Miracle-dz/UniFAR-FTUs huggingface dataset:
Saccharin Stimulates Insulin Secretion Dependent on Sweet Taste Receptor-Induced Activation of PLC Signaling Axis

Background: Saccharin is a common artificial sweetener and a bona fide ligand for sweet taste receptors (STR). STR can regulate insulin secretion in beta cells, so we investigated whether saccharin can stimulate insulin secretion dependent on STR and the activation of phospholipase C (PLC) signaling. Methods: We performed in vivo and in vitro approaches in mice and cells with loss-of-function of STR signaling and specifically assessed the involvement of a PLC signaling cascade using real-time biosensors and calcium imaging. Results: We found that the ingestion of a physiological amount of saccharin can potentiate insulin secretion dependent on STR. Similar to natural sweeteners, saccharin triggers the activation of the PLC signaling cascade, leading to calcium influx and the vesicular exocytosis of insulin. The effects of saccharin also partially require transient receptor potential cation channel M5 (TRPM5) activity. Conclusions: Saccharin ingestion may transiently potentiate insulin secretion through the activation of the canonical STR signaling pathway. These physiological effects provide a framework for understanding the potential health impact of saccharin use and the contribution of STR in peripheral tissues.
Genotype-specific Features Reduce the Susceptibility of South American Yellow Fever Virus Strains to Vaccine-Induced Antibodies

The resurgence of yellow fever in South America has prompted mitigation through vaccination against the etiologic agent, yellow fever virus (YFV). Current vaccines are based on a virulent African isolate, and their capacity to induce neutralizing antibodies against the vaccine strain is widely used as a surrogate for protection. However, the sensitivity of genetically distinct South American strains to vaccine-induced antibodies is unknown. Here, we show that antiviral potency of the polyclonal antibody response in both U.S. and Brazilian vaccinees is attenuated against an emergent Brazilian strain. This reduction was attributable to genetic changes at two sites in the central domain II of the glycoprotein E, including the acquisition of an N–linked glycosylation site, which are unique to and shared among most South American YFV strains. Our findings call for a reevaluation of current approaches to YFV immunological surveillance in South America and suggest approaches for designing updated vaccines.
Bound Gait Reference Generation of a Quadruped Robot via Contact Force Planning

This paper presents a reference generation technique for bounding quadruped locomotion. Synthesis of the reference is carried out by forming contact forces. Contact forces are planned with the aid of linear and angular momentum conservation and impulse laws. For the purpose of obtaining a stable and continuous bound gait, linear and angular momentum changes are set to be equal to zero over a full gait cycle. This condition allows the robot body to keep its initial dynamics at the end of the cycle, thus, producing a stable bound gait throughout the cycles. Periodicity in vertical linear velocity and angular velocity is obtained. These settings also result in almost constant horizontal body linear velocity. Suitable contact forces are produced with an optimization algorithm. Sequential Quadratic Programming (SQP) is utilized as an optimization solver. Linear and angular momentum laws and a non-slipping condition are applied as constraints of optimization. A full-dynamics simulation environment is employed to test the proposed reference generation algorithm. Results verify the validity of the proposed reference generation method for quadruped bounding. 
Ocin_tsim - A DVFS Aware Simulator for NoC Design Space Exploration and Optimization

Networks-on-Chip (NoCs) are a general purpose, scalable replacement for shared medium wired interconnects offering many practical applications in industry. Dynamic Voltage Frequency Scaling (DVFS) is a technique whereby a chip's voltage-frequency levels are varied at run time, often used to conserve dynamic power. Various DVFS-based NoC optimization techniques have been proposed. However, due to the resources required to validate architectural decisions through prototyping, few are implemented. As a result, designers are faced with a lack of insight into potential power savings or performance gains at early architecture stages. This thesis proposes a DVFS aware NoC simulator with support for per node power-frequency modeling and rich visualisation to allow fine-tuning of such optimization techniques early on in the design cycle. The proposed simulator also provides a framework for benchmarking various candidate strategies to allow selective prototyping and optimization. As part of the research, DVFS extensions were built for an existing NoC performance simulator and released for public use. This thesis also serves as a technical manual for the simulator extensions.
DEGENERATED LEMMA (DEL) Is a New Allele of OsRDR6 That Regulates Lemma Development and Affects Rice Grain Yield

