Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast 3 D Scanning for Biometric Identification and Verification June 2011 Authors

This document is in the public domain and may be used and reprinted without special permission. Citation of the source is appreciated. None of the investigators have any affiliations or financial involvement that conflicts with the material presented in this report. (Contract HSHQDC-08-C-00100). The findings and conclusions in this document are those of the author(s), who are responsible for its contents; the findings and conclusions do not necessarily represent the views of the Department of Homeland Security. Therefore, no statement in this article should be construed as an official position of the Department of Homeland Security. , we addressed two major issues holding back the adoption of 3D scanning of faces for biometric identification and recognition. This document is the final report, presenting our findings. Our team's intent under this Institute for Homeland Security Solutions (IHSS) program was to tackle two major problems, the disturbing flashing caused by structured light (the leading 3D acquisition method), and the slow speed of acquisition. We proposed to • develop practical ways to generate imperceptible structured light, a University of North Carolina (UNC) invention that projects patterns and their inverse so rapidly that the subject perceives only white light; and • employ commodity graphics processors as computational engines to make the 3D model extraction as rapid as conventional 2D digital photography. The researchers at UNC primarily worked on the first item, while those at SIS worked on the second. The two groups had regular discussions and meetings to enable testing of the imperceptible structured-light projector by SIS to see how it would integrate into the SIS Snapshot 3D scanner. The projector developed at UNC was lent to SIS over the Christmas and New Year holidays (a time when universities generally close) for testing. Feedback from SIS led the UNC team to change the research to look at two problems with the projector: flicker was perceptible when projecting the grey-scale SIS patterns, and the illumination level was low, which reduced the signal-to-noise ratio, thus making it harder to identify the patterns. In the following sections we describe the work on the projector, detail the computational acceleration, and report on the projector evaluation at SIS. As an appendix, we include a research brief that describes methods of 3D scanning, and contrasts them for the application of face scanning. Readers who are not familiar with the technology should begin by reading the appendix.
The neuroscience of depressive disorders: A brief review of the past and some considerations about the future

Depression is a common and debilitating mental health condition whose underlying aetiology and pathophysiology is still relatively poorly understood. In this article, we first turn to the past and briefly review what neuroscientific investigations have taught us so far about depression. In doing so, we cover neurochemical, neuroendocrine, immunological, functional and structural anatomical, and cognitive levels of description. We then turn our attention to the future and discuss where the field might be moving in the years to come. We argue that future developments may rely on three important lines of enquiry: first, the development of an integrated neuroscientific model of depression and its treatment in which different levels of description can be mechanistically linked, and in which distinct pathophysiological trajectories leading to depressive symptomatology can be identified. Second, the continued search for potentially overlooked pathophysiological factors, especially outside the immediate boundaries of the brain. And third, the improvement in translation of neuroscientific insights to aid and advance clinical practice and research.
max-dmin precoder performances in a polarization diversity MIMO channel

This study deals with three transmission schemes because of their ability to achieve the maximum diversity order. Two of them are systems using the full channel state information at the transmitter side (Tx- CSI), i.e. the max-dmin precoder (maximization of minimum Euclidean distance (dmin) and max-SNR precoder (maximization of the received signal-to-noise ratio), whereas the last one is the Alamouti scheme belonging to the orthogonal space-time block code family which needs no Tx-CSI. Their performances are compared by using a dual-polarization channel model to take into account polarization diversity, transmit/receive correlation and estimation errors.
ERP source reconstruction by using Particle Swarm Optimization

Localization of the sources of Event Related Potentials (ERP) is a challenging inverse problem, especially to resolve sources of neural activity occurring simultaneously. By using an effective dipole source model, we propose a new technique for accurate source localization of ERP signals. The parameters of the dipole ERP sources are optimally chosen by using Particle Swarm Optimization technique. Obtained results on synthetic data sets show that proposed method well localizes the dipoles on their actual locations. On real data sets, the fit error between the actual and reconstructed data is successfully reduced to noise level by localizing a few dipoles in the brain.
Finite-Time Chaos Suppression of Permanent Magnet Synchronous Motor Systems

This paper considers the problem of the chaos suppression for the Permanent Magnet Synchronous Motor (PMSM) system via the finite-time control. Based on Lyapunov stability theory and the finite-time controller are developed such that the chaos behaviors of PMSM system can be suppressed. The effectiveness and accuracy of the proposed methods are shown in numerical simulations.
A Novel Application of Phosphorene as a Flame Retardant

Black phosphorene-waterborne polyurethane (BPWPU) composite polymer with 0.2 wt % of black phosphorene was synthesized. Scanning electron microscopy (SEM) was used to observe the morphology of phosphorene in polyurethane matrix, which indicated that the phosphorene distributes uniformly in the PU matrix. The flammability measurements were carried out to investigate the flame-resistant performances of phosphorene, which indicated that phosphorene could effectively restrict the degradation of the PU membrane. Compared by the pure WPU, the limiting oxygen index (LOI) of BPWPU increased by 2.6%, the heat flow determined by thermal analysis significantly decreased by 34.7% moreover, the peak heat release rate (PHRR) decreased by 10.3%.
Variants in nicotinic receptors and risk for nicotine dependence.

