Miracle-dz/UniFAR-FTUs huggingface dataset:
Solid-State Transformer-Based DC Power Distribution Network for Shipboard Applications

Due to simplicity, efficiency, and the ability to accommodate energy storage devices, DC distribution networks have been seen as an optimal alternative to AC distribution networks, especially aboard future electric ships. The emerging distribution DC system entails new control and management techniques. Therefore, an integrated DC power distribution network aboard an electric ship is selected as the case study in this paper. To meet the requirements of such a large-scale mobile power system, a multiport solid-state transformer (SST) based on silicon carbide (SiC) switches/MOSFETs is proposed. Thus, the system embodiment can significantly be reduced. Moreover, at the DC distribution level, a high penetration of renewable generation with energy storage is allowed and a six-phase asymmetrical induction machine (IM) can directly be integrated. Simulations have been conducted based on a 2 MW shipboard distribution network. The effects of the propulsion system dynamics on the SST are highlighted as well. Finally, a 2 kW lab-scale prototype has been implemented to validate the theoretical findings.
Optimizing the best play in basketball using deep learning

In a close game of basketball, victory or defeat can depend on a single shot. Being able to identify the best player and play scenario for a given opponent’s defense can increase the likelihood of victory. Progress in technology has resulted in an increase in the popularity of sports analytics over the last two decades, where data can be used by teams and individuals to their advantage. A popular data analytic technique in sports is deep learning. Deep learning is a branch of machine learning that finds patterns within big data and can predict future decisions. The process relies on a raw dataset for training purposes. It can be utilized in sports by using deep learning to read the data and provide a better understanding of where players can be the most successful. In this study the data used were on division I women’s basketball games of a private university in a conference featuring top 25 teams. Deep learning was applied to optimize the best offensive play in a game scenario for a given set of features. The system is used to predict the play that would lead to the highest probability of a made shot.
Production of Polyhydroxyalkanoate by Local Strain of Bacillus megaterium AUMC b 272 Utilizing Sugar Beet Wastewater and Molasses

Development of polyhydroxyalkanoates (PHAs) as a potential substitute material to some conventional plastics has drawn much attention due to their biodegradable and compatible properties. The potential applications of PHA in various industries and in the medical field are encouraging. Nevertheless, the production cost of PHA has been a major drawback. Consequently, scientific effort have been made to overcome the high cost of the substrates used in the bio-production. In this study, sugar beet industry wastewater without and with beet molasses was used as potential low cost substrate for production of the biopolymer PHA by a local bacterial strain. This strain was selected after screening of 30 bacterial isolates for PHA production and was identified according to 16S rRNA gene sequencing as Bacillus megaterium AUMC b 272. The maximum PHA formed by this strain reached to 4.053 g/L with a recovery yield equal to 41.79 % of the bacterial biomass using modified mineral salt medium (MSM) medium containing 6 % beet molasses as sole carbon source and 0.5 g/L ammonium oxalate as a nitrogen source. The initial pH of the medium was adjusted at 8.5. Cultures were incubated at 200 rpm and 37o C for 24 hrs. On the other hand, the bacterial strain produced negligible levels of PHA when grown on the same medium constituents under the same conditions with replaced distilled water and molasses by sugar beet wastewater. While the PHA concentration reached to 0.828 g/L with 46 Zohri A. A. et al (2019) Egyptian Sugar Journal, . Vol.13 ــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ recovery yield 20.58 % of biomass in the same medium under the same conditions after replacement of distilled water by sugar beet wastewater. It is worthy to mention that the COD in the sugar beet wastewater medium at the end of fermentation period was removed by 69 %. Characterization of the obtained PHA was achieved using Fourier transform-infra-red spectroscopy (FT-IR) and gas chromatograph mass spectrometric (GCMS). Accumulation of considerable levels of PHA as well as high levels of COD removal from sugar beet wastewater strongly introduced this biotechnological process as valuable method for production of PHA as biodegradable biopolymer from sugar beet industry wastewater in presence of beet molasses as potential low cost substrates and, at the same time, for biological treatment of industry wastewater.
Bayesian-based joint determination of earthquake hypocenters and 1-D velocity structures divided by a structural boundary

