Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanosecond Pulsed Plasma Activated C2H4/O2/Ar Mixtures in a Flow Reactor

The present work combines numerical and experimental efforts to investigate the effect of nanosecond pulsed plasma discharges on the low-temperature oxidation of C2H4/O2/Ar mixtures under reduced pressure conditions. The nonequilibrium plasma discharge is modeled using a one-dimensional framework, employing separate electron and neutral gas temperatures, and using a detailed plasma and combustion chemical kinetic mechanism. Good agreement is seen between the numerical and experimental results, and both results show that plasma enables low-temperature C2H4 oxidation. Compared to zero-dimensional modeling, the one-dimensional modeling significantly improves predictions, probably because it produces a more complete physical description (including sheath formation and accurate reduced electric field). Furthermore, the one- and zero-dimensional models show very different reaction pathways, using the same chemical kinetic mechanism and thus suggest different interpretations of the experimental results. Two kine.
Fpr2−/− Mice Developed Exacerbated Alcohol-Associated Liver Disease

Simple Summary Alcohol-associated liver disease (ALD) is a global healthcare problem, and the mechanisms of ALD development are not fully understood. In this study, we found that loss of formyl peptide receptor 2 (FPR2) worsened alcohol-induced injury and inflammation and altered liver regeneration. An exacerbation of ALD due to FPR2 gene knockout was associated with abnormal immune responses. This study demonstrated that FPR2 plays an important role in the pathogenesis of ALD. Abstract Alcohol-associated liver disease (ALD) is the most common chronic liver disease and carries a significant healthcare burden. ALD has no long-term treatment options aside from abstinence, and the mechanisms that contribute to its pathogenesis are not fully understood. This study aimed to investigate the role of formyl peptide receptor 2 (FPR2), a receptor for immunomodulatory signals, in the pathogenesis of ALD. WT and Fpr2−/− mice were exposed to chronic–binge ethanol administration and subsequently assessed for liver injury, inflammation, and markers of regeneration. The differentiation capacity of liver macrophages and the oxidative burst activity of neutrophils were also examined. Compared to WT, Fpr2−/− mice developed more severe liver injury and inflammation and had compromised liver regeneration in response to ethanol administration. Fpr2−/− mice had fewer hepatic monocyte-derived restorative macrophages, and neutrophils isolated from Fpr2−/− mice had diminished oxidative burst capacity. Fpr2−/− MoMF differentiation was restored when co-cultured with WT neutrophils. Loss of FPR2 led to exacerbated liver damage via multiple mechanisms, including abnormal immune responses, indicating the crucial role of FPR2 in ALD pathogenesis.
Covariate Adjustments to Effective Area in Variable-Area Wildlife Surveys

The problem is that of adjusting estimates of effective area surveyed in line transect or variable circular plot wildlife surveys for covariates that are known to influence delectability. We present a model where this can be accomplished within a general linear models framework (Nelder and Wedderburn, 1982, Journal of the Royal Statistical Society, Series A 135, 370-384). The model treats effective area as a scale parameter for detection areas, and uses the logarithm of effective area as a link to the covariates. Maximum likelihood results are presented along with least squares estimates that provide good starting values for iterative searches. We apply the methodology to a situation arising in an avian survey of Saipan Island.
Potential protective effect of basil leaves extract against zinc oxide nanoparticle-induced nephrotoxicity in rats

: Nanoparticles are compounds with special qualities that are very small in size (less than 100 nm). As a result, nanoparticles pose many different health concerns. Therefore, this study aimed to estimate basil leaf extract's protective effect on nephrotoxicity tempted by zinc oxide nanoparticles (ZnONPs) in male albino rats. Twenty-four male Sprague Dawley rats were divided into four groups. Group 1 rats were given a basal diet for 4 weeks and served as normal control. Group 2 rats were fed on a basal diet+ 500mg/ kg b.w. from leaves extract by gavage) for 4 weeks. Group 3 rats have a single dose of ZnONPs (600 mg/kg i.p.) on the 29 th day. Group 4 rats received a single dose of ZnONPs (600 mg/kg i.p.) on the 29 th day+ 500 mg/ kg b.w. leaf extract via gavage for 4 weeks. At the end of the experiment, blood samples were taken, internal organs were collected, weighted. A complete blood count was performed. Serum was separated to biochemical examination. Basil leaves extract recorded the highest catechein, benzoic, P-OH-benzoic, ellagic and gallic acids, respectively.
Segmentation of Hemorrhagic Areas in Human Brain from CT Scan Images

