Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment Changes and Prognoses in Patients with Incident Drug-Induced Parkinsonism Using a Korean Nationwide Healthcare Claims Database

This retrospective cohort study assessed treatment changes and prognoses after incident drug-induced parkinsonism (DIP). We used the National Health Insurance Service’s National Sample Cohort database in South Korea. We selected patients diagnosed with incident DIP and given prescriptions to take offending drugs (antipsychotics, gastrointestinal (GI) motility drugs, or flunarizine) for a period of time that overlapped with the time of DIP diagnosis during 2004–2013. The proportion of patients experiencing each type of treatment change and prognosis was assessed for 2 years after DIP diagnosis. We identified 272 patients with incident DIP (51.9% of patients were aged ≥ 60 years and 62.5% of them were women). Switching (38.4%) and reinitiation (28.8%) were the most common modifications in GI motility drug users, whereas dose adjustment (39.8%) and switching (23.0%) were common in antipsychotic users. The proportion of persistent users was higher among antipsychotic users (7.1%) than that among GI motility drug users (2.1%). Regarding prognosis, 26.9% of patients experienced DIP recurrence or persistence, the rate being the highest in persistent users and the lowest in patients who discontinued the drug. Among patients with incident DIP diagnoses, the patterns of treatment change and prognosis differed across the types of offending drugs. Over 25% of patients experienced DIP recurrence or persistence, highlighting the need for an effective strategy to prevent DIP.
Mars terrain segmentation algorithm based on improved PSPNet

Planet rovers are becoming more and more crucial as deep space exploration missions develop. Accurate terrain segmentation can increase the rovers' capacity for independent detection. At present, the task of Mars terrain segmentation is difficult and the computational resources on rover are limited. This paper proposes an improved PSPNet algorithm for Mars terrain segmentation. MobileNetV2 is a lightweight network that replaces ResNet as the feature extraction backbone network. The channel attention mechanism SEnet is integrated into the network structure to improve the network's feature extraction capability. The experimental results show that the number of parameters and calculation amount of M-PSPNet are greatly reduced when compared to traditional PSPNet, but the recall rate of M-PSPNet on soil, bedrock, sand, and big rock can reach 92%, 91%, 86%, and 72%, respectively. Engineering-wise, the M-PSPNet is competitive.
A Study on the Fire-Retardant and Sound-Proofing Properties of Stainless Steel EAF Oxidizing Slag Applied to the Cement Panel

Because of incomplete recycling resource management and technology development, inorganic sludge and slag has been misused in Taiwan. The recycling of inorganic sludge and slag is a pressing crisis. Resource materials with a sustainable use value are misplaced and have a significant impact on society and the environment, which greatly reduces industrial competitiveness. To solve the dilemma of EAF oxidizing slag recycled from the steel-making process, it is important to find solutions to improve the stability of EAF oxidizing slags based on the innovative thinking of the circular economy. We can improve the value of recycling resources and solve the contradiction between economic development and environmental impact. The project team intends to investigate the development and application of reclaiming EAF oxidizing slags blended with fire-retardant materials, which will integrate R&D work from four different aspects. First, a verification mechanism is carried out to establish stainless steel furnace materials. Suppliers must be assisted in conducting quality management for EAF oxidizing slags to ensure the quality of the materials provided. Next, high-value building materials must be developed using slag stabilization technology, and fire-retardant tests must be conducted on the recycled building materials. A comprehensive evaluation and verification of the recycled building materials must be undertaken, and high-value green building materials must be produced with fire-retardant and sound-proofing characteristics. Integration with national standards and regulations can drive the market integration of high-value building materials and the industrial chain. On the other hand, the applicability of existing regulations to facilitate the legal use of EAF oxidizing slags will be explored.
A Novel Hybrid Solving Approach Based on Combining Similarity Solutions with Laplace Transformation Technique to Solve Different Engineering Problems

