Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient Real Time Multi View Face Recognition System

In recent years, the biometrics environment has received considerable attention at the global level. One of the most important biometrics is the face recognition. Viola and Jones algorithm is used for front face detection. Facial side images detected through the skin detection methodology. For features extraction step, Histogram oriented gradient (HOG) algorithm is used. This paper suggested using Raspberry pi3 platform in the real time multi-face recognition system to connect three cameras. In the recognition step, Support Vector Machine (SVM) used and compared with the performance of the principal component analysis algorithm (PCA). The system is tested on multiple images of the FEI database.
Investigation of common mode voltages of single stage boost inverter for five phase induction motor drive

In this manuscript, the single stage boost inverter is proposed to eliminate the common-mode voltage (CMV) and electromagnetic interference (EMI) in the motor drives. The proposed topology has the capability of eliminating the effects of intrinsic CMV without any additional filters, active or passive elements, and modified pulse width modulated (PWM) techniques. This topology is proposed with the rearrangement of filter components from ac side to mid place in such a way that the capacitor constantly clamped to the DC bus, and the inductor is placed at the mid-point of half-bridge module and supply to achieve the high gain. This arrangement is also eliminating the effect of switching natured common-mode voltage, which generally occurs in any conventional PWM inverter. Conventional PWM techniques can be implemented to this topology without any modification in the control strategy. The proposed topology is simulated in a MATLAB Simulink to verify the operation and CM reduction capabilities with the results of experimental prototype. In the manuscript, the proposed topology is compared with the traditional inverters and modulation schemes in terms of the CMV effect elimination to explain its effectiveness.
Occurrence probability derivation considering different behavior strategies and decision making under the probabilistic hesitant fuzzy environment

Abstract Compared with the general fuzzy decision making, the calculation process under the probabilistic hesitant fuzzy environment involves two new issues that need further consideration, namely quantitative element probability and qualitative element preference. The contributions of this study are to address them in the same modeling framework. For the quantitative element probability, also element occurrence probability, we propose an optimization method by developing the probabilistic hesitant fuzzy envelopment rate and introducing six behavior strategies. This method deals with two complex scenarios, namely, the occurrence probabilities are completely unknown or partially missing. For the qualitative element preference given by decision makers, we design a fusion technique and propose the probabilistic hesitant fuzzy element preference fusion (PHFEF) model based on the above optimization method. Thus, the PHFEF model is used to address the above issues in the same modeling framework. To apply the above models, we further provide a step-by-step decision-making process to reasonably use the PHFEF model in the probabilistic hesitant fuzzy environment. Finally, an illustrative example is used to show the feasibility and further comparisons are given to present the rationality of the proposed methods.
Exploring the Antibiotic Production Potential of Heterotrophic Bacterial Communities Isolated from the Marine Sponges Crateromorpha meyeri, Pseudaxinella reticulata, Farrea similaris, and Caulophacus arcticus through Synergistic Metabolomic and Genomic Analyses

The discovery of novel secondary metabolites is actively being pursued in new ecosystems. Sponge-associated bacteria have been in the limelight in recent years on account of their ability to produce bioactive compounds. In this study, heterotrophic bacteria associated with four sponge species were isolated, taxonomically identified, and subjected to screening for the production of bioactive entities against a panel of nine microorganisms, including Gram-positive and negative bacteria, as well as yeast and fungi. Of the 105 isolated strains, 66% were represented by Proteobacteria, 16% by Bacteriodetes, 7% by Actinobacteria, and 11% by Firmicutes. Bioactivity screening revealed that 40% of the total isolated strains showed antimicrobial activity against one or more of the target microorganisms tested. Further, active extracts from selective species were narrowed down by bioassay-guided fractionation and subsequently identified by HR-ESI-MS analyses to locate the active peaks. Presumably responsible compounds for the observed bioactivities were identified as pentadecenoic acid, oleic acid, and palmitoleic acid. One isolate, Qipengyuania pacifica NZ-96T, based on 16S rRNA novelty, was subjected to comparative metabolic reconstruction analysis with its closest phylogenetic neighbors, revealing 79 unique functional roles in the novel isolate. In addition, genome mining of Qipengyuania pacifica NZ-96T revealed three biosynthetic gene clusters responsible for the biosynthesis of terpene, beta lactone, lasso peptide, and hserlactone secondary metabolites. Our results demonstrate the ability to target the sponge microbiome as a potential source of novel microbial life with biotechnological potential.
Wireless power transmission of mobile robot for target tracking