Brain hemorrhage is potentially a fatal condition that results from internal bleeding in the human brain. In this study, Computed Tomography (CT) scan images have been used for segmentation tasks to pinpoint the area of hemorrhage. Unique data augmentation techniques using non-linear transformations like, Twirl and Spherical have been used along with traditional data augmentation techniques to increase variation in the dataset. The hemorrhagic portion of the brain in images that are easy to distinguish have been annotated to perform the segmentation task. The segmentation task was applied using U-Net and U-Net++ architecture. U-Net architecture has shown 84.33% Intersection over Union (IoU) and 91.34% dice coefficient score whereas U-Net++ has achieved 17.06% IoU and 28.27% dice coefficient score after applying some non-linear transformations on the dataset.
Glucagon-like Peptide-1 Receptor Agonists in Patients with Type 2 Diabetes Mellitus and Nonalcoholic Fatty Liver Disease—Current Background, Hopes, and Perspectives

Nonalcoholic fatty liver disease (NAFLD) represents the most common chronic liver disease worldwide, reaching one of the highest prevalences in patients with type 2 diabetes mellitus (T2DM). For now, no specific pharmacologic therapies are approved to prevent or treat NAFLD. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are currently evaluated as potential candidates for NAFLD treatment in patients with T2DM. Some representatives of this class of antihyperglycemic agents emerged as potentially beneficial in patients with NAFLD after several research studies suggested they reduce hepatic steatosis, ameliorate lesions of nonalcoholic steatohepatitis (NASH), or delay the progression of fibrosis in this population. The aim of this review is to summarize the body of evidence supporting the effectiveness of GLP-1RA therapy in the management of T2DM complicated with NAFLD, describing the studies that evaluated the effects of these glucose-lowering agents in fatty liver disease and fibrosis, their possible mechanistic justification, current evidence-based recommendations, and the next steps to be developed in the field of pharmacological innovation.
Non-singular Terminal Sliding Model Control of Novel Reaching Law for a Class of Nonlinear Systems

Aimed at addressing the problems of singularity,chattering,and slow convergence of the terminal sliding-mode control for a class of nonlinear uncertain systems,a nonsingular terminal sliding switch function and a novel reaching law are applied together to the sliding-mode control for the first time. Under the assumption of eliminating the singular value,a novel law based on the power-reaching law is introduced to design a new type of nonsingular terminal sliding-mode controller,and its stability is verified. By using the new controller in an inverted pendulum system,it is proved that the reaching performance when system state is far away from sliding surface is enhanced,and system singularity is simultaneously solved. The simulation results show that the system quickly converged to equilibrium,and that the proposed method is effective.
Continuous-time stochastic models of a multigrade population

The continuous-time Markov model of a multigrade organization is extended in several ways. Firstly the internal transitions and the leaving process are generalized to a semi-Markov formulation which allows for the inclusion of well-authenticated leaving distributions such as the mixed exponential distribution. The previous assumption of Poisson recruitment is then generalized to allow for a time-dependent Poisson arrival distribution in which the instantaneous probability of an arrival is a mixture of exponential terms. Finally we extend the capital-related manpower model to describe a multigrade organization.
Population Classification and Sample Structure on Modeling of Single Tree Biomass Equations for National Biomass Estimation in China

The population classification and sample structure on modeling of single-tree biomass equations for national biomass estimation in China was studied in this paper.Firstly,combining the classification of eco-geographic region and administrative region,a scheme of population classification on modeling of single-tree biomass equations was presented,which is mostly compatible with the population classification on modeling of single-tree volume equations,including 34 tree species or species groups,6 large-scale geographic regions,and a total of 70 populations.Secondly,based on the analysis of variation coefficients derived from one-and two-variable tree biomass models fitted with available tree biomass data of several tree species,it was concluded that prediction precision of tree biomass models could be defined as more than 95%,and at least 150 sample trees are needed for a regional model which should be selected in equal numbers for each diameter class,i.e.,not less than 15 trees in each of 10 diameter classes.Finally,by using the 7th National Forest Inventory data,the sample structure of each population was determined,that is,all the sample tree numbers of 70 populations were specified by province and by diameter class.The results will provide a practical reference for the establishment of generalized single-tree biomass models in China.
SERNet: A Novel Speech Emotion Recognition System Using Ensemble Deep Learning Approach

