Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and diagnosis of skin diseases by using snake algorithm and neural networks

This research presents a medical application to diagnose types of skin diseases based on the axis of dermatology, where a computer intelligent system was built based on identifying and diagnosing the type of skin inflammation, and this system called (SANN) (Snake Algorithm Neural Network). The system consists of two stages, the first stage is the axis of locating the presence of skin inflammation and distinguish it from uninfected skin by performing the initial processing of the image using the snake algorithm. while the second stage using neural networks to diagnose types of skin disease that were identified in the first stage by adding some improvements to the neural networks to work more efficiently for diagnosis. The suggested SANN system was applied to 250 images, and the accuracy and execution time were calculated. The results showed that using the system based on the snake algorithm and neural networks in the process of identifying and diagnosing types of dermatitis (psoriasis or Spider birthmark) achieves high performance and accuracy, and gave a diagnosis rate of 88.9%
Muscle Strength, Physical Fitness, Balance, and Walking Ability at Risk of Fall for Prefrail Older People

Aim This study was to explore the relationship of older adults' demographic information, physiological indices, and stages of frailty with their risk of falling. Methods In the cross-sectional study, a total of 221 older adults with the mean age 74.9 (SD = 6.8) years old were surveyed by senior fitness test. Results Results were observed in terms of participants' physical fitness, with significant differences being observed in the correlations of left-hand grip strength (t = 5.05, p < .000), right-hand grip strength (t = 6.03, p < .000), and total grip strength (t = 5.70, p < .000), time up and go test (t = −6.25, p < .000), and 30-sec chair stand test (t = 7.19, p < .000) with the risk of falling. According to the logistic regression analysis results, long-term medication (OR = 0.12, 95% CI =0.02-0.62, p < .01) and right-hand grip strength (OR = 0.86, 95% CI =0.76-0.97, p < .01) are the main predictors of older adults' risk of falling. Conclusions Older females with low education, history of falls, weaker grip strengths; taking longer to finish the TUG test; and standing fewer times during the 30-second chair stand test were at risk of fall. In prediction, older people using long-term medication were at lower risk of falling, and the greater the hand grip strength was, the lower the fall risk was. According to the research results, nursing personnel must develop care programs and improve older adults' risk of falls.
FINITE-ELEMENT ANALYSIS OF PHASE-CHANGE PROBLEMS USING MULTILEVEL TECHNIQUES

Abstract A simple and effective finite-element procedure is presented for the analysis of transient heat transfer with phase changes. An averaged specific heat is employed to simulate the elements including the phase-change zone in this finite-element analysis with fixed mesh. Due to the use of a Gauss-Seidel method and a multigrid algorithm, the computational complexity can be reduced from O(n3) to 0(n In n) with high storage efficiency. The computational results are also in very good agreement with the exact solutions. Results show that the magnitudes of the lime step and freezing-temperature interval have little effects on the maximal and average errors. As a result, a larger time step can be used to save computing time and achieve the same order of accuracy. This algorithm is available for pure metals and alloys that exhibit discontinuous specific heat.
Green Extraction of Graphene from Natural Mineral Shungite

Conventional fabrication methods to produce graphene are cumbersome, expensive, and not ecologically friendly. This is due to the fact that the processing of a large volume of raw materials requires large amounts of acids and alkalis which, in turn, require special disposal. Therefore, it is necessary to develop new technologies or to refine existing ones for the production of graphene—and to create new, ecologically-safe and effective methods. Here, we utilized physical sonication to extract graphene films from natural mineral shungite rock. From our study of the structure of shungite by Raman spectrometry and X-ray phase analysis, we found that shungite is characterized by graphite-like mineral structures. Transmission electron microscopy images obtained from the processed material revealed graphene films—with surfaces as small as 200 nanometers long and several layers wide. Our green method of fabicating graphene can be widely used in a variety of fields, from electro-optics to ecology, to list a few.
Acute Pancreatitis Associated with Atypical Bacterial Pneumonia: Systematic Literature Review

