Miracle-dz/UniFAR-FTUs huggingface dataset:
What Suicides Reveal About Gender Bias

This article uses some general findings in the medical literature on suicide to suggest how male and female suicide rates in a society can be used to measure the "unfreedom" of women relative to that of men. Our definition of "unfreedom" is similar to that of Amartya Sen and consists of all kinds of suppression of mental or physical freedoms such as physical or sexual abuse, poverty, lack of economic opportunities, and so on, as well as an absence of liberty to voice complaints about the denial of the mentioned elementary freedoms. Though suicides are often associated with mental disease partially attributable to genetic factors, a mental illness is neither necessary nor sufficient for suicide. Rather a suicide is often the result of a multiple coincidence of mental disorders and repression of elementary freedoms. Given that the male and female cohorts in a society have the same genetic background, a major change in the male female ratio of suicide rates can conceivably occur only through a change in the relative incidence of unfreedoms. An application of this inference is attempted for Indian states.
Thermal-sensitive design and power optimization for a 3D torus-based optical NoC

In order to overcome limitations of traditional electronic interconnects in terms of power efficiency and bandwidth density, optical networks-on-chip (NoCs) based on 3D integrated silicon photonics have been proposed as an emerging on-chip communication architecture for multiprocessor systems-on-chip (MPSoCs) with large core counts. However, due to thermo-optic effects, wavelength-selective silicon photonic devices such as microresonators, which are widely used in optical NoCs, suffer from temperature-dependent wavelength shifts. As a result, on-chip temperature variations cause significant thermal-induced optical power loss which may counteract the power advantages of optical NoCs. To tackle this problem, in this work, we present a thermal-sensitive design and power optimization approach for a 3D torus-based optical NoC architecture. Based on an optical thermal modeling platform which models the thermal effect in optical NoCs from a system-level perspective, a thermal-sensitive routing algorithm is proposed for the 3D torus-based optical NoC to optimize its power consumption in the presence of on-chip temperature variations. Simulation results show that in an 8×8×2 3D torus-based optical NoC under a set of real applications, as compared with a matched 3D mesh-based optical NoC with traditional dimension order routing, the power consumption is reduced by 25% if thermal tuning for microresonators is not utilized, by 19% if thermal tuning is utilized for microresonators, and by 17% if athermal microresonators are used.
The Effect of Mergers and Acquisitions on Market Power and Efficiency

A fundamental question in the analysis of mergers and acquisitions (M&As) is the potential tradeoff between increased market power and efficiency gains. The evidence on this tradeoff in the literature, however, is far from conclusive. Case studies of M&A find mixed evidence, and estimation in more general settings is hampered by the difficulty of separately identifying productivity from markups. In this paper, we use new techniques to separately estimate productivity and markups across heterogeneous industries using firm‐ or plant‐level data, and then employ these estimates in a differences‐in‐differences framework to examine the average impact of M&A activity on productivity and mark‐ups. We employ data on M&A transactions combined with U.S. Census plant‐level data for the entire U.S. manufacturing sector over the 1997 to 2007 period. Robust to a variety of specifications, we find significant evidence of increased markups after M&A, but no evidence of any average impact on plant‐level productivity. Moreover, we find that the increase in markups generates overstated effects of mergers on traditional revenue productivity measures.
On the recombination operator in the real-coded genetic algorithms

Crossover is the most important operator in real-coded genetic algorithms. However, the choice of the best operator for a specific problem can be a difficult task. In this paper we compare 16 crossover operators on a set of 24 benchmark functions. A detailed statistical analysis is performed in an effort to find the best performing operators. The results show that there are significant differences in efficiency of different crossover operators, and that the efficiency may also depend on the distinctive properties of the fitness function. Additionally, the results point out that the combination of crossover operators yields the best results.
Joint Spatial Division and Multiplexing for mm-Wave Channels

