Miracle-dz/UniFAR-FTUs huggingface dataset:
Open Source Galaxy: Heterogeneous Information Networks in Social Coding

The GitHub has become the source of data for various research efforts. The full list of public events data which concern social coding on public repositories on this platform is available and can be analyzed. Modeling the complex nature of interactions among users on GitHub is challenge as well as dealing with such a huge amount of events data. Most existing research efforts on events data analysis are conducted on homogeneous networks without distinguishing different types of objects and links. In this paper, we design a data infrastructure to support the process of massive events data generated from GitHub and we model the complex interaction nature in collaborative developments as a heterogeneous information network, meta paths are introduced to capture various semantic information. We also propose a general algorithm framework with the ability to aggregate task related features and can generate heterogeneous network instances at arbitrary scale. Then we present the visualization of the open source communities by means of networks analysis.
A Method of Seamless Transitions Between Different Operating Modes for Three-Port DC-DC Converters

This paper presents the design of three-port converters (TPCs) for smooth transitions (i.e., fast settling time, and no obvious overshoot/undershoot) of 7 distinctive operating modes, depending on sources and loads scheduling. Two viable converter configurations have been identified and selected for further analysis and design of PV-battery systems. Conventionally, mode transition is achieved by assigning specific switching patterns through feedback signals and appropriate control algorithms. This incurs a delay in the response and unavoidable noise in the circuit. Additionally, in TPCs, three voltage sensors and three current sensors are generally required for decision making in mode selection, where errors in sensors may lead to an inaccurate response. This paper presents a new control strategy where the number of switching patterns is significantly reduced to 3 patterns instead of minimum 5 patterns for existing reported topologies. Therefore, decisions are simplified so that the transition occurs naturally based on the power availability and load demand but not deliberately as in the conventional method. In addition, instead of six sensors, three voltage sensors and only one current sensor are required to achieve all the necessary operations, namely, MPPT, battery protection, and output regulation. Moreover, these sensors do not participate in mode selection decision, which leads to seamless and fast mode transition. In addition, this work considers two bidirectional ports as compared with only one bidirectional port in most reported topologies. This configuration enables both standalone and DC grid-connected applications. Experimental results are reported to verify the proposed solution.
Design of an Active Battery Equalization Circuit with DC-DC Converter

An active balanced topology circuit based on DC-DC converter is proposed in this paper. It uses the energy of the whole battery pack to charge the lowest voltage cell. In the control strategy, starting and stopping the equalization is well controlled by setting the appropriate thresholds of voltage difference between each cell. Experiment board which can sample and equalize 16 batteries is manufactured, and the experimental results verify the effectiveness of the proposed equalization system.
Optimal Operation of Multi-energy Complementary Microgrid with Cooling, Thermal and Electricity Load

With the rapid development of microgrid (MG), the optimal operation of MG is one of the key technologies researched in the power field currently. The optimal operation is very important to the management of microgrid. This paper proposes a complementary microgrid that inputs solar energy and natural gas energy, supplying three types of loads: cooing, heat, electricity. Based on establishing a mathematical model for device in the microgrid, a model for optimizing operation of the complementary microgrid considering the different loads in different seasons is proposed. This model considers the multiple demands for three types of loads, and aims at the lowest total operation and maintenance cost of the multienergy complementary microgrid. During the operation, the optimization strategy of “Follow Electricity Load” is adopted to solve the mismatching of multiple loads. Finally, through the case study of the complementary microgrid based on the student dormitory, the energy consumption and total operation and maintenance cost are compared with separate supply system for cooling, thermal and electricity load, which verifies the feasibility and economy of the proposed model for optimizing operation.
The Analysis and Application of Decentralized Cyber Layer and Distributed Security Control for Interconnected Conurbation Grids under Catastrophic Cascading Failures

The cluster-featured conurbation cyber-physical power system (CPPS) interconnected with tie-lines facing the hazards from catastrophic cascading failures. To achieve better real-time performance, enhance the autonomous ability and improve resilience for the clustered conurbation CPPS, the decentralized cyber structure and the corresponding distributed security control strategy is proposed. Facing failures, the real-time security control is incorporated to mitigate cascading failures. The distributed security control problem is solved reliably based on alternating direction method of multipliers (ADMM). The system overall resilience degradation index(SORDI) adopted reflects the influence of cascading failures on both the topological integrity and operational security. The case study illustrates the decentralized cyber layer and distributed control will decrease the data congestion and enhance the autonomous ability for clusters, thus perform better effectiveness in mitigating the cascading failures, especially in topological perspective. With the proposed distributed security control strategy, curves of SORDI show more characteristics of second-order percolation transition and the cascading failure threshold increase, which is more efficient when the initial failure size is near the threshold values or step-type inflection point. Because of the feature of geological aggregation under cluster-based attack, the efficiency of the cluster-focused distributed security control strategy is more obvious than other nodes attack circumstances.
A Comparative Study of Neural Network Techniques for Automatic Software Vulnerability Detection