Speech is among the most natural methods for us as human beings to express ourselves. Due to the relevance of emotions in today’s digital world of distant communication, their detection and analysis are crucial. Emotion recognition is extremely difficult since emotions are different for everyone. Speech emotion recognition is one area of application in which deep neural networks have excelled. Single learners have been used in the majority of the work done in this subject. We have developed a Speech Emotion Recognition (SER) system named SERNet that processes and classifies speech inputs to recognize emotions. As part of our research, we tried to explore emotional feelings in audio talks by looking at the acoustic characteristics of such recordings. This study proposes a novel approach using an ensemble of binary classifiers to simplify the multiclass classification problem into a binary classification problem, aiming to improve overall model performance. The binary classifiers are ensembled using a multilayer perceptron to obtain their final predictions on the multiclass classification problem. Utilizing a benchmark dataset designed specifically for the purpose of speech emotion recognition, the efficacy of this strategy has been proven. On the basis of the findings of the experiments, with an accuracy of 98.81%, this technique exceeds the most advanced models currently available.
Predictive Power of Oxygen Desaturation Index (ODI) and Apnea-Hypopnea Index (AHI) in Detecting Long-Term Neurocognitive and Psychosocial Outcomes of Sleep-Disordered Breathing in Children: A Questionnaire-Based Study

Pediatric obstructive sleep apnea can negatively affect children’s neurocognitive function and development, hindering academic and adaptive goals. Questionnaires are suitable for assessing neuropsychological symptoms in children with sleep-disordered breathing. The study aimed to evaluate the effectiveness of using the Oxygen Desaturation Index compared to the Obstructive Apnea–Hypopnea Index in predicting long-term consequences of sleep-disordered breathing in children. We conducted a retrospective analysis of respiratory polysomnography recordings from preschool and school-age children (mean age: 5.8 ± 2.8 years) and followed them up after an average of 3.1 ± 0.8 years from the home-based polysomnography. We administered three validated questionnaires to the parents/caregivers of the children by phone. Our results showed that children with an Oxygen Desaturation Index (ODI) greater than one event per hour exhibited symptoms in four domains (physical, school-related, Quality of Life [QoL], and attention deficit hyperactivity disorder [ADHD]) at follow-up, compared to only two symptoms (physical and school-related) found in children with an Obstructive Apnea–Hypopnea Index greater than one event per hour at the time of diagnosis. Our study also found a significant correlation between the minimum SpO2 (%) recorded at diagnosis and several outcomes, including Pediatric Sleep Questionnaire (PSQ) scores, physical, social, and school-related outcomes, and ADHD index at follow-up. These results suggest that the Oxygen Desaturation Index could serve as a valuable predictor of long-term symptoms in children with sleep-disordered breathing, which could inform treatment decisions. Additionally, measuring minimum SpO2 levels may help assess the risk of developing long-term symptoms and monitor treatment outcomes.
Digital fast neutron radiography of steel reinforcing bar in concrete

Neutron imaging has previously been used in order to test for cracks, degradation and water content in concrete. However, these techniques often fall short of alternative non-destructive testing methods, such as γ-ray and X-ray imaging, particularly in terms of resolution. Further, thermal neutron techniques can be compromised by the significant expense associated with thermal neutron sources of sufficient intensity to yield satisfactory results that can often precipitate the need for a reactor. Such embodiments are clearly not portable in the context of the needs of field applications. This paper summarises the results of a study to investigate the potential for transmission radiography based on fast neutrons. The objective of this study was to determine whether the presence of heterogeneities in concrete, such as reinforcement structures, could be identified on the basis of variation in transmitted fast-neutron flux. Monte-Carlo simulations have been performed and the results from these are compared to those arising from practical tests using a 252Cf source. The experimental data have been acquired using a digital pulse-shape discrimination system that enables fast neutron transmission to be studied across an array of liquid scintillators placed in close proximity to samples under test, and read out in real time. Whilst this study does not yield sufficient spatial resolution, a comparison of overall flux ratios does provide a basis for the discrimination between samples with contrasting rebar content. This approach offers the potential for non-destructive testing that gives less dose, better transportability and better accessibility than competing approaches. It is also suitable for thick samples where γ-ray and X-ray methods can be limited.
Unmanned Aerial Vehicle Serial Aerial Image Automatic Registration Based on Improved SIFT Algorithm

Due to the disperse and regular of view points and the view angle of UAV Aerial Image,the image data was preconditioned at first,then the Harris feature points with SIFT feature vectors were combined,Harris feature points were extracted,the characteristics radius of feature points and SIFT feature vector was calculated,and PCA(Principal Component Analysis) was used to reduce the dimension of SIFT feature vectors.And then the most close method(NN) was used to feature matching,the BBF algorithm was applied to search the nearest neighbor feature for improving the matching speed.Finally,the PROSAC algorithm was used to purify initial feature point matching pairs,and motion model parameters were calculated,the image automatic registration was achieved.The results of experiment proved that such algorithm was more efficient and exact than the classic SIFT algorithm.
Accelerating Parallel Applications Based on Graph Reordering for Random Network Topologies

