Miracle-dz/UniFAR-FTUs huggingface dataset:
Courting Violence: Opportunistic Parties and the Politics of Religion

: In 2016, the Islamic Defenders Front , Front Pembela Islam (FPI), a violent Islamic group, managed to gather hundreds of thousands of people in a series of rallies in the Indonesian capital city. The rallies had two important consequences: on one side, they influenced the election by swaying the voters’ preferences; on the other side, they marked a turning point in the interactions between violent Islamic organizations and political parties. Although FPI had campaigned and organized similar rallies to oppose the Christian governor since 2014, only in 2016 that this issue was picked up by the public, which helped FPI to mobilize them in large numbers. This suggests that there are conditions under which FPI is able to mobilize the public, which were not there in 2014 but evidently were there in 2016. In this paper, I used network analysis and computational content analysis on more than 25.000 news articles published between 2008 and 2018 to examine why the same issue championed by FPI saw different levels of public and political party engagement in 2014 and 2016. Furthermore, I employed network analysis to illustrate the changing relationship between FPI as a violent group with political parties over the years.
LSDN — Manage complex (virtual) networks in cloud environment with Linux kernel facilities

Contemporary data centers highly rely on SDN (Software De-ﬁned Networking) to establish and manage networking among huge number of virtual machines (VM). With a rapid growth of cloud services and their users there is a natural growth of virtual machines providing those services. Therefore reliable SDN solution is a must and all cloud providers depend on it. There are several open-source solutions providing management of virtual networking for example well-known Open vSwitch. However these solutions depend on running daemons and they also add code to the kernel. This fact may decrease reliability. In this paper we describe a tool called LSDN. With LSDN you can easily manage (not only) virtual networks and in addition LSDN brings no other code to the kernel. It relies only on Linux Kernel facilities and in most cases it does not need any running services. In this paper we describe how to properly use LSDN, LSDN internals, its API in C version and DSL (Domain Speciﬁc Language) version and also bugs we found in Linux Kernel when using its recent functionality. Although LSDN is experimentally deployed in non-demanding production with low trafﬁc it is is still a very immature project and there is a huge space for improvements and additional features. We discuss how to tackle some of the most wanted features, e.g. statefull ﬁrewall (now we support only stateless version).
An Empirical Study of Experience Replay for Control in Continuous State Domains

In this thesis, we investigate the empirical performance of several experience replay techniques. E cient experience replay plays an important role in modelfree reinforcement learning by improving sample e ciency through reusing past experience. However, replay-based methods were largely forgotten before being repopularized by the Deep Q-Learning Network (DQN) architecture and have since become a standard component in o✏ine training. In this work, we revisit understudied classic replay strategies, backward replay and on-policy replay, a heuristic for replaying trajectories in the temporally backward order following on-policy action sequences, proposed in the original experience replay literature. We re-evaluate them in several classic reinforcement learning control problems under linear and nonlinear function approximations. We observe that (1) on-policy replay outperforms o↵-policy replay in two continuous state 2D maze domains under an exploratory policy, and (2) contrary to the previous claim in the original replay literature, replay settings exist where on-policy replay underperforms o↵-policy replay. We hypothesize that the practical benefit of on-policy replay is problem dependent and sensitive to the state distribution of the replay bu↵er. In addition, we propose a simple time-stepping replay strategy called “jumpy replay” that takes advantage of state generalization to speed up value propagation, which presents a comparable or better performance with a vanilla backward replay baseline across 5
Perturbation theory for optical bistability of prism and grating couplers and comparison with rigorous method

A perturbation method for studying the bistable behavior of a prism or grating coupler filled with a Kerr nonlinear medium is developed. A field representation limited to its first space harmonic already gives a satisfactory agreement with the much more complicated rigorous differential method. A better accuracy can be obtained by the use of the two first space harmonics. We then obtain an almost perfect agreement with rigorous theory, always with much lower computation times. All the relevant parameters useful to characterize the bistable behavior are given by this perturbation method.
Solving the cosmic lithium problems with primordial late-decaying particles