Software vulnerabilities are usually caused by design flaws or implementation errors, which could be exploited to cause damage to the security of the system. At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or code similarity (source code level) and rely on manually defined vulnerability features. However, these rules and vulnerability features are difficult to be defined and designed accurately, which makes static analysis face many challenges in practical applications. To alleviate this problem, some researchers have proposed to use neural networks that have the ability of automatic feature extraction to improve the intelligence of detection. However, there are many types of neural networks, and different data preprocessing methods will have a significant impact on model performance. It is a great challenge for engineers and researchers to choose a proper neural network and data preprocessing method for a given problem. To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i.e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i.e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers. Specifically, we found that 1) the training speed of RVFL is always faster than Bi-LSTM, but the prediction accuracy of Bi-LSTM model is higher than RVFL; 2) using doc2vec for vector representation can make the model have faster training speed and generalization ability than using word2vec; and 3) multi-level symbolization is helpful to improve the precision of neural network models.
A Machine Learning-Assisted Model for GaN Ohmic Contacts Regarding the Fabrication Processes

Gallium nitride (GaN) devices have been successfully commercialized due to their superior performance, especially their high-power transformation efficiency. To further reduce the power consumption of these devices, the optimization for the ohmic contacts is attracting more and more attention. In the light of the mature and powerful machine learning (ML) techniques, this work provides a novel method to evaluate the fabrication processes of the ohmic contacts in AlGaN/GaN heterojunction, n-type, and p-type GaN, by establishing a regression-based model. The proposed model can not only investigate the influence weight of each process but also predict the contact resistance by inputting the desired recipes. A website (http://ohmic.zeheng.wang/) containing the successfully trained model for the readers’ interests is also provided, which, we believe, would benefit the society of the process development and optimization.
Comparative Analysis of Performance of Different Controllers for a Continuous Stirred Tank Reactor

The main aim of this paper is to develop different control strategies for a jacketed continuous stirred tank reactor. Continuous Stirred Tank Reactor (CSTR) is one of the most important unit operations in chemical industries which exhibits highly non-linear behaviour and usually has wide operating ranges. In this work, performance of different controllers such as Proportional-integral-derivative controller (PID), Internal model controller (IMC) and model reference adaptive controller (MRAC) have been evaluated.
Macrophage-Derived Small Exosomes: Efficient Transmission and Cytotoxicity to Cancer Cells

Tumor-associated macrophages are a key component in the tumor microenvironment, secreting extracellular vesicles (EVs) such as exosomes and other various factors for intercellular communication. However, macrophage-derived EVs heterogeneity and their cytotoxicity to cancer cells has not been well understood. Here, we aimed to separately isolate various types of macrophageEVs by size exclusion chromatography (SEC) method and investigate EV transmission and cytotoxicity to oral cancer cells. For fluorescence-labeling of cellular and EV membranes, palmitoylation signal-fused GFP and tdTomato were expressed in THP-1 monocytic cells and HSC-3 oral cancer cells, respectively. We found that fluorescence-labeled EVs secreted by macrophages were highly transmissive to oral cancer cells than those from parental monocytic cells. In a co-culture system and conditioned medium (CM), a macrophage-secreted unidentified factor was cytotoxic to oral cancer cells. We fractionated macrophage-derived EVs by the SEC method and performed western blotting to characterize various EV types. Three fractions were characterized: small exosomes (EXOS: < 50 nm) fraction containing HSP90α, HSP90β, CD63 (EV marker) and β-actin; large exosomes (EXO-L: 50-200 nm) fraction containing CD9 (EV marker) and HSP90β; large EVs (100-500 nm) fraction. Notably, the macrophage-derived small exosomes fraction was cytotoxic to oral cancer cells, while large exosomes and large EVs were not. Therefore, it was implicated that macrophage-derived small exosomes are cytotoxic with high transmission potential to cancer cells.
Minimally Invasive Treatment for Sacroiliac Dislocation in Dogs

