Miracle-dz/UniFAR-FTUs huggingface dataset:
Significant Performance Enhancement of Graphene Anode for Li-ion Batteries by Using CVD-Graphene-Film/Cu-Foil Composite Collectors

For the first time, CVD-grown graphene film on Cu foil (G/Cu) was used as a composite collector of reduced graphene oxide (rGO) anode for lithium-ion batteries. Significant performance enhancement was observed for rGO anode with G/Cu composite collector: i) the first cycle discharge specific capacity of rGO anode with G/Cu composite is as large as 2947 mAh g-1, nearly twice of that (1509 mAh g-1) using conventional Cu foil collector; ii) rGO anode with G/Cu composite shows much better high-rate specific capacity even at 20 C. It suggests that it is promising for G/Cu composite collector to improve the performance of lithium ion batteries.
Distributed Learning Applications in Power Systems: A Review of Methods, Gaps, and Challenges

In recent years, machine learning methods have found numerous applications in power systems for load forecasting, voltage control, power quality monitoring, anomaly detection, etc. Distributed learning is a subfield of machine learning and a descendant of the multi-agent systems field. Distributed learning is a collaboratively decentralized machine learning algorithm designed to handle large data sizes, solve complex learning problems, and increase privacy. Moreover, it can reduce the risk of a single point of failure compared to fully centralized approaches and lower the bandwidth and central storage requirements. This paper introduces three existing distributed learning frameworks and reviews the applications that have been proposed for them in power systems so far. It summarizes the methods, benefits, and challenges of distributed learning frameworks in power systems and identifies the gaps in the literature for future studies.
Diffusion tensor imaging findings of patients with parkinson's disease refractory to medical treatment

Aim: Diffusion Tensor Imaging (DTI) findings can be useful to detect and measure neurodegeneration that is seen in Parkinson’sdisease (PD). Microstructural changes in regions of the brain related with motor function are evaluated by using DTI measurementsof fractional anisotropy (FA) to find out the possible role of the technique in diagnosis in patients with PD.Materials and Methods: The study includes 18 PD patients who were candidates for deep brain stimulation surgery, and 19 controlgroup patients. DTI was performed in all cases. DTI characteristics of FA were measured in primary motor cortex (M1), supplementarymotor area (SMA), inferior parietal lobule, putamen (P), globus pallidus externus (GPe) and internus (GPi), ventrolateral nucleus ofthalamus (Th), substantia nigra (SN), cuneus, precuneus and cerebellar dentate nucleus (D) bilaterally. Additionally, we processed“raw” FA images and colored them according to fiber orientation to visualize STN and GPi nuclei.Results: Mean age of the control group was 59.2±13.2 (range: 31-79) years, while it was 56.7±16 (range: 42-77) years for the patientgroup. Mean duration of PD was 12.4±7.1 (range: 5-30) years. Study group FA values were significantly lower than the control groupin all areas bilaterally (p<0.05). Additionally, FA-M1, FA-GPi and FA-GPe values were significantly lower on left side compared to rightside (p<0.05). Conclusion: Decrease in FA values in all regions in the study group is thought to result from loss of nerve cells. Additionally, raw FAimages that are processed, and colored in relation to fiber orientation can be useful for a better identification of STN and GPi nuclei.This type of imaging will provide a more precise anatomy necessary for surgical targeting.
On Approaching Relevant Cost-Effective Sustainable Maintenance of Mineral Oil-Filled Electrical Transformers

Fire and explosion accidents of oil-filled electrical transformers are leading to negative impacts, not only on the delivery of energy, but also on workplace health and safety as well as the surrounding environment. Such accidents are still being reported, regardless of applying the regular maintenance strategy in the power plants. The purpose of this paper is to integrate a sustainability perspective into the maintenance strategy. The problem addressed is: how can we approach the relevant cost-effective sustainable maintenance for oil-filled electrical transformers? For this purpose, an empirical study in a power plant in Kuwait was introduced. The first stage was to carry out a sustainability assessment using the ABCD procedure. In this procedure, gaps to approach sustainability were identified and actions prioritized to close these gaps were demonstrated. Applying this procedure yielded an early fault diagnosis (EFD) model for achieving cost-effective sustainable maintenance using a fault trend chart based on a novel numerical method. Implementing this model resulted in an extension of the lifetime of transformers with suspected failure propagation, leading to a deferral of the replacement investment costs. The principal conclusion of this paper is the importance of viewing the maintenance strategy of transformers from a strategic sustainability perspective, in order to approach relevant cost-effective sustainable maintenance.
Integrated Hydrological Analysis of Little Akaki Watershed Using SWAT-MODFLOW, Ethiopia

