Miracle-dz/UniFAR-FTUs huggingface dataset:
The Y Chromosome of the Atelidae Family (Platyrrhini): Study by Chromosome Microdissection

In order to study the intergeneric variability of the Y chromosome, we describe the hybridization of the Y chromosome of Brachytelesarachnoides, obtained by microdissection, to metaphases of Atelesbelzebuthmarginatus, Lagothrixlagothricha, and Alouatta male specimens. Brachytelesarachnoides (Atelinae) has 62 chromosomes and a very small Y chromosome. Our results showed that the Brachytelesarachnoides Y chromosome probe hybridized to Lagothrixlagothricha metaphases yielding one hybridization signal on only the tiny Y chromosome, and when hybridized with Atelesbelzebuthmarginatus metaphases it yielded one hybridization signal on two thirds of the small acrocentric Y chromosome. However, no hybridization signal was observed in Alouatta metaphases (subfamily Alouattinae), a closely related genus in the Atelidae family. Furthermore, our data support a close phylogenetic relationship among Brachyteles, Ateles, and Lagothrix and their placement in the Atelinae subfamily, but exclude Alouatta from this group indicating its placement as basal to this group.
Visual language features supporting human-human and human-computer communication

Fundamental to the design of visual languages are the goals of facilitating communication between people and computers, and between people and other people. The Object Block Programming Environment (OBPE) is a visual design, programming, and simulation tool which emphasizes support for both human-human and human-computer communication. OBPE provides several features to support effective communication: (1) multiple, coordinated views and aspects, (2) customizable graphics, (3) the "machines with push-buttons" metaphor and (4) the host-transient pattern. OBPE uses a diagram-based, visual object-oriented language that is intended for quickly designing and programming visual simulations of factories.
Choosing the diagonal loading factor for linear signal estimation using cross validation

Linear signal estimation based on sample covariance matrices (SCMs) can perform poorly if the training data are limited and the SCMs are ill-conditioned. Diagonal loading (DL) may be used to improve robustness in the face of limited training data. This paper introduces two leave-one-out cross-validation schemes for choosing the DL factor. One scheme repeatedly splits the training data with respect to time, while the other repeatedly splits the out-of-training data with respect to space. We derive computationally efficient implementations and compare them with the oracle choice in terms of the mean squared error.
High precision fault injections on the instruction cache of ARMv7-M architectures

Hardware and software of secured embedded systems are prone to physical attacks. In particular, fault injection attacks revealed vulnerabilities on the data and the control flow allowing an attacker to break cryptographic or secured algorithms implementations. While many research studies concentrated on successful attacks on the data flow, only a few targets the instruction flow. In this paper, we focus on electromagnetic fault injection (EMFI) on the control flow, especially on the instruction cache. We target the very widespread (smartphones, tablets, settop-boxes, health-industry monitors and sensors, etc.) ARMv7-M architecture. We describe a practical EMFI platform and present a methodology providing high control level and high reproducibility over fault injections. Indeed, we observe that a precise fault model occurs in up to 96% of the cases. We then characterize and exhibit this practical fault model on the cache that is not yet considered in the literature. We comprehensively describe its effects and show how it can be used to reproduce well known fault attacks. Finally, we describe how it can benefits attackers to mount new powerful attacks or simplify existing ones.
M1 neural decoding of finger movements using a priori neural activities before movements

One of the efforts on brain-machine interfaces (BMI) is reducing the system delay to perform sophisticated movements. Motor commands in brain are produced in advance before its movement in central nervous system. In the field of electroencephalogram (EEG), this issue has been studied widely as readiness potential (RP) to overcome time critical problem. Neural responses prior to movement in M1, primary motor cortex have been observed. In this paper, we present the neural decoding of finger or wrist movements using neural activity data collected from 0.5 sec. to 1.0 sec. when the movement onset happened at 1.0 sec. With novel temporal window, 30 randomly selected neurons could perform competent decoding accuracy as high as 95%.
Efficient mini-batch training for stochastic optimization

Stochastic gradient descent (SGD) is a popular technique for large-scale optimization problems in machine learning. In order to parallelize SGD, minibatch training needs to be employed to reduce the communication cost. However, an increase in minibatch size typically decreases the rate of convergence. This paper introduces a technique based on approximate optimization of a conservatively regularized objective function within each minibatch. We prove that the convergence rate does not decrease with increasing minibatch size. Experiments demonstrate that with suitable implementations of approximate optimization, the resulting algorithm can outperform standard SGD in many scenarios.
Mathematical Models of E-Antigen Mediated Immune Tolerance and Activation following Prenatal HBV Infection