The lemma and palea are floral organ structures unique to grasses, and their development affects grain size. However, information on the molecular mechanism of lemma development is limited. In this study, we investigated a rice spikelet mutant, degenerated lemma (del), which developed florets with a slightly degenerated or rod-like lemma. The results indicate that the mutation of the DEL gene interfered with lemma development. In addition, del also showed a significant reduction in grain length and width, seed setting rate, and 1000-grain weight, which led to a reduction in yield. The results indicate that the mutation of the DEL gene further affects rice grain yield. Map-based cloning shows a single-nucleotide substitution from T to A within Os01g0527600/DEL, causing an amino acid mutation of Leu-34 to His-34 in the del mutant. DEL is an allele of OsRDR6, encoding the RNA-dependent RNA polymerase 6, and is highly expressed in the spikelet. RT-qPCR results show that the expression of some floral organ identity genes was changed, which indicates that the DEL gene regulates lemma development by modulating the expression of these genes. The present results suggest that DEL plays an important role in lemma development and rice grain yield.
Modelling the Design-Build Development Process for a Facility Component

In unstable environments, characterized by frequent client-driven changes in design criteria and by huge pressure to compress project delivery times, practitioners must search for innovative ways to structure the design-build process. Involving specialty contractors from project inception onwards, helps to satisfy client needs. Based on empirical research in the semiconductor industry, this paper presents a product-process model that reflects the joint system of designing and building a facility component. The model expresses, in a parametric fashion, critical design, procurement, and construction decisions as the design-build process unfolds. A model implementation that uses discrete-event simulation contrasts the effects of early vs. late specialty-contractor involvement in design. Results show that early contractor involvement benefits the average project duration but increases the duration variability and may significantly increase the waste of construction resources if improperly implemented. Postponement of design decisions helps to reduce waste without penalizing the project duration much. Results also show that fabrication decisions should not be neglected in early design efforts when expediting a project.
Brucella abortus Encodes an Active Rhomboid Protease: Proteome Response after Rhomboid Gene Deletion

Rhomboids are intramembrane serine proteases highly conserved in the three domains of life. Their key roles in eukaryotes are well understood but their contribution to bacterial physiology is still poorly characterized. Here we demonstrate that Brucella abortus, the etiological agent of the zoonosis called brucellosis, encodes an active rhomboid protease capable of cleaving model heterologous substrates like Drosophila melanogaster Gurken and Providencia stuartii TatA. To address the impact of rhomboid deletion on B. abortus physiology, the proteomes of mutant and parental strains were compared by shotgun proteomics. About 50% of the B. abortus predicted proteome was identified by quantitative proteomics under two experimental conditions and 108 differentially represented proteins were detected. Membrane associated proteins that showed variations in concentration in the mutant were considered as potential rhomboid targets. This class included nitric oxide reductase subunit C NorC (Q2YJT6) and periplasmic protein LptC involved in LPS transport to the outer membrane (Q2YP16). Differences in secretory proteins were also addressed. Differentially represented proteins included a putative lytic murein transglycosylase (Q2YIT4), nitrous-oxide reductase NosZ (Q2YJW2) and high oxygen affinity Cbb3-type cytochrome c oxidase subunit (Q2YM85). Deletion of rhomboid had no obvious effect in B. abortus virulence. However, rhomboid overexpression had a negative impact on growth under static conditions, suggesting an effect on denitrification enzymes and/or high oxygen affinity cytochrome c oxidase required for growth in low oxygen tension conditions.
Multivariable-Modulation-Based Conduction Loss Minimization in a Triple-Active-Bridge Converter

