Miracle-dz/UniFAR-FTUs huggingface dataset:
Beneficial and Detrimental Remodeling of Glial Connexin and Pannexin Functions in Rodent Models of Nervous System Diseases

A variety of glial cell functions are supported by connexin and pannexin proteins. These functions include the modulation of synaptic gain, the control of excitability through regulation of the ion and neurotransmitter composition of the extracellular milieu and the promotion of neuronal survival. Connexins and pannexins support these functions through diverse molecular mechanisms, including channel and non-channel functions. The former comprise the formation of gap junction-mediated networks supported by connexin intercellular channels and the formation of pore-like membrane structures or hemichannels formed by both connexins and pannexins. Non-channel functions involve adhesion properties and the participation in signaling intracellular cascades. Pathological conditions of the nervous system such as ischemia, neurodegeneration, pathogen infection, trauma and tumors are characterized by distinctive remodeling of connexin expression and function. However, whether these changes can be interpreted as part of the pathogenesis, or as beneficial compensatory effects, remains under debate. Here we review the available evidence addressing this matter with a special emphasis in mouse models with selective manipulation of glial connexin and pannexin proteins in vivo. We postulate that the beneficial vs. detrimental effects of glial connexin remodeling in pathological conditions depend on the impact of remodeling on the different connexin and pannexin channel and non-channel functions, on the characteristics of the inflammatory environment and on the type of interaction among glial cells types.
On the Mathematical Model of Nonlinear Vibrations of a Biologically Active Rod with Consideration of the Rheological Factor

Qualitative and numerical methods of researching nonlinear vibration systems are used to study the mathematical model of nonlinear vibrations of a biologically active rod. This model is widely used in biomechanics and medical research for designing new materials with biofactor elements that possess certain preset features. Conditions are established for the existence of a unique solution of the boundary value problem for the beam vibration nonlinear differential equation, in which there is an integral summand with the fourth derivative by the spatial variables. This summand models the rheological factor in the system. The existence of classes of nonlinear rheological vibration systems with dissipation that have blow-up regimes is stated theoretically. The relation between nonlinearity indices in such regimes is obtained. The theoretical possibility of using the Runge-Kutta method for numerical solution of the corresponding boundary value problem is shown. The results are illustrated by a model example. The importance of the obtained theoretical assumptions for the practical modeling, analysis, and synthesis of parameters of technological vibration systems is shown.
Monte Carlo integrated approach to radiological characterization for nuclear facilities decommissioning

ABSTRACT In the last decades, hundreds of nuclear reactors have been shut-down and have experienced decommissioning. This is also the case of L-54M Politecnico di Milano nuclear research reactor. Since shut-down in 1979, the plant has been managed following deferred dismantling strategy. Recently, preliminary radiological characterizations have been launched, even though a more extended campaign is necessary to implement facility decommissioning and restore unrestricted reuse status. In the framework of the IAEA collaborative research project on irradiated GRAphite Processing Approaches, a general radiochemistry and Monte Carlo integrated approach has been developed to study materials activation and support radiological characterization campaign. This integrated method, thanks to its general principles, could be applied to any nuclear reactor or facility undergoing decommissioning, thus helping to reduce the characterization efforts and, possibly, the associated costs.
A Cyclic Game for Joint Cooperation and Competition of Edge Resource Allocation

Managing edge resources is one of key issues in edge computing. Recent works of resource allocation in edge computing focus on service caching and request scheduling on edge nodes by distributing tasks over cloud and edge nodes, so as to achieve high-quality services and low latency. Unfortunately, most schemes do not pay enough attention on service providers which also have their own resources. To serve users, service providers cooperate with edge nodes and are sometimes independent of the edge operators with their own objectives. To deal with the cooperation and conflict among users, service providers and edge nodes, we propose a cyclic selection model to depict the resource allocation among users, edge nodes and service providers where they cooperate for completing user requests and compete for their own interest. Such resource allocation problem can be formulated as a non-linear integer programming which is very difficult to solve. Thus, we propose a three-sided cyclic game (3CG) involving users, edge nodes, and service providers who make their decisions: users select preferred services, service providers select cost-effective edge nodes, edge nodes select high-value users. 3CG is proved to have pure-strategy Nash equilibriums and an approximation ratio. We develop central and distributed approximate algorithms for resource allocation. The evaluation results of 3CG show the effectiveness and efficiency of the proposed algorithms.
Localized electrochemical deposition – preliminary research

