Miracle-dz/UniFAR-FTUs huggingface dataset:
Endothelin Type A Receptor Genotype is a Determinant of Quantitative Traits of Metabolic Syndrome in Asian Hypertensive Families: A SAPPHIRe Study

Co-heritability of hypertension and insulin resistance (IR) within families not only implies genetic susceptibility may be responsible for these complex traits but also suggests a rational that biological candidate genes for hypertension may serve as markers for features of the metabolic syndrome (MetS). Thus we determined whether the T323C polymorphism (rs5333) of endothelin type A (ETA) receptor, a predominant receptor evoking potent vasoconstrictive action of endothelin-1, contributes to susceptibility to IR-associated hypertension in 1694 subjects of Chinese and Japanese origins. Blood pressures (BPs) and biochemistries were measured. Fasting insulin level, insulin-resistance homeostasis model assessment (HOMAIR) score, and area under curve of insulin concentration (AUCINS) were selected for assessing insulin sensitivity. Genotypes were obtained by methods of polymerase chain reaction-restriction fragment length polymorphism. Foremost findings were that minor allele frequency of the T323C polymorphism was noticeable lower in our overall Asian subjects compared to multi-national population reported in gene database; moreover both the genotypic and allelic frequencies of the polymorphism were significantly different between the two ethnic groups we studied. The genotype distributions at TT/TC/CC were 65, 31, 4% in Chinese and 51, 41, 8% in Japanese, respectively (p < 0.0001). Additionally, carriers of the C homozygote revealed characteristics of IR, namely significantly higher levels of fasting insulin, HOMAIR score, and AUCINS at 29.3, 35.3, and 39.3%, respectively, when compared to their counterparts with TT/TC genotypes in Chinese. Meanwhile, the CC genotype was associated with a higher level of high density lipoprotein cholesterol in Japanese. No association of the polymorphism with BP was observed. This study demonstrated for the first time that T323C polymorphism of ETA receptor gene was associated with an adverse insulin response in Chinese and a favorite atherogenic index in Japanese.
Extraction from Coordinate Structures : Evidence from Language Processing

1 Introduction Decades of psycholinguistic research have witnessed a sustained interest in whether syntactic island constraints are active during online processing the study of syntactic islands seeks to identify environments in which filler-gap dependencies are banned. But to these generalizations, there are, of course, exceptions. One of the more resilient island constraints is Ross's (1967) Coordinate Structure Constraint (CSC), although it, too, admits systematic counterexamples. The focus of this paper is on one such counterexample to the CSC – extraction from so-called 'pseudo-coordination' structures – and its treatment in online processing. At the center of this paper is the following long-recognized puzzle: why is the filler-gap dependency licensed in the pseudo-coordination structure (1a), but not the seemingly identical structure (1b)?
A 3.3 V 32 Mb NAND flash memory with incremental step pulse programming scheme

Due to their small cell size, low power consumption, and fast page based read/program operations, NAND type flash memories are well suited for portable mass storage. This 3.3 V only 32 Mb NAND flash memory achieves typical 2.3 MB/s program performance with an incremental step pulse programming (ISPP) scheme. In addition, self-boosting of program inhibit voltages lowers the page programming current to 4.3 mA and a 24 MB/s read throughput is achieved with interleaved data paths. The device is fabricated in a 0.5 /spl mu/m CMOS process on a 94.9 mm/sup 2/ die.
Molecular and genetic characterization of the gene family encoding the voltage-dependent anion channel in Arabidopsis

The voltage-dependent anion channel (VDAC), a major outer mitochondrial membrane protein, is thought to play an important role in energy production and apoptotic cell death in mammalian systems. However, the function of VDACs in plants is largely unknown. In order to determine the individual function of plant VDACs, molecular and genetic analysis was performed on four VDAC genes, VDAC1–VDAC4, found in Arabidopsis thaliana. VDAC1 and VDAC3 possess the eukaryotic mitochondrial porin signature (MPS) in their C-termini, while VDAC2 and VDAC4 do not. Localization analysis of VDAC–green fluorescent protein (GFP) fusions and their chimeric or mutated derivatives revealed that the MPS sequence is important for mitochondrial localization. Through the functional analysis of vdac knockout mutants due to T-DNA insertion, VDAC2 and VDAC4 which are expressed in the whole plant body are important for various physiological functions such as leaf development, the steady state of the mitochondrial membrane potential, and pollen development. Moreover, it was demonstrated that VDAC1 is not only necessary for normal growth but also important for disease resistance through regulation of hydrogen peroxide generation.
Vision-Based Machine Pose Estimation for Excavation Monitoring and Guidance

