Miracle-dz/UniFAR-FTUs huggingface dataset:
W5+–W5+ Pair Induced LSPR of W18O49 to Sensitize ZnIn2S4 for Full‐Spectrum Solar‐Light‐Driven Photocatalytic Hydrogen Evolution

The localized surface plasmon resonances (LSPR) effect makes W18O49 an effective visible and near‐infrared (NIR) light antenna to realize full‐spectrum solar‐light driven photocatalysis, yet the precise origin remains elusive. Here, the LSPR originates from the localized electron confinement around lattice W5+–W5+ pairs in the unique structure of W18O49 by density‐functional theory calculation, which gives W18O49 a broad absorption ranging from visible to NIR region, independent of the particle shape and size is confirmed. This unique periodic LSPR simplifies the design of W18O49‐sensitized photocatalytic composite into enhancing the light absorbance of W18O49 and screening photocatalytic semiconductors with suitable energy band potentials. To this end, hierarchical‐structure W18O49 microflowers with high absorbance have been coated with ZnIn2S4 nanosheets to achieve cocatalyst‐free photocatalytic composite, which presents an outstanding H2 production rate of 902.57 µmol within 3 h under simulated solar‐light. Comprehensive characterizations, including ultrafast transient absorption spectroscopy, prove the injection of hot electrons from W18O49 to ZnIn2S4 and the increase of long‐lived active electrons. This work clarifies the LSPR origin of oxygen‐deficient semiconductors and paves the way for the search of broad‐spectrum active photocatalyst.
Efficient Cable Path Optimization Based on Critical Robot Poses for Industrial Robot Arms

Although industrial robotic arms are equipped with external cables to supply electricity, gases or other materials, cable path design is a difficult and demanding task. Herein, an efficient optimization method is proposed for automating cable path design under the assumption that the robot motion path is known. The contribution of this study was to reduce the considerable computation time required for the optimization, which was a concern in our previous work. The previous method represented candidates for cable paths as a set of parameter vectors (PVs) that included cable length and guide configurations, and then selected the optimal PV that satisfies stress constraints and provided the shortest cable path. The proposed method extracted critical poses, i.e., several static robot poses that are prone to applying stress to the cable, from the joint angle time series of the motion path, and then performed attachment and motion tests. The cable geometry for the static critical poses was simulated in the attachment test, while the geometry for dynamic robot motion was simulated in the motion test in an ascending order of the cable length among the PV candidates. Experimental results showed that the computation time for cable path optimization could be significantly reduced.
PPMuSA: PROSITE-Pattern Matcher Using Su-x Array

PPMuSA is a pattern matching program for PROSITE [2] signature patterns against amino acid sequence database. To characterize a group of protein among others, it is important work to find occurrences of a signature in an amino acid sequence of the protein. Such signatures are compiled in databases. The PROSITE is one of the databases of signatures that distinguish members of a protein families or domains from other unrelated proteins. In the PROSITE, the signature is described in several forms. One of the forms is a “pattern” that is a motif description based on a regular expressionlike syntax. For instance, the signature pattern is described in a form such as [AC]-x-V-x(4)-{ED}; or <A-x-[ST](2)-x(0,1)-v. These patterns would be interpreted as [Ala or Cys]-any-Val-any-any-any-any{any but Glu or Asp}; and Nterm-Ala-any-[Ser or Thr]-[Ser or Thr]-(any or none)-Val, respectively. ScanProsite [1] is a reference implementation of a PROSITE scanning tool that can take a pattern of the form as the input and report occurrences of the pattern in amino acid sequences. ScanProsite uses a sequential algorithm as opposed to the indexed one. PPMuSA uses prebuilt suffix array [3] indices on the amino acid sequences in order to achieve a fast pattern matching. The suffix array is a data structure for the information retrieval, and is made of an array of the indices of the suffixes obtained by sorting all suffixes of the text. In the case of string retrieval using suffix array, the time complexity is O(m · log n), (O(m+log n) when auxiliary data structure is used), where m is the length of a pattern string and n is the length of the text. PPMuSA takes a pattern of the form as the input, and reports all the occurrences of the pattern in amino acid sequence database.
Uncertainty Modeling for Participation of Electric Vehicles in Collaborative Energy Consumption