Electrochemical deposition has been used in industry for many years. It is most often used in plating and electroforming processes. Relatively unexplored area is localized electrochemical deposition. This is due to the difficulty of keeping under control this process. Because the shape and range of the electric field play a key role in electrochemical processes, a high localization is difficult to achieve (both loss and additive processes). The localized electrochemical deposition gives possibility of producing parts using techniques used in additive methods, which allows for better flexibility in the production process. On the other hand, it limits the possibility of using materials for metals only. This process can be used on both micro and macro scale. The most important problems of this technique are localization of process, material structure, filling of part and aggressive environment of electrolyte. The article presents preliminary research of the localized electrochemical deposition process, which was carried out at the Faculty of Mechanical Engineering of the Cracow University of Technology. In this process a four electrode system was used powered by bipotentiostat which allowed for full control on electrode potentials. In order to obtain a better localization of the process pulsed power supply was applied.Electrochemical deposition has been used in industry for many years. It is most often used in plating and electroforming processes. Relatively unexplored area is localized electrochemical deposition. This is due to the difficulty of keeping under control this process. Because the shape and range of the electric field play a key role in electrochemical processes, a high localization is difficult to achieve (both loss and additive processes). The localized electrochemical deposition gives possibility of producing parts using techniques used in additive methods, which allows for better flexibility in the production process. On the other hand, it limits the possibility of using materials for metals only. This process can be used on both micro and macro scale. The most important problems of this technique are localization of process, material structure, filling of part and aggressive environment of electrolyte. The article presents preliminary research of the localized electrochemical deposition process, which.
Impact of Optimal Timing of Intake of Multi-Ingredient Performance Supplements on Sports Performance, Muscular Damage, and Hormonal Behavior across a Ten-Week Training Camp in Elite Cyclists: A Randomized Clinical Trial

Multi-ingredient performance supplements (MIPS), ingested pre- or post-workout, have been shown to increase physiological level effects and integrated metabolic response on exercise. The purpose of this study was to determine the efficacy of pre-and post-training supplementation with its own MIPS, associated with CHO (1 g·kg−1) plus protein (0.3 g·kg−1) on exercise-related benchmarks across a training camp for elite cyclists. Thirty elite male cyclists participated in a randomized non-placebo-controlled trial for ten weeks assigned to one of three groups (n = 10 each): a control group treated with CHO plus protein after training (CG); a group treated with MIPS before training and a CHO plus protein after training, (PRE-MIPS); a group treated with CHO plus protein plus MIPS after training, (POST-MIPS). Performance parameters included (VO2max, peak; median and minimum power (W) and fatigue index (%)); hormonal response (Cortisol; Testosterone; and Testosterone/Cortisol ratio); and muscle biomarkers (Creatine kinase (CK), Lactate dehydrogenase (LDH), and Myoglobin (Mb)) were assessed. MIPS administered before or after training (p ≤ 0.05) was significantly influential in attenuating CK, LDH, and MB; stimulating T response and modulating C; and improved on all markers of exercise performance. These responses were greater when MIPS was administered post-workout.
A new slip velocity suitable for natural gas flows in energy applications

ABSTRACT Figuring out the natural gas behavior through micro/nanochannels is vital for accurate prediction of the rarefied flows and design optimization of Micro electro mechanical systems (MEMS) and Nano electro mechanical systems (NEMS) in energy applications. Continued with the previous work, introduction of a modified kinetic-based slip velocity for natural gas flows suitable for energy applications is the purpose of the current paper. In comparison with the previous work, this model includes an additional term due to compressibility factor gradient. We used the virial equation of state to calculate the compressibility factor gradient along the flow direction. The new model is verified with previously published results.
Balance Expertise Is Associated with Superior Spatial Perspective-Taking Skills

Balance training interventions over several months have been shown to improve spatial cognitive functions and to induce structural plasticity in brain regions associated with visual-vestibular self-motion processing. In the present cross-sectional study, we tested whether long-term balance practice is associated with better spatial cognition. To this end, spatial perspective-taking abilities were compared between balance experts (n = 40) practicing sports such as gymnastics, acrobatics or slacklining for at least four hours a week for the last two years, endurance athletes (n = 38) and sedentary healthy individuals (n = 58). The balance group showed better performance in a dynamic balance task compared to both the endurance group and the sedentary group. Furthermore, the balance group outperformed the sedentary group in a spatial perspective-taking task. A regression analysis across all participants revealed a positive association between individual balance performance and spatial perspective-taking abilities. Groups did not differ in executive functions, and individual balance performance did not correlate with executive functions, suggesting a specific association between balance skills and spatial cognition. The results are in line with theories of embodied cognition, assuming that sensorimotor experience shapes cognitive functions.
IN-SILICO STUDIES OF SOME INDOLE DERIVATIVES AS AN ANTI-HEPATITIS C DRUG.