The system is novel approach to combine wireless power transmission system (WPT) and automated guided vehicle (AGV). The wireless power transfer for charging the mobile robot is implemented using inductive coupling method. The system setup consists of transmitter coils whose switching action is controlled through transistors, receiver coil connected to full ridge rectifier and mobile robot. The track consists of number of transmitter coil which transmits power in form of electromagnetic waves. The receivers in the robot, which receives these waves and converts it back to electric power to charge the battery. The robot tracks its target destination based on the user command from the smart phone through Bluetooth. Very few theoretical researches are available on this field. A prototype was developed and tested based on the researches. The system achieves good range but falls short in efficiency to charge a battery, charging of battery takes longer time than regular charging time. Further research and extensive exploration can bring this technology from theory to practice.
AGPC-SLAM: Absolute Ground Plane Constrained 3D Lidar SLAM

— 3D LiDAR-based simultaneous localization and mapping (SLAM) is a well-recognized solution for mapping and localization applications. However, the typical 3D LiDAR sensor (e.g. Velodyne HDL-32E) only provides a very limited field of view vertically. As a result, the vertical accuracy of pose estimation is suffered. This paper aims to alleviate this problem by detecting the absolute ground plane to constrain the vertical pose estimation. Different from the conventional relative plane constraint, this paper employs the absolute plane distance to refine the position in the z-axis and the norm vector of the ground plane to constrain the attitude drift. Finally, relative positioning from LiDAR odometry, constraint from ground plane detection, and loop closure are integrated under a proposed factor graph-based 3D LiDAR SLAM framework (AGPC-SLAM). The effectiveness is verified using several datasets collected in scenes of Hong Kong.
Degeneration of Granule Neurons In The Dentate Gyrus (Dg) Area In The Hippocampus In Male Rats Under The Influence of Simvastatin

Background: Simvastatin is a lipophilic statin used to prevent and treat hypercholesterolemia. This study aimed to evaluate the effect of simvastatin on the appearance specifications of the DG region Hippocampus. Method: For the experiment, 36 male Wistar rats with an average weight of 300-250 g were divided into six groups (each group comprised six heads). Groups: 1): Control group, 2): Vitamin D dose 5 µg/kg, 3): Simvastatin group dose 1 mg/kg, 4): Simvastatin group dose 10 mg/kg, 5): Simvastatin group dose 1 mg/kg + vitamin D dose 5 µg/kg, 6): Simvastatin group dose 10 mg/kg + vitamin D dose 5 µg/kg. The duration of drug use was 28 days. At the end of the drug administration period, the animals were slaughtered, and then the brain tissue of the animals was extracted to prepare microscopic sections. Results: Microscopic studies show a negative effect of 10 mg/kg simvastatin on DG neurons. Conclusion: The microscopic studies in the present study indicate that high doses of simvastatin cause degeneration of neurons in the DG region of the hippocampus.
Characterization and Evaluation of Antimicrobial Potential of Trigonella incise (Linn) Mediated Biosynthesized Silver Nanoparticles