This paper proposes an accurate and efficient probabilistic method for modeling the nonlinear and complex uncertainty effects and mainly focuses on the Electric Vehicle (EV) uncertainty in Peer-to-Peer (P2P) trading. The proposed method captures the uncertainty of the input parameters with a low computational burden and regardless of the probability density function (PDF) shape. To this end, for each uncertain parameter, multitude of random vectors with the specification of corresponding uncertain parameters are generated and a fuzzy membership function is then assigned to each vector. Since the most probable samples occur repeatedly, they are recognized by the superposition of the generated fuzzy membership functions. The simulation results on various case studies indicate the high accuracy of the proposed method in comparison with Monte-Carlo simulation (MCs), Unscented Transformation (UT), and Point Estimate Method (PEM). It also scales down the computational burden compared to MCs. Also, a real-world case study is employed to examine the ability of the method in capturing the uncertainty of EVs’ arrival and departure time. The studies on this case reveal that involving EVs in P2P trading augments the amount of energy traded within the prosumers.
A New Approach Towards Ensuring Gender Inclusive SE Job Advertisements

A majority of software engineers are male, perhaps, because of the very way that software engineering (SE) roles are advertised is gender biased. Thus far, only word-based checking tools are available to identify gender biases (e.g., “analyst” is considered a masculine word). However, such word-based analyses end up identifying the skills required for SE job positions as masculine words, and therefore, not sufficient. In this work, we present a more nu-anced mechanism to check for gender bias in SE job advertisements by building on the GenderMag method, which has proven to be successful in gender bias detection in software interfaces. From a survey of 44 software practitioners, we identified 16 factors where male and female participants differ and based on a thematic analysis we derived three SE job applicant persona facets. We verified the facets with a small survey where SE candidates related to the descriptions of those factors. We conducted a pilot study using these facets to evaluate four SE job advertisements and identified gender related biases in two of those. The software engineering (SE) workforce is dominated by male employees. This is potentially because SE job advertisements are gender biased toward men. SE job advertisements are often checked for potential gender bias using word-based bias detection tools. However, these do not take software engineering specific words into consideration. For example the word’ analyst’ is considered male using the word-based tools, and therefore any SE analyst position would be seen (incorrectly) to be biased toward men. As a result, such word-based tools are not good enough to accurately assess for gender bias in SE job ads. We present a more nuanced mechanism to check for gender bias in SE job advertisements by building on the GenderMag method. GenderMag has proven to be successful in gender bias detection in software interfaces. This method identifies five dimensions of problem solving (referred to as facets) on which male and female software users differ. From a survey of software practitioners, we identified factors where male and female SE job applicants differ. We grouped the similar factors together and derived three facets that were important to predict job application behaviour of SE job applicants. We validated these facets with some SE candidates and used them to develop ‘new’ Tim and Abi personas from the facets and evaluated four SE job advertisements. We identified gender related biases in two of these.
A Unified Model for Bi-objective Online Stochastic Bipartite Matching with Two-sided Limited Patience

Bi-objective online stochastic bipartite matching can capture a wide range of real-world problems such as online ride-hailing, crowdsourcing markets, and internet adverting, where the vertices in the left side are known in advance and that in the right side arrive from a known identical independent distribution (KIID) in an online manner. Mutual interest and limited attention-span are two common conditions and can be modeled as the edge existence probability and two-sided limited patience. Existing works fail to take them into bi-objective online optimization. This paper establishes a unified model for bi-objective online stochastic bipartite matching that can provide a general tradeoff among the matched edges (OBJ-1) and vertices (OBJ-2). We formulate two linear programs (LP) and accordingly design four LP-based parameterized online algorithms to tradeoff OBJ-1 and OBJ-2, with the best competitive ratio of (0.3528α, 0.3528β), where α, β are two positive input parameters and α + β = 1. Our hardness analysis proves that any non-adaptive algorithm cannot achieve (δ1, δ2)-competitive such that ${\delta _1} + {\delta _2} > 1 - \frac{1}{e}$. Trace-driven experiments show that our algorithms can always achieve better performance and provide a flexible tradeoff.
The Metabolic Syndrome in Survivors of Acute Lymphoblastic Leukemia of Pediatrics Patients at Zagazig University Hospitals

