Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comprehensive Review on Advancements in Artificial Intelligence Approaches and Future Perspectives for Early Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is a neurological condition that generally strikes people in their average age of onset for PD a neurological disorder, is 55 and up. A wide variety of motor and non-motor symptoms can be observed in patients with PD. The medical community has made great strides in recent years, but Parkinson's disease still has no treatment or cure. Therefore, exploring possible ways for early PD identification is an intriguing scientific endeavor. Full symptoms may not appear for years due to the progressive nature of PD. Thus, early diagnosis is vital to enhance the patient's quality of life. Symptoms will usually worsen with time, so keep that in mind. Several neurodegenerative disorders share very similar symptoms, making early identification crucial for disease prediction. Many people are starting to pay attention to using Artificial Intelligence (AI) methods in medical diagnostics because they can process massive volumes of data and make reliable statistical predictions. This paper covers all the bases when it comes to artificial intelligence (AI) approaches to PD diagnosis, including the many deep and machine learning-based methods that have been deployed and how they have opened new avenues for research. Furthermore, the study explores the current situation and future possibilities of data-driven AI approaches to Parkinson's disease diagnosis. This study is an excellent resource as a review article for researchers interested in creating PD prediction models employing different AI-based modalities.
Partnerships for preserving and enhancing the Padilla Bay agriculture/estuarine ecosystem

The Padilla Bay estuary encompasses one of the largest intertidal eelgrass beds on the west coast of the United States and adjacent land areas provide important habitat for many sedentary and migratory aquatic and terrestrial species. This shallow, orphaned estuary no longer receives fresh water from the Skagit River. Instead, surface waters originating in the residential, industrial, timber, and agricultural lands of the upper Padilla Bay/Bay View watershed drain into the bay through a series of drainage channels. With over half of the land use in the watershed devoted to agriculture, there is substantial potential for agricultural pollution of surface and ground waters, and, ultimately, the marine waters of the bay. Although very few freshwater quality studies have been conducted within the watershed, enough evidence exists to suspect that agriculture is contributing to non-point source pollution of Padilla Bay's surface drainage channels. A surface water survey of the watershed conducted in early 1993 revealed …
Characterization of lactic acid producing Bacillus coagulans Characterization of lactic acid producing Bacillus coagulans strains with their antibacterial activity and L-lactic acid production strains with their antibacterial activity and L-lactic acid production

Objectives: The objective is to study the screening of antibacterial activity, identification, and L-lactic acid production of spore-forming Bacillus isolates. Materials and Methods: Fourteen Bacillus isolates were characterized based on their phenotypic characteristics and 16S rRNA gene sequence analyses. The antibacterial activity was determined by agar diffusion method, and lactic acid production was analyzed using a high-performance liquid chromatography. Four isolates that produced above 85.0 g/L of lactic acid were selected for lactic acid fermentation using mid-log seed culture. Results: All isolates were identified as Bacillus coagulans based on the phenotypic characteristics and 16S rRNA gene sequence similarity (99.02–99.78 %). Strain JC-15 and JC-16 exhibited antibacterial activity against Kocuria rhizophila ATCC 9341. All isolates produced L-lactic acid ranged from 56.7 ± 0.54 to 92.05 ± 0.23 g/L at 37°C under microaerophilic conditions with 99.12 ± 0.10–100 ± 0.00% optical purity of lactic acid. B. coagulans PP-16 showed highest L-lactic acid concentration at 92.05 ± 0.23 g/L, yield of 0.77 ± 0.00 g/g, and productivity of 0.96 ± 0.00 g/L.h. After controlled seed preparation conditions, the four selected strains produced L-lactic acid in the range of 93.25 ± 0.07–103.25 ± 0.21 g/L and 102.85 ± 0.49–111.85 ± 0.21 g/L at 37°C with 98.75 ± 0.00–99.70 ± 0.01 and 88.66 ± 0.02–99.60 ± 0.01% optical purity of lactic acid under microaerophilic and anaerobic conditions, respectively. Yield and productivity were also increased. Fermentation under anaerobic conditions showed higher L-lactic acid titers and yield, whereas microaerophilic conditions gave higher productivity. Strain PP-16 gave the highest optical purity in both conditions.
Fortalecimiento de la empatía a través del teatro clown

