Miracle-dz/UniFAR-FTUs huggingface dataset:
Malware Detection Using Machine Learning Algorithms and Reverse Engineering of Android Java Code

This research paper is focused on the issue of mobile application malware detection by Reverse Engineering of Android java code and use of Machine Learning algorithms. The malicious software characteristics were identified based on a collected set of total number of 1958 applications (including 996 malware applications). During research a unique set of features was chosen, then three attribute selection algorithms and five classification algorithms (Random Forest, K Nearest Neighbors, SVM, Nave Bayes and Logistic Regression) were examined to choose algorithms that would provide the most effective rate of malware detection.
Improved SiC MOSFET SPICE Model to Avoid Convergence Errors

This paper presents improvements to a SPICE model for a commercially available SiC MOSFET to avoid convergence errors while still providing reliable simulation results. Functionality in the internal part of the model that shapes the transconductance of the device according to its junction temperature and gate-source voltage dependency has been improved to provide a continuous characteristic rather than the initial discontinuous performance. Furthermore, the output characteristics from the initial and the proposed model have been compared to lab measurements of an actual device. The results show that the proposed and initial model provide equally reliable simulation results. However, the proposed model does not run into convergence problems.
Synthesis and Characterization of Cobalt Ferrite Nanoparticles via Sol-Gel Auto Combustion Method

This article reports the synthesis of cobalt ferrite (CoFe2O4) nanoparticles by low-cost sol-gel auto combustion method. The synthesized CoFe2O4 nanoparticles were characterized using X-ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM), Energy Dispersive X-ray (EDX), UV-Visible (UV-Vis), Fourier Transform Infrared Spectroscopy (FTIR) and Vibrating Sample Magnetometry (VSM). The XRD pattern inferred the formation of cubic spinel structure with average crystallite size 35.3 nm. The crystallite size was obtained in the range 32-37.5 nm in FESEM analysis. The elemental composition was confirmed using EDX spectroscopy. The presence of spectral lines at positions 465.57 cm-1 and 577.52 cm-1 associated to stretching vibrations of Co-O in octahedral sites and Fe-O in tetrahedral sites confirmed the spinel structure. The magnetic properties such as saturation magnetization (Ms) 67.79 emu/g, coercivity (Oe) 874.76 Oe and remnant (Mr) 29.07 emu/g were obtained from the hysteresis curve. The bandgap 1.409 eV was obtained for synthesized CoFe2O4 using Tauc plot from UV-Vis absorption spectra.
Evaluation of p-Type 4H-SiC Piezoresistance Coefficients in (0001) Plane Using Numerical Simulation

A numerical simulation of p-type 4H-Silicon Carbide (4H-SiC) piezoresistance coefficients in (0001) plane evaluation is shown in this study. A 4H-SiC material has outstanding material characteristics of wide band-gap of 3.26 eV and high temperature robustness. However, many material properties of 4H-SiC material are still unknown, including piezoresistance coefficients. Piezoresistive effect is resistivity change when mechanical stress is applied to the material. Piezoresistance coefficients express the magnitude of this effect, important for designing a mechanical stress sensor. In this study, reported piezoresistance coefficients of p-type 4H-SiC in (0001) plane is evaluated based on numerical simulation. The simulated results of Gauge Factor (GF) values (determined by (ΔR/R)/ε (R is the resistance and ε is the strain of material)) well matched to the theoretical GF values (determined by πE (π is the piezoresistance coefficient and E is Young’s modulus of the material)), shows that reported piezoresistance coefficients are reliable. Also, the internal mappings of piezoresistive effect from the numerical simulation are shown, useful to understand piezoresistive effect which is difficult to see by experimental results.
Quantities of Intra- and Extracellular DNA Reveal Information About Activity and Physiological State of Methanogenic Archaea