Background: Insulin resistance is considered to be of the major causes of the metabolic syndrome. There is a growing body of evidence showing that treatment for Acute Lymphoblastic Leukemia (ALL) has side effects. Objective: The aim of the current work was to detect the prevalence of metabolic syndrome in survivors of childhood ALL to determine the relationship between metabolic syndrome and growth parameters in ALL survivors. Patients and methods: This cross-sectional study included a total of twenty-four ALL survivors, attending at Pediatrics Hematology and Oncology Unit, Faculty of Medicine, Zagazig University Hospitals. Full clinical examination as well as laboratory investigations including estimation of serum insulin, total cholesterol, triglycerides, HDLc, LDLc, fasting plasma glucose were done for all patients. Results: Obesity was significantly higher among metabolic syndrome (MS) cases. Patients with metabolic syndrome in ALL showed greater systolic and diastolic blood pressure than those without metabolic syndrome. It was found that children with metabolic syndrome had higher fasting plasma insulin levels and fasting plasma glucose levels than those without the syndrome. ALL patients who had metabolic syndrome had higher triglyceride levels than those without MS. Conclusion: It could be concluded that ALL survivors are at an elevated risk for metabolic syndrome, as the increased risk for obesity and disturbed lipid profile in those patients.
Structure & Properties of HVOF Sprayed NiCrBSi Coatings

NiCrBSi spray and fuse types of coatings are routinely applied on various jobs where metallurgical bond of the coating to the substrate is desired. These coatings require a subsequent fusing operation at temperature of about 1050°C. In the present study NiCrBSi coatings were formed by the HVOF process and by the conventional spray and fuse route. The coatings were characterized for their microstructure, hardness and porosity. The aim of this study was to see whether HVOF spraying NiCrBSi spray and fuse powder could cause instant fusing of the coating without the need for additional fusing operation. XRD study of the coatings was also carried out to find out the difference between the spray and fused NiCrBSi coatings and the HVOF sprayed coatings. The HVOF spraying of NiCrBSi was carried under different set of parameters to determine the effect of spraying parameters on the properties of coating.
Deep Neural Network Approach Based Segmentation, Detection and Classification of Brain Tumor

The segmentation, detection and extraction of malignant tumor regions from magnetic resonance (MR) images are challenging tasks in medical image analysis. Approaches based on machine and deep learning have been introduced, which performed better than traditional image processing methods. However, many approaches still show limited ability due to the complex dataset and image modalities. This study evaluated the deep learning approach's performance and traditional image processing algorithms for medical imaging segmentation, detection, and classification. The proposed system comprises multiple stages. The Median filters are used in the pre-processing step, and morphological operation and Otsu thresholding are used to segment MR images. Discrete Wavelet Transform (DWT) algorithm is considered in the extraction features, and their classification is executed by a convolutional neural network (CNN) and support vector machine (SVM) algorithms. The Mat lab has been used for simulation and experimental findings to evaluate the suggested method's performance on the brain's complex and highly 2D structures. The results show that the methodology is reliable and efficient, with 93.5% accuracy.
Integration of Inertial Sensors in a Lower Limb Robotic Exoskeleton