Sacroiliac dislocation is the separation of the iliac wing from the pelvic bone and needs to be repaired by surgery. Corrective surgical methods include open reduction and minimally invasive techniques. In the present study, we used a minimally invasive surgical technique in seven dogs with sacroiliac dislocation. Five cases had unilateral sacroiliac joint luxation and two cases had bilateral sacroiliac joint luxation; all were referred to hospital after being hit by an automobile. All cases were treated with a fluoroscope-assisted, minimally invasive technique. Patients were evaluated by measuring surgery time, postoperative ambulatory time, and calculating pelvic canal diameter ratios. Surgery time was measured from initial incision to completion of skin closure. Mean surgery time was 30.6 minutes in unilateral sacroiliac joint luxation and 68 minutes in bilateral sacroiliac joint luxation. Mean preoperative pelvic canal diameter ratio was 1.22 (± 0.27), immediate postoperative pelvic canal diameter ratio was 1.26 (± 0.10), and at 2 weeks after surgery, the pelvic canal diameter ratio was 1.37 (± 0.22). All cases were ambulatory within 1 week and mean postoperative ambulatory time was 5 days. Based on the results, the use of a minimally invasive technique for correction of sacroiliac dislocation can decrease surgical time, lessen operative and postoperative burdens on patients, and provide owners with a good prognosis.
The Effect of Acupressure, Acupuncture and Massage Techniques on the Symptoms of Breast Engorgement and Increased Breast Milk Volume in Lactating Mothers: A Systematic Review

Background: We aimed to review interventional studies on the effect of acupuncture, acupressure, and massage techniques on the symptoms of breast engorgement and breast milk volume. Materials and Methods: Systemic search of online databases (Medline, Cochrane, EMBASE, Web of Science, and Scopus), for randomized control trial and non-randomized prospective or retrospective clinical studies which were published up to Nov 2020, were done. No language or time restrictions were considered. Study selection was done by two reviews. Results: Nine studies were included. In the first study, no significant difference was found in the mean breast milk volume between the two intervention groups (GB21, LI4 and SI1 acupoints), and control group. In the second study, the group receiving acupressure on the SI1, ST17 and CV18 acupoints exhibited a significant increase in the breast milk production. In the third study, the co- administration of affirmation relaxation and acupressure enhanced the breastfeeding self-efficacy (p = 0.045), and the breast milk volume (p = 0.033). In the fourth study the results revealed a significant difference in the mean breast milk volume in breast acupressure and oxytocin than control groups. In the fifth study, treatment with acupuncture significantly increased exclusive breastfeeding in acupuncture group. In the sixth study, milk production was significantly higher in Tuina therapy compared to the control group. Acupressure and acupuncture were effective onbreast milk volume and breast engorgement. Conclusion: Treatment with acupuncture and acupressure on GB21, LI4 and SI1, ST17 and CV18 acupoints, could improve milk volume. Also, combination of acupressure with relaxation or oxytocin massage could improve breast milk production. Acupressure and acupuncture can decrease breast engorment and breast pain in lactating mothers, too.
Optimal stopping problem of American put options for the diffusion risk model

Abstract This paper investigates the optimal stopping problem of American put options for the diffusion risk model. First of all, by using the relevant conclusions of the first hitting time of diffusion risk model, the optimal stopping problem formulation can be obtained. Then, the optimal value function and the optimal trading time of the American put option are obtained. Finally, numerical examples are given to illustrate the applications of the optimal stopping problem for American put options.
Recommendations on exercise training during the COVID-19 pandemic

Secondary prevention after an acute cardiac event through cardiac rehabilitation is confirmed as the most appropriate method to ensure favourable outcomes such as reduction of mortality, morbidity and disability and to increase the quality of life. Recent guidelines drawn up by EAPC give great space to exercise, particularly for implementation of the exercise programme, advances in different training modalities were added and new challenging populations were considered [1]. In this line, the Covid-19 pandemic has generated a new population of patients, new methods of approach and has also redesigned the physical spaces that can be used for greater safety. Covid-19 is an infectious disease characterized by a rapid human-to-human transmission capacity and has opened up new scenarios, particularly for environments such as hospitals and gyms where human contact is often the norm. We propose that CRP gyms should be modified in “Covid-19 version ” , seeking a balance between minimal care and enhanced health security [2,3].
Kurdish Handwritten Classification Based on Human Personality Analysis

This study proposes a holistic technique of classifying Kurdish handwritten text documents, involving several stages. The first stage entails the sectioning of Kurdish handwritten document images into lines, words and characters and the second stage entails the obtaining of structural and statistical features from the sectioned parts that are often utilized in human personality analysis for the examination of feature behavior and effectiveness. This is done by combining the entire potential outcomes to determine the significant features set. The third stage entails the use of F-Measure to evaluate the extracted features performance and their combination in various relationship methods, individually and in groups. The last stage entails the actual experiment using the standard KRDOH dataset of the Kurdish handwritten text, containing 1076 volunteers’ samples of different ages, genders and education levels in a cumulative 4304 manuscripts consisting of 4 contributed pages by each writer. Based on the results obtained from multiple runs of individual clustering method of each distance measures, good set of features generally deliver significant enhanced clustering of handwritten structures.
The potential use of the culture filtrate of an Aspergillus niger strain in the management of fungal diseases of grapevine

