Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlling the Ambipolar current by using Graded drain doped TFET

A Graded Doped Drain TFET (GD-TFET) architecture is proposed in this work to suppress the ambipolar current that exists in Conventional TFET (C-TFET). This graded doping in the drain region improves off-state parameters like off-current, ambipolar current without affecting on-state parameters. The various parameters from different TFET structures like Doping-Less TFET (DL-TFET), Low Doped TFET (LD-TFET), Conventional TFET (C-TFET), and Graded Doping TFET (GD-TFET) are simulated and compared. It has been found that the proposed architecture offers superior suppression of ambipolar current without affecting others parameters. The architecture offers an ambient current of 7×10-15 A/μm which is far less than the other structure of 8×10 -10 A/μm in the case of C-TFET. The structure also offers sub-threshold swing, transconductance, and on-to-off current ratio of 35.0628 mV/decade, 1.44×10-05 S and 6.40×10+08 A/μm, respectively, which is comparable to C-TFET structure.
Proteomic Identification and Quantification of Secretory Proteins in Human Dermal Fibroblast-Conditioned Medium for Wound Repair and Hair Regeneration

Background Human dermal fibroblasts secrete numerous growth factors and proteins that have been suggested to promote wound repair and hair regeneration. Methods Human dermal fibroblast-conditioned medium (DFCM) was prepared, and proteomic analysis was performed. Secretory proteins in DFCM were identified using 1-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, in-gel trypsin protein digestion, and quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS). Identified proteins were analyzed using bioinformatic methods for the classification and evaluation of protein–protein interactions. Results Using LC-MS/MS, 337 proteins were identified in DFCM. Among them, 160 proteins were associated with wound repair, and 57 proteins were associated with hair regeneration. Protein–protein interaction network analysis of 160 DFCM proteins for wound repair at the highest confidence score (0.9) revealed that 110 proteins were grouped into seven distinctive interaction networks. Additionally, protein–protein interaction network analysis of 57 proteins for hair regeneration at the highest confidence score revealed that 29 proteins were grouped into five distinctive interaction networks. The identified DFCM proteins were associated with several pathways for wound repair and hair regeneration, including epidermal growth factor receptor, fibroblast growth factor, integrin, Wnt, cadherin, and transforming growth factor-β signaling pathways. Conclusion DFCM contains numerous secretory proteins that comprise groups of protein–protein interaction networks that regulate wound repair and hair regeneration.
Effect of Dietary Supplementation of Lactiplantibacillus plantarum N-1 and Its Synergies with Oligomeric Isomaltose on the Growth Performance and Meat Quality in Hu Sheep

Probiotics have gained tremendous attention as an alternative to antibiotics, while synbiotics may exhibit a greater growth promoting effect than their counterpart probiotics due to the prebiotics’ promotion on the growth and reproduction of probiotics. The objective of this study was to investigate the influence of Lactiplantibacillus plantarum N-1 and its synbiotic with oligomeric isomaltose on the growth performance and meat quality of Hu sheep. Hu sheep (0–3 days old) were fed with water, probiotics of N-1, or synbiotics (N-1 and oligomeric isomaltose) daily in three pens for 60 days and regularly evaluated to measure growth performance and collect serum (five lambs per group). Longissimus thoracis (LT) and biceps brachii (BB) muscle tissues were collected for the analysis of pH value, color, texture, nutrients, mineral elements, amino acids, volatile compounds, and antioxidant capacity. The results showed that dietary supplementation of N-1 tended to improve growth performance and meat quality of Hu sheep, while the synergism of N-1 with oligomeric isomaltose significantly improved their growth performance and meat quality (p < 0.05). Both the dietary supplementation of N-1 and synbiotics (p < 0.05) increased the body weight and body size of Hu sheep. Synbiotic treatment reduced serum cholesterol and improved LT fat content by increasing the transcription level of fatty acid synthase to enhance fat deposition in LT, as determined via RT-qPCR analysis. Moreover, synbiotics increased zinc content and improved LT tenderness by decreasing shear force and significantly increased the levels of certain essential (Thr, Phe, and Met) and non-essential (Asp, Ser, and Tyr) amino acids of LT (p < 0.05). Additionally, synbiotics inhibited the production of carbonyl groups and TBARS in LT and thus maintained antioxidant stability. In conclusion, it is recommended that the use of synbiotics in livestock breeding be promoted to improve sheep production and meat quality.
In Silico Analysis of miRNA-Mediated Genes in the Regulation of Dog Testes Development from Immature to Adult Form