Motion assistance exoskeletons are designed to support the joint movement of people who perform repetitive tasks that cause damage to their health. To guarantee motion accompaniment, the integration between sensors and actuators should ensure a near-zero delay between the signal acquisition and the actuator response. This study presents the integration of a platform based on Imocap-GIS inertial sensors, with a motion assistance exoskeleton that generates joint movement by means of Maxon motors and Harmonic drive reducers, where a near zero-lag is required for the gait accompaniment to be correct. The Imocap-GIS sensors acquire positional data from the user’s lower limbs and send the information through the UDP protocol to the CompactRio system, which constitutes a high-performance controller. These data are processed by the card and subsequently a control signal is sent to the motors that move the exoskeleton joints. Simulations of the proposed controller performance were conducted. The experimental results show that the motion accompaniment exhibits a delay of between 20 and 30 ms, and consequently, it may be stated that the integration between the exoskeleton and the sensors achieves a high efficiency. In this work, the integration between inertial sensors and an exoskeleton prototype has been proposed, where it is evident that the integration met the initial objective. In addition, the integration between the exoskeleton and IMOCAP is among the highest efficiency ranges of similar systems that are currently being developed, and the response lag that was obtained could be improved by means of the incorporation of complementary systems.
A Symmetric Switched-Capacitor-Based Basic Inverter Unit for Grid-Connected PV Systems

In this article, a new inverter unit is proposed. It is a compact switched-capacitor-based inverter, which is combined of four switches, two diodes, and four capacitors. Since this inverter unit is a mid-point-clamped inverter, it can mitigate the capacitive leakage current in many applications. One of the main applications of the proposed inverter is in grid-tied photovoltaic systems, where the common-mode current brings many challenges. Other than the mentioned feature, the proposed inverter includes the following advantages: 1) spontaneous balancing of the voltage across the capacitors without needing any control system or auxiliary circuits; 2) capability of full reactive power transfer; 3) low voltage stress on the capacitors compared to common three-level inverter topologies (NPC, T-type-NPC, FC, etc.); and 4) symmetric switching sequence, which causes a continuous input current. The feasibility and versatility of the proposed inverter unit is validated by experimental tests, which are conducted by using a lab-scale prototype.
Evaluation and Hydrological Application of Four Gridded Precipitation Datasets over a Large Southeastern Tibetan Plateau Basin

Reliable precipitation is crucial for hydrological studies over Tibetan Plateau (TP) basins with sparsely distributed rainfall gauges. In this study, four widely used precipitation products, including the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE), the High Asia Reanalysis (HAR), and the satellite-based precipitation estimates from Global Precipitation Measurement (GPM) and Tropical Rainfall Measurement Mission (TRMM), were comprehensively evaluated by combining statistical analysis and hydrological simulation over the Upper Brahmaputra (UB) River Basin of TP during 2001–2013. In respect to the statistical assessment, the overall performances of GPM and HAR are comparable to each other, and both are superior to the other two datasets. For hydrological assessment, both daily and monthly GPM-based streamflow simulations perform the best not only at the UB outlet with very good results, but they also illustrate satisfactory results at Yangcun and Lhasa hydrological stations within the UB. Runoff simulation using HAR only performs well at the UB outlet, whereas it shows poor results at both Yangcun and Lhasa stations. The simulated results based on APHRODITE and TRMM show poor performances at UB. Generally, the GPM shows an encouraging potential for hydro-meteorological investigation over UB, although with some bias in flood simulation.
Cultural Change Shapes the Sustainable Development of Religious Ecotourism Villages in Bali, Indonesia