We investigate the modifications to predictions for the abundances of light elements from standard big-bang nucleosynthesis when exotic late-decaying particles with lifetimes exceeding {approx}1 sec are prominent in the early Universe. Utilizing a model-independent analysis of the properties of these long-lived particles, we identify the parameter space associated with models that are consistent with all observational data and hence resolve the much discussed discrepancies between observations and theoretical predictions for the abundances of {sup 7}Li and {sup 6}Li.
Tail inequalities for the eigenvalues of the GUE and related models: some results and questions

In a concise exposition, the note reviews some basic tail inequalities reﬂecting the local asymptotics of the eigenvalues (extreme, bulk, spacing) of the Gaussian Unitary Ensemble, and of related models 1 , raising at the same time (sometimes implicitly) questions seemingly not investigated in the literature (at least to the author’s knowledge).
Closing the Loop in AI, EMR, and Provider Partnerships: The Key to Improved Population Health Management?

The capabilities of and interest in artificial intelligence (AI) in healthcare, and more specifically, population health, have grown exponentially over the past decade. The vast volume of digital data or ‘big data’ in the form of images generated by an aging population, with an ever-increasing demand for imaging, amassed by radiology departments, provides ample opportunity for AI application and has allowed radiology to become a service line leader of AI in the medical field. The screening and detection capabilities of AI make it a valuable tool in population health management, as organizations work to shift their services to early identification and intervention, especially as it relates to chronic disease. In this paper, the clinical, technological, and operational workflows that were developed and integrated within each other to support the adoption of AI algorithms aimed at detecting subclinical osteoporosis and coronary artery disease are described. The benefits of AI are reviewed and weighed against potential drawbacks within the context of population health management and risk contract arrangements. Mitigation tactics are discussed as well as the anticipated outcomes in terms of cost-avoidance, physician use of evidence-based clinical pathways, and reduction in major patient events (e.g. stroke and hip fracture). The plan for data collection and analysis is also described for program evaluation.
Ginsenoside Rb1 Prevents Oxidative Stress-Induced Apoptosis and Mitochondrial Dysfunction in Muscle Stem Cells via NF-κB Pathway

Sarcopenia, featured by the progressive loss of skeletal muscle function and mass, is associated with the impaired function of muscle stem cells (MuSCs) caused by increasing oxidative stress in senescent skeletal muscle tissue during aging. Intact function of MuSCs maintains the regenerative potential as well as the homeostasis of skeletal muscle tissues during aging. Ginsenoside Rb1, a natural compound from ginseng, exhibited the effects of antioxidation and against apoptosis. However, its effects of restoring MuSC function during aging and improving age-related sarcopenia remained unknown. In this study, we investigated the role of Rb1 in improving MuSC function and inhibiting apoptosis by reducing oxidative stress levels. We found that Rb1 inhibited the accumulation of reactive oxygen species (ROS) and protected the cells from oxidative stress to attenuate the H2O2-induced cytotoxicity. Rb1 also blocked oxidative stress-induced apoptosis by inhibiting the activation of caspase-3/9, which antagonized the decrease in mitochondrial content and the increase in mitochondrial abnormalities caused by oxidative stress via promoting the protein expression of genes involved in mitochondrial biogenesis. Mechanistically, it was proven that Rb1 exerted its antioxidant effects and avoided the apoptosis of myoblasts by targeting the core regulator of the nuclear factor-kappa B (NF-κB) signal pathway. Therefore, these findings suggest that Rb1 may have a beneficial role in the prevention and treatment of MuSC exhaustion-related diseases like sarcopenia.
Induction of tissue-speci�c premature stem cell aging via Lef1 de�ciency promotes senescence-like deterioration in remote organs