Although being a common aim of many microbial ecology studies, measuring individual physiological conditions of a microbial group or species within a complex consortium is still a challenge. Here, we propose a novel approach that is based on the quantification of sequentially extracted extracellular (exDNA) and intracellular DNA (iDNA) and reveals information about cell lysis and activity of methanogenic archaea within a biogas-producing microbial community. We monitored the methane production rates of differently treated batch anaerobic cultures and compared the concentrations of the alpha subunit of the methyl coenzyme M reductase gene of methanogenic archaea in extracellular and intracellular DNA fractions and in the classically extracted total DNA pool. Our results showed that this fine-tuned DNA approach coupled with the interpretation of the ratio between free exDNA and iDNA considerably improved microbial activity tracking compared to the classical extraction/quantification of total DNA. Additionally, it allowed to identify and quantify methanogenic populations that are inactive and those that are strongly influenced by cell lysis. We argue that despite the need of further studies, this method represents a novel approach to gain specific physiological information from a complex environmental sample and holds the potential to be applied to other microbes of interest.
Laboratory-Based Factors Predicting Skiing Performance in Female and Male Biathletes

Skiing in biathlon is a high-intensity, intermittent endurance discipline. This study aimed to evaluate the relationships between laboratory-derived physiological variables and skiing performance during a field-based biathlon competition (BC) for female and male biathletes. Fourteen female (23 ± 3 year, V˙O2max 56 ± 4 mL·kg−1·min−1) and 14 male (24 ± 4 year, V˙O2max 66 ± 3 mL·kg−1·min−1) biathletes performed a submaximal incremental test and a maximal time-trial (TT) using treadmill roller-skiing for the assessment of oxygen uptake at a lactate threshold of 4 mmol·L−1 (V˙O2@4mmol), gross efficiency (GE), aerobic (MRae) and anaerobic (MRan) metabolic rates, peak oxygen consumption (V˙O2peak), anaerobic capacity and TT performance. Field-based skiing performance was assessed during a BC. The TT and BC skiing performances were significantly correlated in both sexes (r = 0.68–0.69, p < 0.01). V˙O2peak (31/21%), anaerobic capacity (1/0%), and GE (35/32%) explained 67 and 52% of the variance in BC skiing performance for the females (p < 0.01) and males (p = 0.051), respectively. A second model showed that V˙O2@4mmol (30/35%), anaerobic capacity (0/0%) and GE (37/13%) explained 67 and 48% of the variance in BC skiing performance for the females (p < 0.01) and males (p = 0.077), respectively. Results of this study suggest that a high V˙O2@4mmol and GE, but not anaerobic capacity, are important for BC skiing performance, especially for females. In addition, a laboratory-based TT could be useful for regular laboratory testing of biathletes due to its relationship with field-based skiing performance in biathlon.
Social Learning and the Brain: How Do We Learn From and About Other People?

When you think about learning, you probably think about things you are taught at school. But have you ever realized you use a different type of learning as well, on a daily basis? This type of learning is called social learning, and it has to do with the people around you. That is, you learn from and about others by watching and interacting with them. For example, seeing someone else’s mistakes may teach you to avoid falling into the same trap. Although social learning happens very often, you may not yet know much about it. However, social learning is very important because it helps us to learn more efficiently and to determine how best to behave around others. In this article, we introduce two different types of social learning, and explain how your brain plays an important role.
Purification and characterization of a protein that binds to the recombination signal sequence of the immunoglobulin Jx segment

Abstract A protein that binds to the recombination signal sequence (RS) of the immunoglobulin J kappa segment was purified almost to homogeneity from the nuclear extract of a murine pre-B cell line 38B9. A similar binding protein was found in lymphoid cell lines but not in non-lymphoid cell lines. The binding activity was associated with a polypeptide with a molecular weight of 60,000. DNase I footprinting analysis demonstrated that this binding protein interacted with the heptamer and several 3' bases close to the heptamer. The Kd value of the J kappa RS binding protein to the J kappa RS was 1 nM. One base substitution in the heptamer of the J kappa RS greatly reduced the affinity of the J kappa RS binding protein. The high specificity of the binding site of the J kappa RS binding protein suggests that this protein may be involved in V-J recombination.
A Study of the Relationship Between Uric Acid and Substantia Nigra Brain Connectivity in Patients With REM Sleep Behavior Disorder and Parkinson's Disease

