Miracle-dz/UniFAR-FTUs huggingface dataset:
MEF2B Is a Component of a Smooth Muscle-specific Complex That Binds an A/T-rich Element Important for Smooth Muscle Myosin Heavy Chain Gene Expression*

To understand smooth muscle-specific gene expression, we have focused our studies on the smooth muscle myosin heavy chain (SMHC) gene, a smooth muscle-specific marker. In this study, we demonstrate that the SMHC promoter region (−1594 to −1462 base pairs) containing the A/T-rich element can activate the heterologous thymidine kinase promoter in smooth muscle cells, but not in fibroblasts. Mutations of this A/T-rich element decreased SMHC promoter activity significantly. Both gel mobility shift assays and DNase I footprinting revealed that this region binds to specific protein complexes from smooth muscle nuclear extracts, whereas nuclear extracts from skeletal muscle and fibroblasts produced a different binding pattern. We also demonstrate that the protein complex obtained from smooth muscle nuclear extract reacts with MEF2B-specific antibody, but not with antibodies specific to MEF2A, MEF2C, or MEF2D, suggesting that only MEF2B protein binds to the A/T-rich element. Furthermore, MEF2B overexpression in smooth muscle cells up-regulated the SMHC promoter, suggesting that MEF2B is important for SMHC gene regulation. This is the first report demonstrating a role for MEF2 factors in smooth muscle-specific gene expression.
Fuzzy Communication Leading to Equilibrium through Possibility Messages

A communication system in the {\bf S5}$n$-knowledge model is presented which leads to a Nash equilibrium of a strategic form game through robust messages. In the communication system each player predicts the other players' actions under his/her private information. The players communicate privately their conjectures through message according to the communication graph, where each recipient of the message learns and revises his/her conjecture. We show that the conjectures converges to a mixed strategy Nash equilibrium for the game after long running communication. The emphasis is on that each player sends not exact information about his/her individual conjecture but fuzzy information about the conjectures.
Spin-crossover metal–organic frameworks: promising materials for designing gas sensors

We present a quantitative study of the sensing behavior of micro-patterned gratings based on the metal–organic framework type spin crossover complex Fe(bpac)[Pt(CN)4] (1) in the presence of vapors of various organic compounds. The gratings of 1 were fabricated by combining a sequential assembly technique and a photolithographic method. The guest absorption driven change of the spin state and the associated variation of the refractive index were in situ monitored by optical diffraction on a grating of 1. Our sensor is characterized by good reversibility, room temperature operation, a low limit of detection (∼30 ppm for molecules of iodobenzene) as well as a linear dynamic range of detection (from 300 to 1500 ppm). The possibility of selectively desorbing the analytes by thermal annealing confers also selectivity to the sensor.
Attractor Metabolic Networks

Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed.
The 2021 NIST Speaker Recognition Evaluation

The 2021 Speaker Recognition Evaluation (SRE21) was the latest cycle of the ongoing evaluation series conducted by the U.S. National Institute of Standards and Technology (NIST) since 1996. It was the second large-scale multimodal speaker/person recognition evaluation organized by NIST (the first one being SRE19). Similar to SRE19, it featured two core evaluation tracks, namely audio and audio-visual, as well as an optional visual track. In addition to offering fixed and open training conditions, it also introduced new challenges for the community, thanks to a new multimodal (i.e., audio, video, and selfie images) and multilingual (i.e., with multilingual speakers) corpus, termed WeCanTalk, collected outside North America by the Linguistic Data Consortium (LDC). These challenges included: 1) trials (target and non-target) with enrollment and test segments originating from different domains (i.e., telephony versus video), and 2) trials (target and non-target) with enrollment and test segments spoken in different languages (i.e., cross-lingual trials). This paper presents an overview of SRE21 including the tasks, performance metric, data, evaluation protocol, results and system performance analyses. A total of 23 organizations (forming 15 teams) from academia and industry participated in SRE21 and submitted 158 valid system outputs. Evaluation results indicate: audio-visual fusion produce substantial gains in performance over audio-only or visual-only systems; top performing speaker and face recognition systems exhibited comparable performance under the matched domain conditions present in this evaluation; and, the use of complex neural network architectures (e.g., ResNet) along with angular losses with margin, data augmentation, as well as long duration fine-tuning contributed to notable performance improvements for the audio-only speaker recognition task.
Understanding Common Perceptions from Online Social Media