We propose a Bayesian approach for jointly determining the locations of earthquake hypocenters and velocity structures in a region divided by a structural boundary, such as a fault zone. To accommodate the Markov chain Monte Carlo (MCMC) method in a region containing lateral velocity contrast, we incorporated a data-driven station clustering scheme when estimating earthquake hypocenter locations, a one-dimensional (1-D) velocity model assigned to each cluster, and station corrections for travel times. The proposed method realises the clustering of stations reflecting velocity structures beneath the station network in the framework of the MCMC method. We verified the performances of the proposed method using numerical experiments with different distributions of earthquake hypocenters relative to the structural boundary. The results demonstrated that the proposed method reconstructed earthquake hypocenter locations and velocity structures involving lateral contrast robustly to earthquake distributions. Additionally, the number of 1-D velocity models (the number of station clusters) was optimised by comparing resultant posterior probability proportional to distances between the observed and theoretical travel times. We also applied the proposed method to estimate the earthquake hypocenter locations and velocity structures around the source area of the 2004 Mid-Niigata prefecture earthquake, Japan, to examine the applicability of the proposed method to real observation data. The stations were divided into east and west clusters, coinciding with the lateral velocity variation related to the geological setting. Therefore, the proposed method accurately determines earthquake hypocenters in a region divided by a structural boundary without any knowledge regarding the geological structure.
Case Study of Energy Efficiency in Massive MIMO System

By using large-scale antenna arrays, considerable enhancement in energy and spectral efficiency is accomplished. What will be the optimum number of antennas, active users and transmit power? In single cell consequence Zero Forcing (ZF) processing is used to know how the constraints interact. A conjoint belief is transmitter power is enlarged with large number of antennas that means EE-systems can operate in high Signal to noise ratio systems where interference-suppressing signal processing is mandatory. Systematic and arithmetical results show that, Massive MIMO is the solution to get maximum energy efficiency. A combination of Massive MIMO and Small cell access point is also anticipated to increase the energy proficiency at the UEs, without losing the Quality of Service (QoS). If latter are operator positioned, a spatial soft cell tactic can be used at the multiple transmitters to oblige the users by non-coherent beam forming, overall power ingestion can be
Robotic Automation Technologies in Construction: A Review

Robot technology is a remarkably interdisciplinary research area, one that can be employed in various industrial fields as well as higher value-added fields. The construction industry, on the other hand, has been known as one of the most difficult research fields to apply robotic schemes. Therefore, applying robot technologies in the construction industry is quite a challenging topic. This paper aims to introduce the progress of automated robotic systems in construction fields, namely with respect to construction robots. While construction robots have a very wide range of application depending on the huge market size of the construction industry, there still exist a lot of problems such as highly risky working environment and inefficiency due to the labor intensive characteristic. In order to solve these problems, a variety of construction robots have been developed and, in this paper, the current state of the robotic systems for construction works and the vision of future robot technology in the construction field are introduced.
System Dynamics Model for Systematic Evaluation of China’s Financial Risk

Finance is becoming more important in the national economy. Maintaining financial stability is critical not only for the financial industry’s prosperity and development, but also for a country’s political, economic, and social development. This paper will look at the mechanisms that cause systemic risk to develop and evolve, as well as how to measure systemic financial risk in multiple dimensions. To begin, create a system for evaluating financial risk in a systematic manner. Second, using the AHP and CRITIC methods to determine various indicators and market weights, create a systemic financial risk evaluation model based on the system dynamics model, and calculate the system from 2010 to 2019 comprehensive financial risk index. Finally, simulation research is conducted using the system dynamics model of systemic financial risk, and the simulation results are analyzed. The findings show that China’s financial risk has been gradually increasing since 2016, with relatively small fluctuations in risk state.
The Franson Experiment as an Example of Spontaneous Breaking of Time-Translation Symmetry

We describe an explicit statistical model of local hidden variables that reproduces the predictions of quantum mechanics for the ideal Franson experiment and sheds light on the physical mechanisms that might be involved in the actual experiment. The crux of our model is the spontaneous breaking of time-translation gauge symmetry by the hidden configurations of the pairs of photons locked in time and energy involved in the experiment, which acquire a non-zero geometric phase through certain cyclic transformations.
High positioning repeatability of miniature actuator

Autofocusing actuators in camera phones should have a reduced profile and an improved performance in accordance with the requirements of consumer electronic products. In this study, we first discuss the detailed design of the miniature actuator presented in our previous work(10) and then describe an experiment to test its positioning repeatability. As compared with conventional voice coil motor (VCM) actuators positioned by open-loop control, the proposed miniature VCM actuator is small, has a high positioning repeatability and can improve the positioning repeatability by 87.5% of the typical value.
Regulation Mechanism of ssDNA Aptamer in Nanozymes and Application of Nanozyme-Based Aptasensors in Food Safety