En el presente artículo, se analiza la influencia del teatro clown en el fortalecimiento de los procesos empáticos cognitivos y emocionales en un grupo de voluntarios infantiles y prejuveniles de la Cruz Roja Colombiana seccional Nariño. Se utilizó la metodología cualitativa, con un enfoque histórico-hermenéutico. Los resultados confirman que el arte del clown aportó, mediante las diferentes tramas o situaciones que se pusieron en escena, al fortalecimiento del componente cognitivo de la empatía. Esto se evidenció en el aumento de la imaginación, la tolerancia y el reconocimiento de emociones. Asimismo, se destacó el fortalecimiento del componente emocional, evidenciado en actitudes de compasión, contagio emocional, solidaridad y reconocimiento de emociones negativas. El flujo de estas habilidades se desarrolló de manera más efectiva a través de la interpretación de un personaje clown, propiciando el desarrollo de habilidades para la vida, que se constituyen en promotoras de la salud mental y el bienestar de los niños y preadolescentes participantes.
Research on the slope-landscape TUPU in northern Shaanxi Loess Plateau

Slope spectrum is a statistic model of slope distribution in a certain area. Previous researches display a potential importance of the slope spectrum in geomorphological studies. To quantitatively depict the slope spectrum, three indices (H, Td, S) were proposed, which can appropriately depict quantity features of slope distribution, but are difficult in depicting spatial structure of slope distribution. Hence, this paper suggests slope-landscape TUPU to quantitatively depict the spatial structure of slope distribution. The slope-landscape TUPU take each test area as an independent landscape unit, and the slope class as patches constituting the landscape. So, theory and methodology of landscape ecology are applied to describe the spatial structure of slope distribution directly. Results show that the slope-landscape TUPU is capable of depicting spatial structure of slope spectrum. A continuous changes of the slope-landscape TUPU from south to north of the Loess Plateau shows an obvious spatial variation of surface roughness in the area, which is proved to be of great significance in describing the surface roughness. This research also suggests relationship between digital terrain analysis and landscape ecology.
A Study on Short-Term Passenger Flow Forecasting for Urban Rail Transit

Short-term forecasts of light rail traffic are an indispensable basis for adjusting timetables in real time, improving operational efficiency and providing passengers with informed travel recommendations. At the same time, the subway is the most convenient and widely used mode of transport for people today. The purpose of this paper is to forecast passenger traffic in the subway. To solve the problem of predicting short-term passenger flow at the entrances and exits of metro stations with nonlinear and stochastic characteristics, this paper uses a genetic algorithm (GA) based on ordered long-term and short-term memory (SLSTM) and builds a GA-SLSTM forecasting model to predict future short-term passenger flow by studying the patterns and characteristics of passenger flow in historical data. The model consists of five stages: data preprocessing, model training, model evaluation, and forecast application. Through these steps, the GA-SLSTM model is able to predict the future situation of short-term passenger traffic based on the characteristics and patterns in historical data, providing a reference base for planning and optimizing urban transport.
Palsa Uplift Identified by Stable Isotope Depth Profiles and Relation of δ15N to C/N Ratio