Molecular mechanisms of aging speci�c to each stem cell (SC) are being elucidated. However, the common molecular basis for senescence in various SCs remains largely unexplored. Here, we have shown that the dysregulation of DNA damage response (DDR) modulated by lymphoid enhancer-binding factor 1 (Lef1) and DDR-microRNAs (DDR-miRs) is the common molecular basis for aging in SCs. We identi�ed Lef1as the most repressed transcription factor with aging in common between mesenchymal stem/stromal cells (MSCs) and hematopoietic stem/progenitor cells. Like the expression pro�les of aged MSCs, Lef1 knockdown reduced broad microRNAs and loss of induction of DDR-miRs in young MSCs. DDR capacity was also diminished in aged SCs in vivo. Moreover, Lef1 de�ciency in intestinal stem cells induced precocious dysregulation of DDR and in�ammation and senescence in the remote brain. This study demonstrates that the Lef1/DDR-miR axis is the common molecular basis underlying SC aging. on MSCs
Torque ripple minimization in Consequent-Pole PM Machines using harmonic current injection

 Abstract — In this paper, the torque ripple of consequent-pole PM machines (CPPMMs) is reduced by injecting 2 nd order harmonic of the armature current. In the proposed method, based on the machine back-emf spectrum and the current main harmonic, appropriate 2 nd order harmonic of the armature current is obtained. An analytical model is developed to obtain back-emf of CPPMMs. In addition, the obtained analytical model is used to compute the developed electromagnetic torque as a function of the armature currents. Validity of the analytical model is verified using finite-element analysis. To investigate the efficacy of the proposed 2 nd order current harmonic in torque ripple minimization, the optimum one is obtained separately by a direct search algorithm and the related electromagnetic torque waveforms for two different obtained 2 nd order current harmonics are compared together. The developed analytical model is used in the direct search algorithm for the torque waveform computation. Although the proposed method is not as exact as the direct search method, it is precise enough considering its negligible computation burden over the direct search method.
Entropy maximisation histogram modification scheme for image enhancement

Contrast enhancement plays an important role in image processing applications. The global histogram equalisation (GHE)-based techniques are very popular for their simpleness. In the author's study, the authors originally divide the GHE techniques into two steps, that is, the pixel populations mergence (PPM) step and the grey-levels distribution (GLD) step. In the PPM step, the pixel populations of adjoining grey scales to be mapped to the same grey scale are merged firstly in input histogram. Then, the new grey scales are redistributed according to a corresponding transformation function in the GLD step. This division is meaningful because the entropy of enhanced image is only determined by pixel populations regardless of grey levels. Then, they prove the entropy of enhanced image is reduced because of mergence. Inspired by GHE, they propose a novel entropy maximisation histogram modiﬁcation scheme, which also consists of PPM and GLD steps. However, the entropy is maximised, that is, the reduction of entropy is minimised under originally presented entropy maximisation rule in their PPM step. In the GLD step, they redistribute the grey scales in the merged histogram using a log-based distribution function to control the enhancement level. Experimental results demonstrate the proposed method is effective.
Identi�cation of Change Detection for Satellite Images using Ant Colony Optimization

-Supervision of Earth surface with the help of satellite images helps in land use land cover, resource planning & management, change detection and agricultural development areas. Satellites images are great repository of information and extraction of information from these unclear images is a challenging task. In order to identify the objects and boundaries in satellite images, various digital image based processing techniques like Sobel, Canny and Prewitt have been explored in this paper. Further, Ant Colony Optimization has been used to obtain the optimized images. Hybrid techniques viz.- AC0-Sobel, ACO-Canny and ACO-Prewitt are implemented and the results are quantitatively validated with the help of entropy and PIQE values of output optimized images. The results indicates that ACO-Canny hybrid technique yields better quality satellite images as compared to ACO-Sobel, ACO-Prewitt, Sobel, Canny and Prewitt edge detection techniques
Determination of microscopic optical properties of agar and Zerdine phantoms at 635 nm using Kubelka-Munk function approach: A numerical study