Simple Summary The objective of this investigation was to elucidate the association of miRNA-mediated genes in the regulation of dog testes development from immature to adult form by in-silico analysis. In silico analysis of differentially expressed (DE) testis miRNAs between healthy immature and mature dogs were performed using miRNet, STRING, and ClueGo programs. The determination of mRNA and protein expressions of predicted pivotal genes and their association with miRNA were studied. The predicted genes are involved in the governing of several key biological functions (cell cycle, cell proliferation, growth, maturation, survival, and apoptosis) in the testis as they evolve from immature to adult forms, mediated by several key signaling pathways (ErbB, p53, PI3K-Akt, VEGF, and JAK-STAT), cytokines and hormones (estrogen, GnRH, relaxin, thyroid hormone, and prolactin). Elucidation of DE-miRNA predicted genes’ specific roles, signal transduction pathways, and mechanisms, by mimics and inhibitors, which could perhaps offer diagnostic and therapeutic targets for infertility, cancer, and birth control. Abstract High-throughput in-silico techniques help us understand the role of individual proteins, protein–protein interaction, and their biological functions by corroborating experimental data as epitomized biological networks. The objective of this investigation was to elucidate the association of miRNA-mediated genes in the regulation of dog testes development from immature to adult form by in-silico analysis. Differentially expressed (DE) canine testis miRNAs between healthy immature (2.2 ± 0.13 months; n = 4) and mature (11 ± 1.0 months; n = 4) dogs were utilized in this investigation. In silico analysis was performed using miRNet, STRING, and ClueGo programs. The determination of mRNA and protein expressions of predicted pivotal genes and their association with miRNA were studied. The results showed protein–protein interaction for the upregulated miRNAs, which revealed 978 enriched biological processes GO terms and 127 KEGG enrichment pathways, and for the down-regulated miRNAs revealed 405 significantly enriched biological processes GO terms and 72 significant KEGG enrichment pathways (False Recovery Rate, p < 0.05). The in-silico analysis of DE-miRNA’s associated genes revealed their involvement in the governing of several key biological functions (cell cycle, cell proliferation, growth, maturation, survival, and apoptosis) in the testis as they evolve from immature to adult forms, mediated by several key signaling pathways (ErbB, p53, PI3K-Akt, VEGF and JAK-STAT), cytokines and hormones (estrogen, GnRH, relaxin, thyroid hormone, and prolactin). Elucidation of DE-miRNA predicted genes’ specific roles, signal transduction pathways, and mechanisms, by mimics and inhibitors, which could perhaps offer diagnostic and therapeutic targets for infertility, cancer, and birth control.
Fabrication and Characterization of Eco-Friendly Thin Films as Potential Optical Absorbers for Efficient Multi-Functional Opto-(Electronic) and Solar Cell Applications

The necessity for reliable and efficient multifunctional optical and optoelectronic devices is always calling for the exploration of new fertile materials for this purpose. This study leverages the exploitation of dyed environmentally friendly biopolymeric thin films as a potential optical absorber in the development of multifunctional opto-(electronic) and solar cell applications. Uniform, stable thin films of dyed chitosan were prepared using a spin-coating approach. The molecular interactivity between the chitosan matrix and all the additive organic dyes was evaluated using FTIR measurements. The color variations were assessed using chromaticity (CIE) measurements. The optical properties of films were inspected using the measured UV-vis-NIR transmission and reflection spectra. The values of the energy gap and Urbach energy as well as the electronic parameters and nonlinear optical parameters of films were estimated. The prepared films were exploited for laser shielding as an attenuated laser cut-off material. In addition, the performance of the prepared thin films as an absorbing organic layer with silicon in an organic/inorganic heterojunction architecture for photosensing and solar energy conversion applicability was studied. The current-voltage relation under dark and illumination declared the suitability of this architecture in terms of responsivity and specific detectivity values for efficient light sensing applications. The suitability of such films for solar cell fabrications is due to some dyed films achieving open-circuit voltage and short-circuit current values, where Saf-dyed films achieved the highest Voc (302 mV) while MV-dyed films achieved the highest Jsc (0.005 mA/cm2). Finally, based on all the obtained characterization results, the engineered natural cost-effective dyed films are considered potential active materials for a wide range of optical and optoelectronic applications.
H∞ Control for Continuous‐Time Mean‐Field Stochastic Systems

