Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of climatic changes in the Late Pleistocene on migrations and extinctions of mammals in Europe: four case studies

Climate changes that occurred during the Late Pleistocene have profound effects on the distribution of many plant and animal species and influenced the formation of contemporary faunas and floras of Europe. The course and mechanisms of responses of species to the past climate changes are now being intensively studied by the use of direct radiocarbon dating and genetic analyses of fossil remains. Here, we review the advances in understanding these processes by the example of four mammal species: woolly mammoth (Mammuthus primigenius), cave bear (Ursus spelaeus s. l.), saiga antelope (Saiga tatarica) and collared lemmings (Dicrostonyx ssp.). The cases discussed here as well as others show that the migrations, range shifts and local extinctions were the main responses to climate changes and that the dynamics of these climate driven processes were much more profound than it was previously thought. Each species reacted by its individual manner, which depended on its biology and adaptation abilities to the changing environment and climate conditions. The most severe changes in European ecosystems that affected the largest number of species took place around 33–31 ka BP, during the Last Glacial Maximum 22–19 ka BP and the Late Glacial warming 15–13 ka BP.
Multiscale Edge-Guided Network for Accurate Cultivated Land Parcel Boundary Extraction From Remote Sensing Images

The accurate acquisition of farmland information holds paramount importance for effective agricultural resource monitoring and production management. Traditional semantic segmentation methods struggle to perform precise segmentation at the parcel level. Many existing contour extraction methods tend to generate ambiguous and inaccurate outcomes. To overcome these challenges, this article proposes a multiscale edge-guided network for accurate cultivated land parcel boundary extraction, which consists of the following: 1) multiscale guided transformer module: this module is designed to encode parcel features by combining the shunted transformer and atrous convolution modules; it allows for modeling long-distance context and refining features, enabling accurate representation of farmland parcels; 2) edge enhancement module: this module operates on multiscale features during the feature extraction stage, improving the ability to capture fine details and boundaries of farmland parcels; 3) dual-pyramid structure: this structure consists of a bottom-up pyramid that incorporates deformable convolutions; it enhances the accuracy of multiscale object detection, enabling the network to capture features at different levels of detail; and 4) deoverlap operation: this modular is designed to reduce the ambiguity caused by contour overlap in the extracted results. Specifically, the method effectively mitigates the impact of regional, temporal, and background features. The experimental results showcase the attainment of average precision (AP) and mean intersection over union (MIoU) scores of 0.3421 and 85.28, respectively, for the extracted farmland parcels. Moreover, the method yields competitive results across different farmland parcel types, shapes, and temporal intervals. This positions it as a valuable tool for optimizing agricultural production and enhancing resource monitoring capabilities.
Prediction of Influenza A Cases in Tropical Climate Country using Deep Learning Model

Influenza remains a significant public health concern particularly in tropical climate countries. Accurate prediction of influenza cases is crucial for effective resource allocation and public health planning. This study aimed to design and evaluate deep learning models for the monthly prediction of influenza A cases in a tropical climate country specifically Malaysia. The models considered both univariate and multivariate input configurations incorporating temperature and humidity variables. The study utilized a dataset spanning from January 2006 to December 2019 with training data from January 2006 to December 2016 and test data until December 2019. Various deep learning models such as RNN, LSTM, complex LSTM, GRU, Transformer and Informer were implemented and evaluated. The results demonstrated that the RNN variants specifically LSTM and GRU consistently outperformed the transformer and informer models for both univariate and multivariate prediction. The shorter input sequences (2 months) yielded better performance compared to longer sequences (12 months) with mean square error (MSE) of 0.0069, capturing more relevant temporal patterns and dependencies. The deep learning models produce a better ability to capture complex relationships and temporal patterns in the data. The findings highlight the effectiveness of the RNN variants and the impact of input configurations and sequence lengths on predictive performance. These findings provide valuable insights that can support public health planning and decision-making processes. Dataset can be obtained from the https://shorturl.at/joqxA.
Unleashing the Impact of IT Integration Implementation in Public Sector Organizations Through the Lens of TOE: A Review