The goal of the research was to explore a new green method used to synthesize silver nanoparticles (Ag NPs) from an aqueous extract of Trigonella incise, which serves as a reducing and stabilizing agent. The obtained results showed an 85% yield of nanoparticles by using 2:5 (v/v) of 5% plant extract with a 0.5 M solution of AgNO3. Different techniques were used to characterize the synthesized Ag NPs, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and UV–visible spectroscopy. The UV–visible spectra of green synthesized silver nanoparticles showed maximum absorption at a wavelength of 440 nm. The FT-IR studies revealed the stretching oscillation frequency of synthesized silver nanoparticles in the absorption band near 860 cm−1. Similarly, the bending and stretching oscillation frequencies of the NH function group were assigned to the band in the 3226 cm−1 and 1647 cm−1 regions. The bending vibration of C-O at 1159 cm−1 confirmed the carbonyl functional group that was also assigned to the small intensity band in the range of 2361 cm−1. The X-ray diffraction analysis of Ag NPs revealed four distinct diffraction peaks at 2θ of 38°, 45°, 65° and 78°, corresponds to (111), (200), (220) and (311) of the face-centered cubic shape. The round shape morphology of Ag NPs with a mean diameter in the range 20–80 nm was analyzed via SEM images. Furthermore, the nanoparticles showed more significant antimicrobial activity against Salmonella typhi (S. typhi) and Staphylococcus aureus (S. aureus) with an inhibition zone of 21.5 mm and 20.5 mm at 6 μg/mL concentrations, respectively, once compared to the standard reference. At concentrations of 2 µg/mL and 4 µg/mL, all of the bacterial strains showed moderate activity, with inhibition zones ranging from 11 mm to 18.5 mm. Even at high concentrations of AgNPs, S. typhi showed maximum resistance. The best antifungal activity was observed by synthesized Ag NPs against Candida albicans (C. albicans) with 21 mm zone of inhibition, as compared to a standard drug which gives 22 mm of inhibition. Therefore, we conclude that the antibacterial and antifungal activities showed satisfactory results from the synthesized Ag NPs.
Compact modeling and hybrid circuit design for spintronic devices based on current-induced switching

The shrinking of complementary metal oxide semiconductor (CMOS) fabrication node below 90 nm leads to high static power in memories and logic circuits due to the increasing leakage currents. Emerging spintronic technology is of great interest to overcome this issue thanks to its non-volatility, high access speed and easy integration with CMOS process. Spin transfer torque (STT), a current-induced switching approach, not only simplifies the switching process but also provides an unprecedented speed and power performances, compared with the field-induced switching. This thesis is dedicated to the compact modelling and hybrid circuit design for current-induced switching spintronic devices. Magnetic tunnel junction (MTJ), the basic element of magnetic random access memory (MRAM), and racetrack memory, a novel concept based on current-induced domain wall (CIDW) motion, are particularly investigated. These spintronic devices and circuits are based on the materials with perpendicular-magnetic-anisotropy (PMA) that promises the deep submicron miniaturization while keeping a high thermal stability. Numbers of physical models and realistic parameters are integrated in the compact modeling to achieve a good agreement with experimental measurements. By using these accurate compact models of PMA STT MTJ and PMA racetrack memory, some magnetic logic and memory applications, such as magnetic full adder (MFA) and content addressable memory (CAM), are designed and simulated. We analyze and assess their performance potential in terms of speed, area and power consumption compared with the conventional circuits. Finally, in order to tackle the capacity bottleneck hindering the wide application, we propose two design optimizations: MLC for MRAM and magnetic field assistance for racetrack memory. This MLC design benefits from the STT stochastic behavior to achieve an ultra-high speed while increasing the density. The racetrack memory with magnetic field assistance is based on the observation that CIDW motion can be triggered below the critical current due to “Walker breakdown” effect. This opens a new route to reduce the propagation current and increase the capacity of racetrack memory beyond the improvements of peripheral circuits or materials.
Equilibrium Conformation of a Novel Cable-Driven Snake-Arm Robot under External Loads