An H∞‐type control is considered for mean‐field stochastic differential equations (SDEs) in this paper. A stochastic bounded real lemma (SBRL) is proved for mean‐field stochastic continuous‐time systems with state‐ and disturbance‐dependent noise. Based on SBRL, a sufficient condition is given for the existence of a stabilizing H∞ controller in terms of coupled nonlinear matrix inequalities.
Plant Leaf Disease Classification using Convolutional Neural Network on FPGA

Leaf damage due to disease is a major source of concern for farmers. India’s agriculture-based economy accounts for a considerable share of the country’s GDP. This research proposes the utilization of a machine learning based model on different leaf images to detect the disease of four different types of plants which includes Apple, Maize, Potato and Tomato. A Convolutional Neural Network (CNN) model is used to categorize the kind of disease affecting the leaf, which is trained by using the Plant Village dataset. This trained model is deployed on AMD Xilinx’s Kria KV260 FPGA using Vitis AI for the identification of the disease. The accuracy of disease classification achieved is around 98.04%.
Full CMOS Circuit for Brain-Inspired Associative Memory With On-Chip Trainable Memristive STDP Synapse

Spiking neural networks (SNNs) implemented in neuromorphic computing architectures promise a high degree of bio-plausibility and energy efficiency compared to the artificial neural network (ANN). Thus, SNN-based spiking associative memories are preferred for high capacity, area, and energy-efficient neural associative memories (NAMs). While most previously published works focused on ANN-based NAM, this work implements the full CMOS circuit of memristor crossbar-based spiking NAM for the first time. Instead of using any software-based memristive SPICE model or memristive devices that are yet not available in standard CMOS technology process design kits (PDKs), in our work, the CMOS-based memristive synapse circuit is employed to address practical circuit implementation challenges. The complete ON-chip learning of the system is demonstrated using the bio-plausible spike-timing-dependent plasticity (STDP) learning mechanism without employing any external coprocessor, e.g., microprocessor, field-programmable gate array (FPGA). The entire system is implemented at the transistor level using 180-nm standard CMOS technology to demonstrate the pattern recognition application. The robustness of the proposed circuit is also evaluated to demonstrate the tolerance against the CMOS fabrication non-idealities.
A Novel Methodology For Discovering Ideal Overlay Hubs In Routing

In the event that we are simply worried in showing signs of improvement directing properties among a solitary source hub and a solitary destination, then the quandary is not unpredictable, and judgment the ideal number of hubs gets to be irrelevant on the grounds that the likely contender for superimpose task is modest, and all in all any commitment would be predominant. By and by, when we view as one-to-numerous or numerous to-numerous circumstances, then a solitary overlay hub could concern the path belonging of numerous ways, and accordingly choose the best areas end up being significantly less unimportant. We completely realize this advancement issue. We exhibit that it is NP-hard and get a nontrivial estimate calculation for it, where the guess connection relies on upon careful properties of the current trouble. We take a gander at the sensible component of the framework by evaluate the build one can get over some certifiable situations.
Maternal Weight Management to Prevent the Developmental Programming of MAFLD in Offspring of Obese Mothers