Modern society habitually uses online social media services to publicly share observations, thoughts, opinions, and beliefs at any time and from any location. These geotagged social media posts may provide aggregate insights into people's perceptions on a bad range of topics across a given geographical area beyond what is currently possible through services such as Yelp and Foursquare. This paper develops probabilistic language models to investigate whether collective, topic-based perceptions within a geographical area can be extracted from the content of geotagged Twitter posts. The capability of the methodology is illustrated using tweets from three areas of different sizes. An application of the approach to support power grid restoration following a storm is presented.
A Digital Compendium of Genes Mediating the Reversible Phosphorylation of Proteins in Fe-Deficient Arabidopsis Roots

Post-translational modifications of proteins such as reversible phosphorylation provide an important but understudied regulatory network that controls important nodes in the adaptation of plants to environmental conditions. Iron (Fe) is an essential mineral nutrient for plants, but due to its low solubility often a limiting factor for optimal growth. To understand the role of protein phosphorylation in the regulation of cellular Fe homeostasis, we analyzed the expression of protein kinases (PKs) and phosphatases (PPs) in Arabidopsis roots by mining differentially expressed PK and PP genes. Transcriptome analysis using RNA-seq revealed that subsets of 203 PK and 39 PP genes were differentially expressed under Fe-deficient conditions. Functional modules of these PK and PP genes were further generated based on co-expression analysis using the MACCU toolbox on the basis of 300 publicly available root-related microarray data sets. Results revealed networks comprising 87 known or annotated PK and PP genes that could be subdivided into one large and several smaller highly co-expressed gene modules. The largest module was composed of 58 genes, most of which have been assigned to the leucine-rich repeat protein kinase superfamily and associated with the biological processes “hypotonic salinity response,” “potassium ion import,” and “cellular potassium ion homeostasis. ” The comprehensive transcriptional information on PK and PP genes in iron-deficient roots provided here sets the stage for follow-up experiments and contributes to our understanding of the post-translational regulation of Fe deficiency and potassium ion homeostasis.
Implimentaion of large and medium vectors for SVPWM technique in five phase voltage source inverter

Multiphase variable-speed drives, supplied from two-level voltage-source inverters (VSIs), are nowadays considered for various industrial applications. Depending on the drive structure and/or the motor design, the VSI is required to generate sinusoidal voltages with minimum harmonics. This paper analyses and compare pulse width modulation schemes for two level five phase voltage source inverter. For a five-phase VSI space vector PWM (SVPWM) with only two large vectors and with four large and medium vectors schemes is used. The existing space vector pulse width-modulation (SVPWM) schemes are based on selection of (n−1) active space vectors (for odd phase numbers) within a switching period and they gives either sinusoidal voltage or sinusoidal fundamental voltage in combination with a limited amount of other harmonic content. Experimental and simulation results are presented.
Modular Termination Proofs of Recursive Java Bytecode Programs by Term Rewriting

In [5, 15] we presented an approach to prove termination of non-recursive Java Bytecode (JBC) programs automatically. Here, JBC programs are first transformed to finite termination graphs which represent all possible runs of the program. Afterwards, the termination graphs are translated to term rewrite systems (TRSs) such that termination of the resulting TRSs implies termination of the original JBC programs. So in this way, existing techniques and tools from term rewriting can be used to prove termination of JBC automatically. In this paper, we improve this approach substantially in two ways: (1) We extend it in order to also analyze recursive JBC programs. To this end, one has to represent call stacks of arbitrary size. (2) To handle JBC programs with several methods, we modularize our approach in order to reuse termination graphs and TRSs for the separate methods and to prove termination of the resulting TRS in a modular way. We implemented our approach in the tool AProVE. Our experiments show that the new contributions increase the power of termination analysis for JBC significantly. 1998 ACM Subject Classification D.1. 5 - Object-oriented Programming, D.2. 4 - Software/Program Verification, D.3. 3 - Language Constructs and Features, F.3 - Logics and Meanings of Programs, F.4. 2 - Grammars and Other Rewriting Systems, I.2. 2 - Automatic Programming
A Single-class Support Vector Machine Translation Algorithm To Compensate For Non-stationary Data In Heterogeneous Vision-based Sensor Networks

This paper develops a translation algorithm that adapts an existing support vector machine (SVM) to observations that have a different probability distribution than originally trained with. The primary advantage of this algorithm is that the re-training can be avoided. The support vector translation algorithm can be used in a fully distributed vision-based sensor network for target classification and tracking. Preliminary results are discussed and planned future work is briefly outlined.
The role of ubiquitin and the 26S proteasome in plant abiotic stress signaling