The ability to automatically estimate the pose of an articulated machine's base (e.g., tracks or wheels) and its articulated components (e.g., stick and bucket) is crucial for technical innovations aimed at improving both safety and productivity in several construction tasks. Vision-based pose estimation, in which optical cameras monitor fiducial markers to determine their three dimensional relative pose (i.e., position and orientation), offers a promising low cost alternative to currently available sensor packages that are non-ubiquitous and cost prohibitive. This paper presents an overview of the design and implementation of this technique. A computer vision based solution using a network of cameras and markers is proposed to enable a three-dimensional pose tracking capability for articulated machines. First, markers are installed on both the machine’s components and the jobsite. The site markers are installed and surveyed so their poses are known in a project coordinate frame. Cameras then observe the markers to measure their relative transformations, and calculate the machine components’ poses in the project frame. Several prototypes have been developed to evaluate the system’s performance on an articulated excavator. Through extensive sets of uncertainty analyses and field experiments, the proposed method has been shown to achieve centimeter level depth tracking accuracy at a 15m range with only two ordinary cameras and multiple markers, providing a flexible and cost-efficient alternative to other commercial products that use infrastructure dependent sensors like GPS. A working prototype has been tested on several active construction sites with positive feedback from excavator operators confirming the solution’s effectiveness.
Enhancing Crew Coordination with Intent Inference

Users of complex automation sometimes make mistakes. Vendors and supervisors often place accountability for these mistakes on the users themselves and their limited understanding of how these systems are “supposed” to be used (a perspective that influences how operators are trained and fosters efforts to design systems that explain their actions). Seeking to give users a better understanding of their systems, however, sidesteps the critical issue of how we ought to get computers to shoulder the responsibility of understanding humans. The machine is the piece of this equation that is "supposed" to conform. Our approach has the potential to make what people do naturally be the right thing. This work derives somewhat from related research in Intent Inference, which has focused on representing the tasks and actions of a user so that a system can maintain a representation of the user’s intent and can tailor its decision support accordingly. There is a growing need to extend the notion of intent inference to multi-operator venues, as systems are targeted increasingly at collaborative environments and operators are called upon to perform in multiple roles. In this paper we describe an approach to Crew Intent Inference that relies on models representing the goals and actions of individual operators and the overall team. We focus on the potential for intent inference to enhance coordination and present example scenarios highlighting the utility of intent inference in a multi-operator domain.
The Feasibility of Cable Sheath Fault Detection by Monitoring Sheath-to-Ground Currents at the Ends of Cross-Bonding Sections

This paper aims at checking the possibility that cable sheath faults in unipolar three-phase HV and extra HV cables with sheath cross-bonding systems can be detected by monitoring sheath-to-ground currents at the solid bonding ends of major cross-bonding sections. This goal is achieved by calculating such currents for some reference case studies of faults of the outer thermoplastic jacket in unipolar three-phase land cables for power transmission in flat formation. The case studies differ as to cable voltage ratings, resistance and location of the fault, symmetry of minor sections, and number of major sections. The results show that the aforementioned possibility does exist, particularly for some fault types and for sufficiently high cable load.
TRO40303, a New Cardioprotective Compound, Inhibits Mitochondrial Permeability Transition

3,5-Seco-4-nor-cholestan-5-one oxime-3-ol (TRO40303) is a new cardioprotective compound coming from a chemical series identified initially for neuroprotective properties. TRO40303 binds specifically to the mitochondrial translocator protein 18 kDa (TSPO) at the cholesterol site. After intravenous administration, TRO40303 tissue distribution was comparable to that of TSPO, and, in particular, the drug accumulated rapidly in the heart. In a model of 35 min of myocardial ischemia/24 h of reperfusion in rats, TRO40303 (2.5 mg/kg) reduced infarct size by 38% (p < 0.01 versus control), when administered 10 min before reperfusion, which was correlated with reduced release of apoptosis-inducing factor from mitochondria to the cytoplasm in the ischemic area at risk. Although TRO40303 had no effect on the calcium retention capacity of isolated mitochondria, unlike cyclosporine A, the drug delayed mitochondrial permeability transition pore (mPTP) opening and cell death in isolated adult rat cardiomyocytes subjected to 2 h of hypoxia followed by 2 h of reoxygenation and inhibited mPTP opening in neonatal rat cardiomyocytes treated with hydrogen peroxide. The effects of TRO40303 on mPTP in cell models of oxidative stress are correlated with a significant reduction in reactive oxygen species production and subsequent calcium overload. TRO40303 is a new mitochondrial-targeted drug and inhibits mPTP triggered by oxidative stress. Its mode of action differs from that of other mPTP inhibitors such as cyclosporine A, thus providing a new pharmacological approach to study mPTP regulation. Its efficacy in an animal model of myocardial infarctions makes TRO40303 a promising new drug for the reduction of cardiac ischemia-reperfusion injury.
A Scalable Monitoring Infrastructure for Self-Organizing Many-Core Architectures