In this study Laplace transformation technique combined with similarity solutions are used to solve PDE involves derivatives with respect to time and two spatial parameters. The hybrid approach is based on transforming the PDE from the real physical time domain to the Laplacian domain. The obtained PDE in the Laplacian domain involves only derivatives with respect to the two spatial parameters. This transformed PDE is then solved by similarity solution approach to convert it from a PDE in the Laplacian domain to an ODE in another domain involves independent parameter consists of the Laplace parameter s and the two independent spatial parameters. A case is discussed to demonstrate the capabilities of the proposed approach in solving different engineering problems.
The role of monocytes in malaria infection

Malaria remains one of the most common human infections worldwide. In endemic areas, malaria is a leading cause of morbidity and mortality and it imposes significant socioeconomic burdens on the people affected. Monocytes are part of the immune system controlling parasite burden and protecting the host against malaria infection. Monocytes play their protective roles against malaria via phagocytosis, cytokine production and antigen presentation. Though monocytes are crucial for clearance of malaria infection, they have also been shown to cause adverse clinical outcomes. In this review, we discuss recent findings regarding the role of monocytes in malaria via mechanisms such as parasite detection and clearance, pro-inflammatory activities, and activation of other immune components. We also highlight the role of different monocyte subsets, and other myeloid cells that are involved in malaria infection. However, more investigations are required in order to explore the exact roles of these monocytes in malaria infection.
Bio-Fabrication of Silver Nanoparticles Using Citrus aurantifolia Fruit Peel Extract (CAFPE) and the Role of Plant Extract in the Synthesis

The green synthesis of silver nanoparticles has been proposed as an eco-friendly and cost-effective substitute for chemical and physical methods. The aim of this study was to synthesize and characterize silver nanoparticles using the peel extract of Citrus aurantifolia fruit, and to determine the possible phytochemical constituents’ presence in the plant extracts that might be responsible for the synthesis. Citrus aurantifolia fruit peel extraction was followed by phytochemical studies of secondary metabolites, FTIR analysis confirmation of functional groups, and GC–MS analysis. Silver nanoparticles were synthesized through bio-reduction of silver ions (Ag+) to silver nanoparticles using CAFPE and characterized using UV-Vis spectroscopy, HR–TEM, FESEM, EDX, XRD, DLS, and FTIR. The presence of plant secondary metabolites such as alkaloids, flavonoids, tannins, saponins, phenols, terpenoids, and steroids was detected. The FTIR analysis of the extract revealed the presence of functional groups like hydroxyl, carboxyl, carbonyl, amine, and phenyl, whereas the GC–MS analysis indicated presence of chemical compounds such as 1,2,4-Benzenetricarboxylic acid, Fumaric acid, nonyl pentadecyl, and 4-Methyl-2-trimethylsilyloxy-acetophenone, etc., with similar functional groups. The synthesized silver nanoparticle (AgNP) has displayed the characteristics of a surface plasmon resonance (SPR) band peak from 360–405 nm. High resolution transmission electron microscope (HR-TEM) and field emission scan electron microscope (FESEM) confirm polydisperse, spherical shaped, and smooth surface nanoparticles with an average size of 24.023 nm. Energy dispersive X-ray (EDX) analysis further revealed that silver is the most abundant element found in the micrograph of the nanoparticles, and FTIR analysis further confirmed the presence of different functional groups in the surface of the nanoparticle. The XRD analysis also confirmed that the nanoparticles synthesized are crystalline in nature. Based on the findings of this study, it is understood that the variety of natural compounds that are present in plant extracts of Citrus aurantifolia fruit peel can act as both reducing and stabilizing agents for the synthesis of silver nanoparticles. It is, therefore, concluded that Citrus aurantifolia peel extract can be potentially used for the large production of silver nanoparticles for several applications.
A Novel Gemcitabine-Resistant Gallbladder Cancer Model Provides Insights into Molecular Changes Occurring during Acquired Resistance