OBJECTIVE A recent study provisionally identified numerous genetic variants as risk factors for the transition from smoking to the development of nicotine dependence, including an amino acid change in the alpha5 nicotinic cholinergic receptor (CHRNA5). The purpose of this study was to replicate these findings in an independent data set and more thoroughly investigate the role of genetic variation in the cluster of physically linked nicotinic receptors, CHRNA5-CHRNA3-CHRNB4, and the risk of smoking. METHOD Individuals from 219 European American families (N=2,284) were genotyped across this gene cluster to test the genetic association with smoking. The frequency of the amino acid variant (rs16969968) was studied in 995 individuals from diverse ethnic populations. In vitro studies were performed to directly test whether the amino acid variant in the CHRNA5 influences receptor function. RESULTS A genetic variant marking an amino acid change showed association with the smoking phenotype (p=0.007). This variant is within a highly conserved region across nonhuman species, but its frequency varied across human populations (0% in African populations to 37% in European populations). Furthermore, functional studies demonstrated that the risk allele decreased response to a nicotine agonist. A second independent finding was seen at rs578776 (p=0.003), and the functional significance of this association remains unknown. CONCLUSIONS This study confirms that at least two independent variants in this nicotinic receptor gene cluster contribute to the development of habitual smoking in some populations, and it underscores the importance of multiple genetic variants contributing to the development of common diseases in various populations.
Sequential Decision Making for Improving Efficiency in Urban Environments

Rapid "urbanization" (more than 50% of world's population now resides in cities) coupled with the natural lack of coordination in usage of common resources (ex: bikes, ambulances, taxis, traffic personnel, attractions) has a detrimental effect on a wide variety of response (ex: waiting times, response time for emergency needs) and coverage metrics (ex: predictability of traffic/security patrols) in cities of today. Motivated by the need to improve response and coverage metrics in urban environments, my research group is focussed on building intelligent agent systems that make sequential decisions to continuously match available supply of resources to an uncertain demand for resources. Our broad approach to generating these sequential decision strategies is through a combination of data analytics (to obtain a model) and multistage optimization (planning/scheduling) under uncertainty (to solve the model). While we perform data analytics, our contributions are focussed on multi-stage optimization under uncertainty. We exploit key properties of urban environments, namely homogeneity and anonymity, limited influence of individual entities, abstraction and near decomposability to solve "multi-stage optimization under uncertainty" effectively and efficiently.
JF-Cut : A Parallel Graph Cut Approach for Large-scale Data

Graph Cut has proven to be an effective scheme to solve a wide variety of segmentation problems in graphics community. The main limitation of conventional graph-cut implementations is that they can hardly handle largescale datasets because of high computational complexity. Even though there are some parallelization solutions, they commonly suffer from the problems of low parallelism (on CPU) or low convergence rate (on GPU). In this paper, we present a novel graph cut algorithm that leverages a parallelized jump flooding (JF) technique and a heuristic pushing and relabeling scheme to enhance the components of the graph cut process, namely, multi-pass relabel, convergence detection and block-wise push-relabel. The entire process is parallelizable on GPU, and outperforms existing GPU-based implementations in terms of global convergence, information propagation, and performance. We design an intuitive user interface for specifying interested regions in cases of occlusions when handling volumetric data or video sequences. Experiments on a variety of datasets, including images (up to 15K × 10K), videos (up to 2.5K × 1.5K × 50), and volumetric data, achieve high quality results and a maximum 164-fold speedup over conventional approaches.
Key Elements of an Evidence Detection System

Single point technologies that solve aspects of the evidence detection problem are useful, but incomplete. The combination of these technologies is a necessary step towards providing a comprehensive solution. 21st Century Technologies proposes the fusion of existing technologies to obtain higher order situational awareness. These technologies include: a high-speed scalable search platform, graph pattern matching, analytics, and a shared processing pipeline.
Low Complexity Receiver for Uplink SCMA System via Expectation Propagation

Sparse code multiple access (SCMA) scheme is considered to be one promising non-orthogonal multiple access technology for the future fifth generation (5G) communications. Due to the sparse nature, message passing algorithm (MPA) has been used at the receiver to achieve close to maximum likelihood (ML) detection performance with much lower complexity. However, the complexity order of MPA is still exponential with the size of codebook and the degree of signal superposition on a given resource element. In this paper, we propose a novel low complexity iterative receiver based on expectation propagation algorithm (EPA), which reduces the complexity order from exponential to linear. Simulation results demonstrate that the proposed EPA receiver achieves nearly the same block error rate (BLER) performance as the conventional message passing algorithm (MPA) receiver with orders less complexity.
Genomic Characterization of Group C Orthobunyavirus Reference Strains and Recent South American Clinical Isolates