Palsas develop as permafrost aggradation uplifts peat out of the zone influenced by groundwater. Here we relate δ15N values to C/N ratios along depth profiles through palsas in two peatlands near Abisko, northern Sweden, to identify perturbation of the peat. The perturbation by uplift as well as the potential nutrient input from the adjacent hollows can be detected in soil δ15N values when related to the C/N ratio at the same depth. Nine out of ten profiles show a perturbation at the depth where peat was uplifted by permafrost. Palsa uplift could be detected by the δ15N depth pattern, with the highest δ15N values at the so‐called turning point. The δ15N values increase above and decrease below the turning point, when permafrost initiated uplift. Onset of permafrost aggradation calculated from peat accumulation rates was between 80 and 545 years ago, with a mean of 242 ( ±66) years for Stordalen and 365 ( ±53) years for Storflaket peatland. The mean ages of permafrost aggradation are within the Little Ice Age. Depth profiles of δ15N, when related to C/N ratio, seem to be a suitable tool to detect perturbation and uplift of palsas. Copyright © 2016 John Wiley & Sons, Ltd.
RGTGAN: Reference-Based Gradient-Assisted Texture-Enhancement GAN for Remote Sensing Super-Resolution

Reference (Ref)-based super-resolution (Ref-SR) is a heated topic distinguished from single-image super-resolution (SISR). It aims at transferring more texture details from the Ref image with a different perspective to super-resolve the low-resolution (LR) image. However, the development of Ref-SR within the remote sensing (RS) community is limited by three problems. First, RS images exhibit more complex texture details compared to natural images. It is challenging to learn and reconstruct the fine texture of RS images. Second, the lack of a high-quality RS image dataset, which contains massive RS image pairs from different perspectives, hampers the model training and diminishes the generalization of Ref-SR within the RS community. Third, the lack of a physical system prevents it from verifying the feasibility of Ref-SR in RS practice. To address these problems, this article proposes a novel Ref-based gradient-assisted texture-enhancement generative adversarial network (RGTGAN), a novel dataset, namely, KaggleSRD, and a novel physical simulation system, namely, dual-zoom-lens system (DZLS). Specifically, this article proposes a gradient-assisted texture-enhancement module (GTEM) to fully release the potential of the gradient branch to learn fine structures during the feature extraction process, a novel dense-intern deformable convolution (DIDConv) to boost the alignment effect between features from different image branches during the feature alignment process, and a novel dense-restore-residual (DRR) module to effectively transfer features. Extensive experimental results on both datasets, RRSSRD and KaggleSRD, demonstrate the superiority of the proposed method over state-of-the-art methods. Furthermore, DZLS verifies promising application prospects of the proposed method. Our code and dataset are publicly available at https://github.com/stdinR/RGTGAN.
Principle and Application of Biophotonic Chips

Contemporarily, biophotonic chips have garnered significant attention from researchers due to their strong immunity to electromagnetic interference, high sensitivity, rapid response rate, and relatively simple structural design. They have found extensive applications in fields such as medical diagnosis, food quality and safety testing, environmental monitoring, and national security. This article provides an overview of the development history, fundamental principles, applications, and fabrication processes of biophotonic chips. The earliest development of biophotonic chips can be traced back to the end of the 20th century. The basic principle involves the interaction of light, utilizing technologies like photonic crystals, surface plasmon resonance, and fluorescence spectroscopy to achieve the detection and analysis of biological molecules. The article briefly describes the fabrication process of biophotonic chips, which involves intricate techniques such as photolithography and electron beam exposure. Furthermore, it analyzes and discusses their widespread applications in medical diagnosis, drug development, and environmental monitoring, among other fields. Lastly, the study evaluates the key challenges present in biophotonic chips and provides an analysis of their future development prospects.
Studying brain networks via topological data analysis and hierarchical clustering

In this thesis we apply the idea of a barcode from persistent homology to four hierarchical clustering methods: single, average, complete, and Ward’s linkage. Desirable theoretical properties of dendrograms, the standard tool to visualize the output of hierarchical clustering methods, were described by Carlsson in [7]. We define analogous properties for hierarchical clustering quasi-barcodes and prove that average and complete quasi-barcodes possess a property that dendrograms do not. We discuss how to decide where to “cut” the output of hierarchical clustering quasi-barcodes based on the distance between the heights at which clusters merge. We find the best possible matching for calculating the Wasserstein distance between quasi-barcodes built from the same number of data points all born at time 0. We also prove that single, average, and complete quasi-barcodes are stable in the sense that small perturbations in distances between points produce small changes in quasibarcodes. In order to test the efficiency of quasi-barcodes and the cut-off criteria, we generate datasets of points arranged in blobs or concentric circles and look whether the combination of the quasi-barcode with the cut-off criteria successfully finds the right amount of clusters in the dataset and whether it places points in the correct clusters. Finally, we apply these tools to datasets from New York University and Peking University of typically developed controls and attention hyperactivity deficit disorder subjects between the ages of 7 and 18.
Aflatoxin B1 induces infertility, fetal deformities, and potential therapies