The Message Passing Interface (MPI) is a crucial programming tool for enabling communication between processes in parallel applications. The goal of MPI users is to allocate tasks to processors in a way that maximizes both spatial and temporal locality in the network. However, this can be challenging, especially in large-scale networks where maximizing processor locality may not be feasible at runtime. To address this issue, we propose the use of Hamorder, an offline node reassignment approach that takes into account physical processor locations based on graph reordering for Random network topologies. Hamorder aims to optimize task mapping for improved performance in parallel applications, whether for multiple tasks or within a single task. Additionally, we investigate the potential of improving MPI applications through runtime parameter tuning based on Hamorder. Our evaluation results show that Hamorder provides a 27.3% improvement in performance compared to the Gorder algorithm on Random topologies, which is a state-of-the-art solution designed with the aim of enhancing cache locality and achieves this goal by rearranging the vertices of a graph in a way that places the vertices that are typically accessed together in close proximity. Moreover, our autotuning framework using Hamorder results in an average speedup of $1.38\times $ for targeted MPI applications by searching through various runtime parameter combinations.
Perceived Inequality Increases Support for Structural Solutions to Climate Change

Economic inequality is fuelling climate change. The question, however, remains whether the degree to which people perceive their country as unequal influences their motivation to support climate policies. Across three studies (N = 1,459), we investigated whether perceived inequality influences people’s support for structural climate policies over policies aimed at individual-level behavior change. In an Australian (Study 1) and a United Kingdom (Study 2) sample, we found that perceived inequality positively predicts people’s support for structural (vs. individual-level behavior) change policies, even after controlling for political orientation. In an experimental study (Study 3), people who imagined living in an unequal (vs. equal) country more strongly wanted their country to implement structural (vs. individual-level behavior) change policies. These effects were mediated by a greater desire for drastic changes. This suggests that recognizing one’s country’s unequal wealth distribution may act as a catalyst for the structural change urgently needed to limit climate change.
Transforming the Well-Being of Persons with Autism

ABSTRACT The prospects for attaining well-being do not appear to be improving for most persons with Autism. We believe it is essential to understand the obstacles preventing persons from experiencing life satisfaction and optimism for the future. The current paper seeks to address this question and provide an alternate model that we believe can significantly increase the potential for autistic persons to achieve greater well-being. We first review recent findings concerning the well-being of autistic adults. Next, we present evidence supporting our belief that a significant factor suppressing autistic well-being is the failure to develop Dynamic Intelligence, the mental resources needed to function successfully in situations resembling Complex Dynamic Systems. This section includes a brief qualitative study of four young men with Autism who participated as children in Relationship Development Intervention (RDI). RDI is a family-based program where through careful assessment, support and training, RDI consultants provide parents with Autism a new opportunity to form and manage an Experience Guiding Relationship (EGR) with their autistic children. The Experience Guiding Relationship is the universal pathway for developing the mental resources needed to thrive in Complex, Dynamic environments. We provide strong evidence supporting our belief that due to a diverse range of early vulnerabilities, future Autistic infants and their parents cannot form this critical relationship. The final section offers recommendations for adapting intervention goals and methods for persons with Autism.
Characteristics of a Gaussian focus embedded within spiral patterns in common-path interferometry with phase apertures

Abstract. A phase-only method is proposed to transform an optical vortex field into desired spiral diffraction–interference patterns. Double-ring phase apertures are designed to produce a concentric high-order vortex beam and a zeroth-order vortex beam, and the diffracted intensity ratio of two beams is adjustable between 0 and 1. The coherent superposition of the two diffracted beams generates a brighter Airy spot (or Poisson spot) in the middle of the spiral pattern, where the singularity for typical vortex beam is located. Experiments employing circular, triangular, and rectangular phase apertures with topological charges from 3 to 16 demonstrate a stable, compact, and flexible apparatus for vortex beam conversion. By adjusting the parameters of the phase aperture, the proposed method can realize the optical Gaussian tweezer function and the optical vortex tweezer function simultaneously along the same axis or switch the experimental setup between the two functions. It also has potential applications in light communication through turbulent air by transmitting an orbital angular momentum-coded signal with a concentric beacon laser.
Theoretical Framework of Knowledge Representation for Information Sharing

Since information from enterprises should be shared and exchanged in order to be understood and recognized, whereby unambiguous and transparent data is considered a vital requirement, information sharing has become crucial to the correct use of information assets. Sharing information may be seen as the most significant component of a company. Sharing or integrating information is used to bring together seemingly unrelated bodies of knowledge in an effort to enhance creativity. Development and training programs, reports, Information Technology (IT) platforms, official papers, and collaborative teams are all instances of information integration. It is possible to boost product and service quality, customer service responsiveness, innovation, and environmental sustainability via pervasive information integration. In this article, we take a look back at the revolutionary idea underpinning internal communication networks for Knowledge Management (KM), and Knowledge Representation (KR).