Group C orthobunyaviruses (family Bunyaviridae, genus Orthobunyavirus), discovered in the 1950s, are vector-borne human pathogens in the Americas. Currently there is a gap in genomic information for group C viruses. In this study, we obtained complete coding region sequences of reference strains of Caraparu (CARV), Oriboca (ORIV), Marituba (MTBV) and Madrid (MADV) viruses, and five clinical isolates from Peru and Bolivia, using an unbiased de novo approach consisting of random reverse transcription, random anchored PCR amplification, and high throughput pyrosequencing. The small, medium, and large segments encode for a 235 amino acid nucleocapsid protein, an approximately 1430 amino acid surface glycoprotein polyprotein precursor, and a 2248 amino acid RNA-dependent RNA polymerase, respectively. Additionally, the S segment encodes for an 83 amino acid non-structural protein, although this protein is truncated or silenced in some isolates. Phylogenetically, three clinical isolates clustered with CARV, one clustered with MTBV, and one isolate appeared to be a reassortant or a genetic drift resulted from the high variability of the medium segment which was also seen in a few other orthobunyaviruses. These data represent the first complete coding region sequences for this serocomplex of pathogenic orthobunyaviruses. The genome-wide phylogeny of reference strains is consistent with the antigenic properties of the viruses reported in the original serological studies conducted in the 1960s. Comparative analysis of conserved protein regions across group C virus strains and the other orthobunyavirus groups revealed that these group C viruses contain characteristic domains of potential structural and functional significance. Our results provide the basis for the developments of diagnostics, further genetic analyses, and future epidemiologic studies of group C viruses.
Optical switching: switch fabrics, techniques, and architectures

The switching speeds of electronics cannot keep up with the transmission capacity offered by optics. All-optical switch fabrics play a central role in the effort to migrate the switching functions to the optical layer. Optical packet switching provides an almost arbitrary fine granularity but faces significant challenges in the processing and buffering of bits at high speeds. Generalized multiprotocol label switching seeks to eliminate the asynchronous transfer mode and synchronous optical network layers, thus implementing Internet protocol over wavelength-division multiplexing. Optical burst switching attempts to minimize the need for processing and buffering by aggregating flows of data packets into bursts. In this paper, we present an extensive overview of the current technologies and techniques concerning optical switching.
Switching Asymmetric GARCH and Options on a Volatility Index

Few proposed types of derivative securities have attracted as much attention and interest as option contracts on volatility. Grunbichler and Longstaff (1996) is the only study that proposes a model to value options written on a volatility index. Their model, which is based on modeling volatility as a GARCH process, does not take into account the switching regime and asymmetry properties of volatility. We show that the Grunbichler and Longstaff (1996) model underprice a 3-month option by about 10%. A Switching Regime Asymmetric GARCH is used to model the generating process of security returns. The comparison between the switching regime model and the traditional uni-regime model among GARCH, EGARCH, and GJR-GARCH demonstrates that a switching regime EGARCH model fits the data best. Next, the values of European call options written on a volatility index are computed using Monte Carlo integration. When comparing the values of the option based on the Switching Regime Asymmetric GARCH model and the traditional GARCH specification, it is found that the option values obtained from the different processes are very different. This clearly shows that the Grunbichler-Longstaff model is too stylized to be used in pricing derivatives on a volatility index.
Monitoring the Progressing Glaucoma Patient – What Are the Challenges?

Glaucoma is a chronic, progressive optic neuropathy mostly associated with elevated intraocular pressure (IOP). Without adequate management, glaucoma can lead to reduced quality of life (QoL) and irreversible visual loss. Glaucoma affects approximately 67 million people worldwide and is the second leading cause of blindness in the world. Detection of glaucoma progression is crucial for the identification of patients at risk of visual loss.
Neuroprotective Effects of Ginsenoside Rb1 on High Glucose-Induced Neurotoxicity in Primary Cultured Rat Hippocampal Neurons