A combined three-dimensional quantitative structure-activity relationship (QSAR) modeling and molecular docking studies were carried out on the 64 indole derivatives and was accomplished to profoundly understand the structure-activity correlation of indole-based inhibitors of the HCV NS5B polymerase against HCV. Genetic function approximation (GFA) of Material studio software version 8 was used to perform the QSAR study while Autodock vina version 4.0 of Pyrx software was used for molecular docking studies of the selected indole derivatives. The optimum model builds exhibited statistically significant results: squared correlation coefficient (R 2 ) of 0.760, adjusted squared correlation coefficient (R 2 adj) value of 0.708, Leave one out (LOO) cross-validation coefficient value of 0.634 and the external validation (R 2 pred) of 0.621. Molecular docking study of the indole derivative with 1G8Q as the protein target revealed that the best binding affinity with the docking scores of -9.4 kcal/mol formed hydrophobic interaction and H-bonding with amino acid residues of HCV NS5B polymerase. The QSAR model generated and molecular docking results proposed that the model had a good level of stability, strength, and predictability at internal and external validation, and the physicochemical parameters are to be analyzed when designing new indole derivatives agent with better activity against the 1G8Q target site.
Cooper Test Provides Better Half-Marathon Performance Prediction in Recreational Runners Than Laboratory Tests

This study compared the ability to predict performance in half-marathon races through physiological variables obtained in a laboratory test and performance variables obtained in the Cooper field test. Twenty-three participants (age: 41.6 ± 7.6 years, weight: 70.4 ± 8.1 kg, and height: 172.5 ± 6.3 cm) underwent body composition assessment and performed a maximum incremental graded exercise laboratory test to evaluate maximum aerobic power and associated cardiorespiratory and metabolic variables. Cooper’s original protocol was performed on an athletic track and the variables recorded were covered distance, rating of perceived exertion, and maximum heart rate. The week following the Cooper test, all participants completed a half-marathon race at the maximum possible speed. The associations between the laboratory and field tests and the final time of the test were used to select the predictive variables included in a stepwise multiple regression analysis, which used the race time in the half marathon as the dependent variable and the laboratory variables or field tests as independent variables. Subsequently, a concordance analysis was carried out between the estimated and actual times through the Bland-Altman procedure. Significant correlations were found between the time in the half marathon and the distance in the Cooper test (r = −0.93; p < 0.001), body weight (r = 0.40; p < 0.04), velocity at ventilatory threshold 1, (r = −0.72; p < 0.0001), speed reached at maximum oxygen consumption (vVO2max), (r = −0.84; p < 0.0001), oxygen consumption at ventilatory threshold 2 (VO2VT2) (r = −0.79; p < 0.0001), and VO2max (r = −0.64; p < 0.05). The distance covered in the Cooper test was the best predictor of time in the half-marathon, and might predicted by the equation: Race time (min) = 201.26 – 0.03433 (Cooper test in m) (R2 = 0.873, SEE: 3.78 min). In the laboratory model, vVO2max, and body weight presented an R2 = 0.77, SEE 5.28 min. predicted by equation: Race time (min) = 156.7177 – 4.7194 (vVO2max) – 0.3435 (Weight). Concordance analysis showed no differences between the times predicted in the models the and actual times. The data indicated a high predictive power of half marathon race time both from the distance in the Cooper test and vVO2max in the laboratory. However, the variable associated with the Cooper test had better predictive ability than the treadmill test variables. Finally, it is important to note that these data may only be extrapolated to recreational male runners.
A Comprehensive Evaluation for the Tunnel Conditions with Ground Penetrating Radar Measurements

We aim to develop a comprehensive tunnel lining detection method and clustering technique for semi-automatic rebar identification in order to investigate the ten tunnels along the South-link Line Railway of Taiwan (SLRT). We used the Ground Penetrating Radar (GPR) instrument with a 1000 MHz antenna frequency, which was placed on a versatile antenna holder that is flexible to the tunnel’s condition. We called it a Vehicle-mounted Ground Penetrating Radar (VMGPR) system. We detected the tunnel lining boundary according to the Fresnel Reflection Coefficient (FRC) in both A-scan and B-scan data, then estimated the thinning lining of the tunnels. By applying the Hilbert Transform (HT), we extracted the envelope to see the overview of the energy distribution in our data. Once we obtained the filtered radargram, we used it to estimate the Two-dimensional Forward Modeling (TDFM) simulation parameters. Specifically, we produced the TDFM model with different random noise (0–30%) for the rebar model. The rebar model and the field data were identified with the Hierarchical Agglomerative Clustering (HAC) in machine learning and evaluated using the Silhouette Index (SI). Taken together, these results suggest three boundaries of the tunnel lining i.e., the air–second lining boundary, the second–first lining boundary, and the first–wall rock boundary. Among the tunnels that we scanned, the Fangye 1 tunnel is the only one in category B, with the highest percentage of the thinning lining, i.e., 13.39%, whereas the other tunnels are in category A, with a percentage of the thinning lining of 0–1.71%. Based on the clustered radargram, the TDFM model for rebar identification is consistent with the field data, where k = 2 is the best choice to represent our data set. It is interesting to observe in the clustered radargram that the TDFM model can mimic the field data. The most striking result is that the TDFM model with 30% random noise seems to describe our data well, where the rebar response is rough due to the high noise level on the radargram.
A Lyapunov-Like Characterization of Predefined-Time Stability