We develop mathematical models for the role of hepatitis B e-antigen in creating immunological tolerance during hepatitis B virus infection and propose mechanisms for hepatitis B e-antigen clearance, subsequent emergence of a potent cellular immune response, and the effect of these on liver damage. We investigate the dynamics of virus-immune cells interactions, and derive parameter regimes that allow for viral persistence. We modify the model to account for mechanisms responsible for hepatitis B e-antigen loss, such as seroconversion and virus mutations that lead to emergence of cellular immune response to the mutant virus. Our models demonstrate that either seroconversion or mutations can induce immune activation and that instantaneous loss of e-antigen by either mechanism is associated with least liver damage and is therefore more beneficial for disease outcomes.
A Greater Role for Surgical Treatment of Epilepsy: Why and When?

urgical treatment for epilepsy is arguably the most underutilized of all proven effective therapeutic interventions in the field of medicine. Our failure, worldwide, to make optimal use of surgical treatment for epilepsy is all the more unacceptable, given the magnitude of the global health burden represented by epilepsy (1). The annual direct and indirect cost attributable to epilepsy in the United States is $12.5 billion, and 80% of this is accounted for by patients whose seizures are not adequately controlled by antiepileptic drugs (AEDs) (2). More than half a million people in the United States have epileptic seizures that continue despite appropriate pharmacotherapy (3), and it has been estimated that 100,000 to 200,000 of these are potential surgical candidates (4). Yet, in 1985, only 500 therapeutic surgical procedures were performed in the United States for epilepsy, which increased to 1,500 in 1990 (5), and, at most, may have doubled since then. Thus only a very small fraction of people with epilepsy who might benefit from surgical intervention receive it.
Sparse Nonparametric Topic Model for Transfer Learning

Count data arises for example in bioinformatics or analy- sis of text documents represented as word count vectors. With several data sets available from related sources, exploiting their similarities by transfer learning can improve models compared to modeling sources in- dependently. We introduce a Bayesian generative transfer learning model which represents similarity across document collections by sparse sharing of latent topics controlled by an Indian Buffet Process. Unlike Hierarchi- cal Dirichlet Process based multi-task learning, our model decouples topic sharing probability from topic strength, making sharing of low-strength topics easier, and outperforms the HDP approach in experiments.
Activation and Regulation of Purinergic P2X Receptor Channels

Mammalian ATP-gated nonselective cation channels (P2XRs) can be composed of seven possible subunits, denoted P2X1 to P2X7. Each subunit contains a large ectodomain, two transmembrane domains, and intracellular N and C termini. Functional P2XRs are organized as homomeric and heteromeric trimers. This review focuses on the binding sites involved in the activation (orthosteric) and regulation (allosteric) of P2XRs. The ectodomains contain three ATP binding sites, presumably located between neighboring subunits and formed by highly conserved residues. The detection and coordination of three ATP phosphate residues by positively charged amino acids are likely to play a dominant role in determining agonist potency, whereas an AsnPheArg motif may contribute to binding by coordinating the adenine ring. Nonconserved ectodomain histidines provide the binding sites for trace metals, divalent cations, and protons. The transmembrane domains account not only for the formation of the channel pore but also for the binding of ivermectin (a specific P2X4R allosteric regulator) and alcohols. The N- and C- domains provide the structures that determine the kinetics of receptor desensitization and/or pore dilation and are critical for the regulation of receptor functions by intracellular messengers, kinases, reactive oxygen species and mercury. The recent publication of the crystal structure of the zebrafish P2X4.1R in a closed state provides a major advance in the understanding of this family of receptor channels. We will discuss data obtained from numerous site-directed mutagenesis experiments accumulated during the last 15 years with reference to the crystal structure, allowing a structural interpretation of the molecular basis of orthosteric and allosteric ligand actions.
Hybrid Automatic Repeat Requests for MB-OFDM Ultra-Wideband

This paper analyzes the design and performance of hybrid automatic repeat request (HARQ) extensions to the multi- band orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) standard. It is shown how both Type-I and Type-III HARQ can significantly reduce the packet error rate (PER) in realistic frequency-selective channels. An exhaustive search is used to find an optimal low-complexity Type-III HARQ scheme by deriving the distance spectra and bit error upper- bound for all sets of complementary puncturing matrices. The consequences of selecting sub-optimal puncturing matrices are also quantified.
Visible to near-infrared photodetectors based on MoS2 vertical Schottky junctions