Massive MIMO systems are well-suited for mm-Wave communications, as large arrays can be built with reasonable form factors, and the high array gains enable reasonable coverage even for outdoor communications. One of the main obstacles for using such systems in frequency-division duplex mode, namely, the high overhead for the feedback of channel state information (CSI) to the transmitter, can be mitigated by the recently proposed joint spatial division and multiplexing (JSDM) algorithm. In this paper, we analyze the performance of this algorithm in some realistic propagation channels that take into account the partial overlap of the angular spectra from different users, as well as the sparsity of mm-Wave channels. We formulate the problem of user grouping for two different objectives, namely, maximizing spatial multiplexing and maximizing total received power in a graph-theoretic framework. As the resulting problems are numerically difficult, we proposed (sub optimum) greedy algorithms as efficient solution methods. Numerical examples show that the different algorithms may be superior in different settings. We furthermore develop a new, “degenerate” version of JSDM that only requires average CSI at the transmitter and thus greatly reduces the computational burden. Evaluations in propagation channels obtained from ray tracing results, as well as in measured outdoor channels, show that this low-complexity version performs surprisingly well in mm-Wave channels.
Digital Ira and Beyond : Creating Photoreal Real-Time Digital Characters

classroom use is granted without fee provided that copies are not made or distributed for commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author. Sum m ar y Statem ent This course explains a complete process for creating next-generation realtime digital human characters, using the Digital Ira collaboration between USC ICT and Activision as an example, covering highres facial scanning, blendshape rigging, video-based performance capture, animation compression, realtime skin and eye shading, hair, latest results, and future directions. This course will present the process of creating "Digital Ira" seen at the SIGGRAPH 2013 Real-Time live venue, covering the complete set of technologies from high resolution facial scanning, blendshape rigging, video-based performance capture, animation compression, realtime skin and eye shading, and hair rendering. The course will also present and explain late-breaking results and refinements and point the way along future directions which may increase the quality and efficiency of this kind of digital character pipeline. The actor from this project was scanned in 30 high-resolution expressions from which eight were chosen for real-time performance rendering. Performance clips were captured using multi-view video. Expression UVs were interactively corresponded to the neutral expression, retopologized to an artist mesh. An animation solver creates a performance graph representing dense GPU optical flow between video frames and the eight expressions; dense optical flow and 3D triangulation are computed, yielding per-frame spatially varying blendshape weights approximating the performance. The performance is converted to standard bone animation on a 4k mesh using a bone-weight and transform solver. Surface stress values are used to blend albedo, specular, normal, and displacement maps from the high-resolution scans per-vertex at run time. DX11 rendering includes SSS, translucency, eye refraction and caustics, physically based two-lobe specular reflection with microstructure, DOF, antialiasing, and grain. The course will explain each of processes, mentioning why each design choice was made and pointing to alternative components which may have been employed in place of any of the steps. We will also cover emerging technologies in performance capture and facial rendering. Attendees will receive a solid understanding of the techniques used to create photoreal digital characters in video games and other applications, and the confidence to incorporate some of the techniques into their own pipelines. Pr er equisites Some experience with video game pipelines, …
Low-Actuation Voltage MEMS Digital-to-Analog Converter with Parylene Spring Structures

We propose an electrostatically-actuated microelectromechanical digital-to-analog converter (M-DAC) device with low actuation voltage. The spring structures of the silicon-based M-DAC device were monolithically fabricated using parylene-C. Because the Young’s modulus of parylene-C is considerably lower than that of silicon, the electrostatic microactuators in the proposed device require much lower actuation voltages. The actuation voltage of the proposed M-DAC device is approximately 6 V, which is less than one half of the actuation voltages of a previously reported M-DAC equipped with electrostatic microactuators. The measured total displacement of the proposed three-bit M-DAC is nearly 504 nm, and the motion step is approximately 72 nm. Furthermore, we demonstrated that the M-DAC can be employed as a mirror platform with discrete displacement output for a noncontact surface profiling system.
Methods of Fluid Properties for Compressible Refrigerant CFD Analysis

