Miracle-dz/UniFAR-FTUs huggingface dataset:
Battery type hybrid supercapacitor based on conducting polymers

The electrochemically synthesized polypyrrole and lead-lead sulfate are examined as a potential electrodes for battery-type hybrid supercapacitors in acidic solution. Discharge in the specific current range of ∼0.6–2.27 A g based on the active masses, can deliver capacity of 90–72 Ah kg, energy of 58–40 Wh kg and power of 40–1350 W kg, with the specific capacitance of the cell in the range of 300–250 F g. The device exhibits battery-type behavior at low discharge rate, e.g. <0.5 A g, and supercapacitors-type behavior at a higher discharge rate. It is estimated that cell will lose 20% of initial capacitance after ∼500-600 cycles. The electrochemically synthesized polyaniline and lead sulfate are investigated as a possible active material of the aqueous based hybrid asymmetric supercapacitors. The electrochemical characteristics of polyaniline (doping-dedoping reactions), as well as electrical characteristics (specific capacitance, capacity, energy, and power) of the PbSO4|PANI cell, are determined. The cell capacitance, ranging from 216 F g −1 to 230 F g is determined. In the specific current range of 0.3–1.5 A g based on the active masses, the specific energy decrease from 30 to 20 Wh kg, while specific power increased from 200 to ∼800 W kg. The specific capacity of the cell, slightly decreased from 47 Ah g to 40 Ah g by increasing the specific current. It is estimated that cell will lose 20% of initial capacitance after ∼550 cycles. Based on the estimated specific energy and power, it is suggested that investigated cells could be classified as hydride asymmetric battery type supercapacitors оr “supercapattery” type of electrochemical power sources.
A Three-Dimensional Simulation Study of the Performance of Carbon Nanotube Field-Effect Transistors With Doped Reservoirs and Realistic Geometry

This paper simulates the expected device performance and scaling perspectives of carbon nanotube (CNT) field-effect transistors with doped source and drain extensions. The simulations are based on the self-consistent solution of the three-dimensional Poisson-Schroumldinger equation with open boundary conditions, within the nonequilibrium Green's function formalism, where arbitrary gate geometry and device architecture can be considered. The investigation of short channel effects for different gate configurations and geometry parameters shows that double-gate devices offer quasi-ideal subthreshold slope and drain-induced barrier lowering without extremely thin gate dielectrics. Exploration of devices with parallel CNTs shows that on currents per unit width can be significantly larger than the silicon counterpart, while high-frequency performance is very promising
Multi-view Subspace Learning with Diversity Enforced Skeleton Embedding

We consider the task of multi-view subspace learning which integrates multi-view information to learn a unified representation for multimedia data. In real-world scenarios, we encounter views with high diversities of semantic levels. Neglecting the problem of semantic inconsistency, existing graph-based methods directly convert heterogeneous information into local affinity matrices to conduct a fusion process, which inevitably destroys the valuable high-semantic-level structure. To address semantic inconsistency, we propose Multi-view Subspace Skeleton Embedding (MSSE), in which the high-level semantic structure of the learned subspace is explicitly taken as the skeleton of the learned subspace. Specifically, cooperating with a set of anchor points, the high-level semantic structure is adopted as semantic constraints to guide the multi-graph learning process based on RESCAL tensor factorization. To guarantee sufficient geometric coverage of the skeleton in the learned subspace, we enforce the diversity of anchor points by a Determinantal Point Process (DPP) regularizer. Compared with traditional methods, the learned subspace is endowed with higher semantic consistency and more robust to noisy views. Experiments on real-world image datasets demonstrate the promising performance comparing to state-of-the-art graph-based methods.
Optimal Pruning for Multi-Step Sensor Scheduling

In the considered linear Gaussian sensor scheduling problem, only one sensor out of a set of sensors performs a measurement. To minimize the estimation error over multiple time steps in a computationally tractable fashion, the so-called information-based pruning algorithm is proposed. It utilizes the information matrices of the sensors and the monotonicity of the Riccati equation. This allows ordering sensors according to their information contribution and excluding many of them from scheduling. Additionally, a tight lower is calculated for branch-and-bound search, which further improves the pruning performance.
Power Allocation Based on System Capacity under Cooperative Communication Systems

Different effects of power allocation between the source node and all the relay nodes on the system capacity are taken into consideration in an amplify-and-forward cooperative communication system. An optimum power allocation algorithm based on harmonic mean of relay channel strength to increase the system capacity was proposed. Furthermore, exact formulations of Ps, Pr and Pi were derived. The simulations show that the algorithm proposed increases the system capacity significantly compared with the traditional average power allocation algorithm, especially when the signal-to-noise ratio is low, the increase ratio can reach more than 90%. And the scheme proposed has a very strong practicability because of its low computational complexity.
SWAP: Parallelization through Algorithm Substitution