This article presents the design, development, and optimization of pulsewidth modulation (PWM) scheme of an isolated bidirectional triple-active-bridge (TAB) dc–dc converter composed of three full-bridge modules and a high-frequency planar transformer. This article aims at improving the efficiency of the TAB converter by means of conduction loss minimization. The approach utilizes multiple control variables as degrees of freedom for the converter modulation. The optimization is based on the minimization of the true rms current, formulated using generalized harmonic approximation technique. The approach constitutes of two steps: the modulation pattern with least algorithmic complexity for efficiency maximization is first found depending on the operating load and gain condition, and, subsequently, the optimum control variables are calculated using the gradient descent algorithm applied on the identified modulation pattern. An 800-W TAB converter proof-of-concept is built to verify all theoretical considerations and model-oriented analysis. While the converter has an input dc bus voltage of 160 V, the two output ports of the converter can deliver 400 W each at voltage levels of 110–130 V and 18–27 V, respectively. With the implementation of the proposed optimal phase-duty control, the experimental results show a nonunity gain light load efficiency increment up to 6.1% compared with the conventional modulation technique.
Sportsman’s Mental State Evaluation and Early Warning Method Using Decision Tree

Aiming at the intelligent needs of psychological state assessment of university students, the text information-based psychological problem identification approach is investigated in the paper. This approach uses the text of student forums within universities as the database and introduces the convolutional neural network (CNN) model in deep learning, which contains a convolutional layer, a pooling layer, and a fully connected layer. After the convolution is completed, the convolution result is de-linearized by the activation function, and then pooling is performed to improve the fitting ability of the network for nonlinearities. For data processing, behavioral features attribute features, content features, and social relationship features are extracted from text information as the input of the CNN by using the decision tree. The psychological lexicon of expertise (LIWC) is used to enhance the efficiency of text word frequency statistics when performing text content extraction. To evaluate the performance of the proposed method, simulations are performed in the open dataset of CLPsyh2017 ReachOut Forum, and the FastText method is used as a comparison. The results show that the CNN model achieves an accuracy of 0.71 in the full-sample domain, which is significantly higher than that of the FastText model at 0.64. In the early warning evaluation of mental states, the CNN performance is better than that of FastText.
Brain-Derived Neurotrophic Factor Suppressed Proinflammatory Cytokines Secretion and Enhanced MicroRNA(miR)-3168 Expression in Macrophages

We investigated the role of brain-derived neurotrophic factor (BDNF) and its signaling pathway in the proinflammatory cytokines production of macrophages. The effects of different concentrations of BDNF on proinflammatory cytokines expression and secretion in U937 cell-differentiated macrophages, and human monocyte-derived macrophages were analyzed using enzyme-linked immunosorbent assay and real-time polymerase chain reaction. The CRISPR-Cas9 system was used to knockout p75 neurotrophin receptor (p75NTR), one of the BDNF receptors. Next-generation sequencing (NGS) was conducted to search for BDNF-regulated microRNA. A very low concentration of BDNF (1 ng/mL) could suppress the secretion of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and IL-6 in lipopolysaccharide (LPS)-stimulated macrophages but did not change their mRNA expression. BDNF suppressed IL-1β and IL-6 secretion in human monocyte-derived macrophages. In U937 cells, BDNF suppressed the phosphorylation of JNK and c-Jun. The p75NTR knockout strongly suppressed IL-1β, IL-6, and TNF-α secretion in macrophages and LPS-stimulated macrophages. BDNF regulated the expression of miR-3168 with Ras-related protein Rab-11A as its target. In conclusion, BDNF suppressed proinflammatory cytokines secretion in macrophages and inhibited the phosphorylation of JNK. Knockout of p75NTR suppressed proinflammatory cytokines expression and secretion. BDNF upregulated the expression of miR-3168. The inhibition of p75NTR could be a potential strategy to control inflammation.
Improved Design Tools for Surface Water and Standing Column Well Heat Pump Systems (DE-EE0002961)