Ubiquitin is a small, highly conserved, ubiquitously expressed eukaryotic protein with immensely important and diverse regulatory functions. A well-studied function of ubiquitin is its role in selective proteolysis by the ubiquitin-proteasome system (UPS). The UPS has emerged as an integral player in plant response and adaptation to environmental stresses such as drought, salinity, cold and nutrient deprivation. The UPS has also been shown to influence the production and signal transduction of stress-related hormones such as abscisic acid. Understanding UPS function has centered mainly on defining the role of E3 ubiquitin ligases, which are the substrate-recruiting component of the ubiquitination pathway. The recent identification of stress signaling/regulatory proteins that are the subject of ubiquitin-dependent degradation has increased our knowledge of how the UPS facilitates responses to adverse environmental conditions. A brief overview is provided on role of the UPS in modulating protein stability during abiotic stress signaling. E3 ubiquitin ligases for which stress-related substrate proteins have been identified are discussed.
The PSI-Process Scales. A new measure to assess the intensity and breadth of parasocial processes

Abstract Research on parasocial interactions (PSI) and parasocial relationships (PSR) refers back to a tradition of 50 years. However, research on both phenomena still suffers from overlapping definitions and resulting measurements that do not distinguish between PSI and PSR. The present study presents a post-exposure measurement tool (the PSI-Process Scales) that aims to measure PSI instead of PSR. It is derived from a theoretical model that specifically focuses on PSI. Psychometric analyses indicate the tool's high usability. It is capable of displaying both the intensity and the dimensionality of PSI. It can be applied to measure both positive and negative PSI across all TV formats, without changing the item wording. In sum, the PSI-Process-Scales may offer a valuable alternative for researchers in the field, specifically if they want to assess parasocial processes that take place throughout TV exposure.
Computing word-of-mouth trust relationships in social networks from Semantic Web and Web 2.0 data sources

Social networks can serve as both a rich source of new information and as a filter to identify the information most relevant to our specific needs. In this paper we present a methodology and algorithms that, by exploiting existing Semantic Web and Web2.0 data sources, help individuals identify who in their social network knows what , and who is the most trustworthy source of information on that topic . Our approach improves upon previous work in a number of ways, such as incorporating topic-specific rather than global trust metrics. This is achieved by generating topic experience profiles for each network member, based on data from Revyu and del.icio. us , to indicate who knows what. Identification of the most trustworthy sources is enabled by a rich trust model of information and recommendation seeking in social networks. Reviews and ratings created on Revyu provide source data for algorithms that generate topic expertise and person to person affinity metrics. Combining these metrics, we are implementing a user-oriented application for searching and automated ranking of information sources within social networks.
Plasma proteins modify the endothelial cell glycocalyx of frog mesenteric microvessels.

1. We have investigated the interaction of plasma proteins with the endothelial cell using cationized ferritin as a marker of the cell surface glycocalyx. 2. Single microvessels of the frog mesentery were sequentially perfused using glass micropipettes with solutions containing cationized ferritin (CF, 6.7 mg ml‐1) in 0.10 M‐NaCl and then with either frog plasma or bovine serum albumin (BSA; 50 or 10 mg ml‐1), or protein‐free Ringer solution, before suffusion fixation in 2.5% glutaraldehyde. 3. A layer of CF, usually two to four molecules thick, was associated with the luminal endothelial cell surface. In vessels post‐flushed with protein‐free Ringer solution the CF layer was closely adherent to all regions of the luminal endothelium, including the plasma membrane, vesicle diaphragms, coated pits and the entrances to clefts. However, when plasma was present during fixation the CF layer was separated from the cell surface by up to 100 nm over all regions. In vessels post‐flushed with BSA the CF layer was also separated from the membrane but the effect was less striking. 4. The association of cationized ferritin with the endothelial cell surface was assessed quantitatively using electron micrographs of transverse sections (approximately 50 nm thick) of the perfused vessels, and expressed in terms of the depth of the layer of CF associated with the endothelial cell surface, its separation from the plasma membrane of the luminal endothelium, and the concentration of CF in the layer. The mean (+/‐ S.D.) separation in the presence of plasma, 32.3 +/‐ 10.5 nm (n = 12), was significantly greater (P less than 0.01) than that with either protein‐free Ringer solution, 3.0 +/‐ 1.4 nm (n = 9), or BSA in Ringer solution, 8.3 +/‐ 3.0 nm (n = 8). The separation seen with BSA in Ringer was also significantly greater than that measured with a final Ringer solution perfusion (P less than 0.01). The effects of 10 and 50 mg ml‐1 BSA were not different from one another. The total glycocalyx thickness, defined as the sum of the separation layer and depth of CF layer, with plasma present, 56.2 +/‐ 13.7 nm, was twice the value seen with Ringer solution, 28.0 +/‐ 9.1 nm (P less than 0.01), while the total thickness with BSA, 30.9 +/‐ 5.4 nm, was not different from the Ringer solution value. (ABSTRACT TRUNCATED AT 400 WORDS)
Spectrum Monitoring and Interference Minimization Algorithm for OFDM-Based Cognitive Radio Networks