By explicitly indicating which algorithms they use and encapsulating these algorithms within software components, programmers make it possible for an algorithm-aware compiler to replace their original algorithm implementations with compatible parallel implementations, or with the parallel implementations of compatible algorithms, using the so-called specification compatibility graph (SCG). Along with the SCG, a software environment is introduced for performing algorithm-aware compilation.
Systematic Inspection of Scheduling Policies And Algorithms in Grid Computing

Resource supervision and scheduling is an intricate problem in grid. Load scheduling is the method of improving the performance of grid environment through a redistribution of load among the computers. A grid based distributed system can solve the problem by allowing multiple independent jobs to run over a network of heterogeneous computing nodes. Keeping the jobs poise over network of computers requires load scheduling algorithm that are dynamic and quick. Scheduling is the decision making process and the main intention of scheduling is the minimum completion time, minimizing communication delays, maximizing resource utilization and maximizing throughput, avoid overheads and starvation. The intention of the paperwork is to review the different dynamic load scheduling algorithm used in grid environment.
Bond Markets Co-Movement Dynamics and Macroeconomic Factors: Evidence from Emerging and Frontier Markets

This paper examines the co-movement dynamics of ten emerging and four frontier government bond markets with the US market and the impact of macroeconomic factors and global bond market uncertainty on the time-varying co-movement. We find that macroeconomic factors play important role in explaining time variations in the bond return co-movement. Specifically, domestic macroeconomic factors have higher relative importance than global factors, with domestic monetary policy and domestic inflationary environment identified as the most influential factors. The global bond market uncertainty, based on an implied volatility measure, has explanatory power in driving co-movement dynamics in emerging and frontier bond markets.
Characterization of an Androgen-Specific Response Region Within the 5′ Flanking Region of the Murine Epididymal Retinoic Acid Binding Protein Gene1

Abstract The epididymis provides the optimal milieu for sperm maturation and storage. Epididymal secretory proteins are believed to be involved in that process. Androgens are the major endocrine and paracrine regulatory signals that regulate gene expression in the epididymis. We have previously identified an androgen-dependent retinoic acid-binding protein (mE-RABP) that is secreted into the luminal fluid from the mouse mid/distal caput epididymidis. The mE-RABP protein belongs to the lipocalin superfamily and may be involved in the trafficking of retinoic acid within the epididymis. We have recently demonstrated that 5 kilobases of the 5′ flanking region of the mE-RABP gene contained all the information for the hormonal regulation and the tissue-, region-, and cell-specific expression of the mE-RABP gene. In this study, we have identified a complex androgen-specific response region (ARR) within the first 600 base pairs of the mE-RABP gene promoter. Androgen (DHT) but not glucocorticoid (DEX) activates the ARR in HeLa and PC-3 cells. Two androgen receptor binding sites have been located at positions −445/−459 and −102/−88 and were named ARBS-1 and ARBS-0, respectively. Point mutations of ARBS-0 resulted in a slight decrease of the androgen response. However, mutations of ARBS-1 led to a total loss of the androgen responsiveness, suggesting that it was a major cis-acting element. When ARBS-1 is isolated from its promoter context, it serves as a weak androgen-responsive element that was activated by both androgens and glucocorticoids. Also, the −543/−88 DNA promoter fragment behaved as a poor androgen-responsive region, suggesting that regulatory elements located within the proximal mE-RABP promoter were required for a full androgen response. In conclusion, the mE-RABP ARR is a good model for the study of molecular mechanisms that lead to an androgen-specific responsiveness in vivo.
Nonmarital Romantic Relationships and Mental Health in Early Adulthood

Although social scientists have long assumed that intimate social relationships are more closely associated with women’s than men’s mental health, recent research indicates that there are no gender differences in the advantages of marriage and disadvantages of unmarried statuses when males’ and females’ distinct expressions of emotional distress are considered. These findings have led to the conclusion that there has been a convergence in the importance of intimate relationships for men’s and women’s mental health. However, these patterns may not be evident for nonmarital romantic relationships among current cohorts of young adults. In this article, we examine the associations among several dimensions of these relationships and symptoms of both depression and substance abuse/dependence in a diverse sample of young adults in Miami, Florida. We find gender differences that vary across dimensions of relationships: While current involvements and recent breakups are more closely associated with women’s than men’s mental health, support and strain in an ongoing relationship are more closely associated with men’s than women’s emotional well-being. Our findings highlight the need to consider the period in the life course as well as experiences of specific cohorts of men and women when theorizing about gender differences in the importance of intimate relationships for mental health.
Molecular Statics Simulation of the Effect of Hydrogen Concentration on {112} Edge Dislocation Mobility in Alpha Iron