Ground-source heat pump (GSHP) systems are perhaps the most widely used “sustainable” heating and cooling systems, with an estimated 1.7 million installed units with total installed heating capacity on the order of 18 GW. They are widely used in residential, commercial, and institutional buildings. Standing column wells (SCW) are one form of ground heat exchanger that, under the right geological conditions, can provide excellent energy efficiency at a relatively low capital cost. Closed-loop surface water heat pump (SWHP) systems utilize surface water heat exchangers (SWHE) to reject or extract heat from nearby surface water bodies. For building near surface water bodies, these systems also offer a high degree of energy efficiency at a low capital cost. However, there have been few design tools available for properly sizing standing column wells or surface water heat exchangers. Nor have tools for analyzing the energy consumption and supporting economics-based design decisions been available. The main contributions of this project lie in providing new tools that support design and energy analysis. These include a design tool for sizing surface water heat exchangers, a design tool for sizing standing column wells, a new model of surface water heat pump systems implemented in EnergyPlus and amore » new model of standing column wells implemented in EnergyPlus. These tools will better help engineers design these systems and determine the economic and technical feasibility. « less
Synthesis of Functionalized Thiophene Based Pyrazole Amides via Various Catalytic Approaches: Structural Features through Computational Applications and Nonlinear Optical Properties

In the present study, pyrazole-thiophene-based amide derivatives were synthesized by different methodologies. Here, 5-Bromothiophene carboxylic acid (2) was reacted with substituted, unsubstituted, and protected pyrazole to synthesize the amide. It was observed that unsubstituted amide (5-bromo-N-(5-methyl-1H-pyrazol-3-yl)thiophene-2-carboxamide (7) was obtained at a good yield of about 68 percent. The unsubstituted amide (7) was arylated through Pd (0)-catalyzed Suzuki–Miyaura cross-coupling, in the presence of tripotassium phosphate (K3PO4) as a base, and with 1,4-dioxane as a solvent. Moderate to good yields (66–81%) of newly synthesized derivatives were obtained. The geometry of the synthesized compounds (9a–9h) and other physical properties, like non-linear optical (NLO) properties, nuclear magnetic resonance (NMR), and other chemical reactivity descriptors, including the chemical hardness, electronic chemical potential, ionization potential, electron affinity, and electrophilicity index have also been calculated for the synthesized compounds. In this study, DFT calculations have been used to investigate the electronic structure of the synthesized compounds and to compute their NMR data. It was also observed that the computed NMR data manifested significant agreement with the experimental NMR results. Furthermore, compound (9f) exhibits a better non-linear optical response compared to all other compounds in the series. Based on frontier molecular orbital (FMO) analysis and the reactivity descriptors, compounds (9c) and (9h) were predicted to be the most chemically reactive, while (9d) was estimated to be the most stable among the examined series of compounds.
sEMG-Based Motion Recognition of Upper Limb Rehabilitation Using the Improved Yolo-v4 Algorithm

The surface electromyography (sEMG) signal is widely used as a control source of the upper limb exoskeleton rehabilitation robot. However, the traditional way of controlling the exoskeleton robot by the sEMG signal requires one to specially extract and calculate for complex sEMG features. Moreover, due to the huge amount of calculation and individualized difference, the real-time control of the exoskeleton robot cannot be realized. Therefore, this paper proposes a novel method using an improved detection algorithm to recognize limb joint motion and detect joint angle based on sEMG images, aiming to obtain a high-security and fast-processing action recognition strategy. In this paper, MobileNetV2 combined the Ghost module as the feature extraction network to obtain the pretraining model. Then, the target detection network Yolo-V4 was used to estimate the six movement categories of the upper limb joints and to predict the joint movement angles. The experimental results showed that the proposed motion recognition methods were available. Every 100 pictures can be accurately identified in approximately 78 pictures, and the processing speed of every single picture on the PC side was 17.97 ms. For the train data, the mAP@0.5 could reach 82.3%, and mAP@0.5–0.95 could reach 0.42; for the verification data, the average recognition accuracy could reach 80.7%.
Green Route for Fabrication of Water-Treatable Thermoelectric Generators