This article studies Lyapunov-like conditions to ensure a class of dynamical systems to exhibit predefined-time stability. The origin of a dynamical system is predefined-time stable if it is fixed-time stable, and an upper bound of the settling-time function can be arbitrarily chosen a priori through a suitable selection of the system parameters. We show that the studied Lyapunov-like conditions allow us to demonstrate the equivalence between previous Lyapunov theorems for predefined-time stability for autonomous systems. Moreover, the obtained Lyapunov-like theorem is extended for analyzing the property of predefined-time ultimate boundedness with predefined bound, which is useful when analyzing uncertain dynamical systems. Therefore, the proposed results constitute a general framework for analyzing the predefined-time stability, and they also unify a broad class of systems that present the predefined-time stability property. On the other hand, the proposed framework is used to design robust controllers for affine control systems, which induce predefined-time stability (predefined-time ultimate boundedness of the solutions) w.r. t. to some desired manifold. A simulation example is presented to show the behavior of a developed controller, especially regarding the settling time estimation.
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators

Convolutional Neural Networks (CNNs) have emerged as highly successful tools for image generation, recovery, and restoration. This success is often attributed to large amounts of training data. However, recent experimental findings challenge this view and instead suggest that a major contributing factor to this success is that convolutional networks impose strong prior assumptions about natural images. A surprising experiment that highlights this architectural bias towards natural images is that one can remove noise and corruptions from a natural image without using any training data, by simply fitting (via gradient descent) a randomly initialized, over-parameterized convolutional generator to the single corrupted image. While this over-parameterized network can fit the corrupted image perfectly, surprisingly after a few iterations of gradient descent one obtains the uncorrupted image. This intriguing phenomenon enables state-of-the-art CNN-based denoising and regularization of linear inverse problems such as compressive sensing. In this paper, we take a step towards demystifying this experimental phenomenon by attributing this effect to particular architectural choices of convolutional networks, namely convolutions with fixed interpolating filters. We then formally characterize the dynamics of fitting a two-layer convolutional generator to a noisy signal and prove that early-stopped gradient descent denoises/regularizes. This result relies on showing that convolutional generators fit the structured part of an image significantly faster than the corrupted portion.
Development of a Strategy for Enhancing the Biomass Growth and Lipid Accumulation of Chlorella sp. UJ-3 Using Magnetic Fe3O4 Nanoparticles

In this study, magnetic Fe3O4 nanoparticles (NPs) were used as an effective enhancer to increase the biomass and total lipid production of Chlorella sp. UJ-3. It was found that the biomass of algal cells increased significantly when they were exposed to low concentrations of Fe3O4 NPs (20 mg/L), while the best total lipid content of algal cells was achieved when they were exposed to high concentrations of Fe3O4 NPs (100 mg/L). Therefore, we established a strategy to promote the growth and lipid accumulation of microalgae by initially exposing the algal cells to low concentrations of Fe3O4 NPs and then treating them with an increased concentration of Fe3O4 NPs after 12 days of culture. For this strategy, the biomass and total lipid production of algal cells increased by 50% and 108.7%, respectively, compared to the untreated control. The increase in lipid production and change in the fatty acid composition of Chlorella cells were found to help them to cope with the increased number of reactive oxygen species produced due to oxidative stress in alga cells after the addition of Fe3O4 NPs. This study provided a highly efficient way to improve the lipid production of microalgae using nanoparticles.
Robust Hybrid Analog/Digital Beamforming for Uplink Massive-MIMO with Imperfect CSI

In this paper, we study the design of hybrid analog/digital beamformers for uplink connection in massive multiple-input multiple-output (MIMO) systems under imperfect channel state information (CSI). The norm-bounded channel error model is used to capture characteristics of imperfect CSI in practical systems. The objective function is formulated based on the minimum mean squared error (MMSE) worst-case robustness. We consider both single user (SU) and multiuser (MU) reception modes of a millimeter-Wave (mmWave) massive-MIMO base station (BS). For the SU scenario, we study hierarchical beamformer optimization as well as joint precoder/combiner optimization for users with limited and extended computational capabilities, respectively. These optimization techniques are subsequently extended to the MU case where a new hybrid robust combiner design is proposed. Simulation results are presented confirming the superiority of our designs when compared to recent robust hybrid designs in the literature.