Treatment options for advanced gallbladder cancer (GBC) are scarce and usually rely on cytotoxic chemotherapy, but the effectiveness of any regimen is limited and recurrence rates are high. Here, we investigated the molecular mechanisms of acquired resistance in GBC through the development and characterization of two gemcitabine-resistant GBC cell sublines (NOZ GemR and TGBC1 GemR). Morphological changes, cross-resistance, and migratory/invasive capabilities were evaluated. Then, microarray-based transcriptome profiling and quantitative SILAC-based phosphotyrosine proteomic analyses were performed to identify biological processes and signaling pathways dysregulated in gemcitabine-resistant GBC cells. The transcriptome profiling of parental and gemcitabine-resistant cells revealed the dysregulation of protein-coding genes that promote the enrichment of biological processes such as epithelial-to-mesenchymal transition and drug metabolism. On the other hand, the phosphoproteomics analysis of NOZ GemR identified aberrantly dysregulated signaling pathways in resistant cells as well as active kinases, such as ABL1, PDGFRA, and LYN, which could be novel therapeutic targets in GBC. Accordingly, NOZ GemR showed increased sensitivity toward the multikinase inhibitor dasatinib compared to parental cells. Our study describes transcriptome changes and altered signaling pathways occurring in gemcitabine-resistant GBC cells, which greatly expands our understanding of the underlying mechanisms of acquired drug resistance in GBC.
Analysis, Control, and Synchronization of a 3-D Novel Jerk Chaotic System with Two Quadratic Nonlinearities

In this research work, a seven-term 3-D novel jerk chaotic system with two quadratic nonlinearities has been proposed. The basic qualitative properties of the novel jerk chaotic system have been described in detail. Next, an adaptive backstepping controller is designed to stabilize the novel jerk chaotic system with two unknown parameters. Moreover, an adaptive backstepping controller is designed to achieve complete chaos synchronization of the identical novel jerk chaotic systems with two unknown parameters. MATLAB simulations have been shown in detail to illustrate all the main results developed for the 3-D novel jerk chaotic system.
The Predictive Power of Implied Volatility and GARCH Forecasted Volatility During the COVID-19 Pandemic: Evidence from Chinas Stock Market

In this study, we explore how the performance of several popular historical and forward-looking forecasting measures for equity index volatility is affected by the COVID-19 related uncertainty. Our findings present convincing evidence for the advantages of implied volatility in predicting future volatility in the context of the COVID-19 pandemic. Our results also reveal that GARCH forecasted volatility contains unique information about market risk, but the information efficiency is sensitive to economic uncertainty. Therefore, the empirical evidence from Chinas stock market is supportive of a popular theoretical view that GARCH and implied volatility capture different aspects of market uncertainty and an appropriate combination of both measures may perform best in terms of information efficiency. This article contributes to the stream of postCOVID19 literature on its impact on financial markets and provides useful implications for financial practitioners.
On a class of backward stochastic differential equations and applications to the stochastic resonance

In this paper, we intend to prove a result on the solvabillity of a class of backward stochastic differential equations by the McShane type. We will considered some more general conditions by the coefficient functions and prove a result on the existence and the pathwise uniqueness by the Nagumo type, extended the Athanassov results ([Athanassov, 19901) for the ordinary differential equations. In final, we study the control of some electronic circuits in the presence of the stochastic resonance.
Individuals May Improve Their Intimate Relationship by Improving Attachment, Self-esteem, and Personality

The current study aimed to examine the relationship between romantic relationships and three important factors: attachment, self-esteem and personality. These studies briefly described previous research on attachment, self-esteem and personality and their effects on romantic relationships, and discussed their malleability and application of the intervention. People with insecure attachment, low self-esteem and personality vulnerability have less satisfaction within their romantic relationships. High-quality relationships have a positive impact on the enhancement of those factors. Besides, those factors are malleable in response to social experiences and specific interventions. Attachment styles can shift after completing the process of EFT. CBT treatments are an effective approach to enhancing self-esteem and personality. These findings provide evidence that people could change their attachment, self-esteem and personality, which implies that it is possible that individuals could improve their romantic relationships by changing their attachment, self-esteem and personality.
An audit of uterine perforation and its effect on the final outcome in an academic research medical center: An optimized balance between overall treatment time and medical crisis