This paper provides a comprehensive review of the Technology-Organization-Environment (TOE) model, which is a framework often used to analyze the impact of IT integration implementation in organizations. The TOE model, developed by Tornatzky and Fleischer in 1990, focuses on understanding the adoption and implementation of technological innovations by considering three key aspects: the technological context, organizational context, and environmental context. This review highlights the strengths, limitations, and suitability of the TOE model in the context of IT integration implementation within public sector organizations to improve service delivery.
Development of NEU-LIFE ASSIST Android Application and Bibliometric Analysis of mHealth Applications

This study includes the development of the NEU-LIFE Assist Android application and bibliometric analysis of mHealth applications. The NEU-LIFE Assist application was developed using Android Studio. This application was designed in a manner such that large amounts of information and emergency care can be accessed with just one touch. In the bibliographic analysis of the study, explanatory graphical models were created with VosViewer to display the studies screened in the Web of Science using the “mHealth Applications” keyword. The aim of this study is to develop the NEU-LIFE Assist Android application for the elderly and people with disabilities and to determine the bibliometric analysis results of studies conducted on mHealth Applications in the related topic. In this context, the aim is to determine the trend of the studies related to mHealth Applications and to research the design focal points that should be used when designing applications. The most cited authors, the most used keywords, the most cited journals and conferences and countries where most studies are conducted related to mHealth applications were listed through a bibliometric analysis. The results shown that an increase in the applications related to mHealth are being designed. One of the most frequently used keywords in this context was determined to be “usability”, which presents the need to design easy and accessible applications.
Tax economics and tax policy and the market reactions of taxpayers

In a market economy, allocation decisions are more or less visibly related to the monetary savings of entities. The tendency of entities to save depends on both the interest rate on deposits and inflation, as well as the tax rate on income from capital (monetary savings). Also, the willingness of business entities to invest depends on the income from invested capital. Tax policy, its nature, implemented solutions, instruments in the form of reliefs and exemptions, and, above all, stability and predictability are an important element of effectively influencing taxpayers' behavior.Induction was used as the main research method. It involves drawing general conclusions or establishing regularities based on the analysis of empirically identified phenomena and processes. Moreover, the work uses two general research methods, i.e. analytical and synthetic methods, characterized by a specific approach to the study of reality.To ensure economic growth and development, it is necessary to develop favorable tax solutions. Taxes should not affect the taxpayer's assets to an extent that prevents their further development. Therefore, it is important to balance the amount of tax collected from the company.A simple consequence of the fiscal function of income taxes is a direct impact on the allocation of resources in the economy, because when the tax is paid, there is a final flow of income between the taxpayer and the state. The fiscal function of income taxes is always related to the allocation of resources, as it reduces the incomes of households and businesses, which limits their ability to invest, consume and save.
A eudicot MIXTA family ancestor likely functioned in both conical cells and trichomes

The MIXTA family of MYB transcription factors modulate the development of diverse epidermal features in land plants. This study investigates the evolutionary history and function of the MIXTA gene family in the early-diverging eudicot model lineage Thalictrum (Ranunculaceae), with R2R3 SBG9-A MYB transcription factors representative of the pre-core eudicot duplication and thus hereby referred to as “paleoMIXTA” (PMX). Cloning and phylogenetic analysis of Thalictrum paleoMIXTA (ThPMX) orthologs across 23 species reveal a genus-wide duplication coincident with a whole-genome duplication. Expression analysis by qPCR confirmed that the highest expression is found in carpels, while newly revealing high expression in leaves and nuanced differences between paralogs in representative polyploid species. The single-copy ortholog from the diploid species T. thalictroides (TthPMX, previously TtMYBML2), which has petaloid sepals with conical–papillate cells and trichomes on leaves, was functionally characterized by virus-induced gene silencing (VIGS), and its role in leaves was also assessed from heterologous overexpression in tobacco. Another ortholog from a species with conical–papillate cells on stamen filaments, TclPMX, was also targeted for silencing. Overexpression assays in tobacco provide further evidence that the paleoMIXTA lineage has the potential for leaf trichome function in a core eudicot. Transcriptome analysis by RNA-Seq on leaves of VIGS-treated plants suggests that TthPMX modulates leaf trichome development and morphogenesis through microtubule-associated mechanisms and that this may be a conserved pathway for eudicots. These experiments provide evidence for a combined role for paleoMIXTA orthologs in (leaf) trichomes and (floral) conical–papillate cells that, together with data from other systems, makes the functional reconstruction of a eudicot ancestor most likely as also having a combined function.
HARMONIZING HEALING: THE VITAL ROLE OF INTEGRATED YOGA AND WELLNESS THERAPY IN CANCER CARE – A CONCISE OVERVIEW