Concerns over global warming and energy scarcity issues have led to the global promotion of a hydrogen energy society. Assurance of the strength reliability of structural elements used for hydrogen gas stations and/or hydrogen gas pipelines, particularly for steel from an economical viewpoint, are becoming an important issue. Hydrogen embrittlement (HE) is a phenomenon in which absorbed hydrogen causes marked reduction of the mechanical properties in steel.1) Recent studies on HE have supported the following distinctive HE mechanisms: (a) hydrogen-enhanced decohesion2–4) (HEDE), in which hydrogen reduces the cohesive strength between metallic bonds and yields brittle fracture; (b) hydrogen-enhanced localized plasticity5–7) (HELP), in which absorbed hydrogen affects the dislocations and locally enhances the plastic deformation; and (c) hydrogenenhanced strain-induced vacancies8,9) (HESIV), in which hydrogen enhances the formation and accumulation of vacancies accompanied by plastic deformation, which faciliMolecular Statics Simulation of the Effect of Hydrogen Concentration on {112} < 111 > Edge Dislocation Mobility in Alpha Iron
Stress analysis in solid-liquid parts of solidifying castings

In the paper, we present results of stress analysis in domains which are a mixture of solid and liquid phases. Such mixtures occur in solidifying castings and are a result of forming a structure with solid skeleton and filling of a liquid phase. In this structure, stress occurs due to the appearance of temperature gradients, different values of material properties for the solid and liquid phase, and the appearance of friction forces between the solidified part of the casting and the mold on a macroscopic scale. This can lead to casting defects, such as hot cracking. The results are obtained with the use of a authors computer program based on the Finite Element Method. The stress analysis takes into account the elastic-plastic state of considered computational area. The presented results are focused on the microscopic scale, for which a finite element mesh is created which imitates the growing grains of the metal alloy in the casting, on the basis of macroscopic parameters.
Role of the DExH motif of the Japanese encephalitis virus and hepatitis C virus NS3 proteins in the ATPase and RNA helicase activities.

The role of the conserved DExH motif of the Japanese encephalitis virus (JEV) NS3 protein in the ATPase and RNA helicase activities was compared with that of the hepatitis C virus (HCV) NS3 protein. In the DExH motif of JEV NS3, Asp-285 and Glu-286 were essential for both ATPase and RNA helicase activities. Cys-287 was critical for the RNA helicase activity of JEV NS3 but not for ATPase activity. A His-288-to-Ala substitution in the DExH motif of HCV NS3 resulted in an increase in ATPase activity which was suppressed by poly(U). In contrast, alanine substitution at the same site in JEV NS3 did not increase basal ATPase activity which remained to be stimulated by poly(U). Thus, the mutational effect at His in motif II was different in the HCV and JEV NS3 proteins. Mutagenesis at His-288 of JEV NS3 revealed that His was the most preferable amino acid for ATPase activity and Ala, Gly, Asn, Gln, Ser, or Arg could partly substitute for it. However, any other mutation at His-288 completely disrupted the RNA helicase activity of JEV NS3. The results suggest that Cys-287 and His-288 are essential residues especially for the RNA helicase activity of JEV NS3 and the ATPase and helicase activities are separable enzymatic functions.
Moment Feature Based Fast Feature Extraction Algorithm for Moving Object Detection Using Aerial Images

Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerningmoving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents thecoherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology.
Theta-Frequency Bursting and Resonance in Cerebellar Granule Cells: Experimental Evidence and Modeling of a Slow K+-Dependent Mechanism

Neurons process information in a highly nonlinear manner, generating oscillations, bursting, and resonance, enhancing responsiveness at preferential frequencies. It has been proposed that slow repolarizing currents could be responsible for both oscillation/burst termination and for high-pass filtering that causes resonance (Hutcheon and Yarom, 2000). However, different mechanisms, including electrotonic effects (Mainen and Sejinowski, 1996), the expression of resurgent currents (Raman and Bean, 1997), and network feedback, may also be important. In this study we report theta-frequency (3–12 Hz) bursting and resonance in rat cerebellar granule cells and show that these neurons express a previously unidentified slow repolarizing K+ current (IK-slow). Our experimental and modeling results indicate that IK-slow was necessary for both bursting and resonance. A persistent (and potentially a resurgent) Na+ current exerted complex amplifying actions on bursting and resonance, whereas electrotonic effects were excluded by the compact structure of the granule cell. Theta-frequency bursting and resonance in granule cells may play an important role in determining synchronization, rhythmicity, and learning in the cerebellum.
A neural network approach for human emotion recognition in speech

