Miracle-dz/UniFAR-FTUs huggingface dataset:
A Research on the Influence of College Student Time Management on Their Academic Development

Time management is of great significance to the learning of college students. As a personality trait, time management has huge differences among individuals. This study surveyed 74 students from different universities, including 16 men and 58 women, and collected relevant data by issuing questionnaires. The results show that students 'time management ability significantly affects their short-term learning development and long-term learning development, while other control variables such as gender, parents' occupations and disciplines have no significant impact. Based on this finding, we recommend that educators pay more attention to the cultivation of students 'time management ability, because time management ability not only affects students' short-term academic performance, but also has a certain impact on their future development. Educators should look at problems with a developmental perspective.
Computing team-maxmin equilibria in zero-sum multiplayer games

Efficiently computing Nash Equilibria (NEs) for multiplayer games is still an open challenge in computational game theory. In fact, it is not only hard to compute NEs in multiplayer games, but also hard for players independently choosing strategies and then forming an NE because NEs are not exchangeable. This thesis focuses on computing Team-Maxmin Equilibria (TMEs), which was introduced as a solution concept for zerosum multiplayer games where players in a team having the same utility function play against an adversary. The Correlated TME (CTME) is a variant of the TME, where team players can synchronize (correlate) their strategies by exploiting a mediator recommending actions to them through communication. According to different forms of communication, the CTME in extensive-form games includes: 1) the TME with Coordination device (TMECor) for the situation where team players can communicate their actions only before the play of the game; and 2) the TME with Communication device (TMECom) for the situation where team players can communicate their actions before the play of the game and during the game’s execution. The TME has some fascinating properties, e.g., it is unique in general, which can avoid the equilibrium selection problem. Moreover, TMEs can capture many realistic scenarios, including: 1) a team of players play against a target player in poker games; and 2) multiple defense resources schedule and patrol against the adversary in security games. Unfortunately, existing algorithms are inefficient to compute TMEs in large games. Therefore, in this thesis, we develop efficient algorithms to compute TMEs in normal-form and extensive-form games, including general algorithms and domain-specific algorithms for applications. First, we develop a novel incremental strategy generation algorithm to compute TMEs in normal-form games efficiently, which is the first incremental strategy generation algorithm guaranteeing to converge to a TME. Second, we apply the TME to a novel
Learning Spatiotemporal Correlations for Missing Noisy PMU Data Correction in Smart Grid

While various promising phasor measurement unit (PMU) data-driven applications have been developed for modern smart grids, how to improve the overall PMU data quality to ensure the reliability of these applications in practice still remains an open issue. Considering the challenging task of missing PMU data correction (MPDC) in practical complicated and noisy measurement contexts, this article develops a novel spatiotemporal correlation learning scheme (SCLS) for online MPDC in smart grids. In particular, the SCLS is strategically realized with two successive modules. First, from four complementary spatiotemporal perspectives, statistical missing data imputation is carried out to derive initial correction results in noisy contexts. Second, a well-designed deep learning architecture with the integration of convolutional neural network (CNN) and residual learning techniques is introduced to refine the correction results. With the help of these two modules, the SCLS is capable of performing precise MPDC for regional PMU measurements as well as filtering out potential noises. Extensive numerical test results on the IEEE 39-bus test system and the real-world Guangdong power grid in South China demonstrate the efficacy of the SCLS in practical complicated contexts.
Overtemperature Protection Circuit for GaN Devices Using a di/dt Sensor

Power semiconductor devices have maximum junction temperature limits, but it is not straightforward to sense or infer temperature inside sealed devices in running converters. One method is to observe electrical behavior that is known to be temperature dependent. For example, in some gallium nitride (GaN) power semiconductor devices, the maximum slope of the device current at turn-on has been shown to reduce as the junction temperature increases. This article demonstrates the first noncontact overtemperature protection circuit for GaN power devices that exploits this effect and overcomes the complication that this inverse proportionality is affected by load current. A variant of a previously reported magnetic field “Infinity Sensor,” named after its figure-of-eight topology and high bandwidth (>200 MHz), measures di/dt. Using the sensor signal as the only input, a detection circuit finds peak di/dt, and a high-speed integrator derives instantaneous load current. The reference voltage for the decision-making part of the circuit is automatically adjusted as a function of load current, in order to counteract the dependence of di/dt on load current. Experimental results on a 400 V, 2 kW buck converter show the protection circuit successfully activating within ±5 °C of a preprogrammed junction temperature setting, independently of load current, for settings of 100, 120, and 140 °C.
Isothermal desorption kinetics of crystalline H2O, H218O, and D2O ice multilayers