Cancer care extends beyond physical health, profoundly impacting the mind and spirit. Holistic approaches recognize that medical interventions are just one facet of the complex cancer journey, which also involves emotional turmoil, psychological resilience, and the quest for meaning. Traditional treatments are crucial for managing physical symptoms, yet they often overlook the emotional toll of the disease.This concise overview delves into the pivotal role of Integrated Yoga and Wellness Therapy in cancer care. Merging ancient yoga wisdom with modern wellness practices, this approach prioritizes comprehensive well-being, understanding that genuine health surpasses the absence of disease. Holistic strategies, tailored to individual needs and preferences, equip patients with tools to manage stress, enhance emotional resilience, and find empowerment. Embracing integrated therapy in healthcare institutions is imperative for enhanced patient outcomes, reduced side effects, and an overall improvement in the quality of life for cancer patients. Through research, awareness, and collaboration, holistic approaches pave a transformative path for both patients and healthcare systems, bridging the gap between curing the body and nurturing the individual as a whole. KEYWORDS: Integrated Therapy, Holistic Care, Cancer Care, Yoga Therapy, Patien
Modiomytilus, a new mytilid bivalve from the Tertiary of southern Patagonia

Modiomytilus n. gen. is described from Tertiary sediments exposed in the southwestern corner of Santa Cruz province (Argentina). This large mytilid is characterized by its ornamentation of strong comarginal undulations, its smooth ligamentary ridge, and its relatively large anterior adductor muscle. Two new species are assigned to it: Modiomytilus argentinensis n. sp. , from the Centinela Formation (Miocene) south of Lago Argentino, and Modiomytilus mercerati n. sp. , from the Río Turbio Formation (Eocene) in Sierra Dorotea. Although other species belonging to this new taxon and previously referred to Mytilus have been described from Tertiary sediments in the region, none are known so far from rocks of comparable age outside Patagonia.
Spatial Distribution Characteristics of Soil Organic Carbon and Difference in Stable Carbon Isotope Composition in Slopes of Karst Areas

Two different degree of degenerate typical mountain slopes in karst areas were selected as a case to study effect of soil erosion and deposition on dynamics of soil organic carbon(SOC) by determining some properties and δ13C value of the soils at different topographic positions.The results showed that in natural slope surface layer,soil organic carbon contents were quite high,being(6.3%～16.2%),the decrease in δ13C with slope gradient from-14.3‰-21.7‰. In addition,soil organic carbon contents and δ13C value are between 4.4%～7.4%,-20.3‰～-21.4‰ in the wasteland slope soil surface.The variation range of its is smaller than natural slope,which indicates that the loss of new carbon was greater.Both were significantly correlated with kind of plants.The change in δ13C and soil organic carbon contents with depth in soil profiles at different topographic position reflected input of plant residue and accumulation of two mountain slopes,which helps to analyze impact of soil organic carbon erosion and deposition in the slope soil.
Use of Methotrexate for More Than 4 Years Is Not Associated with Liver Fibrosis in Rheumatoid Arthritis Patients