: Cognitive radios network is programmable wireless devices to monitor spectrum used, and networking protocol as needed for better network and application performance. In Cognitive radio networks detection of licensed user reappearance during the non-licensed user transmission is very much required. This paper presents a spectrum monitoring algorithm in support of that purpose for OFDM based CR networks. The technique decreases the rate of spectrum monitoring and offers the chance of less time between primary transmission and its detection. Interference impact on proposed technique is studied and results are also presented.
Electrical Property of Carbon Nanotube Fibers from Chemical Vapor Deposition Synthesis

Because of facile synthesis, carbon nanotube (CNT) fibers from chemical vapor deposition can be used for diverse applications. In this study, the electrical property of CNT fibers was investigated. The room-temperature electrical conductivity of a typical CNT fiber was measured to be 5 × 10 5 S/m. The electrical-conductivity transport mechanism of CNT fibers was elucidated according to the temperature dependence of the resistance, indicating that the Mott's variable-range hopping mechanism operates Moreover, the thermoelectric power was measured, indicating that the carrier within the fiber is a hole.
REGULARIZATION MODELING FOR LARGE-EDDY SIMULATION OF DIFFUSION FLAMES

We analyze the evolution of a diffusion flame in a turbulent mixing layer using large-eddy simulation. The large-eddy simulation includes Leray regularization of the convective transport and approximate inverse filtering to represent the chemical source terms. The Leray model is compared to the more conventional dynamic mixed model. The location of the flame-center is defined by the 'stoichiometric' interface. Geometrical properties such as its surface-area and wrinkling are characterized using an accurate numerical level-set quadrature method. This allows to quantify flame-properties as well as turbulence modulation effects due to coupling between combustion and turbulent transport. We determine the active flame-region that is responsible for the main part of the chemical conversion in the flame and compare direct and large-eddy simulation predictions.
An efficient causal ordering algorithm for mobile computing environments

Causal message ordering is required for several distributed applications. In order to preserve causal ordering, only direct dependency information between messages with respect to the destination process(es) should be sent with each message. By eliminating other kinds of control information from the messages, the communication overheads can be significantly reduced. In this paper we present an algorithm that uses this knowledge to efficiently enforce causal ordering of messages. The proposed algorithm does not require any prior knowledge of the network or communication topology. As computation proceeds, it acquires knowledge of the logical communication topology and is capable of handling dynamically changing multicast communication groups. With regard to communication overheads, the algorithm is optimal for the broadcast communication case. Its energy efficiency and four bandwidth requirement make it suitable for mobile computing systems. We present a strategy that employs the algorithm for causally ordered multicasting of messages in mobile computing environments.
The damping behavior of magnetorheological gel based on polyurethane matrix

As a kind of new MR material, Magnetorheological Gel (MRG) can be considered to be the intermediate system between the MR fluids (MRF) and MR elastomers (MRE). And damping performance plays a significant role in its application system (especially in the vibration and noise control). However, the damping mechanism and source of MRG have not been investigated comprehensively. In this study, several samples of MRGs with different iron particle contents (0, 20, 40, 60, and 80 wt%) were prepared. The nonmagnetic damping (without magnetic field) and magneto-induced damping (with several constant magnetic fields) of MRG were systematically studied by using an advanced commercial rheometer under oscillatory shear modes. The influence of time history, strain amplitude and frequency in the zero-field and several constant magnetic fields on the nonmagnetic damping and magneto-induced damping of MRG was also systematically studied. The experimental results show that, just the opposite to MRE, the loss factor of MRG decrease with the increase of carbonyl iron powder particles (CIP) content. The reasons are known through theoretical analysis combined with microstructure observation that the polyurethane molecular chain will become shorter with the increase of CIP content is a very important factor, and the formation and thickening of the chain structure of CIP is the reason for the loss factor of MRG decline with the magnetic field. POLYM. COMPOS. , 2015. © 2015 Society of Plastics Engineers