Over the past few years, two-dimensional (2D) nanomaterials, such as MoS2, have been widely considered as the promising channel materials for next-generation high-performance phototransistors. However, their device performances still mostly suffer from slow photoresponse (e.g. with the time constant in the order of milliseconds) due to the relatively long channel length and the substantial surface defect induced carrier trapping, as well as the insufficient detectivity owing to the relatively large dark current. In this work, a simple multilayer MoS2 based photodetector employing vertical Schottky junctions of Au-MoS2-ITO is demonstrated. This unique device structure can significantly suppress the dark current down to 10−12 A and enable the fast photoresponse of 64 μs, together with the stable responsivity of ∼1 A W−1 and the high photocurrent to dark current ratio of ∼106 at room temperature. This vertical-Schottky photodetector can also exhibit a wide detection range from visible to 1000 nm. All these results demonstrate clearly that the vertical Schottky structure is an effective configuration for achieving high-performance optoelectronic devices based on 2D materials.
SnapDRAGON: a method to delineate protein structural domains from sequence data.

We describe a method to identify protein domain boundaries from sequence information alone based on the assumption that hydrophobic residues cluster together in space. SnapDRAGON is a suite of programs developed to predict domain boundaries based on the consistency observed in a set of alternative ab initio three-dimensional (3D) models generated for a given protein multiple sequence alignment. This is achieved by running a distance geometry-based folding technique in conjunction with a 3D-domain assignment algorithm. The overall accuracy of our method in predicting the number of domains for a non-redundant data set of 414 multiple alignments, representing 185 single and 231 multiple-domain proteins, is 72.4 %. Using domain linker regions observed in the tertiary structures associated with each query alignment as the standard of truth, inter-domain boundary positions are delineated with an accuracy of 63.9 % for proteins comprising continuous domains only, and 35.4 % for proteins with discontinuous domains. Overall, domain boundaries are delineated with an accuracy of 51.8 %. The prediction accuracy values are independent of the pair-wise sequence similarities within each of the alignments. These results demonstrate the capability of our method to delineate domains in protein sequences associated with a wide variety of structural domain organisation.
RISC-based architecture for computer hardware introduction

Nowadays, computers are indispensable tools for most of everyday activities ranging from consumer electronics to industrial process automation. Complexity of new applications leads computer engineers to use embedded systems in order to develop high performance technological solutions that can achieve high speed processing while exploiting hardware resources efficiently. In order to develop embedded systems is necessary to understand the basic operation of a computer system, mainly composed of memory, a peripheral controller and a microprocessor. This work presents the design and implementation of an 8 bit RISC soft core processor intended for computer architecture introduction considered to be an effective solution for computer comprehension. Final circuit can be used as a soft core for FPGA embedded designs mainly for control and automation applications.
Factorbook.org: a Wiki-based database for transcription factor-binding data generated by the ENCODE consortium

The Encyclopedia of DNA Elements (ENCODE) consortium aims to identify all functional elements in the human genome including transcripts, transcriptional regulatory regions, along with their chromatin states and DNA methylation patterns. The ENCODE project generates data utilizing a variety of techniques that can enrich for regulatory regions, such as chromatin immunoprecipitation (ChIP), micrococcal nuclease (MNase) digestion and DNase I digestion, followed by deeply sequencing the resulting DNA. As part of the ENCODE project, we have developed a Web-accessible repository accessible at http://factorbook.org. In Wiki format, factorbook is a transcription factor (TF)-centric repository of all ENCODE ChIP-seq datasets on TF-binding regions, as well as the rich analysis results of these data. In the first release, factorbook contains 457 ChIP-seq datasets on 119 TFs in a number of human cell lines, the average profiles of histone modifications and nucleosome positioning around the TF-binding regions, sequence motifs enriched in the regions and the distance and orientation preferences between motif sites.
Studies on the electrical transport properties of carbon nanotube composites