Self-organizing principles can address the growing complexity and the huge challenge of management and efficient utilization of adaptive many-core architectures. Fundamental for realizing a self-organizing behavior within such architectures is a dedicated monitoring infrastructure that provides the essential information about the system status and system behavior for realizing the basic property of self-awareness. This paper therefore proposes a flexible, hierarchical and scalable monitoring infrastructure for self-organizing, adaptive many-core architectures. The employed basic monitoring unit in the bottom monitoring layer performs data aggregation and filtering and reduces the amount of data that must be processed in higher monitoring layers. The middle layer performs first data analysis and is further responsible for hiding the heterogeneity of the underlying hardware configuration to the topmost monitoring layer. The latter is finally responsible for detecting changes in the system behavior and realizing self-awareness. The proposed monitoring infrastructure was evaluated entirely using a simulation framework. Results show that the infrastructure is able of detecting changes in the system behavior of an entire many-core system causing only a minor system disturbance. Further, the prototypical implementation of the basic monitoring unit proved that it can be realized very efficiently in hardware.
Performance Analysis and Simulation of Both QPSK and OQPSK

In the modern information transmission technology, digital communication has become an important mean. According to today's modern communication technology, the paper studies the principle of QPSK and OQPSK , which is widely used in current communication system. It makes use of Matlab to simulate and verify the performance of QPSK / OQPSK. The results can make compensate for errors caused by the interference in hardware devices. Compared with the previous M files, it is simple in structure, quick and intuitive in operation, convenient and flexible in modification and easy-to-save function, and so on.
Anomalous diffusion on the Hanoi networks

Diffusion is modeled on the recently proposed Hanoi networks by studying the mean-square displacement of random walks with time, ⟨r2⟩∼t2/dw. It is found that diffusion —the quintessential mode of transport throughout Nature— proceeds faster than ordinary, in one case with an exact, anomalous exponent dw=2- log2(ϕ)=1.30576… . It is an instance of a physical exponent containing the “golden ratio” that is intimately related to Fibonacci sequences and since Euclid's time has been found to be fundamental throughout geometry, architecture, art, and Nature itself. It originates from a singular renormalization group fixed point with a subtle boundary layer, for whose resolution ϕ is the main protagonist. The origin of this rare singularity is easily understood in terms of the physics of the process. Yet, the connection between network geometry and the emergence of ϕ in this context remains elusive. These results provide an accurate test of recently proposed universal scaling forms for first passage times.
Human Action Recognition Using DFT

Action is any meaningful movement of the human and it is used to convey information or to interact naturally without any mechanical devices. Human action recognition is motivated by some of the applications such as video retrieval, Human robot interaction, to interact with deaf and dumb people etc. In any Action Recognition System, some pre-processing steps are done for removing the noise caused because of illumination effects, blurring, false contour etc. Background subtraction is done to remove the static or slowly varying background. In this paper, multiple background subtraction algorithms are tested and then one of them is selected for the further process of action recognition. Background subtraction is also known as foreground/background segmentation or foreground extraction. The next step is the feature extraction which deals with the extraction of the important feature (like corner points, optical flow, shape, motion vectors etc.) from the image frame. The proposed novel action recognition algorithm uses discrete Fourier transform (DFT) of the small image block.
Two systems for automatic music genre recognition: what are they really recognizing?

We re-implement two state-of-the-art systems for music genre recognition, and closely examine their behavior. First, we find specific excerpts each system consistently and persistently mislabels. Second, we test the robustness of each system to spectral adjustments to audio signals. Finally, we expose the internal genre models of each system by testing if human can recognize the genres of music excerpts composed by each system to be highly genre-representative. Our results suggest that, though they have high mean classification accuracies, neither system is recognizing music genre.
Semantic tags generation and retrieval for online advertising

One of the main problems in online advertising is to display ads which are relevant and appropriate w.r. t. what the user is looking for. Often search engines fail to reach this goal as they do not consider semantics attached to keywords. In this paper we propose a system that tackles the problem by two different angles: help (i) advertisers to create more efficient ads campaigns and (ii) ads providers to properly match ads content to keywords in search engines. We exploit semantic relations stored in the DBpedia dataset and use an hybrid ranking system to rank keywords and to expand queries formulated by the user. Inputs of our ranking system are (i) the DBpedia dataset; (ii) external information sources such as classical search engine results and social tagging systems. We compare our approach with other RDF similarity measures, proving the validity of our algorithm with an extensive evaluation involving real users.
HERD BEHAVIOR AND AGGREGATE FLUCTUATIONS IN FINANCIAL MARKETS

We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated power law, similar to distributions observed in recent empirical studies of high-frequency market data. Our model provides a link between two well-known market phenomena: the heavy tails observed in the distribution of stock market returns on one hand and herding behavior in financial markets on the other hand. In particular, our study suggests a relation between the excess kurtosis observed in asset returns, the market order flow, and the tendency of market participants to imitate each other.
Predictivity of Simulated ADME AutoQSAR Models over Time