In Ethiopia, groundwater is the main source of freshwater to support human consumption and socio-economic development. Little Akaki watershed is located in Upper Awash basin, known for its high annual rainfall and considered as the potential groundwater recharge zone. On the contrary, urbanization and industrial expansion are increasing at an alarming rate in the area. This became a concern threatening the groundwater resources’ sustainability. To address these challenges, integrated analysis of groundwater recharge and groundwater numerical simulations were made. For groundwater recharge estimation, SWAT model was used. The result indicated that recharge in the watershed mostly occurs from July to October with maximum values in August. On average, the estimated annual catchment recharge was 179 mm. For the numerical simulation and prediction of the groundwater flow system, MODFLOW 2005 was used. The model simulations indicated that the groundwater head converges towards the main river and, finally, to the outlet of the watershed. The study indicated areas of interactions between the river and groundwater. The scenario examination result reveals increasing the present pumping rate by over fifty percent (by 50%, 100%, and 200%) will surely cause visible groundwater head decline near the outlet of the watershed, and substantial river baseflow reduction. The recharge reduction scenario also indicates the huge risk of groundwater sustainability in the area.
Deep social force network for anomaly event detection

Anomaly event detection is vital in surveillance video analysis. However, how to learn the discriminative motion in the crowd scene is still not tackled. Here, a deep social force network by exploiting both social force extracting and deep motion coding is proposed. Given a grid of particles with velocity provided by the optical ﬂow, the interaction force in the crowd scene is investigated and a social force module is embedded in a deep network. A deep motion convolution was further designed with a 3D (DMC-3D) module. The DMC-3D not only eliminates the noise motion in the crowd scene with a spatial encoder–decoder but also learns the 3D feature with a spatio-temporal encoder. The deep social force coding is modelled with multiple features, in which each feature can describe speciﬁc anomaly motion. The experiments on UCF-Crime and ShanghaiTech datasets demonstrate that our method can predict the temporal localization of anomaly events and outperform the state-of-the-art methods.
Fabrication of Flexible and Transferable RTDs via Fused Deposition Modelling 3D Printing

Fused Deposition Modelling (FDM) 3D printing is a simple and cost-effective manufacturing method. This study investigates the capabilities of using FDM 3D printing to produce simple Resistance Temperature Detectors (RTDs) as temperature sensors. Two types of conductive PLA filaments were used: carbon black (CB) and graphene PLA filaments. The CB and graphene PLA sensors showed conductance of 0.0238 mS and 0.1042 mS respectively. When measuring the response of the sensors against a change in temperature ranging from 15 °C to 80 °C, the CB PLA sensor showed a sensitivity of 0.01416 ± 0.00004 °C-1 whereas the graphene PLA sensor had a sensitivity of 0.00498 ± 0.00004 °C-1. The 3D printed temperatures sensors showed good flexibility and stability, even after being transferred to different substrates.
New Thermo-Sensitive Hydrogel Based on Copolymer of 2-hydroxyethyl Acrylate and Ethyl Acrylate

In this work firstly the thermo-sensitive polymer hydrogels were obtained by three-dimensional radical copolymerization of water-soluble HEA and hydrophobic monomer ethyl acrylate (EA) in the presence of crosslinking agent N,NвЂ™-methylenebisacrylamide (BAA). The hydrogels with certain copolymer compositions showed thermo-sensitive behavior in aqueous solutions. The regularity of complex formation of cross-linked copolymer HEA-EA with anionic and cationic surface-active substances have been studied. The swelling behavior of the hydrogels in cetylpyridinium bromide aqueous solutions was studied. Increased swelling of the hydrogels was observed in the surfactant solutions. The increased swelling was more prominent for the hydrogels with a higher content of the hydrophobic moiety in the copolymer composition and with the higher surfactant concentration. The reason for the observed phenomenon is discussed.
Synthesis, characterization of mixed- ligand complexes containing 2,2-Bipyridine and 3-aminopropyltriethoxysilane

