Miracle-dz/UniFAR-FTUs huggingface dataset:
Glycolipids Derived from the Korean Endemic Plant Aruncus aethusifolius Inducing Glucose Uptake in Mouse Skeletal Muscle C2C12 Cells

Aruncus spp. has been used as a traditional folk medicine worldwide for its anti-inflammatory, hemostatic, and detoxifying properties. The well-known species A. dioicus var. kamtschaticus has long been used for multifunctional purposes in Eastern Asia. Recently, it was reported that its extract has antioxidant and anti-diabetic effects. In this respect, it is likely that other Aruncus spp. possess various biological activities; however, little research has been conducted thus far. The present study aims to biologically identify active compounds against diabetes in the Korean endemic plant A. aethusifolius and evaluate the underlying mechanisms. A. aethusifolius extract enhanced glucose uptake without toxicity to C2C12 cells. A bioassay-guided isolation of A. aethusifolius yielded two pure compounds, and their structures were characterized as glycolipid derivatives, gingerglycolipid A, and (2S)-3-linolenoylglycerol-O-β-d-galactopyranoside by an interpretation of nuclear magnetic resonance and high-resolution mass spectrometric data. Both compounds showed glucose uptake activity, and both compounds increased the phosphorylation levels of insulin receptor substrate 1 (IRS-1) and 5′-AMP-activated protein kinase (AMPK) and protein expression of peroxisome proliferator-activated receptor γ (PPARγ). Gingerglycolipid A docked computationally into the active site of IRS-1, AMPK1, AMPK2, and PPARγ (−5.8, −6.9, −6.8, and −6.8 kcal/mol).
Geospatial data mining for digital raster mapping

We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.
Investigating the causal relationship and potential shared diagnostic genes between primary biliary cholangitis and systemic lupus erythematosus using bidirectional Mendelian randomization and transcriptomic analyses

Background The co-occurrence of primary biliary cholangitis (PBC) and systemic lupus erythematosus (SLE) has been consistently reported in observational studies. Nevertheless, the underlying causal correlation between these two conditions still needs to be established. Methods We performed a bidirectional two-sample Mendelian randomization (MR) study to assess their causal association. Five MR analysis methods were utilized for causal inference, with inverse-variance weighted (IVW) selected as the primary method. The Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and the IVW Radial method were applied to exclude outlying SNPs. To assess the robustness of the MR results, five sensitivity analyses were carried out. Multivariable MR (MVMR) analysis was also employed to evaluate the effect of possible confounders. In addition, we integrated transcriptomic data from PBC and SLE, employing Weighted Gene Co-expression Network Analysis (WGCNA) to explore shared genes between the two diseases. Then, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment methods to perform on the shared genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was utilized to identify potential shared diagnostic genes. Finally, we verified the potential shared diagnostic genes in peripheral blood mononuclear cells (PBMCs)-specific cell populations of SLE patients by single-cell analysis. Results Our MR study provided evidence that PBC had a causal relationship with SLE (IVW, OR: 1.347, 95% CI: 1.276 - 1.422, P < 0.001) after removing outliers (MR-PRESSO, rs35464393, rs3771317; IVW Radial, rs11065987, rs12924729, rs3745516). Conversely, SLE also had a causal association with PBC (IVW, OR: 1.225, 95% CI: 1.141 - 1.315, P < 0.001) after outlier correction (MR-PRESSO, rs11065987, rs3763295, rs7774434; IVW Radial, rs2297067). Sensitivity analyses confirmed the robustness of the MR findings. MVMR analysis indicated that body mass index (BMI), smoking and drinking were not confounding factors. Moreover, bioinformatic analysis identified PARP9, ABCA1, CEACAM1, and DDX60L as promising diagnostic biomarkers for PBC and SLE. These four genes are highly expressed in CD14+ monocytes in PBMCs of SLE patients and potentially associated with innate immune responses and immune activation. Conclusion Our study confirmed the bidirectional causal relationship between PBC and SLE and identified PARP9, ABCA1, CEACAM1, and DDX60L genes as the most potentially shared diagnostic genes between the two diseases, providing insights for the exploration of the underlying mechanisms of these disorders.
Modified Model Predictive Control for Coordinated Signals along an Arterial under Relaxing Assumptions

This paper proposes modified model predictive control (MMPC) for coordinated signals, aiming to enhance a model’s fidelity to the realistic traffic environment by relaxing typical assumptions. We focus on the arterial, where every intersection is equipped with a dual-ring-barrier signal controller that complies with the standards of the National Electric Manufacturers Association. MMPC employs the store-and-forward model to describe traffic flow, thereby transforming the signal control problem into a model-based rolling-horizon optimization problem, in which the prediction horizon is composed of several future sample intervals, commonly equal to the cycle length. A radar detector is used to collect vehicle data upstream of the stop line at every sampling instant. The optimization problem is solved to minimize the number of vehicles within the prediction horizon, and the next timing plan is determined based on the optimization results. Constraints are added and modified in order to incorporate the typical relaxed assumptions in the optimization process. For this purpose, MMPC introduces a transition-free ring-barrier structure, vehicle distribution ratio, and percent arrival before the end of green. Simulation results indicate that coordination can be maintained by MMPC without the need for transitions, and the estimation of current and future traffic states can be improved with the assistance of modified constraints. Compared with benchmark techniques, MMPC offers superior vehicle progression for coordinated movement and significant improvements in delays, number of stops, and total travel time from a system-wide perspective, with an acceptable small increase in runtime.
Optimalisasi Temu Kembali Informasi Dengan Teknologi Kecerdasan Buatan di Perpustakaan