Since the precise and accurate determination of the optical properties of materials is very important for the development and application of optical technology, the investigation of the optical properties of biological tissues with tissue-like phantoms is an important research field in the applications of lasers in medicine. In this study, after directly determining the macroscopic optical properties of the agar and Zerdine phantoms at 635 nm, including the absorbance, transmittance, reflectance, refractive index, and total attenuation coefficient with the single integrating sphere test apparatus; the microscopic optical characterization of these two different soft tissue phantoms were realized at 635 nm by using the Kubelka-Munk function approach. For this, the microscopic optical parameters, which are the absorption coefficient, scattering coefficient, reduced scattering coefficient, and penetration depth, were calculated over these determined macroscopic optical properties.
Machine Learning of Pacing Patterns for Half Marathon

Every year over 40 000 runners participate in Gothenburg Half Marathon, one of the world’s largest half-marathons. Based on pub-licly available results data (423 496 entries) for ten years (2010 – 2019) 1 , we investigate machine learning models for two tasks: prediction of finishing times and identification of runners risking hitting the wall. Our models improve results over the current baseline on finish time prediction and manage to correctly identify many of the runners who later hit the wall, although it also misclassifies many who do not.
Detection and Molecular Characterization of Staphylococcus aureus and Methicillin-Resistant Staphylococcus aureus (MRSA) Nasal Carriage Isolates from Healthy Domestic Animal in Duhok Province Egyptian Journal of Veterinary Sciences

T HE study was aimed to determine and characterize the nasal carriage rate of S. aureus among apparently healthy farm animals including cattle, sheep, and goats using traditional and molecular characterization. The study was conducted in Duhok province during the period from November 2021 to March 2022. Furthermore, the isolates were screened for the presence of MRSA using the standard Kirby-Bauer disk diffusion method (oxacillin discs) and genotypically by PCR targeting the mecA gene. Among the 300 tested nasal swabs, 209 (69.7%) samples were positive for S. aureus isolation using traditional methods. The isolation rate was 62.7% (47/75), 66.7% (100/150), and 82.7% (62/75) in cattle, sheep, and goats, respectively. Amplification of species-specific nuc gene confirmed that 119 of 209 (56.9%) animals carried S. aureus in their nasal cavity. The isolates showed variation toward different antibiotics used in this study and the highest resistance rate was recorded toward penicillin at a ratio of 72.3% (86/119). This study confirms the occurrence of MRSA for the first time in nasal swabs from a healthy animal in Duhok Province. The MRSA isolates were found only in cattle (7/119) and none of the nasal carriages isolates from sheep and goats were carried MRSA isolates. The presence of MRSA and multidrug-resistant MRSA among healthy cattle could be considered as a potential reservoir for transmission of multidrug-resistant MRSA to humans especially farm workers and they could act as a reservoir to spread MRSA in livestock. Further studies are required for a better understanding of pathogenic transmission and for confirming the origin of the strains, whether are of human origin or vice versa.
Solving the HP model with Nested Monte Carlo Search

In this paper we present a new Monte Carlo Search (MCS) algorithm for finding the ground state energy of proteins in the HP-model. We also compare it briefly to other MCS algorithms not usually used on the HP-model and provide an overview of the algorithms used on HP-model. The algorithm presented in this paper does not beat state of the art algorithms, see PERM (Hsu and Grassberger 2011), REMC (Thachuk, Shmygelska, and Hoos 2007) or WLRE (W\"ust and Landau 2012) for better results. Hsu, H. -P.; and Grassberger, P. 2011. A review of Monte Carlo simulations of polymers with PERM. Journal of Statistical Physics, 144 (3): 597 to 637. Thachuk, C. ; Shmygelska, A. ; and Hoos, H. H. 2007. A replica exchange Monte Carlo algorithm for protein folding in the HP model. BMC Bioinformatics, 8(1): 342. W\"ust, T. ; and Landau, D. P. 2012. Optimized Wang-Landau sampling of lattice polymers: Ground state search and folding thermodynamics of HP model proteins. The Journal of Chemical Physics, 137(6): 064903.
Curcumin Regulates Gut Microbiota and Exerts a Neuroprotective Effect in the MPTP Model of Parkinson's Disease