Background: Extra-pulmonary features sometimes occur in association with atypical bacterial pneumonia and include neurologic manifestations, diarrhea, rashes, altered liver enzymes, or kidney injury, among other conditions. Acute pancreatitis has been associated with atypical pneumonias since 1973. Methods: We performed a systematic review of the literature in the Excerpta Medica, National Library of Medicine, and Web of Science databases. We retained 27 reports published between 1973 and 2022 describing subjects with an otherwise unexplained pancreatitis temporally associated with an atypical pneumonia. Results: The reports included 33 subjects (19 males, and 14 females; 8 children and 25 adults) with acute pancreatitis temporally associated with atypical pneumonia caused by Mycoplasma pneumoniae (n = 18), Legionella species (n = 14), or Coxiella burnetii (n = 1). Approximately 90% of patients (n = 29) concurrently presented with respiratory and pancreatic diseases. No cases associated with Chlamydophila pneumoniae, Chlamydophila psittaci, or Francisella species were found. Conclusions: Acute pancreatitis has been associated with various infectious agents. The present review documents the association with atypical pneumonia induced by Mycoplasma pneumoniae, Legionella species, and Coxiella burnetii.
“We Like That It Matters!”: Towards a Socially Sustainable Retail Store Brand Experience

Social sustainability is a topic that is gaining increased attention and yet has not been overly discussed, in particular with reference to the fashion industry. There is a shift in consumer demands, where brands are urged to stand for values, affect change in the industry, and have a clear purpose and positive impact over society. At the same time, brands are struggling to provide offers beyond products, or product-related experiences, at the risk of dissatisfying consumers expectations. Part of such dissatisfaction is clearly represented by the lack of footfall in retail stores and the fast-pace abandonment of the high-street by brands that cannot afford empty stores. This paper suggests an opportunity to rethink the retail store functionality as a space for brands to provide consumers with educational initiatives related to important societal issues, hence build their socially responsible profile. A netnographic exploratory analysis of Patagonia platforms was conducted in order to pinpoint potential positive reaction to a purpose-driven brand and its educational initiatives. The brand was chosen due to its value-committed strategy and constant educational effort towards consumers, both offline (product-related) and online (societal-related). This paper suggests that brands such as Patagonia, purpose and value driven in positively impacting society, should bring their activism and educational efforts on the high-street and in the retail spaces. By doing so, brands would concurrently provide consumers with experiences beyond product consumption, could revitalise our high-street, and could reinstate a sense of community belonging while raise their socially sustainable profile. This paper contributes to the existing literature of consumer education in retailing by expanding into the specific domain of fashion, a domain in which many social issues could be successfully addressed through a socially-driven consumer education at the moment still overlooked by researchers and brands.
Regulation of P-glycoprotein and Breast Cancer Resistance Protein Expression Induced by Focused Ultrasound-Mediated Blood-Brain Barrier Disruption: A Pilot Study

The blood-brain barrier (BBB) controls brain homeostasis; it is formed by vascular endothelial cells that are physically connected by tight junctions (TJs). The BBB expresses efflux transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), which limit the passage of substrate molecules from blood circulation to the brain. Focused ultrasound (FUS) with microbubbles can create a local and reversible detachment of the TJs. However, very little is known about the effect of FUS on the expression of efflux transporters. We investigated the in vivo effects of moderate acoustic pressures on both P-gp and BCRP expression for up to two weeks after sonication. Magnetic resonance-guided FUS was applied in the striatum of 12 rats. P-gp and BCRP expression were determined by immunohistochemistry at 1, 3, 7, and 14 days postFUS. Our results indicate that FUS-induced BBB opening is capable of (i) decreasing P-gp expression up to 3 days after sonication in both the treated and in the contralateral brain regions and is capable of (ii) overexpressing BCRP up to 7 days after FUS in the sonicated regions only. Our findings may help improve FUS-aided drug delivery strategies by considering both the mechanical effect on the TJs and the regulation of P-gp and BCRP.
Dynamic security log processing using deep learning techniques

—Recently, the number of discovered cyber attacks increases rapidly. Tools for stealing personal data, destroying systems, or controlling infrastructure become continuously sophisticated to achieve malicious aims. Companies are trying to reduce the number of risks on their assets by using various security monitoring devices and tools. SIEM solutions are used for security monitoring, allowing different logs to be correlated. They offer visibility for security teams and allow early response to attacks. The main problem of SIEM software is the implementation of log parsing, which directly influences correlation rules efficiency. Usually, the biggest limitation is parsing dynamic log structures from different event sources. The main contribution of this paper is to apply advanced deep neural networks which use attention mechanisms for efficient log content parsing and its understanding. The proposed question answering model for feature extraction from raw logs should achieve automatic log procession. Obtained results show indisputable advantages of deep attention techniques compared to the common approaches.
A Robust Computer-Aided Automated Brain Tumor Diagnosis Approach Using PSO-ReliefF Optimized Gaussian and Non-Linear Feature Space