The isothermal desorption rates of crystalline H2O, H218O, and D2O ice multilayers were measured over a temperature range from 175 to 190 K. The desorption rates were measured with optical interferometry using ice multilayers grown epitaxially on a Ru(001) surface in an ultrahigh vacuum chamber. The Arrhenius parameters for the desorption of H2O and H218O were identical within experimental error. For H2O, the preexponential was ν = 1032.6±0.3 cm-2 s-1 and the activation energy was E = 13.9 ± 0.2 kcal mol-1. For H218O, the preexponential was ν18 = 1032.4±0.3 cm-2 s-1 and the activation energy was E18 = 13.8 ± 0.2 kcal mol-1. Despite the near equivalence in the Arrhenius parameters, H218O desorbed at a rate that was slower by ∼9% throughout the range of temperatures. In contrast, the desorption rate of D2O was slower by 49−62% compared with H2O over the measured temperature range. The Arrhenius parameters for the desorption of D2O were νD = 1033.4±0.5 cm-2 s-1 and ED= 14.8 ± 0.4 kcal mol-1. A transition sta.
Depression as a Mental Health Problem in the Patients Suffering from Cancer

About two patients from every ten patients who have been diagnosed with cancer, suffer from depression. This depression is something apart from usual sadness. Patients who have been diagnosed with cancer may encounter various stressful issues. Depression in this patients group can be occurred and needs special attention to be diagnosed and be treated appropriately. Issues like changes in daily life and life plans, changes in self-confidence and body image, being afraid of death and being worried about legal and money issues are some examples about such stressful issues for the cancer patients. When a patient is diagnosed with cancer, he or she would encounter with various degrees of grief and sadness and some other symptoms related to the depression like having problem with sleep and appetite, being worried about the future and related anxiety and some feelings like despair disbelief and also denial. Although these are common symptoms in the patients who have been diagnosed with cancer, but the reaction of the patients and their degrees of possible depression is different between various patients. Some patients can deal with the diagnosis of cancer better and would not encounter depression and anxiety problems and some others deal with such diagnosis in a way that they would encounter anxiety disorder and major depressive disorder. Usually the patients who can continue their roles in their lives like being a parent or a spouse and can be active during their daily life, have adjusted to the cancer diagnosis and its course much better than other patients. Family members of the patients who have been diagnosed with cancer, are also at risk of developing anxiety and depression.
Colonising new frontiers—microarrays reveal biofilm modulating polymers

Polymer microarrays provide an innovative approach to identify materials with novel bacterial binding or repellent properties which could subsequently be used in a variety of practical applications. Here, we report a polymer microarray screen of hundreds of synthetic polymers to identify those which either selectively capture the major food-borne pathogen, Salmonella enterica serovar Typhimurium (S. Typhimurium), or prevent its binding. A parallel study with a lab strain of Escherichia coli (E. coli) is also reported; revealing polymers which either display a common binding activity or which exhibit species discrimination. Moreover, substrates were also uncovered which showed no binding of either organism, even when cultured at high density. The correlation between polymer structure and microbial-modulating behaviour was analysed further, while SEM analysis allowed visualization of the detailed interactions between surface and bacteria. Such polymers offer many new opportunities for bacterial enrichment or surface repulsion, in cleaning materials, as surface coatings for use in the food production industry or as a “bacterial scavenger” resin.
AIRSHIP GUST RESPONSE PROBABILISTIC MODEL CONSTRUCTION

In the context of random environment, time-domain simulation of structural responses is often necessary when the structure is nonlinear, but not only : when the structure is linear and the excitation modelled as a non-stationnary non-Gaussian process, Monte Carlo approaches are necessary to identify the probabilistic distribution of the output. In this paper we use a stochastic model developped for non-stationnary and non- Gaussian random processes. It is based on an empirical Karhunen-Loeve expansion of the process constructed from an available data basis. We study the particular case of linear structures: the Monte Carlo becomes particularely simple: one needs only to consider the construction of a low number of responses, corresponding to the deterministic eigen functions of the Karhunen-Loeve expansion, hence avoiding high number of calls to industrial codes. The KL expansion of the response is then obtained directly using these responses and the system output probabilistic characterization can be constructed through Monte Carlo simulation of the KL output model. This approach is used in order to quantify the effect of gusts on a future airship using a database obtained during a winter storm from which a model of vertical gusts isconstructed. Response comparisons for realistic and gusts and the one prescribed by national regulation requirements will be shown.
Scope and Limitations of Palladium‐Catalyzed Cross‐Coupling Reactions with Organogold Compounds