Ginsenoside Rb1 is one of the main active principles in traditional herb ginseng and has been reported to have a wide variety of neuroprotective effects. Endoplasmic reticulum (ER) stress has been implicated in neurodegenerative diseases, so the present study aimed to observe the effects of ginsenoside Rb1 on ER stress signaling pathways in high glucose-treated hippocampal neurons. The results from MTT, TUNEL labeling and Annexin V-FITC/PI/Hoechst assays showed that incubating neurons with 50 mM high glucose for 72h decreased cell viability and increased the number of apoptotic cells whereas treating neurons with 1 μM Rb1 for 72h protected the neurons against high glucose-induced cell damage. Further molecular mechanism study demonstrated that Rb1 suppressed the activation of ER stress-associated proteins including protein kinase RNA (PKR)-like ER kinase (PERK) and C/EBP homology protein (CHOP) and downregulation of Bcl-2 induced by high glucose. Moreover, Rb1 inhibited both the elevation of intracellular reactive oxygen species (ROS) and the disruption of mitochondrial membrane potential induced by high glucose. In addition, the high glucose-induced cell apoptosis, activation of ER stress, ROS accumulation and mitochondrial dysfunction can also be attenuated by the inhibitor of ER stress 4-phenylbutyric acid (4-PBA) and anti-oxidant N-acetylcysteine(NAC). In conclusion, these results suggest that Rb1 may protect neurons against high glucose-induced cell injury through inhibiting CHOP signaling pathway as well as oxidative stress and mitochondrial dysfunction.
VANNGen: a flexible CAD tool for hardware implementation of artificial neural networks

The inherent parallelism of artificial neural networks (ANNs) introduces several difficulties for its software implementation because of the sequential nature of von Neumann architectures. In contrast, hardware implementations offer the possibility to explore the massive parallelism implicit in this model. Also, due to the dynamic nature of ANN's synapses, a flexible hardware platform is required for obtaining efficient solutions. Implementations of ANNs in FPGAs overcome the lack of flexibility of ASICs, and are the most adequate technology for this task. One important question in this field is how to quickly and efficiently evaluate several alternative implementations taking into account the area and timing restrictions of the circuit. This paper presents a flexible high level description and synthesis tool called VANNGen, which allows the designer to explore different hardware implementations of ANNs. In addition, the user can generate synthesizable VHDL code for the Xilinx and Altera FPGA devices
Cognition in an Ever-Changing World: Climatic Variability Is Associated with Brain Size in Neotropical Parrots

Research on the conditions favoring the evolution of complex cognition and its underlying neural structures has increasingly stressed the role of environmental variability. These studies suggest that the ability to learn, behave flexibly and innovate would be favored under unpredictable variations in the availability of resources, as it would enable organisms to adjust to novel conditions. Despite the growing number of studies based on the idea that larger-brained organisms would be better prepared to cope with environmental challenges, direct testing of the association between brain size and environmental variability per se remains scant. Here we focus on Neotropical parrots as our model group and test the hypothesis that if relatively larger brains were favored in climatically variable environments, larger-brained species should currently tolerate a higher degree of environmental uncertainty. Although we show that there are also other factors underlying the dynamics of brain size variation in this group, our results support the hypothesis that proportionally larger-brained species are more tolerant to climatic variability, both on a temporal and spatial scale. Additionally, they suggest that the differences in relative brain size among Neotropical parrots represent multiple, recent events in the evolutionary history of the group, and are particularly tied to an increased dependence on more open and climatically unstable habitats. As this is the first study to present evidence of the link between brain size and climatic variability in birds, our findings provide a step towards understanding the potential benefits underlying variation in brain size and the maintenance of highly enlarged brains in this and other groups.
PACT: an experiment in integrating concurrent engineering systems

The Palo Alto Collaborative Testbed (PACT), a concurrent engineering infrastructure that encompasses multiple sites, subsystems, and disciplines, is discussed. The PACT systems include NVisage, a distributed knowledge-based integration environment for design tools; DME (Device Modeling Environment), a model formulation and simulation environment; Next-Cut, a mechanical design and process planning system; and Designworld, a digital electronics design, simulation, assembly, and testing system. The motivations for PACT and the significance of the approach for concurrent engineering is discussed. Initial experiments in distributed simulation and incremental redesign are reviewed, and PACT's agent-based architecture and lessons learned from the PACT experiments are described. <<ETX>>
Almost Linear Biobasis Function Neural Networks

An analysis of biobasis function neural networks is presented, which shows that the similarity metric used is a linear function and that bio-basis function neural networks therefore often end up being just linear classifiers in high dimensional spaces. This is a consequence of four things: the linearity of the distance measure, the normalization of the distance measure, the recommended default values of the parameters, and that biological data sets are sparse.
Learning lightness from human judgement on relative reflectance

We develop a new approach to inferring lightness, the perceived reflectance of surfaces, from a single image. Classic methods view this problem from the perspective of intrinsic image decomposition, where an image is separated into reflectance and shading components. Rather than reason about reflectance and shading together, we learn to directly predict lightness differences between pixels. Large-scale training from human judgement data on relative reflectance, and patch representations built using deep networks, provide the foundation for our model. Benchmarked on the Intrinsic Images in the Wild dataset [4], our local lightness model achieves on-par performance with the state-of-the-art global lightness model, which incorporates multiple shading/reflectance priors and simultaneous reasoning between pairs of pixels in a dense conditional random field formulation.