Based on the anti-parallelogram mechanism, an approximate cylindrical rolling joint is proposed to develop a novel cable-driven snake-arm robot with multiple degrees of freedom (DOF). Furthermore, the kinematics of the cable-driven snake-arm robot are established, and the mapping between actuator space and joint space is simplified by bending decoupling motion in the multiple segments. The workspace and bending configurations of the robot are obtained. The static model is established by the principle of minimum potential energy. Furthermore, the simplified cable constraints in the static model are proposed through Taylor expansion, which facilitates the equilibrium conformation analysis of the robot under different external forces. The cable-driven snake-arm robot prototype is developed to verify the feasibility of the robot design and the availability of the static model through the experiments of the free bending motion and the external load on the robot.
HOW TO BECOME POLITICAL? BASIC CONCEPTS FOR EXPLORING EARLY CHILDHOOD UNDERSTANDING OF POLITICS

"In the interdisciplinary project PoJoMeC, we investigate children's understanding of politics at preschool and primary school age. The interdisciplinary research approach is based on the perspectives of political didactics, literature and media didactics, and journalism. Initially, we will use qualitative approaches to find out how children's political awareness is shown. Our research methods focus on the one hand on the children's explicit knowledge, but on the other hand already on concepts of rule-governed action. The different degrees of abstraction of these concepts are based on a modification of the ecological model of human development according to Uri Bronfenbrenner (1979). The paper reconstructs the argumentative process of developing an acceptable interdisciplinary concept of politics for our joint research. Considering political didactics, literature and media studies, and philosophy, a research framework is presented that does not start with terms and concepts but considers more fundamental forms of social perception. "
Investigating the value of integrated operations planning: A case-based approach from automotive industry

During the last decade, many researchers have focused on joint consideration of various operations planning aspects like production scheduling, maintenance scheduling, inventory control, etc. Such joint considerations are becoming increasingly important from the point of view of current advancement in intelligent manufacturing, also known as Industry 4.0. Under the concept of Industry 4.0, advanced data analytics aim to remove human intervention in decision-making. Thus, the managerial level coordination of decisions taken independently by various departments will be out of trend. Therefore, developing an approach that optimises various operations planning decisions simultaneously is essential. Available literature on such joint considerations is more of the exploratory in nature and is limited to simplistic production environments. This necessitates the investigations of value of integrated operations planning for wide range of manufacturing scenarios. Present paper adopts a case-oriented approach to investigate the value of integrated operations planning. First, an integrated approach for simultaneously determining job sequencing, batch-sizing, inventory levels and preventive maintenance schedule is developed. The approach is tested in a complex production environment of an automotive plant and substantial economic improvement was realised. Second, a comprehensive evaluation is performed to study the robustness and implications of proposed approach for various production scenarios. Results of such pervasive performance investigations confirm the value of proposed approach over conventional approaches.
Ameliorative Effect of Citropten Isolated from Citrus aurantifolia Peel Extract as a Modulator of T Cell and Intestinal Epithelial Cell Activity in DSS-Induced Colitis

Citropten is a coumarin that is mainly found in fruits of Rutaceae trees, but its anti-inflammatory activities in colitis is still unknown. In this study, we investigated its attenuating effect of citropten isolated from Citrus aurantifolia extract on DSS-induced colitis through the modulation of the activity of T cells and intestinal epithelial cells. We found that pre-treatment with citropten downregulates the activity of T cells and intestinal epithelial cells without a negative effect on the viability of Jurkat and HT-29 cells. The results from the Western blot analysis revealed that pre-treatment with citropten reduces the NFκB and MAPK signaling pathway in activated T cells and intestinal epithelial cells. We elucidated that the oral administration of citropten alleviates the colonic inflammation and activity of effector T cells in DSS-induced colitis by measuring changes in body weight, histological scoring from H&E-stained sections, mRNA levels of pro-inflammatory cytokines and the phosphorylation level of the MAPK signaling pathway.
Endothelial Nitric Oxide Synthase in the Perivascular Adipose Tissue