Low levels of the natural antioxidant uric acid (UA) and the presence of REM sleep behavior disorder (RBD) are both associated with an increased likelihood of developing Parkinson's disease (PD). RBD and PD are also accompanied by basal ganglia dysfunction including decreased nigrostriatal and nigrocortical resting state functional connectivity. Despite these independent findings, the relationship between UA and substantia nigra (SN) functional connectivity remains unknown. In the present study, voxelwise analysis of covariance was used in a cross-sectional design to explore the relationship between UA and whole-brain SN functional connectivity using the eyes-open resting state fMRI method in controls without RBD, patients with idiopathic RBD, and PD patients with and without RBD. The results showed that controls exhibited a positive relationship between UA and SN functional connectivity with left lingual gyrus. The positive relationship was reduced in patients with RBD and PD with RBD, and the relationship was found to be negative in PD patients. These results are the first to show differential relationships between UA and SN functional connectivity among controls, prodromal, and diagnosed PD patients in a ventral occipital region previously documented to be metabolically and structurally altered in RBD and PD. More investigation, including replication in longitudinal designs with larger samples, is needed to understand the pathophysiological significance of these changes.
Microbial Profile During Pericoronitis and Microbiota Shift After Treatment

The microflora of the distal pocket is considered as the major cause of pericoronitis. How the oral microflora changes during pericoronitis and whether different types of impacted third molar harbor the same microflora are still unknown. Saliva, subgingival plaque, and gingival plaque of mandibular third molars (M3Ms) were collected from twelve patients with acute pericoronitis. They were given local irrigation or local irrigation + antibiotics according to symptoms. Samples were harvested at the first visit with pericoronitis, 1 week after treatment, and 6 weeks after treatment. 16S rRNA gene polymerase chain reaction products were generated and sequenced after DNA isolation. Comparison of three sampling sites showed that, the subgingival plaque of M3Ms had most remarkable changes in symptomatic period, including a significant increase in microbial richness, and a convergent trend in microbial composition. After treatment, the subgingival microbiome was altered and largely returned to the state in asymptomatic period. In summary, the distal subgingival microbiota of M3M was most likely to be associated with the pathogenesis of pericoronitis. The post-treatment microbiota shift of M3M proved the effectiveness of treatment. The inclination type of impacted M3Ms and treatment method would also make a difference to the pericoronal microbiota.
HuD Binds to and Regulates Circular RNAs Derived From Neuronal Development- and Synaptic Plasticity-Associated Genes

The RNA-binding protein (RBP) HuD is involved in neuronal differentiation, regeneration, synaptic plasticity and learning and memory. RBPs not only bind to mRNAs but also interact with several types of RNAs including circular RNAs (circRNAs), a class of non-coding RNAs generated by pre-mRNA back-splicing. This study explored whether HuD could regulate the expression of neuronal circRNAs. HuD controls target RNA’s fate by binding to Adenylate-Uridylate Rich Elements (AREs). Using bioinformatics analyses, we found HuD-binding ARE-motifs in about 26% of brain-expressed circRNAs. By RNA immunoprecipitation (RIP) from the mouse striatum followed by circRNA arrays, we identified over 600 circRNAs bound to HuD. Among these, 226 derived from genes where HuD also bound to their associated mRNAs including circHomer1a, which we previously characterized as a synaptic HuD target circRNA. Binding of HuD to two additional plasticity–associated circRNAs, circCreb1, and circUfp2, was validated by circRNA-specific qRT-PCR. Interestingly, we found that circUpf2 is also enriched in synaptosomes. Pathway analyses confirmed that the majority of HuD-bound circRNAs originate from genes regulating nervous system development and function. Using striatal tissues from HuD overexpressor (HuD-OE) and knock out (KO) mice for circRNA expression analyses we identified 86 HuD-regulated circRNAs. These derived from genes within the same biological pathways as the HuD RIP. Cross-correlation analyses of HuD-regulated and HuD-bound circRNAs identified 69 regulated in either HuD-OE or HuD-KO and 5 in both sets. These include circBrwd1, circFoxp1, and circMap1a, which derive from genes involved in neuronal development and regeneration, and circMagi1 and circLppr4, originating from genes controlling synapse formation and linked to psychiatric disorders. These circRNAs form competing endogenous RNA (ceRNA) networks including microRNAs and mRNAs. Among the HuD target circRNAs, circBrwd1 and circFoxp1 are regulated in an opposite manner to their respective mRNAs. The expressions of other development- and plasticity-associated HuD target circRNAs such as circSatb2, cirHomer1a and circNtrk3 are also altered after the establishment of cocaine conditioned place preference (CPP). Collectively, these data suggest that HuD interactions with circRNAs regulate their expression and transport, and that the ensuing changes in HuD-regulated ceRNA networks could control neuronal differentiation and synaptic plasticity.
Predicting Leadership Competency Development and Promotion Among High-Potential Executives: The Role of Leader Identity