This work presents a probabilistic approach to model the electrical transport properties o f carbon nanotube composite materials. A pseudo-random generation method is presented with the ability to generate 3-D samples with a variety of different configurations. Periodic boundary conditions are employed in the directions perpendicular to transport to minimize edge effects. Simulations produce values for drift velocity, carrier mobility, and conductivity in samples that account for geometrical features resembling those found in the lab. All results show an excellent agreement to the well-known power law characteristic of percolation processes, which is used to compare across simulations. The effect of sample morphology, like nanotube waviness and aspect ratio, and agglomeration on charge transport within CNT composites is evaluated within this model. This study determines the optimum simulation box-sizes that lead to minimize size-effects without rendering the simulation unaffordable. In addition, physical parameters within the model are characterized, involving various density functional theory calculations within Atomistix Toolkit. Finite element calculations have been performed to solve Maxwell’s Equations for static fields in the COMSOL Multiphysics software package in order to better understand the behavior of the electric field within the composite material to further improve the model within this work. The types of composites studied within this work are often studied for use in electromagnetic shielding, electrostatic reduction, or even monitoring structural changes due to compression, stretching, or damage through their effect on the conductivity. However, experimental works have shown that based on various processing techniques the electrical properties of specific composites can vary widely. Therefore, the goal of this work has been to form a model with the ability to accurately predict the conductive properties as a function physical characteristics o f the composite material in order to aid in the design of these composites. APPROVAL FOR SCHOLARLY DISSEMINATION The author grants to the Prescott Memorial Library o f Louisiana Tech University the right to reproduce, by appropriate methods, upon request, any or all portions o f this Thesis. It is understood that “proper request” consists o f the agreement, on the part o f the requesting party, that said reproduction is for his personal use and that subsequent reproduction will not occur without written approval o f the author o f this Thesis. Further, any portions o f the Thesis used in books, papers, and other works must be appropriately referenced to this Thesis. Finally, the author o f this Thesis reserves the right to publish freely, in the literature, at any time, any or all portions o f this Thesis.
Software synthesis from the dataflow interchange format

Specification, validation, and synthesis are important aspects of embedded systems design. The use of dataflow-based design environments for these purposes is becoming increasingly popular in the domain of digital signal processing (DSP). The dataflow inter-change format (DIF) [11] and the associated DIF package have been developed for specifying, working with, and transferring dataflow-based DSP designs across tools. In this paper, we present the newly developed DIF-to-C software synthesis framework for automatically generating monolithic C-code implementations from DSP system specifications that are programmed in DIF. This framework allows designers to efficiently explore the complex range of implementation tradeoffs that are available through various dataflow-based techniques for scheduling and memory management. Furthermore, the DIF-to-C framework provides a standard, vendor-neutral mechanism for linking coarse grain data-flow optimizations with fine grain hand-optimized libraries and the large body of optimization techniques in the area of C compilers for DSP. Through experiments involving several DSP applications, we demonstrate the novel and useful capabilities of our DIF-to-C software synthesis framework.
TRIBASIM : A NOVEL NETWORK ON CHIP SIMULATOR BASED ON SYSTEM C

In this paper, we develop a simulator for the Triplet Based (TriBA) Network On Chip processor architecture. TriBA(Triple-based Architecture) is a multiprocessor architecture whose basic idea is to bundle together the object programming basic philosophy and hardware multicore systems[1] . In TriBA ,nodes are connected in recursive triplets . TriBA network topology performance analysis have been carried out from different perspectives [2] and routing algorithms have been developed [3][4] but the architecture still lacks a simulator that the researcher can use to run simple and fast behavioral analysis on the architecture based on common parameters in the Network On Chip arena. We present TriBASim in this paper ,a simulator for TriBA ,based on system c[6] . TriBASim will lessen the burden on researchers on TriBA ,by giving them something to just plug in desired parameters and have nodes and topology set up ready for analysis.
The facilitation effect and language thresholds

Lechner and Siemund (2014) set out to determine whether bilinguals have an advantage for learning additional languages over monolinguals, purporting to evaluate the Threshold Hypothesis of Cummins (1979a) in this context. The study investigated the attainment of English literacy by Turkish-German, Vietnamese-German, and RussianGerman simultaneous and sequential bilinguals for whom English is a third language, and found significant correlations (at 0.01 level) for the second language (German) with the third language (English) at 0.580, and for the heritage language with the second language at 0.638; while the heritage language
Does Product Market Competition Reduce Inflation? Evidence from EU Countries and Sectors

In this paper we explore the link between the intensity of product market competition and inflation rates across EU countries and sectors. We consider long-term averages of inflation rates in order to remove the cyclical behavior of inflation over time and as alternative proxies of competition we use the level of mark-up, profit margin, the profit rate and a survey based "intensity of competition" variable. Results for both aggregate and sectoral panels show that the extent of product market competition, as proxied by the level of mark-up in particular, is an important driver of inflation. Notwithstanding some caveats associated with the measurement of the proxies of competition used, our findings suggest that higher product market competition reduces average inflation rates for a prolonged period of time. Moreover, results both at the aggregate and sectoral level are generally confirmed by a wide set of robustness tests.