Since future energy harvesting technologies require stable supply and high-efficiency energy conversion, there is an increasing demand for high-performance organic thermoelectric generators (TEGs) based on waterproof thermoelectric materials. The poor stability of n-type organic semiconductors in air and water has proved a roadblock in the development of reliable thermoelectric power generators. We developed a simple green route for preparing n-type carbon nanotubes (CNTs) by doping with cationic surfactants and fabricated films of the doped CNTs using only aqueous media. The thermoelectric properties of the CNT films were investigated in detail. The nanotubes doped using a cationic surfactant (cetyltrimethylammonium chloride (CTAC)) retained an n-doped state for at least 28 days when exposed to water and air, indicating higher stability than that for contemporary CNT-based thermoelectric materials. The wrapping of the surfactant molecules around the CNTs is responsible for blocking oxygen and water from attacking the CNT walls, thus, extending the lifetime of the n-doped state of the CNTs. We also fabricated thermoelectric power conversion modules comprising CTAC-doped (n-type) and sodium dodecylbenzenesulfonate- (SDBS-) doped (p-type) CNTs and tested their stabilities in water. The modules retained 80±2.4% of their initial maximum output power (at a temperature difference of 75°C) after being submerged in water for 30 days, even without any sealing fills to prevent device degradation. The remarkable stability of our CNT-based modules can enable the development of reliable soft electronics for underwater applications.
Critical language assessment literacy of EFL teachers: Scale construction and validation

Critical language assessment (CLA) has been addressed in numerous studies. However, the majority of the studies have overlooked the need for a practical framework to measure the CLA dimension of teachers’ language assessment literacy (LAL). This gap prompted us to develop and validate a critical language assessment literacy (CLAL) scale to further underscore the role of CLA principles and their practice as an essential part of teachers’ LAL. In the first phase, a pool of items was generated through a comprehensive review of the related studies. In the quantitative phase, the developed scale was administered to 255 English as a foreign language teachers selected through convenience and snowball sampling. The data were analyzed through exploratory factor analysis for construct validity and Cronbach’s alpha for estimating internal consistency. The results showed that the items loaded on five factors: (a) teachers’ knowledge of assessment objectives, scopes, and types; (b) assessment use consequences; (c) fairness; (d) assessment policies; and (e) national policy and ideology. It was found that the scale had a high level of internal consistency and construct validity, which suggests that this scale has the potential to be useful in assessing language teachers’ CLAL and to raise language teachers’ awareness of CLAL constructs.
The Okubo–Weiss criterion in hydrodynamic flows: geometric aspects and further extension

The Okubo (1970 Deep Sea Res. 17 445)–Weiss (1991 Physica D 48 273) criterion, has been extensively used as a diagnostic tool to divide a two-dimensional (2D) hydrodynamical flow field into hyperbolic and elliptic regions and to serve as a useful qualitative guide to the complex quantitative criteria. The Okubo–Weiss criterion is frequently validated on empirical grounds by the results ensuing its application. So, we will explore topological implications into the Okubo–Weiss criterion and show the Okubo–Weiss parameter is, to within a positive multiplicative factor, the negative of the Gaussian curvature of the vorticity manifold. The Okubo–Weiss criterion is then reformulated in polar coordinates, and is validated for several examples including the Lamb–Oseen vortex, and the Burgers vortex. These developments are then extended to 2D quasi-geostrophic (QG) flows. The Okubo–Weiss parameter is shown to remain robust under the β-plane approximation to the Coriolis parameter. The Okubo–Weiss criterion is shown to be able to separate the 2D flow-field into coherent elliptic structures and hyperbolic flow configurations very well via numerical simulations of quasi-stationary vortices in QG flows. An Okubo–Weiss type criterion is formulate for 3D axisymmetric slows, and is validated via application to the round Landau–Squire Laminar jet flow.