Perivascular adipose tissue (PVAT) is a special type of ectopic fat depot that adheres to most vasculatures. PVAT has been shown to exert anticontractile effects on the blood vessels and confers protective effects against metabolic and cardiovascular diseases. PVAT plays a critical role in vascular homeostasis via secreting adipokine, hormones, and growth factors. Endothelial nitric oxide synthase (eNOS; also known as NOS3 or NOSIII) is well-known for its role in the generation of vasoprotective nitric oxide (NO). eNOS is primarily expressed, but not exclusively, in endothelial cells, while recent studies have identified its expression in both adipocytes and endothelial cells of PVAT. PVAT eNOS is an important player in the protective role of PVAT. Different studies have demonstrated that, under obesity-linked metabolic diseases, PVAT eNOS may be even more important than endothelium eNOS in obesity-induced vascular dysfunction, which may be attributed to certain PVAT eNOS-specific functions. In this review, we summarized the current understanding of eNOS expression in PVAT, its function under both physiological and pathological conditions and listed out a few pharmacological interventions of interest that target eNOS in PVAT.
Current Trends in the Management of Epithelial Lacrimal Gland Tumors: A Retrospective National Cancer Database Analysis

Background: Lacrimal gland tumors are rare with data limited to very few large studies. Contemporary strategies like orbit sparing surgeries and neoadjuvant intraarterial chemotherapy remain controversial. Methods: This is a retrospective cohort analysis of epithelial lacrimal gland tumors from the 2004-2016 National Cancer Database. Patients were stratified based on the type of surgery (limited vs destructive) and various treatment modalities employed. Results: Squamous cell carcinoma (33.48%) and adenoid cystic carcinoma (29.45%) were the commonest histologies (N=669). Comparison of limited (46.33%) vs destructive procedures (53.11%) among 482 patients did not show any survival difference, nor the comparison between surgery vs ± chemotherapy vs ± radiotherapy among 472 patients. Conclusion: Squamous cell carcinoma and adenoid cystic carcinoma are the commonest types of lacrimal gland tumors seen in our study. Tumor spread from adjacent sites may have contributed to the higher percentage of squamous cell carcinomas seen. The type of surgery or chemoradiation use did not alter survival.
BK Virus Infection and BK-Virus-Associated Nephropathy in Renal Transplant Recipients

Poliomavirus BK virus (BKV) is highly infective, causing asymptomatic infections during childhood. After the initial infection, a stable state of latent infection is recognized in kidney tubular cells and the uroepithelium with negligible clinical consequences. BKV is an important risk factor for BKV-associated diseases, and, in particular, for BKV-associated nephropathy (BKVN) in renal transplanted recipients (RTRs). BKVN affects up to 10% of renal transplanted recipients, and results in graft loss in up to 50% of those affected. Unfortunately, treatments for BK virus infection are restricted, and there is no efficient prophylaxis. In addition, consequent immunosuppressive therapy reduction contributes to immune rejection. Increasing surveillance and early diagnosis based upon easy and rapid analyses are resulting in more beneficial outcomes. In this report, the current status and perspectives in the diagnosis and treatment of BKV in RTRs are reviewed.
HERMES: Using Commit-Issue Linking to Detect Vulnerability-Fixing Commits

Software projects today rely on many third-party libraries, and therefore, are exposed to vulnerabilities in these libraries. When a library vulnerability is fixed, users are notified and advised to upgrade to a new version of the library. However, not all vulnerabilities are publicly disclosed, and users may not be aware of vulnerabilities that may affect their applications. Due to the above challenges, there is a need for techniques which can identify and alert users to silent fixes in libraries; commits that fix bugs with security implications that are not officially disclosed. We propose a machine learning approach to automatically identify vulnerability-fixing commits. Existing techniques consider only data within a commit, such as its commit message, which does not always have sufficiently discriminative information. To address this limitation, our approach incorporates the rich source of information from issue trackers. When a commit does not link to an issue, we use a commit-issue link recovery technique to infer the potential missing link. Our experiments are promising; incorporating information from issue trackers boosts the performance of a vulnerability-fixing commit classifier, improving over the strongest baseline by 11.1% on the entire dataset, which includes commits that do not link to an issue. On a subset of the data in which all commits explicitly link to an issue, our approach improves over the baseline by 12.5%.