A mixed-ligand metal complexes with divalent ion Co, Ni and Cu containing 3-aminopropyltriethoxysilane(3-APTES) as a primary ligand and 2,2-bipyridine as a secondary ligand were prepared. The new complexes were characterized by, Molar conductance measurement, magnetic susceptibility, Uv-visible spectra (Uv-Vis), infrared spectroscopy (FT-IR), Nuclear magnetic resonance(1H-NMR), Thermogravimetric analysis (TGA-DTA) and atomic absorption spectroscopy(ASS). FT-IR and 1H-NMR spectra indicate that both ligands 3-APTES and 2,2-bipyridine are coordinated to the metal ions via nitrogen amino group in 3-APTES and nitrogen atoms for bpy. Molar conductance value for the complexes indicate that the complex are non-electrolyte. The TGA-DTA analysis shows that the degradation of complexes occurs between 200-593 °C. The complexes assume octahedral geometry in which the Co(II),Ni(II),Cu(II) have two molecules of 3-APTES and one molecule from 2,2-bipyridine in the coordination sphere.
Dificultades en la generación de inferencias causales en la lectura de textos narrativos en estudiantes de 4. grado de educación primaria

El presente artículo de investigación explora las dificultades que enfrentan los estudiantes de cuarto grado de primaria en la generación de inferencias causales en la lectura de textos narrativos, los cuales formaron parte de las evaluaciones estandarizadas aplicadas por el Ministerio de Educación del Perú (ECE 2016, ECE 2018 y EM 2019). El análisis se realiza sobre la base de la tasa de acierto y la dificultad del ítem, luego del procesamiento bajo el modelo probabilístico Rasch. El corpus del presente estudio lo conforman 12 ítems de opción múltiple (48 respuestas: 36 distractores y 12 respuestas correctas) queevaluaron la capacidad de inferir relaciones causales en la lectura de textos narrativos. Según la tasa de acierto de los ítems seleccionados, los estudiantes evidencian problemas para discriminar información causal en el texto, sobre todo cuando hay información en competencia. Esta dificultad tiene impacto en la comprensión global del texto. Además, cuando los estudiantes no encuentran X (la causa de la proposición focal) optan por buscar una pista textual (elemento causal) próxima o una pista muy notoria en el texto, y cuando no ocurre ello, activan sus conocimientos previos. Cuando esta activación es inadecuada, interfiere en la generación de inferencias porque la aleja del texto.
Subsidiarity, wicked problems and the matter of failing states

ABSTRACT In the political context, the tenet of subsidiarity states that societal tasks should be solved by subordinate entities in society if these entities have the competencies to solve such problems without governmental assistance. Transferred to the business context the tenet of subsidiarity describes the assignment of co-responsibilities to corporate actors in the process of corporate-governmental task sharing. However, in a recently published article Tempels, Blok, and Verweij [2017. “Understanding Political Responsibility in Corporate Citizenship: Towards a Shared Responsibility for the Common Good. ” Journal of Global Ethics 13 (1): 90–108. doi: 10.1080/17449626.2017. 1320577. ] doubt that subsidiarity might function as a governance principle for the corporate-governmental task-sharing especially in the context of wicked problems and in cases of failing nation-states. Wicked problems are typical in the social context since solving societal problems often requires efforts from various actors and does not allow for assigning responsibilities to clearly defined authorities, especially in cases where nation-states as guarantor of the political order fail to provide adequate political conditions for the subsidiary task-sharing in society. However, as we will outline in our contribution, a deeper analysis of the tenet of subsidiarity reveals that subsidiarity, at least partially, may function as a structuring principle for societal task-sharing even in the context of wicked problems and in the absence of a well-ordered nation-state since it allows for decentralized task-related decision-making.
Speculative Packet Dispatch for Virtual Output Queuing Architecture Using LSTM Recurrent Neural Network