The global surge of obesity amongst women of reproductive age has raised concerns surrounding the health consequences for their offspring as there is a formidable link between an obesogenic maternal environment and the developmental programming of metabolic dysfunction in the offspring. Specifically, the offspring of mothers with obesity have a three-fold higher risk of developing metabolic-associated fatty liver disease (MAFLD) compared to the offspring of healthy-weight mothers. Given the burgeoning burden of obesity and its comorbidities, it is essential to focus research efforts on methods to alleviate the intergenerational onset of obesity and MAFLD. This review summarizes the current research surrounding the developmental programming of MAFLD in the offspring of mothers with obesity and examines the potential for weight interventions to prevent such metabolic dysfunction in the offspring. It focuses on the benefits of pre-pregnancy interventional strategies, including dietary and exercise intervention, to ameliorate adverse liver health outcomes in the offspring. The utility and translation of these interventions for humans may be difficult for prospective mothers with obesity, thus the use of pre-pregnancy therapeutic weight loss aids, such as glucagon-like peptide-1 receptor agonists, is also discussed.
Lipid Mediators Metabolic Chaos of Asthmatic Mice Reversed by Rosmarinic Acid

Background and objective: Asthma is a common chronic inflammatory disease of the airways with no known cure. Lipid mediators (LMs) are a kind of inflammatory signaling molecules which are believed to be involved in the development of asthma. Hyssopus cuspidatus Boriss. is a traditional Uyghur medicine, which is widely used in the treatment of asthma and other respiratory diseases. Extraction of Hyssopus cuspidatus Boriss. was reported to neutralize asthma symptoms. The purpose of the study was to investigate both the anti-inflammatory and immunoregulation properties of the Hyssopus cuspidatus Boriss. extract (SXCF) and its main active constituent, rosmarinic acid (RosA), in vivo. The effect of RosA, a major constituent of SXCF, was evaluated on an asthmatic model, with both anti-inflammatory and immunoregulation properties. Materials and methods: Anti-inflammatory effect of SXCF and RosA was assessed using OVA-induced asthma model mice by UPLC-MS/MS method. Results: Overall, RosA played a critical role in anti-asthma treatment. In total, 90% of LMs species that were significantly regulated by SXCF were covered. On the most important LMs associated with asthma, RosA equivalent induced similar effects as SXCF did. It is believed that some constituents in SXCF could neutralize RosA excessive impacts on LMs.
QCD diffraction: a critical phenomenon reflecting both confinement and chiral-symmetry breaking

Arguments are presented for studying soft diffractive physics at anti p-p colliders in terms of Critical Pomeron Reggeon Field Theory. It is emphasized that both confinement and chiral-symmetry breaking play a vital role in the occurrence of the Critical Pomeron in QCD. SU(3) is the unique strong-interaction gauge group giving the Critical Pomeron and the maximum number of quarks allowed by asymptotic freedom is required for criticality.
VARIABLE STEP-SIZE CORRELATION PHASE ALGORITHM: ANALYSIS AND SIMULATIONS

Based on “phase” of a correlation between error signal and filter reference input, this paper first derives Correlation Phase Algorithm (CΦA) for adaptive filters in the complex-number domain, and further proposes a simple Variable Step-Size control method to be combined with the CΦA. The proposed VSS-CΦA achieves significant improvement in convergence speed of the CΦA, while preserving its robustness against impulse noise. Through analysis and experiment, we demonstrate effectiveness of the VSS-CΦA in realizing sufficiently fast-convergent and robust adaptive filters. Good agreement between simulated and theoretical convergence behavior in transient phase and steady state proves the validity of the analysis.
Multiscale Geometric Integration of Deterministic and Stochastic Systems