Food safety issues are a worldwide concern. Pathogens, toxins, pesticides, veterinary drugs, heavy metals, and illegal additives are frequently reported to contaminate food and pose a serious threat to human health. Conventional detection methods have difficulties fulfilling the requirements for food development in a modern society. Therefore, novel rapid detection methods are urgently needed for on-site and rapid screening of massive food samples. Due to the extraordinary properties of nanozymes and aptamers, biosensors composed of both of them provide considerable advantages in analytical performances, including sensitivity, specificity, repeatability, and accuracy. They are considered a promising complementary detection method on top of conventional ones for the rapid and accurate detection of food contaminants. In recent years, we have witnessed a flourishing of analytical strategies based on aptamers and nanozymes for the detection of food contaminants, especially novel detection models based on the regulation by single-stranded DNA (ssDNA) of nanozyme activity. However, the applications of nanozyme-based aptasensors in food safety are seldom reviewed. Thus, this paper aims to provide a comprehensive review on nanozyme-based aptasensors in food safety, which are arranged according to the different interaction modes of ssDNA and nanozymes: aptasensors based on nanozyme activity either inhibited or enhanced by ssDNA, nanozymes as signal tags, and other methods. Before introducing the nanozyme-based aptasensors, the regulation by ssDNA of nanozyme activity via diverse factors is discussed systematically for precisely tailoring nanozyme activity in biosensors. Furthermore, current challenges are emphasized, and future perspectives are discussed.
IMGG: Integrating Multiple Single-Cell Datasets through Connected Graphs and Generative Adversarial Networks

There is a strong need to eliminate batch-specific differences when integrating single-cell RNA-sequencing (scRNA-seq) datasets generated under different experimental conditions for downstream task analysis. Existing batch correction methods usually transform different batches of cells into one preselected “anchor” batch or a low-dimensional embedding space, and cannot take full advantage of useful information from multiple sources. We present a novel framework, called IMGG, i.e., integrating multiple single-cell datasets through connected graphs and generative adversarial networks (GAN) to eliminate nonbiological differences between different batches. Compared with current methods, IMGG shows excellent performance on a variety of evaluation metrics, and the IMGG-corrected gene expression data incorporate features from multiple batches, allowing for downstream tasks such as differential gene expression analysis.
nth order current mode leapfrog-type filter design based on CCCII

It is presented a method of the nth order current mode leapfrog-type filter based on CCCII(second generation current controlled conveyor). By defining the transfer function H(s)(Io(j)/Iin) from the filter input to the output of integrator,the corresponding transfer function H(s) of the all-pole filters and filters with arbitrary transmission zeros can be derived.Parameter values of the designed filter can be obtained from the coefficient matching equations based on the comparison between the numerator and denominator polynomials coefficients of H(s) and the given Hd(s). Parameter values of the designed filter can be computed easily.As an example,it is also maked design of parameter values and PSPICE simulation for the realization of the fourth-order Butterworth low-pass leapfrog-type filter.
Improvements in ultra‐light and flexible epitaxial lift‐off GaInP/GaAs/GaInAs solar cells for space applications

A thin, lightweight, flexible solar cell is developed that maximizes the power‐to‐mass ratio under AM0 illumination and has a competitive efficiency after typical high energy electron irradiation. The inverted metamorphic triple junction (IMM3J) solar cells with Ga0.51In0. 49P/GaAs/Ga0.73In0. 27As subcells are grown on GaAs substrates and have a total epitaxy thickness of about 10 μm. After epitaxial growth, the inverted layer stack is metallized, with the metal serving as back‐contact, back reflector and support layer for the ultra‐thin solar cells before the GaAs substrate is separated by an epitaxial lift‐off (ELO) process. The nondestructive nature of the ELO process makes multiple reuses of the GaAs substrate possible. The solar cell structure is optimized for maximum EOL efficiency, that is, after 1‐MeV electron irradiation with a fluence of 1 × 1015 cm−2, by means of simulations that include the irradiation induced defects in the various semiconductor alloys. Assuming realistic charge carrier lifetime in the materials, we predict a near‐term efficiency potential for the IMM3J ELO of 30.9% under AM0 illumination before and 26.7% after irradiation. Several IMM3J ELO solar cells with an area of approximately 20 cm2 from different development stages were tested under AM0 illumination. The newest solar cells (generation III) with a mass density of only 13.2 mg/cm2 reach conversion efficiencies of 30.2% at 25°C. The resulting power‐to‐mass ratio of 3.0 W/g for the bare solar cell is one of the highest published ratios. After irradiation, a conversion efficiency of 25.4% was measured for “generation II” devices under AM0 illumination, which corresponds to a power‐to‐mass ratio of 2.6 W/g. IMM3J ELO solar cells from “generation I” were also tested for mechanical stability as “de‐risking” test of this new cell technology. No degradation of the cell performance was found after dipping the cell in liquid N2 and then heating up to 25°C for five times, despite of strong deformation of the flexible cell during the temperature cycle.
Unpacking the Criminogenic Aspects of Stress Over the Life Course: The Joint Effects of Proximal Strain and Childhood Abuse on Violence and Substance Use in a High-Risk Sample of Women