Virtual Output Queuing (VOQ) is an architecture widely employed in modern networking products. Traffic from every ingress port is stored in a set of queues mirroring the structure of the egress ports. This architecture allows congestion on one egress port to be isolated from the other ports. A request-grant protocol is used to route packets from ingress to egress. When a packet is received, a request signal is issued. After the request reaches the egress side, a grant signal is generated based on some fixed threshold indicating there is space in the egress buffer to absorb the largest packet size dispatched from ingress. The buffer must be sized deep enough to accommodate in-flight traffic associated with a scenario where heavy congestion is found after the grant is issued. Awaiting a grant signal to arrive before dispatching packets incurs significant end-to-end latency. To alleviate this problem, a speculative packet dispatch approach (SPD) is proposed in which the request grant protocol is completely eliminated. Packets are dispatched speculatively from ingress to egress based on predictions that there is enough space in the egress buffer. This is achieved by incorporating an LSTM recurrent neural network as part of the VOQ controller. The LSTM is trained by time-series data sets generated from past observations on the queue occupancy. The experimental results show that SPD delivers excellent improvement on the system performance, reduces buffering requirements and preserves the property of VOQ.
Efficient disparity estimation from stereo images using hybrid-guided image filter

ABSTRACT Stereo vision process involves capturing the pictures from a camera of the same scene from at least two different locations and calculating the three-dimensional information. Conventionally, these two versions of snapshots are called left and right views which yield the depth information of an object upon relative comparison of its location in two views. Although the stereo image and its applications are becoming increasingly prevalent, there has been very limited research on disparity estimation from stereo images. Most of the existing techniques suffer from the gradient reversal artefacts issue. Therefore, to handle this issue, we have proposed a hybrid-guided image filter for improving the disparity estimation from stereo images. The hybrid filter utilizes the features of guided image filter and Bayesian non-local means with edge aware constraint. Maximum likelihood and local area homogeneity analysis are used to generate the guidance image for the proposed filter. To enhance the quality of disparity estimation from stereo images, segmentation is also done using the modified mean shift technique. Experimental results show that the proposed technique can efficiently estimate the depth maps over the available techniques. One-way ANOVA analysis on experimental results validates that the hybrid filter-based stereo matching outperforms consistently over the state-of-art approaches.
Characterization of 4.5 kV Charge-Balanced SiC MOSFETs

This work demonstrates a novel charge-balanced (CB) silicon carbide (SiC) MOSFET that boasts a specific on-resistance of 10 mΩ•cm2 at 4.5 kV breakdown voltage, surpassing the 1-D SiC unipolar limit. This is achieved through buried p-doped regions inside the drift layers, which are more easily scalable to higher voltages compared to the p-doped pillars used in super-junction (SJ) devices. Medium-voltage CB SiC MOSFETs with different p-doped bus widths and pitches have been fabricated and characterized in this work. The unique microstructure of these devices causes interesting macro-scale characteristics, such as distinctive steps in the capacitance–voltage curves and a turn-on voltage tail that reduces with increased temperature. The switching energy of the CB MOSFET is 92% lower than that of an IGBT at 150 °C. This paper presents and interprets these intriguing static and dynamic characteristics.
FRAGMENT-BASED LEAD COMPOUND DESIGN TO INHIBIT EBOLA VP35 THROUGH COMPUTATIONAL STUDIES