Purpose Intra-cavitary brachytherapy is an integral component of cervical cancer management, and uterine perforation is the most significant complication, which may lead to prolonged overall treatment time and decreased local control in these patients. Material and methods A retrospective analysis of cervical cancer patients who completed radiotherapy (external beam radiotherapy and brachytherapy) in our department was conducted to determine the incidence, effect on overall treatment time, and final outcome in patients with uterine perforation during brachytherapy procedure. Results Among 55 women, of the 398 applications, 85 (21.36%) resulted in uterine perforation. Out of these 85 applications, treatment time was extended among 3 (3.5%) applications only, as re-insertion was done nearly after one week, while the remaining 82 (96.5%) applications were completed in time. At the time of analysis, the median follow-up was 12 months, and 32 patients were disease-free, 3 had distant metastatic disease, 2 had residual disease, and 18 were lost to follow-up. Conclusions In our study, uterine perforation incidence was found to be comparable with other centers worldwide. In asymptomatic and uncomplicated uterine perforation, treatment can be continued with computer-based optimized treatment plans without loading a specific dwell position and without affecting overall treatment time.
Quantitative Evaluation of Oxygen Extraction Fraction Changes in the Monkey Brain during Acute Stroke by Using Quantitative Susceptibility Mapping

Background: The oxygen extraction fraction (OEF) indicates the brain’s oxygen consumption and can be estimated by using the quantitative susceptibility mapping (QSM) MRI technique. Recent studies have suggested that OEF alteration following stroke is associated with the viability of at-risk tissue. In the present study, the temporal evolution of OEF in the monkey brain during acute stroke was investigated using QSM. Methods: Ischemic stroke was induced in adult rhesus monkeys (n = 8) with permanent middle cerebral artery occlusion (pMCAO) by using an interventional approach. Diffusion-, T2-, and T2*-weighted images were conducted on day 0, day 2, and day 4 post-stroke using a clinical 3T scanner. Progressive changes in magnetic susceptibility and OEF, along with their correlations with the transverse relaxation rates and diffusion indices, were examined. Results: The magnetic susceptibility and OEF in injured gray matter of the brain significantly increased during the hyperacute phase, and then decreased significantly on day 2 and day 4. Moreover, the temporal changes of OEF in gray matter were moderately correlated with mean diffusivity (MD) (r = 0.52; p = 0.046) from day 0 to day 4. Magnetic susceptibility in white matter progressively increased (from negative values to near zero) during acute stroke, and significant increases were seen on day 2 (p = 0.08) and day 4 (p = 0.003) when white matter was significantly degenerated. However, significant reduction of OEF in white matter was not seen until day 4 post-stroke. Conclusion: The preliminary results demonstrate that QSM-derived OEF is a robust approach to examine the progressive changes of gray matter in the ischemic brain from the hyperacute phase to the subacute phase of stroke. The changes of OEF in gray matter were more prominent than those in white matter following stroke insult. The findings suggest that QSM-derived OEF may provide complementary information for understanding the neuropathology of the brain tissue following stroke and predicting stroke outcomes.
Family Social Support and Children’s Mental Health Resilience during COVID-19—Case of Morocco