Purpose: Drawing on concepts from strain, feminist, and life-course perspectives, we investigate the proximal effects of strain on violence and serious drug use along with the distal “carryover” effects of childhood abuse among women. Methods: Using 36 months of retrospective data collected from 778 incarcerated women, we estimate monthly within-person effects of four types of strain experienced in adulthood (i.e., negative life events and three forms of victimization) on respondent-initiated violence and serious drug use. Cross-level interactions assess the moderating “carryover” effects of childhood abuse and cumulative adversity. Results: Negative life events increased women's initiation of violence and serious drug use. Having a near violent experience was positively associated with violence, while violent conflict increased drug use. Experiencing both childhood physical and sexual abuse accentuated the effect of predatory victimization on violence, and physical victimization amplified the positive relationship between near violence and drug use. Unexpectedly, women who experienced childhood sexual abuse were less likely to use drugs after experiencing strain. The accumulation of adversity among abused women could not account for these moderating effects. Conclusion: Findings suggest women's recent life experiences can explain offending in the foreground, while childhood abuse can account for some within-sex heterogeneity in these relationships.
Employee mindfulness and creativity: when emotions and national culture matter

ABSTRACT Mindfulness has recently attracted more attention from service scholars due to its positive effect on various job outcomes. Yet, the linkage between mindfulness and service employees’ creativity is still not well understood. This study aims to bridge this gap by examining how emotions might influence the mindfulness and creativity relationship from different cultural perspectives. Frontline service employees from three countries, the Philippines, Turkey, and the United States, were sampled to form a cross-border dataset. PLS multigroup results show that creativity positively influences service recovery performance and error reporting across the three nations. Furthermore, the mindfulness-creativity link is mediated by gratitude as a positive emotion in the United States, but by envy as a negative emotion in the Philippines and Turkey. This suggests that the link between mindfulness and creativity may be culturally contextual. These results might provide insights for mindfulness practices within the service work environment.
Informing Parents as Caregivers With a Symptom Assessment App Developed for Children With Cancer

Background: Mobile health technologies can assist children to communicate their symptom experiences in a developmentally appropriate format. However, few investigations have examined how mHealth resources may also assist parents in their caregiver role. The purpose of this study was to explore how a symptom assessment app designed for school-age children with cancer could further inform parents as caregivers. Methods: Nineteen parents (18 mothers; median 35 years old, range 26–48 years) of children (6–12 years of age) receiving cancer treatment participated in the feasibility/acceptability trial of a game-based symptom assessment app. Acceptability interviews with parents were completed after each child’s trial with the app. We completed a secondary analysis of the parent interviews using thematic analysis to examine how the app could support parents in their caregiving role. Results: Parents perceived the app to (1) elicit the child’s voice about his/her symptom experience; (2) provide a supportive and safe environment for the child to report symptoms; and (3) create an opportunity to facilitate communication between the child, parent, and clinical team. Parents expressed a willingness for their child to represent his/her experience with the app so that they could make informed decisions regarding symptom care. Discussion: Perceived benefits of the app extended to parents as they described developing further insight into their child’s cancer experience. The knowledge gained allowed parents the potential to enhance symptom communication and supportive care strategies. Future research should further evaluate how mHealth tools facilitate shared symptom management between children receiving treatment for cancer and their caregivers.
Analysis of the upper limit accuracy of an imaging radar altimeter from satellite formation

The ocean surface topography usually varies only a few centimeters among hundreds of kilometers spatially, therefore, the altimetric accuracy of an Imaging Radar Altimeter (IRA) needs to be on centimeter-level for ocean altimetry. The baseline of an IRA from satellite formation is flexible, which can reach to thousands of meters while maintain higher stability than an IRA from single platform. The large baseline can increase the altimetric accuracy with great potential, however, the signal decorrelation deteriorates as well as the baseline increases, prevents the accuracy from further being improved as the baseline reaches to a certain length. The baseline decorrelation can be compensated by a carrier frequency shift, however still left the volumetric decorrelation associated to wave height variation deteriorates with the increasing baseline. In this paper, the upper limit accuracy of an IRA system determined by the wave volumetric decorrelation was deduced, the parameters of the IRA system were optimized accordingly. The simulation results indicates that the altimetric accuracy of the proposed IRA system can reach to sub-centimeter level on a 1km resolution gird, with the baseline length ranges from 650~1000m.