Five different alkenylgold(I) phosphane complexes were prepared and then investigated in [1,1′-bis(diphenylphosphino)ferrocene]palladium(II) dichloride-catalyzed cross-coupling reactions with different aryl halides, heterocyclic halides, an alkenyl halide, an alkynyl halide, allylic substrates, benzyl bromide and an acid chloride. With regard to the halides, the iodides were highly reactive, bromides or chlorides gave significantly reduced yields or failed, allylic acetates failed, too. The cross-coupling partners contained a number of different functional groups, while free carboxylic acids did not deliver cross-coupling products and o,o-disubstituted arenes failed as well, a broad range of other functional groups like nitro groups, nitrile groups, ester groups, α,β-unsaturated ester groups and lactones, aldehydes, alkoxy groups, pyridyl groups, thienyl groups, unprotected phenols and anilines, even aryl azides were tolerated. The structures of one alkenylgold(I) species and of four of the cross-coupling products were proved by crystal structure analyses.
Regulation of Nuclear Mechanics and the Impact on DNA Damage

In eukaryotic cells, the nucleus houses the genomic material of the cell. The physical properties of the nucleus and its ability to sense external mechanical cues are tightly linked to the regulation of cellular events, such as gene expression. Nuclear mechanics and morphology are altered in many diseases such as cancer and premature ageing syndromes. Therefore, it is important to understand how different components contribute to nuclear processes, organisation and mechanics, and how they are misregulated in disease. Although, over the years, studies have focused on the nuclear lamina—a mesh of intermediate filament proteins residing between the chromatin and the nuclear membrane—there is growing evidence that chromatin structure and factors that regulate chromatin organisation are essential contributors to the physical properties of the nucleus. Here, we review the main structural components that contribute to the mechanical properties of the nucleus, with particular emphasis on chromatin structure. We also provide an example of how nuclear stiffness can both impact and be affected by cellular processes such as DNA damage and repair.
Distinguishing adsorption and surface precipitation of phosphate on goethite (α-FeOOH).

The reaction between phosphate and goethite changes from adsorption into surface precipitation with no discernible changes in the adsorption isotherm. Distinguishing the two processes, by plotting the loss of phosphate from solution versus final phosphate concentration or based on theoretical calculations, is difficult. This paper presents a method for distinguishing between the two processes based on the change in zeta potential with increasing adsorption. During adsorption, the incoming phosphate results in a more negative surface charge as the more acidic phosphate ion replaces a less acidic surface hydroxyl. The amount of negative charge imparted to the surface should vary linearly with surface coverage for adsorption. Phosphate that is bound to a surface precipitate, on the other hand, imparts a much smaller negative charge to the surface, since there is no change in the character of the surface due to the additional phosphate. Zeta potential measurements of phosphated goethite at varying solution pH values and surface coverages are used to determine the transition point from adsorption to surface precipitation. The transition occurs at dissolved phosphate concentrations much lower than those calculated for phosphate in equilibrium with goethite and iron phosphate.
Microfluidic wet-spinning of alginate microfibers: a theoretical analysis of fiber formation

We investigate the conditions under which fibers can be fabricated in a microfluidic chip upon gelation of alginate with a calcium salt. We develop a device which permits us to generate a perfectly centered axial coflow and we study the influence of control parameters, namely the salt concentration, the residence time, and the size of the polymeric jet, on the gelation process. We monitor several states which include no gel, continuous fibers, pieces of gel and clogging. To describe the resulting state diagrams, we develop a model of reaction–diffusion under flow which permits us to estimate the density of links created during the gelation. While the no-gel and clogging states are chiefly governed by the density of links (respectively very low and very high), the selection of fibers against pieces-of-gel is controlled by the stress exerted on the jet at the level of the injection nozzle, also called spinneret. This simple modeling of conditions required to create fibers as an interplay between gel strength and local elongational stress might be useful for the fabrication and miniaturization of functional fibers.
Density Functional Characterization of the Band Edges, the Band Gap States, and the Preferred Doping Sites of Halogen-Doped TiO2

First-principles density functional theory (DFT) electronic structure calculations were carried out for model halogen-doped anatase TiO2 structures to evaluate the effect of halogen doping on the band edges and the photocatalytic activity of TiO2. The model structures of X-doped TiO2 were constructed by using the 48-atom 2 × 2 × 1 supercell of anatase TiO2 with one O or one Ti atom replaced with X (=F, Cl, Br, I). The unit cell parameters and the atom positions of the resulting X-doped TiO2 with X at an O site (X@O) and that with X at a Ti site (X@Ti) were optimized by performing first-principles DFT calculations. On the basis of the optimized structures of X-doped TiO2 with X@O and X@Ti, the defect formation energies and the plots of the density of states were calculated to analyze the band edges, the band gap states, and the preferred doping sites. Our work shows that the doping becomes more difficult in the order F < Cl < Br < I for X-doped TiO2 with X@O, while the doping becomes less difficult in the .
Robust Voltage Control Considering Uncertainties of Renewable Energies and Loads via Improved Generative Adversarial Network