This research aims to investigate the impact of the family on the social support for children with mental health disorders in a vulnerable environment such as the COVID-19 pandemic and the ability of parents to provide consistent care giving using their social support. The main question of this research paper is: what is the impact of the family in the situation of COVID-19 on the diversity of the processes actors provided in creating social adaptability for children with mental health? The previous question was treated via the following hypotheses: H1: the more the whole family is committed to the social support of the child with a mental health disorder, the less independent the achievement of resilience on an individual basis; H2: the more the child with a mental illness belongs to the family, the greater the family’s involvement in social support, even for low-income families. This quantitative field study was conducted in southern Morocco by contacting a sample of respondents (86 respondents) from health institutions, civil society, and the children’s parents and relatives. The study reflected two main findings: that the majority of children were with their families during the pandemic; and the lack of independence of parents and children in the adjustment process.
Determination of broken KAM surfaces for particle orbits in toroidal confinement systems

The destruction of Kolmogorov–Arnold–Moser surfaces in a Hamiltonian system is an important topic in nonlinear dynamics, and in particular in the theory of particle orbits in toroidal magnetic confinement systems. Analytic models for transport due to mode-particle resonances are not sufficiently correct to give the effect of these resonances on transport. In this paper we compare three different methods for the detection of the loss of stability of orbits in the dynamics of charged particles in a toroidal magnetic confinement device in the presence of time dependent magnetic perturbations.
Analyzing The Phenomenon of Self-presentation Content on Social Media Platforms

In the new media era, the rapid and easy dissemination of information on the Internet has made the use of social media software an indispensable activity in interpersonal communication. The excessive use of social media software can make the audience's emotions influenced by its content. The purpose of this study was to investigate the effect of excessive attention to self-presentation on social media platforms on the audience's self-confidence. Based on TPB theory, the study explored whether the audience's confidence is affected by their personal outlook, perceptions, or education when they pay too much attention to self-presentation on social media platforms. A questionnaire was used to analyze the data with descriptive statistics. This study concluded that the content of self-presentation on social media platforms can cause self-presentation. The personal intention of the audience, the posting of self-presentation by their friends, and the pushing of the media have made more and more people willing to show themselves on social media platforms, and the good comments and likes they receive make them more confident.
Numerical experiments in 2D variational fracture

In the present work we present some results of numerical experiments obtained with a variational model for quasi-static Griffith-type brittle fracture. Essentially the analysis is based on a recent formulation by Francfort and Marigo the main difference being the fact that we rely on local rather than on global minimization. Propagation of fracture is obtained by minimizing, in a step by step process, a form of energy that is the sum of bulk and interface terms. To solve the problem numerically we adopt discontinuous finite elements based on variable meshes and search for the minima of the energy through descent methods. We use a sort of mesh dependent relaxation of the interface energy to get out of small energy wells. The relaxation consists in the adoption of a carefully tailored cohesive type interface energy, tending to the Griffith limit as the mesh size tends to zero.
Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process

The biological treatment process is responsible for removing organic and inorganic matter in wastewater. This process relies heavily on microorganisms to successfully remove organic and inorganic matter. The aim of the study was to model biomass growth in the biological treatment process. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to model biomass growth. Three metrics: coefficient of determination (R2), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the model. Sensitivity analysis was applied to confirm variables that have a strong influence on biomass growth. The results of the study showed that MLP ANN algorithm was able to model biomass growth successfully. R2 values were 0.844, 0.853, and 0.823 during training, validation, and testing phases, respectively. RMSE values were 0.7476, 1.1641, and 0.7798 during training, validation, and testing phases respectively. MSE values were 0.5589, 1.3551, and 0.6081 during training, validation, and testing phases, respectively. Sensitivity analysis results showed that temperature (47.2%) and dissolved oxygen (DO) concentration (40.2%) were the biggest drivers of biomass growth. Aeration period (4.3%), chemical oxygen demand (COD) concentration (3.2%), and oxygen uptake rate (OUR) (5.1%) contributed minimally. The biomass growth model can be applied at different wastewater treatment plants by different plant managers/operators in order to achieve optimum biomass growth. The optimum biomass growth will improve the removal of organic and inorganic matter in the biological treatment process.