Brain tumors are among the deadliest diseases in the modern world. This study proposes an optimized machine-learning approach for the detection and identification of the type of brain tumor (glioma, meningioma, or pituitary tumor) in brain images recorded using magnetic resonance imaging (MRI). The Gaussian features of the image are extracted using speed-up robust features (SURF), whereas its non-linear features are obtained using KAZE, owing to their high performance against rotation, scaling, and noise problems. To retrieve local-level information, all brain MRI images are segmented into an 8 × 8 pixel grid. To enhance the accuracy and reduce the computational time, the variance-based k-means clustering and PSO-ReliefF algorithms are employed to eliminate the redundant features of the brain MRI images. Finally, the performance of the proposed hybrid optimized feature vector is evaluated using various machine learning classifiers. An accuracy of 96.30% is obtained with 169 features using a support vector machine (SVM). Furthermore, the computational time is also reduced to 1 min compared to the non-optimized features used for training of the SVM. The findings are also compared with previous research, demonstrating that the suggested approach might assist physicians and doctors in the timely detection of brain tumors.
Hydroxyl absorption in NGC 520, NGC 2623, and NGC 6240

On rapporte les observations de l'absorption extragalactique d'hydroxyle pour les galaxies NGC 520, NGC 2623 et NGC 6240. On a egalement observe une absorption HI. Les caracteristiques des raies d'absorption OH extragalactiques sont compatibles avec l'existence de disques moleculaires denses dans les regions interieures des galaxies
Design and Modeling of a Fully Integrated Microring-Based Photonic Sensing System for Liquid Refractometry

The design of a refractometric sensing system for liquids analysis with a sensor and the scheme for its intensity interrogation combined on a single photonic integrated circuit (PIC) is proposed. A racetrack microring resonator with a channel for the analyzed liquid formed on the top is used as a sensor, and another microring resonator with a lower Q-factor is utilized to detect the change in the resonant wavelength of the sensor. As a measurement result, the optical power at its drop port is detected in comparison with the sum of the powers at the through and drop ports. Simulations showed the possibility of registering a change in the analyte refractive index with a sensitivity of 110 nm per refractive index unit. The proposed scheme was analyzed with a broadband source, as well as a source based on an optoelectronic oscillator using an optical phase modulator. The second case showed the fundamental possibility of implementing an intensity interrogator on a PIC using an external typical single-mode laser as a source. Meanwhile, additional simulations demonstrated an increased system sensitivity compared to the conventional interrogation scheme with a broadband or tunable light source. The proposed approach provides the opportunity to increase the integration level of a sensing device, significantly reducing its cost, power consumption, and dimensions.
Entire solutions for some reaction–diffusion systems

This paper is concerned with the existence of entire solutions of some reaction–diffusion systems. We first consider Belousov–Zhabotinskii reaction model. Then we study a general model. Using the comparing argument and sub-super-solutions method, we obtain the existence of entire solutions which behave as two wavefronts coming from the both sides of x-axis, where an entire solution is meant by a classical solution defined for all space and time variables. At last, we give some examples to explain our results for the general models.
Heterozygote Dopamine Transporter Knockout Rats Display Enhanced Cocaine Locomotion in Adolescent Females

Cocaine is a powerful psychostimulant that is one of the most widely used illicit addictive. The dopamine transporter (DAT) plays a major role in mediating cocaine’s reward effect. Decreases in DAT expression increase rates of drug abuse and vulnerability to comorbid psychiatric disorders. We used the novel DAT transgenic rat model to study the effects of cocaine on locomotor behaviors in adolescent rats, with an emphasis on sex. Female rats showed higher response rates to cocaine at lower acute and chronic doses, highlighting a higher vulnerability and perceived gender effects. In contrast, locomotor responses to an acute high dose of cocaine were more marked and sustained in male DAT heterozygous (HET) adolescents. The results demonstrate the augmented effects of chronic cocaine in HET DAT adolescent female rats. Knockout (KO) DAT led to a level of hyperdopaminergia which caused a marked basal hyperactivity that was unchanged, consistent with a possible ceiling effect. We suggest a role of alpha synuclein (α-syn) and PICK 1 protein expressions to the increased vulnerability in female rats. These proteins showed a lower expression in female HET and KO rats. This study highlights gender differences associated with mutations which affect DAT expression and can increase susceptibility to cocaine abuse in adolescence.
Technological Innovation to Support 21st Century Learning Outcomes and Sustainability at Universitas Islam Negeri (UIN) Antasari