There are numerous ways of defining fluid properties for computational fluid dynamic (CFD) simulations. This paper examines three methods of defining fluid properties that are available in a commercial CFD code. Simulations were carried out for an R410a scroll compressor used in air conditioning applications and the effects are illustrated through the compression process. The first method used is the real gas property data from the National Institute of Standards and Technology (NIST). While considered the most accurate, it is not available in all CFD codes. A second method is the Peng Robinson equation of state, which approximates the real gas properties. The most widely available method, the ideal gas equation of state model, is also examined. Using the three different methods for defining fluid properties, CFD simulations of two different discharge porting schemes were analyzed. Modeling results are evaluated, used in overall compressor performance estimates, and then compared to laboratory tests results. The results of these analyses are reviewed to illustrate the impact of the choice of property-definition methods on important design decisions. This information can also have an impact on the choice of CFD software, since not all CFD software has the fluid property options described in this paper.
Extracting aspEcts , sEntimEnt and catEgoriEs of aspEcts in UsEr rEviEws aboUt rEstaUrants and cars

This paper describes a method for solving aspect-based sentiment analysis tasks in restaurant and car reviews subject domains. These tasks were articulated in the Sentiment Evaluation for Russian (SentiRuEval-2015) initiative. During the SentiRuEval-2015 we focused on three subtasks: extracting explicit aspect terms from user reviews (tasks A), aspect-based sentiment classification (task C) as well as automatic categorization of aspects (task D). In aspect-based sentiment classification (tasks C and D) we propose two supervised methods based on a Maximum Entropy model and Support Vector Machines (SVM), respectively, that use a set of term frequency features in a context of the aspect term and lexicon-based features. We achieved 40% of macro-averaged F-measure for cars and 40,05% for reviews about restaurants in task С. We achieved 65.2% of macro-averaged F-measure for cars and 86.5% for reviews about restaurants in task D. This method ranked first among 4 teams in both subject domains. The SVM clas-sifier is based on unigram features and pointwise mutual information to calculate category-specific score and associate each aspect with a proper category in a subject domain. In task A we carefully evaluated performance of a method based on syntactic and statistical features incorporated in a Conditional Random Fields model. Unfortunately, the method did not show any significant improvement over a baseline. However, its results are also presented in the paper.
Microenvironment and Immunology DermatanSulfate Is Involved in the TumorigenicProperties of Esophagus Squamous Cell Carcinoma

Extracellular matrix, either produced by cancer cells or by cancer-associated fibroblasts, influences angiogenesis, invasion, and metastasis. Chondroitin/dermatan sulfate (CS/DS) proteoglycans, which occur both in the matrix and at the cell surface, play important roles in these processes. The unique feature that distinguishes DS from CS is the presence of iduronic acid (IdoA) in DS. Here, we report that CS/DS is increased five-fold in human biopsies of esophagus squamous cell carcinoma (ESCC), an aggressive tumor with poor prognosis, as compared with normal tissue. Themain IdoA-producing enzyme, DS epimerase 1 (DS-epi1), together with the 6-Oand 4-Osulfotransferases, were highly upregulated in ESCC biopsies. Importantly, CS/DS structure in patient tumors was significantly altered compared with normal tissue, as determined by sensitive mass spectrometry. To further understand the roles of IdoA in tumor development, DS-epi1 expression, and consequently IdoA content, was downregulated in ESCC cells. IdoA-deficient cells exhibited decreasedmigration and invasion capabilities in vitro, whichwas associatedwith reduced cellular binding of hepatocyte growth factor, inhibition of pERK-1/2 signaling, and deregulated actin cytoskeleton dynamics and focal adhesion formation. Our findings show that IdoA in DS influences tumorigenesis by affecting cancer cell behavior. Therefore, downregulation of IdoA by DS-epi1 inhibitors may represent a new anticancer therapy. Cancer Res; 72(8); 1943–52. 2012 AACR.
Targeted knockdown of Bcl2 in tumor cells using a synthetic TRAIL 3′‐UTR microRNA