The automation of model building and model updating (autoQSAR) is an important step forward towards real‐time small molecule drug discovery project support using the latest experimental data. We present here a simulation study using real company data of the behaviour of QSAR models over time. Three different global QSAR models, namely, human plasma protein binding, aqueous solubility and log D7.4, are updated on a monthly basis over a period of three years. The effect of updating the models on their predictivity is studied using a series of monthly temporal test sets in addition to a final terminal temporal test set. Partial Least Squares (PLS), Random Forest (RF) and Bayesian Neural Networks (BNN) models are examined, covering three distinctly different approaches to QSAR modelling. It is demonstrated that the models are able to predict forward in time, but that updating models on a regular basis increases their ability to make predictions for current compounds. The degree of the improvement depends on the property studied and the model building technique used. These results demonstrate the importance of updating models on a regular basis. For both static models predicting forward in time, and regularly updating models it is shown that RF models are the most predictive for these data sets.
Schumacher's quantum data compression as a quantum computation.

An explicit algorithm for performing Schumacher's noiseless compression of quantum bits is given. This algorithm is based on a combinatorial expression for a particular bijection among binary strings. The algorithm, which adheres to the rules of reversible programming, is expressed in a high-level pseudocode language. It is implemented using O(${\mathit{n}}^{3}$) two- and three-bit primitive reversible operations, where n is the length of the qubit strings to be compressed. Also, the algorithm makes use of O(n) auxiliary qubits. Space-saving techniques based on those proposed by Bennett are developed which reduce this workspace to O(\ensuremath{\surd}n) while maintaining a running time of O(${\mathit{n}}^{3}$) (albeit with a larger constant). This latter algorithm is of interest because it has a slightly smaller time-space product, which is considered to be the relevant figure of merit for efficiency in some physical models. \textcopyright{} 1996 The American Physical Society.
Interference-Based Capacity Analysis for Vehicular Ad Hoc Networks

Although some scaling law-based studies have been conducted for describing the asymptotic capacity of Vehicular Ad Hoc Networks (VANETs), the obtained results are not easy to directly use for estimating the actual capacity of a communication link or the entire network. To overcome this drawback, an interference-based capacity analysis is carried out in this letter for the abstracted 1-dimensional VANETs scenario. For a reasonable and tractable modeling, the classic Car-Following model is applied to represent the dynamic change of the inter-vehicle distance, which strongly affects the power decay of both the signal and interference in the network. Based on that, a series of probability characteristics is derived for the worst-case interfering scenario, which finally leads to the stochastic characteristics for both the link and network capacity.
Discussion Paper No . 2003 / 07 Idiosyncratic Risk in the 1990 s : Is It an IT Story ?

This paper examines trends in idiosyncratic risk in different ‘new economy’ and ‘old economy’ industries, and explores whether these developments can be attributed to the use of IT. A CAPM-based decomposition of equity returns is employed to estimate idiosyncratic risk. The results provide evidence of an increase in idiosyncratic risk in the 1990s. A substantial part reflects high volatility of firms in the IT sector, and in particular that of new IT firms. However, it is not clear whether the increase in idiosyncratic risk results from changes in the risk perception of financial markets or from new ways of firm organization’, production and competition related to IT. The jump in volatility in 1998 supports the view that the perception of risk by equity investors has changed. The positive relation between the share of intangible assets (as a proxy for IT-related changes) and the increase in firm-specific risk in the 1990s is consistent with the view that IT increases the uncertainty with respect to firm valuation, particularly if associated with a fundamental change in the business model.
A Phenomenological Study of the Experiences of Elementary Title I Teachers' Use of Digital Technology in the Classroom

If Title I elementary students are not given opportunities to learn how to utilize digital technology in their classrooms, a whole segment of the population will lack the knowledge and skills to become successful upon graduation and contribute to the betterment of society. The purpose of this transcendental phenomenological study was to describe the experiences of Central Texas elementary teachers’ use of digital technology in their Title I classrooms. The central research question in this study was: how do Title I elementary teachers in Central Texas describe their experiences using digital technology in the classroom? Two theories framed this investigation. The first was the experiential learning theory which emphasizes the relationship experience plays in adult learning. The second theory was Social Constructivism, specifically Lev Vygotsky’s zone of proximal development which describes how students move through three zones of development to master concepts. Findings from this research revealed how 11 Title I elementary teachers are preparing their students for life in the 21st century through technology integration. Data collection was conducted through interviews, focus groups, and writing prompts. All data was analyzed using Moustakas’ steps for data analysis. This research revealed the depth of technology integration in Title I elementary schools and the dedication these participants had regardless of the barriers they had to overcome. Recommendations include further research with more Title I elementary schools and added student perspectives.