Objectives The experiment aimed to explore the effects of curcumin on motor impairment, dopamine neurons, and gut microbiota in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mice model. Methods Mice were randomly assigned to six groups: normal control group, solvent control group, MPTP group, curcumin-low-dose group (40 mg/kg), curcumin-medium-dose group (80 mg/kg), and curcumin-high-dose group (160 mg/kg). After 14 days, each group of mice was subjected to the pole text, the hanging test, and the open-field test. Tyrosine hydroxylase (TH) immunohistochemistry was used to observe the survival of nigrostriatal dopamine neurons. Moreover, ultrastructural changes were observed with a transmission electron microscope in mice striatal tissue cells. Then, 16S rRNA was used to assess changes in the gut microbiota. Results (1) Each dose of curcumin reduced pole climbing time and increased suspension score and total distance moved dose-dependently. (2) All curcumin groups improved cell wrinkling and vacuolar degeneration, increased the number of TH positives, improved cell survival, and the higher the dose of curcumin, the better the effect. (3) There were differences in microbiota composition and a relative abundance among the groups. The relative abundance of Patescibacteria, Proteobacteria, and Verrucomicrobia was higher in the MPTP group. The relative abundance of Patescibacteria, Enterobacteriaceae, Enterococcaceae all decreased in all curcumin groups. In addition, the Kyoto Encyclopedia of Genes and Genomes pathways showed a reduction in the superpathway of N-acetylneuraminate degradation after medium- and high-dose curcumin administration. Conclusions Curcumin regulates gut microbiota and exerts a neuroprotective effect in the MPTP mice model. This preliminary study demonstrates the therapeutic potential of curcumin for Parkinson's disease, providing clues for microbially targeted therapies for Parkinson's disease.
GEARBOX FAULT DIAGNOSIS OPTIMIZATION USING CONVENTIONAL NEURAL NETWORKS AND MACHINE LEARNING METHODS

- Machine condition monitoring is considered an effective approach for performing maintenance in a variety of industries. The gearbox is susceptible to failure under difficult working conditions, so it requires the practice of fault diagnosis. Deep learning has been shown to be efficient in vector assessment and vibration signal analysis. The main advantage of the method is the ability to extract representative information and sensitive features from raw data. However, the application of deep learning in feature extraction for vibration diagnosis is currently restricted, and little research has compared the efficacy of feature learning with different data types. This research aims to develop a convolutional neural network (CNN) with different configurations to learn features directly from the time series data of vibration signals and to evaluate the effectiveness of learning features from raw data. Seven typical machine learning methods are provided as comparisons. The reliability of the proposed approach is validated using UoC gearbox data. The results confirm that the proposed approach can adaptively learn features from time data and achieve higher diagnostic accuracy than comparable traditional techniques.
GaN junctionless trigate field-effect transistor with deep-submicron gate length: Characterization and modeling in RF regime

Radio-frequency (RF) performances of a gallium nitride (GaN)-based junctionless (JL) trigate field-effect transistor (TGFET), or fin-shaped FET (FinFET), are demonstrated along with RF modeling for the first time. The fabricated GaN JL TGFET had a gate length of 350 nm and had no AlGaN/GaN heterojunction on which conventional high-mobility electron transistors (HEMTs) had been based to have a fully junctionless channel. The device with five fin channels exhibits a maximum drain current of 403 mA/mm and maximum transconductance of 123.6 mS/mm. The maximum cutoff frequency (fT) and maximum oscillation frequency (fmax) are 2.45 and 9.75 GHz, respectively. In order to confirm its potential for high-frequency applications, small-signal modeling has been carried out up to a frequency above the maximum fT.