The present study was aimed to examine the use of culture filtrates of defensin-producing fungal strains against the most important fungal and pseudofungal infections of grapevine as an environmentally sound alternative of chemical control. Twenty-seven isolates of five defensin-producing fungal species were tested for antifungal activity. Four isolates (one Aspergillus giganteus and three Aspergillus niger) decreased the viability of the test organism successfully. The isolate with the highest antifungal efficacy (Aspergillus niger SZMC2759) was subjected to detailed investigation. The culture filtrate of the strain was effective against epicuticular mycelia and conidia of Botrytis cinerea, Guignardia bidwellii and Erysiphe necator, but not against subcuticular mycelia and Plasmopara viticola cells. The culture filtrate also prevented the development of powdery mildew symptoms on grapevine cuttings. Several modes of action were detected: inhibition of germination, membrane permeabilization, plasmolysis, fragmentation of nuclei. Certain parameters (pH, stress, aeration) of the fermentation were optimized for the highest antifungal activity. According to the results, culture filtrate of Aspergillus niger can be a promising agent in the management of fungal diseases of grapevine.
Voluntary intake, digestibility, serology and testosterone level of West African dwarf bucks fed air-dried leaf meal-based diets

Corresponding author: E-mail: l +2348032110281 *Department of Animal Production and Health, Federal University of Agriculture, Abeokuta, Nigeria. Institute of Food Security, Environmental Resources and Agricultural Research, Federal University of Agriculture, Abeokuta, Ogun State. world Bank Africa Centre of Excellence for Agricultural Development and Sustainable Environment (CEADESE), Federal University of Agriculture, Abeokuta, Ogun State, Nigeria. 1
Total replacement of fish meal by enriched‐fatty acid
 Hermetia illucens
 meal did not substantially affect growth parameters or innate immune status and improved whole body biochemical quality of Nile tilapia juveniles

Total replacement of fish meal by enriched-fatty acid Hermetia illucens meal did not substantially affect growth parameters or innate immune status and improved whole body biochemical quality of Nile tilapia juveniles Agbohessou, Pamphile S. ; Mandiki, Syaghalirwa N.M. ; Gougbédji, Armel; Megido, Rudy Caparros; Hossain, Md Sakhawat; De Jaeger, Pauline; Larondelle, Yvan; Francis, Frédéric; Lalèyè, Philippe A. ; Kestemont, Patrick
The influence of the institutional context on interfirm relationships: A Comparative study between low- and high-income countries

Today's competitive environment has pushed companies to developed collaborative relationships with other firms on the market to improve their performance and achieve a competitive advantage. Among the existing collaborative strategies, horizontal collaboration has gained much attention recently. However, besides the potential improvement this strategy can bring, very few successful long-term cases are reported in the literature. In this paper, we investigate the role that country context plays in determining the collaboration success, specifically the strength of the institutional context. A model linking collaboration activities to its outcomes is tested in two independent samples representing upper-middle-high-income (UMHI) and lower-middle-low-income countries (LMLI). The results show that firms in UMHI countries are more likely to commit to the relationship once trust is established, whereas firms in LMLI countries are more likely to be satisfied with the relationship as a result of developed trust. Citation: Ismail Badraoui and Youssef Boulaksil and Tarik Saikouk and G.A. J. van der Vorst, (2021) ''The influence of the institutional context on interfirm relationships: A Comparative study between lowand high-income countries'', Economics Bulletin, Vol. 41 No. 2 pp. 802-815. Contact: Ismail Badraoui ismailbadraoui@gmail.com, Youssef Boulaksil youssef.boulaksil@gmail.com, Tarik Saikouk saikoukt@gmail.com, G.A. J. van der Vorst jack.vandervorst@wur.nl. Submitted: November 18, 2020. Published: April 09, 2021.
CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION FOR RETINAL IMAGE

In the field of the medical science, Engineering plays the major role in the part of diagnose the diseases and rectify the problem occur in human body. Mostly affected part in the human eye is Retina and many of the diseases acquired there. May it leads to blindness in eye. Now a days many of techniques used to diagnosis the problem especially fundus photography used for taking photographs the rear of an eye. But it has some of shortcomings such as blurring image, very low contrast and uneven luminescence. To overcome this problem by using Enhancement technique and colour images learned theoretically through generalized setup. Whenever RGB colour space changed to other colour spaces such as LHS, HSI, YIQ, etc., At this stage the gamut problem is arises. To rectify the gamut problem using enhancement technique subsequently followed by adaptive gamma correction. Through this process we can achieve the equalized enhancement of all range of pixels in a colour Image .