We propose that distinct leadership competencies differ in their development over time. Extending the integrative model of leader development (Day et al., 2009), we further propose that leader identity will form complex relationships with leadership competencies over time. To test these propositions, we use longitudinal data (i.e., 5 months, four measurement points) of the 80 in total high-potential executives in a corporate leadership development program. We find a significant difference in the initial levels and the changes of eight distinct leadership competencies. We also find that leader identity relates to the development of certain – but not all – leadership competencies. Finally, we demonstrate the importance of developing leadership competencies by linking them to career advancement (i.e., job promotion). These findings are discussed in light of their theoretical and practical implications.
Chimeric Antigen Receptor, Teamwork, Education, Assessment, and Management (CAR-TEAM): A Simulation-Based Inter-professional Education (IPE) Intervention for Management of CAR Toxicities

Chimeric antigen receptor (CAR) therapies such as tisagenlecleucel, indicated for children and young adults with relapsed and/or refractory CD19+ acute lymphoblastic leukemia (ALL), have been associated with striking treatment outcomes and overall survival. Yet, they are also associated with unique and potentially life-threatening complications. Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity (ICANS) are generally reversible complications of CAR therapies, but many patients may require critical care support especially if they are not promptly recognized and appropriately managed by frontline healthcare staff. As CAR therapies become more widely available, it is important that inter-professional staff members be aware of general principles regarding diagnosis and management. We hypothesized that an inter-professional education (IPE) simulation-based education intervention (CAR-TEAM) would improve knowledge base and confidence regarding complications of CAR therapies among inter-professional staff. Here, we demonstrate that following CAR-TEAM training, >90% of participants demonstrated knowledge proficiency and confidence in the IPE content area. CAR-TEAM training may serve as an important tool to establish initial and continued competency among sites introducing CAR therapies.
Newly Isolated Acidithiobacillus sp. Ksh From Kashen Copper Ore: Peculiarities of EPS and Colloidal Exopolysaccharide

A novel strain of an iron- and sulfur-oxidizing bacterium was isolated from a natural biotope at Kashen copper ore (Martakert Province, Republic of Artsakh). The strain is able to grow and oxidize ferrous ions in the range of pH 1.4–2.6 with optimal pH 2.0. The optimal temperature for growth is 35°C. Acidithiobacillus sp. Ksh has shown the highest activity for pyrite oxidation among other strains. It also demonstrated high activity in oxidation for copper and copper-gold bearing ores (Armenia). The isolate Acidithiobacillus sp. Ksh was identified as Acidithiobacillus ferrooxidans based on phylogenetic and physiological studies. Comparative studies of EPS production by cells grown on ferrous ions or pyrite were carried out. The chemical composition of capsular and colloidal EPS produced by Acidithiobacillus (At.) ferrooxidans Ksh were revealed to be proteins and carbohydrates. Exosaccharide produced by At. ferrooxidans Ksh is present mainly as polysaccharide in contrast to Leptospirillum (L.) ferriphilum CC, which is oligosaccharide. The structural difference of colloidal particles of these polysaccharides was due to the degree of hydration of the saccharide molecules.
Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic Computing