Abstract Aflatoxin B1 (AFB1) is a subsidiary poisonous metabolite, archetypally spawned by Aspergillus flavus and A. parasiticus, which are often isolated in warm or tropical countries across the world. AFB1 is capable of disrupting the functioning of several reproductive endocrine glands by interrupting the enzymes and their substrates that are liable for the synthesis of various hormones in both males and females. In men, AFB1 is capable of hindering testicular development, testicular degeneration, and reduces reproductive capabilities. In women, a direct antagonistic interaction of AFB1 with steroid hormone receptors influencing gonadal hormone production of estrogen and progesterone was responsible for AFB1-associated infertility. AFB1 is potentially teratogenic and is responsible for the development of malformation in humans and animals. Soft-tissue anomalies such as internal hydrocephalus, microphthalmia, cardiac defects, augmented liver lobes, reproductive changes, immune modifications, behavioral changes and predisposition of animals and humans to neoplasm development are AFB1-associated anomalies. Substances such as esculin, selenium, gynandra extract, vitamins C and E, oltipraz, and CDDO-Im are potential therapies for AFB1. Thus, this review elucidates the pivotal pathogenic roles of AFB1 in infertility, fetal deformities, and potential therapies because AFB1 toxicity is a key problem globally.
Write Summary Step-by-Step: A Pilot Study of Stepwise Summarization

Nowadays, neural text generation has made tremendous progress in abstractive summarization tasks. However, most of the existing summarization models take in the whole document all at once, which sometimes cannot meet the needs in practice. Practically, social text streams such as news events and tweets keep growing from time to time, and can only be fed to the summarization system step by step. Hence, in this paper, we propose the task of Stepwise Summarization, which aims to generate a new appended summary each time a new document is proposed. The appended summary should not only summarizes the newly added content but is also coherent with the previous summary, to form an up-to-date complete summary. To tackle this challenge, we design an adversarial learning model, named Stepwise Summary Generator (SSG). First, SSG selectively processes the new document under the guidance of the previous summary, obtaining polished document representation. Next, SSG generates the summary considering both the previous summary and the document. Finally, a convolutional-based discriminator is employed to determine whether the newly generated summary is coherent with the previous summary. For the experiment, we extend the traditional two-step update summarization setting to multi-step stepwise setting, and re-propose a large-scale stepwise summarization dataset based on a public story generation dataset. Extensive experiments on this dataset show that SSG achieves state-of-the-art performance in terms of both automatic metrics and human evaluations. Ablation studies demonstrate the effectiveness of each module in our framework. We also discuss the benefits and limitations of recent large language models on this task.
Towards using bacterial microcompartments as a platform for spatial metabolic engineering in the industrially important and metabolically versatile Zymomonas mobilis

Advances in synthetic biology have enabled the incorporation of novel biochemical pathways for the production of high-value products into industrially important bacterial hosts. However, attempts to redirect metabolic fluxes towards desired products often lead to the buildup of toxic or undesirable intermediates or, more generally, unwanted metabolic cross-talk. The use of shells derived from self-assembling protein-based prokaryotic organelles, referred to as bacterial microcompartments (BMCs), as a scaffold for metabolic enzymes represents a sophisticated approach that can both insulate and integrate the incorporation of challenging metabolic pathways into industrially important bacterial hosts. Here we took a synthetic biology approach and introduced the model shell system derived from the myxobacterium Haliangium ochraceum (HO shell) into the industrially relevant organism Zymomonas mobilis with the aim of constructing a BMC-based spatial scaffolding platform. SDS-PAGE, transmission electron microscopy, and dynamic light scattering analyses collectively demonstrated the ability to express and purify empty capped and uncapped HO shells from Z. mobilis. As a proof of concept to internally load or externally decorate the shell surface with enzyme cargo, we have successfully targeted fluorophores to the surfaces of the BMC shells. Overall, our results provide the foundation for incorporating enzymes and constructing BMCs with synthetic biochemical pathways for the future production of high-value products in Z. mobilis.
L'huîtrier pie Haematopus ostralegus hivernant en France : évolution des effectifs et modalités d'occupation de l'espace