Targeting tumor‐related overexpression of anti‐apoptotic Bcl2 protein by RNAi has been suggested as a potential treatment for cancer. However, the stability of RNAi and its delivery are still major obstacles to the clinical testing of Bcl2 RNAi. Here, we explore a novel strategy of expressing a synthetic Bcl2 microRNA (smRNA) in the 3′ untranslated region (UTR) of the tumor necrosis factor‐related apoptosis‐inducing ligand (TRAIL), an apoptosis‐inducing protein without apparent toxic effects in normal cells. TRAIL was specifically expressed from the human telomerase reverse transcriptase promoter (pTRT) that is active in many human tumors. Using this approach, we demonstrated that pTRT drove the tumor‐specific expression of Bcl2 smRNA, which was processed by the host RNAi machinery and silenced endogenous Bcl2 expression in tumor cells. Bcl2 smRNA induced tumor cell apoptosis by activating caspase‐3 and led to significant sensitization of tumor cells to TRAIL‐induced apoptosis, while normal cells were spared. We also showed that the combined therapy of TRAIL‐induced apoptosis and Bcl2 downregulation was superior to the mono‐therapy of TRAIL or Bcl2 smRNA alone. This study proves a general paradigm for cancer therapy by using 3′ UTR microRNA technology.
Quantitative reduction of 2,3,4-triphenyl tetrazolium chloride by hamster trachea organ cultures: effects of Mycoplasma pneumoniae cells and membranes

The ability of Mycoplasma pneumoniae cells and membranes to affect tetrazolium reduction by hamster trachea organ cultures was evaluated. Uninfected trachea explants reduced 2,3,5-triphenyl tetrazolium chloride (TTC) and nitro-blue tetrazolium when incubated at 37 C in the absence of air. Reduced tetrazolium salts (formazans) were extractable with acetone or ethylene glycol and could be quantitated spectrophotometrically. The optimal assay system involved the use of three or more tracheal rings incubated for 2 h in 0.12% TTC in Tyrode balanced salts supplemented with 1.2% sodium succinate. Formazan was extracted for 5 min with acetone, and the optical density (490 nm) was determined. Trachea explants with metabolic activity reduced or obliterated by freeze-thaw lysis, heat (56 C X 30 min), or cyanide (0.1 M NaCN X 30 min) had negligible ciliary activity and tetrazolium reduction activity (optical density at 490 nm [dry weight]). Tracheas exposed to mycoplasma cells or membranes also showed significantly decreased ciliary activity and tetrazolium reduction; e.g., only 5pc of the ciliary activity and reduction capacity remained after 5 days in culture when infected with M. pneumonia PI 1428 cells. The data indicate that the exposure of ciliated respiratory epithelium to mycoplasma cells or membranes results in diminished oxidative metabolism, and that the ability to reduce TTC to its formazan is correlated with relative ciliary activity.
Lions and Prions and Deer Demise

Background Contagious prion diseases – scrapie of sheep and chronic wasting disease of several species in the deer family – give rise to epidemics that seem capable of compromising host population viability. Despite this prospect, the ecological consequences of prion disease epidemics in natural populations have received little consideration. Methodology/Principal Findings Using a cohort study design, we found that prion infection dramatically lowered survival of free-ranging adult (>2-year-old) mule deer (Odocoileus hemionus): estimated average life expectancy was 5.2 additional years for uninfected deer but only 1.6 additional years for infected deer. Prion infection also increased nearly fourfold the rate of mountain lions (Puma concolor) preying on deer, suggesting that epidemics may alter predator–prey dynamics by facilitating hunting success. Despite selective predation, about one fourth of the adult deer we sampled were infected. High prevalence and low survival of infected deer provided a plausible explanation for the marked decline in this deer population since the 1980s. Conclusion Remarkably high infection rates sustained in the face of intense predation show that even seemingly complete ecosystems may offer little resistance to the spread and persistence of contagious prion diseases. Moreover, the depression of infected populations may lead to local imbalances in food webs and nutrient cycling in ecosystems in which deer are important herbivores.
A Semantic Knowledge Management System for Government Repositories