Hand gestures are a form of non-verbal communication used by individuals in conjunction with speech to communicate. Nowadays, with the increasing use of technology, hand-gesture recognition is considered to be an important aspect of Human-Machine Interaction (HMI), allowing the machine to capture and interpret the user's intent and to respond accordingly. The ability to discriminate between human gestures can help in several applications, such as assisted living, healthcare, neuro-rehabilitation, and sports. Recently, multi-sensor data fusion mechanisms have been investigated to improve discrimination accuracy. In this paper, we present a sensor fusion framework that integrates complementary systems: the electromyography (EMG) signal from muscles and visual information. This multi-sensor approach, while improving accuracy and robustness, introduces the disadvantage of high computational cost, which grows exponentially with the number of sensors and the number of measurements. Furthermore, this huge amount of data to process can affect the classification latency which can be crucial in real-case scenarios, such as prosthetic control. Neuromorphic technologies can be deployed to overcome these limitations since they allow real-time processing in parallel at low power consumption. In this paper, we present a fully neuromorphic sensor fusion approach for hand-gesture recognition comprised of an event-based vision sensor and three different neuromorphic processors. In particular, we used the event-based camera, called DVS, and two neuromorphic platforms, Loihi and ODIN + MorphIC. The EMG signals were recorded using traditional electrodes and then converted into spikes to be fed into the chips. We collected a dataset of five gestures from sign language where visual and electromyography signals are synchronized. We compared a fully neuromorphic approach to a baseline implemented using traditional machine learning approaches on a portable GPU system. According to the chip's constraints, we designed specific spiking neural networks (SNNs) for sensor fusion that showed classification accuracy comparable to the software baseline. These neuromorphic alternatives have increased inference time, between 20 and 40%, with respect to the GPU system but have a significantly smaller energy-delay product (EDP) which makes them between 30× and 600× more efficient. The proposed work represents a new benchmark that moves neuromorphic computing toward a real-world scenario.
Climate, trophic interactions, density dependence and carry‐over effects on the population productivity of a migratory Arctic herbivorous bird

Several driving forces can aff ect recruitment rates in bird populations. However, our understanding of climate-induced eff ects or bottom–up vs top–down biological processes on breeding productivity typically comes from small-scale studies, and their relative importance is rarely investigated at the population level. Using a 31-year time series, we examined the eff ects of selected environmental parameters on the annual productivity of a key Arctic herbivore, the greater snow goose Anser caerulescens atlanticus. We determined the extent to which breeding productivity, defi ned as the percentage of juveniles in the fall population, was aff ected by 1) climatic conditions, 2) fl uctuations in predation pressure caused by small rodent oscillations, and 3) population size. Moreover, we took advantage of an unplanned large-scale manipulation (i.e. management action) to examine the potential non-lethal carry-over eff ects caused by disturbance on spring staging sites. Th e most parsimonious model explained 66% of the annual variation in goose productivity. Th e spring North Atlantic Oscillation and Arctic snow depth were the primary climatic parameters inversely aff ecting the production of juveniles, likely through bottom–up processes. Indirect trophic interactions generated by fl uctuations in lemming abundance explained 18% of the variation in goose productivity (positive relationship). Mean temperature during brood-rearing and disturbance on staging sites (carry-over eff ects) were the other important factors aff ecting population recruitment. We observed a strong population increase, and found no evidence of density-dependent eff ects. Spatially restricted studies can identify factors linking environmental parameters to local bird reproduction but if these factors do not act synchronously over the species range, they may fail to identify the relative importance of mechanisms driving large-scale population dynamics.