: Ebola virus (EBOV) is a virus that is classified under Filoviridae family as a pathogenic organism. On March 2016, World Health Organization (WHO) reported that 28.646 cases caused by EBOV. Thus, it is important to find the antiviral drug for this disease because it can create the epidemic around the world. EBOV VP35 is a potential drug target because it has the component of the viral RNA polymerase complex that will hamper the host interferon (IFN) production. In this research, about 6.662 fragments were obtained from ZINC15 Biogenic Database after the Rules of Three, and pharmacological properties parameters were applied. After that, these fragments were docked into the active side of EBOV VP35 using MOE 2014.09 software. The potential fragments from previous docking simulations were linked each other, resulting 91 ligands in the process. Furthermore, the docking simulation was conducted again and discovered the best three ligands that have lower Gibbs free binding energy than the standards. Moreover, the pharmacological prediction tests were also done to find the ligand with excellent molecular properties. The best three ligands from these tests were continued into molecular dynamics simulation. In the end, we conclude that the LEB 31 ligand can be the new drug candidate as EBOV VP35 inhibitor based on molecular docking, pharmacological prediction test, and molecular dynamic.
2D Graphitic Carbon Nitride for Energy Conversion and Storage

Graphitic carbon nitride (g‐C3N4) have attracted great attention in the field of energy conversion and storage due to its unique layered structure, tunable bandgap, metal‐free characteristic, high physicochemical stability, and easy accessibility. 2D g‐C3N4 nanosheets have the features of short charge/mass transfer path, abundant reactive sites and easy functionalization, which are beneficial to optimizing their performance in different fields. However, the reviews of the comprehensive applications of 2D g‐C3N4 for energy conversion and storage are rare. Herein, this review first introduces the physicochemical properties of bulk g‐C3N4 and g‐C3N4 nanosheets, and then summarizes the synthetic strategies of 2D g‐C3N4 nanosheets in detail, such as thermal oxidation etching, chemical exfoliation, ultrasonication‐assisted liquid phase exfoliation, chemical vapor deposition, and others. Emphasis is focused on the rational design and development of 2D g‐C3N4 nanosheets for the diversified applications in energy conversion and storage, including photocatalytic H2 evolution, CO2 reduction, electrocatalytic H2 evolution, O2 evolution, O2 reduction, alkali‐metal ion batteries, lithium‐metal batteries, lithium–sulfur batteries, metal‐air batteries, and supercapacitors. Finally, the current challenges and perspectives of 2D g‐C3N4 nanosheets for energy conversion and storage applications are discussed.
Negotiation Impasses: Types, Causes, and Resolutions

Although impasses are frequently experienced by negotiators, are featured in newspaper articles, and are reflected in online searches and can be costly, negotiation scholarship does not appear to consider them seriously as phenomena worth explaining. A review of negotiation tasks to study impasses reveals that they bias negotiators toward agreement. We systematically organize past findings on impasses and integrate them in the impasse type, cause, and resolution model (ITCR model). Our fundamental assumption is that a positive bargaining zone does not imply symmetric preferences for an agreement. One or both negotiators may prefer an impasse over an agreement despite a positive bargaining zone. We argue that it is beneficial for management research to distinguish between three impasse types: If both negotiators perceive benefit from an impasse, they are wanted; if one negotiator perceives benefits from an impasse, they are forced; and if both do not perceive benefits from the impasse, they are unwanted. We review structural (e.g., bargaining zone, communication channels), interpersonal (e.g., tough tactics, emotions), and intrapersonal (e.g., biases, available information, and framing) factors as the likely antecedents of the three impasse types. We also examine evidence that suggests that wanted impasses can be resolved by changing the negotiation structure for both parties, forced impasses can be resolved through persuasion, and unwanted impasses can be overcome by debiasing both parties. Finally, we review current methodological guidance and provide updated recommendations on how scholars should deal with impasses in both study designs and data analyses.
Modeling behavioral intention toward traveling in times of a health-related crisis

This study proposes an integrated model based on the Risk Perception Attitude (RPA) framework and the Theory of Planned Behavior (TPB) model to investigate behavioral intention toward traveling in times of a health-related crisis. A survey was conducted via online networks of travelers, yielding 338 valid cases. The findings indicate that health risk perception is affected by information search about the Covid-19 disease. The relationship between health risk perception and behavioral intention toward traveling during a health-related crisis is not direct, but indirect via health self-efficacy and attitude about their future trip. The study contributes to understand a cognitive process of tourists’ behavior intention toward traveling in a health-related crisis. Practically, this study’s findings provide tourists, government agencies, tourism marketers, and policy-makers and other tourism stakeholders with important suggestions for tourism recovery during and after the pandemic.