Background. Methotrexate is an anchor drug in the management of rheumatoid arthritis (RA). However, the association between methotrexate and development of liver fibrosis remains a subject of controversy. Non-invasive methods to assess liver fibrosis, such as the FIB-4 score, have been developed. RA patients on methotrexate therapy should be monitored for any signs of liver fibrosis. This study aims to investigate the correlation between methotrexate cumulative dose and the FIB-4 score in rheumatoid arthritis patients who received methotrexate therapy to assess the hepatotoxic effects of methotrexate. Methods. This cross-sectional study involved rheumatoid arthritis patients who received methotrexate therapy at Dr. Hasan Sadikin General Hospital Bandung from September 2022 to November 2022. Clinical data, laboratory tests (including platelet values and liver function test), and cumulative methotrexate doses were extracted from medical records. Data were analyzed using the Spearman correlation test. Results. This study involved 100 subjects aged between 22-82 years, comprising 93% women and 7% men. The median FIB-4 score was 0.73 (0.24-6.80), while the median methotrexate cumulative dose was 2477.5 mg, with a range of 1005-10400 mg. The results showed that correlation coefficient between the FIB-4 score and methotrexate cumulative dose in rheumatoid arthritis patients was -0.089 (p=0.378). Conclusion. There is no significant correlation between FIB-4 score and cumulative dose of methotrexate in rheumatoid arthritis patients. The use of methotrexate in RA patients over 4 years is relatively safe as it does not increase the risk of liver fibrosis.
City Tourism Product Development and Marketing: The Case of the Provincial Capital city of Mahikeng

This article explores the city tourism product composition of Mahikeng, the capital city of South Africa’s North West Province. Its goal is twofold: to capture the industry’s views on the city’s current urban tourism product offering and to identify the necessary marketing activities for tourism development in Mahikeng. The study used quantitative data from an online survey involving 62 tourism businesses operating in Mahikeng. The results highlight a limited level of tourism product offerings, ineffective marketing activities, and the need to develop a more diverse city tourism product mix to ensure the success of Mahikeng as a tourist city. The authors recommend the development of a varied product mix and, through this, the implementation of marketing activities more suited to cities with a provincial status.
Sixth-Week Immune-Nutritional-Inflammatory Biomarkers: Can They Predict Clinical Outcomes in Patients with Advanced Non-Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors?

Background: We investigated the relationships between inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Lung Immune Prognostic Index (LIPI), and modified Glasgow prognostic score (mGPS) to determine whether they could predict treatment response to pembrolizumab or nivolumab (immunotherapy) 6 weeks after the start of treatment (post-treatment). Methods: We included all patients with lung cancer treated with immunotherapy. We examined the biomarker trends and explored their associations with progression-free survival (PFS), overall survival (OS), and response rate (RR) at 6 weeks. Results: Eighty-three patients were enrolled in the study. The presence of liver metastasis, low post-treatment NLR (<5), low post-treatment PLR (<170), intermediate post-treatment LIPI, and immune-related adverse events were significantly associated with the response. The multivariate analysis revealed that high post-treatment NLRs ≥ 5 (p = 0.004) and PLRs ≥ 170 (p ≤ 0.001) were independent prognostic factors of shorter OS. A good LIPI status was associated with better PFS (p = 0.020) and OS (p = 0.065). Post-treatment mGPS (0–2) was significantly associated with improved PFS (p = 0.009) and OS (p = 0.064). Conclusions: Post-treatment NLR, PLR, LIPI, and mGPS are associated with worse OS and recurrence. These findings should be independently and prospectively validated in further studies.
An integrated analysis of bulk and single-cell sequencing data reveals that EMP1+/COL3A1+ fibroblasts contribute to the bone metastasis process in breast, prostate, and renal cancers