In order to accelerate computations and improve long time accuracy of numerical simulations, this thesis develops multiscale geometric integrators. For general multiscale stiff ODEs, SDEs, and PDEs, FLow AVeraging integratORs (FLAVORs) have been proposed for the coarse time-stepping without any identification of the slow or the fast variables. In the special case of deterministic and stochastic mechanical systems, symplectic, multisymplectic, and quasi-symplectic multiscale integrators are easily obtained using this strategy. For highly oscillatory mechanical systems (with quasi-quadratic stiff potentials and possibly high-dimensional), a specialized symplectic method has been devised to provide improved efficiency and accuracy. This method is based on the introduction of two highly nontrivial matrix exponentiation algorithms, which are generic, efficient, and symplectic (if the exact exponential is symplectic). For multiscale systems with Dirac-distributed fast processes, a family of symplectic, linearly-implicit and stable integrators has been designed for coarse step simulations. An application is the fast and accurate integration of constrained dynamics. In addition, if one cares about statistical properties of an ensemble of trajectories, but not the numerical accuracy of a single trajectory, we suggest tuning friction and annealing temperature in a Langevin process to accelerate its convergence. Other works include variational integration of circuits, efficient simulation of a nonlinear wave, and finding optimal transition pathways in stochastic dynamical systems (with a demonstration of mass effects in molecular dynamics).
Exercise Programming and Optimization for Untrained Individual using Mixed Integer Linear Programming

Maintaining physical fitness through sports or exercise plays a role in our overall health and well-being, from recovering from cardiovascular diseases to avoiding serious injury. Although sports and exercise are as much as social or recreational activities, not all activities would be equivalent in terms of required physical exertion to maintain cardiovascular health and muscle hypertrophy. Broad guidelines guide medical and sports training professionals to prescribe the correct amount of physical activity for a training session. However, prescribing based on real-life exertion and fitness goals is left entirely to the trainer's discretion. Furthermore, given that the restrictions of one's schedule may discourage some people from getting any physical activity whatsoever, finding an exercise program that satisfies minimum fitness requirements in the least amount of time may encourage more to be more active. This study presents an optimization of a high-intensity interval training program using mixed integer linear programming (MILP), which seeks to select workouts that provide efficient aerobic and muscular gains while minimizing the time needed to perform the program. The program was constrained to suit a high-intensity aerobic program while engaging five muscle groups proportionately. An eight-exercise program was created using MILP, performed at a high intensity while ordering muscle groups' utilization sizes in descending order.
Digital Agent's Engagement and Affective Posture Impact Its Social Presence and Trustworthiness in Group Decision-Making

This poster introduces a user study investigating whether a digital agent's engagement and affective posture in a group decision-making scenario influence how users perceive the digital agent's social presence and trustworthiness. Our experiment was conducted with a three-person group discussion with two participants and one digital agent, and a 2 × 2 within-subject study manipulating the engagement and affective posture of a digital agent. Our findings indicate that during group discussions, the engagement posture of digital agents positively affected user perception of digital agents, whereas their affective posture negatively affected user perception.
Metaheuristic Algorithm Implementation for PV Array Reconfiguration under Realistic Moving Cloud Condition

Partial shading imposes a major issue while generating power using solar photovoltaics (SPV) and consequences in the formation of hot spots and manifold peaks in the power-voltage (P-V) curve of the SPV arrays. As a result, a main deforming concern arises i.e., The power loss due to mismatch in the SPV system is dependent on and directly caused by the shading pattern. Mitigation of this MPL can be assessed by selecting a proper configuration of the SPV array and optimal shading dispersion over the complete SPV array. This paper focuses on the implementation of renowned metaheuristic algorithms (MAs) to optimally disperse the shading effect for a partially shaded total-cross-tied (TCT) SPV array configuration. A partial shading effect is generated using a realistic moving cloud model by incorporating various affecting environmental parameters. Furthermore, MAs are tested for the designed moving cloud model and a comprehensive analysis is presented among the various SPV array configurations.
Real-Time Voltage Drop Compensation Method With Cable Impedance Detection Capability for Remote Power Supply Systems

When a power supply runs for a remote load through long cables, a voltage drop will occur due to the cable impedance. To maintain sufficient load voltage, the compensation of the cable voltage drop is necessary. In this letter, a real-time voltage drop compensation method with cable impedance detection capability is proposed. This method does not require additional auxiliary components, and the detection of cable impedance can be realized by simply adjusting the position of the filter capacitor. Further, this method can implement cable voltage drop compensation by controlling the cable current, and then realize real-time accurate control of the remote load voltage by setting the correction period. Compared with traditional methods, this method operates on the power supply side, does not affect the system efficiency and power density, and is not limited by cable parameters and environmental factors, which is more attractive in engineering applications.