The fluctuation of output power of renewable energies and loads brings challenges to the scheduling and operation of the distribution network. In this paper, a robust voltage control model is proposed to cope with the uncertainties of renewable energies and loads based on an improved generative adversarial network (IGAN). Firstly, both real and predicted data are used to train the IGAN consisting of a discriminator and a generator. The noises sampled from the Gaussian distribution are fed to the generator to generate a large number of scenarios that are utilized for robust voltage control after scenario reduction. Then, a new improved wolf pack algorithm (IWPA) is presented to solve the formulated robust voltage control model, since the accuracy of the solutions obtained by traditional methods is limited. The simulation results show that the IGAN can accurately capture the probability distribution characteristics and dynamic nonlinear characteristics of renewable energies and loads, which makes the scenarios generated by IGAN more suitable for robust voltage control than those generated by traditional methods. Furthermore, IWPA has a better performance than traditional methods in terms of convergence speed, accuracy, and stability for robust voltage control.
A Review of Single-Photon Avalanche Diode Time-of-Flight Imaging Sensor Arrays

Time-of-flight (ToF) sensors using light pulses or continuous waves allow accurate distance measurements. Three-dimensional imagers can be based on an array of timing or time-gated integration pixels. Single-photon avalanche diodes (SPADs) have been increasingly chosen as the pixel’s photodetector device to develop fast, long-range ToF sensors. Solid-state ToF cameras are replacing other alternatives, showing attractive characteristics and bringing up new potential applications. This paper presents the technical evolution of SPAD ToF 3D imaging sensors, and provides insight into their development over the last few decades. Starting with the first SPAD imagers reported in the early 2000’s, various direct and indirect arrays up to present day state-of-the-art prototypes are referenced. The existing methods, options and possible implementations are described, addressing their advantages and drawbacks, and showing the progress yet to be made. The performance of the different presented approaches are given and compared.
Hybrid Connected Unified Power Quality Conditioner Integrating Distributed Generation With Reduced Power Capacity and Enhanced Conversion Efficiency

In this article, a hybrid connected unified power quality conditioner integrating distributed generation (HCUPQC-DG) is proposed. Two dc ports are created at the dc link of the HCUPQC-DG, in which one low-voltage (LV) dc port is directly connected to distributed generation (DG), and the other high-voltage (HV) dc port is indirectly connected to DG through the front-end dc–dc converter. With the hybrid connected configuration, the HV is designed to ensure the dc–ac voltage conversion capability, whereas the LV, i.e., the voltage of DG, can be relatively low and vary in a wide range. Besides, most active power can be directly transferred from DG to the ac load or grid through the direct power flow path. Hence, the conversion efficiency is enhanced, and the power capacity of the front-end dc–dc converter is significantly reduced. The operating principle and the control and modulation strategies of the proposed HCUPQC-DG are discussed. Moreover, the power flow through the HCUPQC-DG is analyzed in detail to understand the system operation. Experimental results with a 3-kVA prototype are provided to verify the feasibility and effectiveness of the proposed HCUPQC-DG.
DC Transport in Self-Assembled 2D Layers of Ag Nanoparticles†

The temperature dependence of the DC resistivity of silver quantum dot self-assembled 2D Langmuir monolayers was obtained. The films exhibit a metallic-like resistance at high temperatures (above 200 K), and a thermally activated mechanism at intermediate temperatures (60−200 K) which strongly supports the model of a Mott−Hubbard band gap. The transition temperature from the metallic-like regime to the thermally activated regime was found to correlate with the activation barrier.
Cytokine Profile in Plasma Extracellular Vesicles of Parkinson’s Disease and the Association with Cognitive Function

Plasma extracellular vesicles (EVs) containing various molecules, including cytokines, can reflect the intracellular condition and participate in cell-to-cell signaling, thus emerging as biomarkers for Parkinson’s disease (PD). Inflammation may be a crucial risk factor for PD development and progression. The present study investigated the role of plasma EV cytokines as the biomarkers of PD. This cross-sectional study recruited 113 patients with PD, with mild to moderate stage disease, and 48 controls. Plasma EVs were isolated, and the levels of cytokines, including pro-interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-β1, were evaluated. Patients with PD had significantly increased plasma EV pro-IL-1β and TNF-α levels compared with controls after adjustment for age and sex. Despite the lack of a significant association between plasma EV cytokines and motor symptom severity in patients with PD, cognitive dysfunction severity, assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment, was significantly associated with plasma EV pro-IL-1β, IL-6, IL-10, and TNF-α levels. This association was PD specific and not found in controls. Furthermore, patients with PD cognitive deficit (MMSE < 26) exhibited a distinguished EV cytokine profile compared to those without cognitive deficit. The findings support the concept of inflammatory pathogenesis in the development and progression of PD and indicate that plasma EV cytokines may serve as PD biomarkers in future.