In this paper, we present a language-independent emotion recognition system for the identification of human affective state in the speech signal. A corpus of emotional speech from various subjects, speaking different languages is collected for developing and testing the feasibility of the system. The potential prosodic features are first identified and extracted from the speech data. Then we introduce a systematic feature selection approach which involves the application of Sequential Forward Selection (SFS) with a General Regression Neural Network (GRNN) in conjunction with a consistency-based selection method. The selected features are employed as the input to a Modular Neural Network (MNN) to realize the classification of emotions. The proposed system gives quite satisfactory emotion detection performance, yet demonstrates a significant increase in versatility through its propensity for language independence.
Trait dimensionality and population choice alter estimates of phenotypic dissimilarity

Abstract The ecological niche is a multi‐dimensional concept including aspects of resource use, environmental tolerance, and interspecific interactions, and the degree to which niches overlap is central to many ecological questions. Plant phenotypic traits are increasingly used as surrogates of species niches, but we lack an understanding of how key sampling decisions affect our ability to capture phenotypic differences among species. Using trait data of ecologically distinct monkeyflower (Mimulus) congeners, we employed linear discriminant analysis to determine how (1) dimensionality (the number and type of traits) and (2) variation within species influence how well measured traits reflect phenotypic differences among species. We conducted analyses using vegetative and floral traits in different combinations of up to 13 traits and compared the performance of commonly used functional traits such as specific leaf area against other morphological traits. We tested the importance of intraspecific variation by assessing how population choice changed our ability to discriminate species. Neither using key functional traits nor sampling across plant functions and organs maximized species discrimination. When using few traits, vegetative traits performed better than combinations of vegetative and floral traits or floral traits alone. Overall, including more traits increased our ability to detect phenotypic differences among species. Population choice and the number of traits used had comparable impacts on discriminating species. We addressed methodological challenges that have undermined cross‐study comparability of trait‐based approaches. Our results emphasize the importance of sampling among‐population trait variation and suggest that a high‐dimensional approach may best capture phenotypic variation among species with distinct niches.
The development of internal representations of magnitude and their association with Arabic numerals.

Developmental aspects of number concepts were evaluated using participants from the beginning and end of first grade (6-7 years old), third and fifth grades (7-11 years old), and university (22 years old). Participants evaluated the numerical value or physical size of stimuli varying along both dimensions. The numerical distance effect appeared in all groups. In contrast, the size congruity effect started to appear only at the end of first grade. Based on our results, a model of internal representation of magnitude claiming that there are two different representations was propose. At the beginning of first grade children can automatically access only one of these representations and only from the end of first grade can they access both of these representations.
Indirect targeting of IGF receptor signaling in vivo by substrate-selective inhibition of PAPP-A proteolytic activity

The insulin-like growth factor (IGF) signaling pathway is involved in certain human cancers, and the feasibility of directly targeting the IGF receptor has been actively investigated. However, recent evidence from clinical trials suggests that this approach can be problematic. We have developed an alternative strategy to indirectly inhibit the IGF signaling by targeting the metalloproteinase, pregnancy-associated plasma protein-A (PAPP-A). PAPP-A associated with the cell surface cleaves IGF binding protein-4 (IGFBP-4), when IGF is bound to IGFBP-4, and thereby increases IGF bioavailability for receptor activation in an autocrine/paracrine manner. We hypothesized that inhibition of PAPP-A would suppress excessive local IGF signaling in tissues where this is caused by increased PAPP-A proteolytic activity. To test this hypothesis, we developed an inhibitory monoclonal antibody, mAb 1/41, which targets a unique substrate-binding exosite of PAPP-A. This inhibitor selectively and specifically inhibits proteolytic cleavage of IGFBP-4 with an inhibitory constant (Ki) of 135 pM. In addition, it inhibited intracellular signaling of the IGF receptor (AKT phosphorylation) in monolayers of A549 cells, an IGF-responsive lung cancer-derived cell line found to express high levels of PAPP-A. We further showed that mAb 1/41 is effective towards PAPP-A bound to cell surfaces, and that it is capable of inhibiting PAPP-A activity in vivo. Using a murine xenograft model of A549 cells, we demonstrated that mAb 1/41 administered intraperitoneally significantly inhibited tumor growth. Analysis of xenograft tumor tissue recovered from treated mice showed penetration of mAb 1/41, reduced IGFBP-4 proteolysis, and reduced AKT phosphorylation. Our study provides proof of concept that IGF signaling can be selectively reduced by targeting a regulatory proteinase that functions extracellularly, upstream of the IGF receptor. PAPP-A targeting thus represents an alternative therapeutic strategy for inhibiting IGF receptor signaling.