollination. In this case, a third phenomenon, the directional bias in favor of transitions from melittophily to ornithophily, also needs explanation. Older treatments chiefly ascribed convergence to cognitive and morphological properties of pollinators and ascribed transitions to geographical differences in pollinator availability. Those treatments did not specifically address what factors would overcome and disrupt the stabilizing selection that would be expected to preserve the pollination syndrome of a plant species. Here, we focus on possible contributors to destabilization, especially considering the possible roles of (1) differences among pollinators in pollen‐transfer efficiency, (2) mutations with large effects on floral phenotypes, and (3) losses of function in the biochemical pathways that produce floral pigments. We conclude that all of these can influence the evolution of pollinator transitions but that the process usually needs to be initiated by external ecological factors that change the visitation rates of pollinators. We discuss the roles of particular floral characters in several plant genera that have undergone transitions. We expect that transitions reach completion through a “centripetal” process of selection that incrementally recruits changes in multiple characters.
A Comparison of Case Acquisition Strategies for Learning from Observations of State-Based Experts

This paper focuses on case acquisition strategies in the context of Case-based Learning from Observation (CBLfO). In Learning from Observation (LfO), a system learns behaviors by observing an expert rather than being explicitly programmed. Specifically, we focus on the problem of learning behaviors from experts that reason using internal state information, that is, information that can not be directly observed. The unobservability of this state information means that the behaviors can not be represented by a simple perception-to-action mapping. We propose a new case acquisition strategy called Similarity-based Chunking, and compare it with existing strategies to address this problem. Additionally, since standard classification accuracy in predicting the expert’s actions is known to be a poor measure for evaluating LfO systems, we propose a new evaluation procedure based on two complementary metrics: behavior performance and similarity with the expert.
Holographic power-law traps for the efficient production of Bose-Einstein condensates

We use a phase-only spatial light modulator to generate light distributions in which the intensity decays as a power law from a central maximum with order ranging from 2 (parabolic) to 0.5. We suggest that a sequence of these can be used as a time-dependent optical dipole trap for all-optical production of Bose-Einstein condensates (BECs) in two stages: efficient evaporative cooling in a trap with adjustable strength and depth, followed by an adiabatic transformation of the trap order to cross the BEC transition in a reversible way. Realistic experimental parameters are used to verify the capability of this approach in producing larger BECs than by evaporative cooling alone.
Score-based vs Constraint-based Causal Learning in the Presence of Confounders

We compare score-based and constraint-based learning in the presence of latent confounders. We use a greedy search strategy to identify the best ﬁtting maximal ancestral graph (MAG) from continuous data, under the assumption of multivariate normality. Scoring maximal ancestral graphs is based on (a) residual iterative conditional ﬁtting [Drton et al., 2009] for obtaining maximum likelihood estimates for the parameters of a given MAG and (b) factorization and score decomposition results for mixed causal graphs [Richardson, 2009, Nowzohour et al., 2015]. We compare the score-based approach in simulated settings with two standard constraint-based algorithms: FCI and conservative FCI. Results show a promising performance of the greedy search algorithm.
ANISOTROPY BASED SEEDING FOR HYPERSTREAMLINE

This paper presents a new seeding strategy for visualizing 3D symmetric tensor data using hyperstreamlines. The goal is to automate the process of generating seeding patterns to identify important hyperstreamline features. The method is based on anisotropy measurements to optimize the seeding positions and density of hyperstreamlines to reduce visual clutter. Additionally, user can place random distributed seeding points in the tensor field to ensure other minor hyperstreamline features are captured as well. The main advantage of this approach is that the user is not required to have a knowledge of the tensor field in advance.
Neuroprotective Activity of Coptisine from Coptis chinensis (Franch)

Coptis chinensis rhizomes (CR) are one important ingredient of traditional Chinese herbal formulas such as San-Huang-Xie-Xin-Tang which is used for treatment of cardiovascular and neurodegenerative diseases. Recent studies suggest that the extract of CR might be a potential therapeutic agent for amelioration of neurological disorders associated with oxidative stress. In the present study we aimed at revealing the main active compound(s) of the CR extract and at investigating the mechanism of action. Four main alkaloids of the CR extract (berberine, coptisine, jatrorrhizine, and palmatine) were selected for this study. Results showed that out of those alkaloids only pretreatment with coptisine significantly attenuated tert-butylhydroperoxide induced reduction of cell viability, increased rate of apoptosis, and declined mitochondrial membrane potential. Elisa assay and quantitative real-time PCR analyses revealed that thioredoxin-interacting protein (TXNIP) gene expression was downregulated by coptisine, which could explain the neuroprotective effect, hypothetically, by strengthening the thioredoxin defense system against oxidative stress and attenuation of apoptosis signal-regulating kinase (Ask1) mediated apoptotic signaling. A comparison between coptisine and CR extract identified coptisine as the main single component responsible for the neuroprotective effect. Based on the results the CR extract and coptisine are promising candidate agents for prevention or improvement of diabetic neuropathy and neurodegenerative disorders.
Research on Frequency Envelope Mapping Based on GMM

A mapping function between different speaker frequency envelopes based on GMM is put forward, in which several linear functions are combined by probability, and LSF parameter is adopted to reflect the frequency envelope. The initial mapping parameter are gotten by the relation of average and covariance between source and target GMM. Furthermore, the EM algorithm is adopted to refine the mapping function, by which the estimation of target feature can be gotten from the source feature. All the analysis of histogram, the difference between estimation and the real target feature with time and the DTW distance show that, the proposed mapping function can well characterize the relationship between source and target features.
Interference Graph-Based Resource-Sharing Schemes for Vehicular Networks

This paper investigates the resource-sharing problem in vehicular networks, including both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication links. A novel underlaying resource-sharing communication mode for vehicular networks is proposed, in which different V2V and V2I communication links are permitted to access the same resources for their individual data transmission. To solve the resource-sharing problem in vehicular networks, we, for the first time, apply graph theory and propose the following two interference graph-based resource-sharing schemes: 1) the interference-aware graph-based resource-sharing scheme and 2) the interference-classified graph-based resource-sharing scheme. Compared with the traditional orthogonal communication mode in vehicular networks, the proposed two resource-sharing schemes express better network sum rate. The utility of the proposed V2V and V2I underlaying communication mode and the two proposed interference graph-based resource-sharing schemes are verified by simulations.