Over the last 10 years the French coast has become increasingly important for overwintering Oystercatchers, primarily due to a decrease in food resources in the Wadden Sea. Almost all French sites have shown either stable or increasing overwintering numbers of Oystercatcher in mid-January. The most important sites for the species are still on the shore of the English Channel holding 69% of the French population. This is probably explained by their relative proximity to the northerly breeding range of the species. Mud flats are an important factor during cold spells, whereas nature reserves have a key role in the northernmost sites. The species is present at higher densities on areas where shellfish, especially cockles, are collected, thus explaining the potential conflict between birds and fishermen.
A Study of Executive Compensation Incentives and Firm Performance

Proper executive incentives alleviate agency conflict and improve firm performance. This study examined the pertinent literature on the recent study of executive compensation incentives and company performance. Through the literature analysis method, the last five years of relevant literatures were classified according to monetary pay incentives, equity pay incentives and pay gap incentives. This paper summarized the common conclusions that were obtained from the current researches and discussed some deficiencies of current researches. At the same time, this paper also put forward suggestions on sample selection, research methodology and other shortcomings in the current researches. By analyzing and integrating the literature from 2018 to 2023, it helps company owners to improve company performance starting from executive compensation incentives in the corporate governance process. At the same time, this paper will provide an outlook on the possible directions of future related research and provide new ideas for future research.
Efficacy and Experience of Bacteriophages in Biofilm-Related Infections

Bacterial infection has always accompanied human beings, causing suffering and death while also contributing to the advancement of medical science. However, the treatment of infections has become more complex in recent times. The increasing resistance of bacterial strains to antibiotics has diminished the effectiveness of the therapeutic arsenal, making it less likely to find the appropriate empiric antibiotic option. Additionally, the development and persistence of bacterial biofilms have become more prevalent, attributed to the greater use of invasive devices that facilitate biofilm formation and the enhanced survival of chronic infection models where biofilm plays a crucial role. Bacteria within biofilms are less susceptible to antibiotics due to physical, chemical, and genetic factors. Bacteriophages, as biological weapons, can overcome both antimicrobial resistance and biofilm protection. In this review, we will analyze the scientific progress achieved in vitro to justify their clinical application. In the absence of scientific evidence, we will compile publications of clinical cases where phages have been used to treat infections related to biofilm. The scientific basis obtained in vitro and the success rate and safety observed in clinical practice should motivate the medical community to conduct clinical trials establishing a protocol for the proper use of bacteriophages.
On the boundedness of solutions of some fuzzy dynamical control systems

The asymptotic behavior of solutions of fuzzy control systems is a component of the study of fuzzy control theory. The study of stability for T-S (Takagi-Sugeno) fuzzy systems, which process qualitative data through linguistic expressions, is the subject of this paper. Asymptotic stability is conservative in many real-world applications due to measurement noise and other disruptions. The ultimate limit, which indicates that the mistakes stay in a specific area close to the origin after a long enough amount of time, is a crucial characteristic that is frequently defined for such systems. We are interested with the problem of the state feedback controller for T-S fuzzy models with uncertainties where the global exponential ultimate boundedness of solutions is studied for certain fuzzy control systems. We use common quadratic Lyapunov function and parallel distributed compensation controller techniques to study the asymptotic behavior of the solutions of fuzzy control system in presence of perturbations. An example demonstrating the validity of the main result is discussed.