This research aims to determine the impact of technology, commitment, and cultural change on the sustainable development of religious ecotourism villages. This study utilized quantitative research methods. The sampling technique used was random sampling, determined by the slovin formula—data collection techniques through the distribution of questionnaires and measurement using a Likert scale. The study was done in an ecotourism village in Bali Province with a population of 155 individuals, and the sample size was 100. The Structural Equation Model using WarpPLS 5.0 software modelling was used for the statistical analysis. The results demonstrate that the technology and commitment variables have no significant effect on the development of religious ecotourism villages; however, cultural changes have a substantial effect. The development of religious ecotourism villages is the dependent variable in this study; nevertheless, the research is primarily focused on how each village develops its ecotourism, which is increasingly being activated through a religious by the government. Religion, often known as a religious tradition, has a particular role in preserving and sustaining a village’s ancient legacy. The application of the concept of religion in Bali strengthens the joints of Balinese cultural life. Ecotourism villages with religious values pay attention to surrounding customs to maintain and preserve ancestral heritage.
9022 Technology , Market Structure and the Gains from Trade

We study the gains from trade in a model with oligopolistic competition, heterogeneous firms and innovation, and provide a formula to decompose the mechanism. The new insight we provide is that market concentration can be a welfare-relevant feature of market power above and beyond markup dispersion. Trade liberalisation increases foreign competition and reduces the number of active firms in the market, thereby increasing concentration. A more concentrated economy is more efficient due to increasing returns in production. Moreover, higher concentration produces a scale effect on firms’ incentives to innovate, which increases welfare via productivity improvements. In the calibrated version of the model we show that a trade-induced increase in concentration contributes substantially to the gains from trade, mostly via its stimulating effect on innovation. Sizeable gains also come from the reduction of the inefficiency produced by trade in identical goods; i.e. through a reduction in reciprocal dumping. Changes in markup dispersion, in contrast, have only negligible effects. JEL-Codes: F120, F130, O310, O410.
AI-driven Service-aware Real-time Slicing for beyond 5G Networks

Wide network softwarization is creating fertile ground for the application of novel concepts in the management of the deployed network functions. This allows a drastic shift for the applications hosted on top of the network, as instead of configuring their behaviour to match the network status (network-aware applications) the technology can shift to a self-organizing network that adapts to the hosted applications (service-aware network). In this work, we design, develop and evaluate such a service-aware approach for the telecommunications network. By employing Machine Learning, we are able to classify and predict traffic exchanges made over the network, and appropriately dynamically allocate the slices in the network in real-time. We use as a reference platform the OpenAirInterface framework, and the FlexRAN controller for programming the slice decisions at the RAN level, and evaluate our scheme under real-world settings in a testbed environment.
Prognostic Significance of Acid Base Disturbances among Patients with Acute Aluminum Phosphide Poisoning

Background: Aluminum phosphide (ALP) is used to protect stored grains from rodents & pests. ALP poisoning is considered one of the significant public health problems which could occur accidentally, suicidal, or even occupational. The main presentations of acute ALP poisoning are gastrointestinal symptoms, profound circulatory collapse, arrhythmia, and electrolyte & acid-base disturbances. Objectives: The current study evaluated acid-base disturbances on admission as a simple outcome predictor in acute ALP poisoned patients. Patients & methods: 100 adult patients with acute ALP poisoning were included in this study. Patients with cardiovascular, chronic renal and liver diseases were excluded. Additionally, patients admitted with mixed intoxication or associated trauma and those who received any medications before admission were excluded from this study. Arterial blood gases (ABG) were done and analyzed to all included patients on admission before receiving any medications. Results: There was a significant positive correlation between pH value and pre-hospitalization period, systolic blood pressure (SBP), diastolic blood pressure (DBP), and period of hospital stay. A significant negative correlation existed between pH and dose of ALP, respiratory rate, and dose of required vasopressor. Bicarbonate level (HCO3) registered a significant positive correlation with SBP and DBP. Meanwhile, a significant negative correlation existed between HCO3 and both respiratory rate and dose of required vasopressor. There was a significant difference between survivors and non-survivors regarding pH, HCO3, PaCO2, and PaO2. Furthermore, there was a significant difference between patients who required and did not require mechanical ventilation considering pH, HCO3, and PaO2. Conclusion: It could be concluded that determining acid-base disturbance on admission in acute ALP poisoned patients is a simple, cheap, and reliable marker that may help to predict mortality and mechanical ventilation requirement.