Introduction Bone metastasis (BoM) occurs when cancer cells spread from their primary sites to a bone. Currently, the mechanism underlying this metastasis process remains unclear. Methods In this project, through an integrated analysis of bulk-sequencing and single-cell RNA transcriptomic data, we explored the BoM-related features in tumor microenvironments of different tumors. Results We first identified 34 up-regulated genes during the BoM process in breast cancer, and further explored their expression status among different components in the tumor microenvironment (TME) of BoM samples. Enriched EMP1+ fibroblasts were found in BoM samples, and a COL3A1-ADGRG1 communication between these fibroblasts and cancer cells was identified which might facilitate the BoM process. Moreover, a significant correlation between EMP1 and COL3A1 was identified in these fibroblasts, confirming the potential connection of these genes during the BoM process. Furthermore, the existence of these EMP1+/COL3A1+ fibroblasts was also verified in prostate cancer and renal cancer BoM samples, suggesting the importance of these fibroblasts from a pan-cancer perspective. Discussion This study is the first attempt to investigate the relationship between fibroblasts and BoM process across multi-tumor TMEs. Our findings contribute another perspective in the exploration of BoM mechanism while providing some potential targets for future treatments of tumor metastasis.
A mathematical model of collisions in passive dynamic walking of a compass-like biped walker with an angle limiter

Compass-like biped robots are biped robots with no knees. They are useful for investigating walking dynamics, since they are simple and capture the essence of walking, especially passive dynamic walking. Passive compass-like biped robots have angle limiters in some experimental arrangements, and the relative angle between the two legs is limited. For a compass-like biped robot with an angle limiter, an impact occurs at the time of collision between the limiter and a leg, but its dynamics have not been modeled yet. Therefore, the effect of the angle limiter is unclear, while it is experimentally known that the angle limiter improves walking robustness for passive dynamic walkers. This paper provides a mathematical model of dynamics at the impact time of collision between the limiter and a leg of a compass-like biped robot. The obtained model helps to analyze the limiter effect of compass-like biped robots computationally and/or theoretically. It may be useful for understanding the dynamics of bipedal walking and for generating human-like biped locomotion.
AI Clinical Decision Support System (AI-CDSS) for Cardiovascular Diseases

The AI-CDSS (Artificial Intelligence Clinical Decision Support System) is a powerful tool designed to assist healthcare professionals in making informed and evidence-based decisions in patient care. It leverages artificial intelligence algorithms and data analysis techniques to provide personalized recommendations and insights. This system explores the features and benefits of the AI-CDSS, including patient data analysis, diagnostics and treatment recommendations, drug interaction and adverse event detection, predictive analytics, real-time monitoring and alerts, and continuous learning and improvement. The model also discusses the applications of AI-driven decision-making systems in healthcare, focusing on areas such as cancer diagnosis and treatment, chronic disease management, medication optimization, surgical decision support, infectious disease outbreak management, radiology and medical imaging analysis, mental health support, and clinical trials and research. Additionally, the paper highlights existing methodologies, such as deep learning models like CNNs and RNNs, that have shown potential in cardiovascular disease prediction. However, it emphasizes the need for rigorous validation, evaluation, and consideration of ethical and regulatory aspects before deploying AI models in clinical practice. Ultimately, the integration of AI-driven decision-making systems has the potential to revolutionize chronic disease management, improve patient consequences, and enhance the quality of care provided to individuals with longterm health conditions.
Lunar Environment Evaluation of Sleeve Antenna

Communication in the lunar environment presents unique challenges that require carefully designed and specialized antenna solutions. This study investigates the antenna performance of the Rashid lunar rover in Atlas Crater. Thermal studies show that the temperature at Atlas Crater can go higher than 80°C during the lunar mid-day. The results in this paper highlight the effect of different materials used as a thermal coating for Rashid rover antenna. To enhance our understanding of antenna performance, the study has been extended to include the influence of lunar regolith conductivity and depth in the Atlas Crater. By incorporating lunar regolith considerations, this paper contributes to the development of a robust communication system for Rashid rover and for future lunar missions.