Nowadays, in a knowledge-driven economy, the organizations, public or private, require to make an appropriate managing knowledge assets to sustain competitive edge in global markets or in governmental services. Advances in Information and Communications Technologies have supported innovations in Knowledge Management (KM). Since the KM has been recognized as one of the critical factors for obtaining organizational competitiveness. KM is among the promising areas for the application of Semantic Web. In this paper we propose an approach to the development of a technological platform for KM that integrates semantic Web technologies. This platform supports all processes required in knowledge management. Therefore, the platform enables the automatic identification of patterns and generation of the taxonomies from unstructured texts (documents). The platform consists of tools that allow storing documents (from a knowledge contributor interface), processing of source documents, i.e. identifying sentences, stop-words, identifying n-grams, and generating bags of words, denoting lexical patterns, taxonomic-relation extraction, and inference algorithms to retrieve knowledge from a set of repositories. These algorithms use the previous phases to retrieve knowledge more accurately derived from the semi-structured or structured information previously generated.
EFFECT OF HYPERPHENYLALANINEMIA ON FATTY ACID COMPOSITION OF LIPIDS OF RAT BRAIN MYELIN

Abstract— We have studied the fatty acid compositions of cerebral myelin lipids in phenyl‐alanine‐treated and control rats. The proportion of long chain fatty acids and the ratio of unsaturated to saturated fatty acids of whole brain lipids was low in the penylalanine‐treated animals. Both of these reductions were more pronounced in the myelin from phenylalanine‐treated rats. The ratio of unsaturated to saturated fatty acids in ethanolamine phosphatides was markedly decreased in the hyperphenylalaninemic condition. The reduction in the proportion of long chain fatty acids was predominant in non‐hydroxy fatty acids in cerebrosides and ethanolamine phosphatides. The lipid composition of the myelin expressed as mole percentages of individual phospholipid and sphingolipid components was not significantly different in the two groups of rats, nor did it change with age. Our results indicate a deficiency in the fatty acid elongation and desaturation system in the brains of phenylalanine‐treated rats. We suggest that in hyperphenylalaninemic rats, a reduction in the amounts of unsaturated fatty acid and long chain fatty acid alters, respectively, the biochemical reactivity and the stability of the myelin.
The relative value of operon predictions

For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation, (iv) sequence elements and (v) experimental evidence. The performance estimates of operon predictions reported in literature cannot directly be compared due to differences in methods and data used in these studies. Here, we survey the current status of operon prediction methods. Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement. We expect that existing and newly generated genomics and transcriptomics data will further improve accuracy of operon prediction methods.
A hybrid-based filtering approach for user authentication

Big data based user authentication is a new approach that leverages the power of Big Data analytics to develop a fertile field for the next generation user authentication. This new approach relies on “something you do”-based verification methods, where the users' dynamic behaviors are analyzed in order to generate real-time uniquely identifiable information about them. Once the unique user's identification is generated “authentication on demand” can be achieved through user challenging questions. In this paper, a new model is proposed to generate these users' identifiable information, where the main concepts of creating users' profiles in Recommendation Systems (RS) is used. RS are using the users' profiles to determine the user's preferences so that they can suggest a list of recommendations to other users with similar preferences. However, in the proposed model these profiles are employed to determine the user's personality traits that have a substantial influence on his/her identity verification. Based on these users' profiles the challenging questions will be issued only once to protect the users' responses from being compromised, and will be generated for the most recent user actions to help the legitimate user to easily remember and successfully complete the challenge.