This study analyzes how technological innovation supports and improves student learning outcomes and sustainability at Universitas Islam Negeri (UIN) Antasari. This study obtained data from interviews with senior lecturers and researchers and 12 resource persons, and 12 open questions. We conducted a series of questions for interviews and a literature study to understand how this change occurred. Next, the researchers analyzed the interview results with a phenomenological approach; to ascertain how technological innovation supports 21st-century learning in higher education. Based on the existing data and discussion, concluded that technological innovations such as the internet and digital applications currently in academic activities in the distance learning process and student face-to-face classes strongly support that goal. This considers the penetration of the internet and computer technology used in learning and teaching. With the experience of lecturers and students at UIN Antasari. Technological innovation supports learning there with the clear advantages of existing technology. Thus, it is hoped that the results of this study be helpful to improve the quality of further research. Keywords: Technological Innovation, 21st-Century Learning Outcomes, Learning Outcome
Potential targets of severe acute respiratory syndrome coronavirus 2 of clinical drug fluvoxamine: Docking and molecular dynamics studies to elucidate viral action

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has continued evolving for survival and adaptation by mutating itself into different variants of concern, including omicron. Several studies and clinical trials found fluvoxamine, an Food and Drug Administration‐approved antidepressant drug, to be effective at preventing mild coronavirus disease 2019 (COVID‐19) from progressing to severe diseases. However, the mechanism of fluvoxamine's direct antiviral action against COVID‐19 is still unknown. Fluvoxamine was docked with 11 SARS‐CoV‐2 targets and subjected to stability, conformational changes, and binding free energy analyses to explore its mode of action. Of the targets, nonstructural protein 14 (NSP14), main protease (Mpro), and papain‐like protease (PLpro) had the best docking scores with fluvoxamine. Consistent with the docking results, it was confirmed by molecular dynamics simulations that the NSP14 N7‐MTase ((N7‐guanine)‐methyltransferase)–fluvoxamine, Mpro–fluvoxamine, and PLpro–fluvoxamine complexes are stable, with the lowest binding free energies of −105.1, −82.7, and − 38.5 kJ/mol, respectively. A number of hotspot residues involved in the interaction were also identified. These include Glu166, Asp187, His41, and Cys145 in Mpro, Gly163 and Arg166 in PLpro, and Glu302, Gly333, and Phe426 in NSP14, which could aid in the development of better antivirals against SARS‐CoV‐2.
Estimating Household Preferences for Coastal Flood Risk Mitigation Policies Under Ambiguity

Risk mitigation policies (like dike rising) are essential to address increasing coastal flood risks due to global warming. Furthermore, the optimal level of risk mitigation policy should be determined by public preferences for risk reduction. However, it is difficult to reveal public preferences for coastal flood risk reduction because projections of coastal flood risks inevitably involve uncertainty. This study aims to estimate household preference for coastal flood reduction under ambiguity and multiple projections of coastal flood risks. By coupling storm surge inundation simulations and stated preference experiments with decision models, we estimate the expected loss reduction, risk premium, and ambiguity premium for coastal flood risk mitigation policies. The study shows that ignoring the ambiguity premium causes significant undervaluation of coastal flood risk mitigation.
Modal solutions in stratified multi-layered fluid-solid half-space

A new systematic and efficient algorithm to calculate the modal solutions of multi-layered ocean-Earth model is presented. Our algorithm distinguishes itself as terseness of formulation, efficiency in numerical computation, and stableness at high frequencies, thus, thoroughly solving the problem of loss-of-precision at high frequencies. This new algorithm is expected to be very useful in studying the surface waves propagating in ocean-Earth model and other related topics.
Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.
A meshless grain element for micromechanical analysis with crystal plasticity

This study concerns the development of a 2‐D meshless grain element for elasto‐plastic deformation and intergranular damage initiation and propagation in polycrystalline fcc metals under static loading. The crystallographic material behaviour of the grains is represented by a rate‐independent single‐crystal plasticity model while including material orthotropy. The two slip planes are arbitrarily located with respect to the crystallographic axis of the grain. A non‐linear constitutive model known as the cohesive zone model is employed to represent the inelastic interaction between the grain boundaries, thus permitting grain boundary opening and sliding. The cohesive model describes the deformation characteristics of the grain boundaries through a non‐linear relation between the effective grain boundary tractions and displacements. Because of the presence of non‐linear material behaviour both inside the grain and along the cohesive grain boundaries, the method utilizes the principle of virtual work in conjunction with the meshless formulation in the derivation of the system of non‐linear incremental equilibrium equations. The solution is obtained via an incremental procedure based on the Taylor series expansion about the current equilibrium configuration. The fidelity of the present approach is verified by considering simple polycrystalline metals of only a few grains. Copyright © 2006 John Wiley & Sons, Ltd.