The purpose of this research is to describe how information retrieval using artificial intelligence in STIPRAM Yogyakarta library is optimal because artificial intelligence (AI) technology has been widely used in libraries to optimize information retrieval and improve user experience. This research method is descriptive and qualitative, and uses observation and interview techniques. The results of this study indicate that artificial intelligence in the STIPRAM library is very influential for users so that it can help users and librarians in conducting research and work more easily because information retrieval in the STIPRAM library can work optimally
HIV Productively Infects Highly Differentiated and Exhausted CD4+ T Cells During AIDS

Background: Throughout HIV infection, productively infected cells generate billions of viral particles and are thus responsible for body-wide HIV dissemination, but their phenotype during AIDS is unknown. As AIDS is associated with immunological changes, analyzing the phenotype of productively infected cells can help understand HIV production during this terminal stage. Methods: Blood samples from 15 untreated viremic participants (recent infection, n=5; long-term infection, n=5; active opportunistic AIDS-defining disease, n=5) and 5 participants virologically controlled on antiretroviral therapy (ART) enrolled in the Analysis of the Persistence, Reservoir and HIV Latency (APRIL) study (NCT05752318) were analyzed. Cells expressing the capsid protein p24 (p24+ cells) after 18 hours of resting or 24 hours of stimulation (HIV-Flow) revealed productively infected cells from viremic participants or translation-competent reservoir cells from treated participants, respectively. Results: The frequency of productively infected cells tended to be higher during AIDS in comparison with recent and long-term infections (median, 340, 72, and 32/million CD4+ T cells, respectively) and correlated with the plasma viral load at all stages of infection. Altogether, these cells were more frequently CD4low, HLA-ABClow, CD45RA-, Ki67+, PD-1+, with a non-negligible contribution from pTfh (CXCR5+PD-1+) cells, and were not significantly enriched in HIV coreceptors CCR5 nor CXCR4 expression. The comparison markers expression between stages showed that productively infected cells during AIDS were enriched in memory and exhausted cells. In contrast, the frequencies of infected pTfh were lower during AIDS compared to non-AIDS stages. A UMAP analysis revealed that total CD4+ T cells were grouped in 7 clusters and that productive p24+ cells were skewed to given clusters throughout the course of infection. Overall, the preferential targets of HIV during the latest stages seemed to be more frequently highly differentiated (memory, TTD-like) and exhausted cells and less frequently pTfh-like cells. In contrast, translation-competent reservoir cells were less frequent (5/million CD4+ T cells) and expressed more frequently HLA-ABC and less frequently PD-1. Conclusions: In long-term infection and AIDS, productively infected cells were differentiated and exhausted. This could indicate that cells with these given features are responsible for HIV production and dissemination in an immune dysfunction environment occurring during the last stages of infection.
Sinking, Swimming, or just treading water. : The Olympic Legacy for London 2012- 4 Years on. Has it made a difference? Pupil Voice and an an analysis of Swimming Provision. To be published by ATINER The Athens Journal of Sport

Barry Costas, 'Sinking, Swimming or just Treading Water. The Olympic Legacy from London 2012 – 4 Years On. Has it made any difference? Pupil Voice and an Analysis of Swimming Provision', Athens Journal of Sports, Vol. 4(1): 35-52, March 2017. This is an Open Access article, available online at: https://www.athensjournals. gr/ajspo/past/v4i1.
Fetal and Infant Effects of Maternal Opioid Use during Pregnancy: A Literature Review including Clinical, Toxicological, Pharmacogenomic, and Epigenetic Aspects for Forensic Evaluation

The two primary classes of opioid substances are morphine and its synthetic derivative, heroin. Opioids can cross the placental barrier, reaching fetal circulation. Therefore, at any gestational age, the fetus is highly exposed to pharmacologically active opioid metabolites and their associated adverse effects. This review aimed to investigate all the studies reported in a timeframe of forty years about prenatal and postnatal outcomes of opioid exposition during pregnancy. Clinical and toxicological aspects, as well as pharmacogenetic and epigenetic research focusing on fetal and infant effects of opioid use during pregnancy together with their medico-legal implications are exposed and discussed.
Socioeconomic Status and its Impact on Receptive Vocabulary and Executive Function in Young Children

This article examines the impact of Socioeconomic Status (SES) on the development of receptive vocabulary and executive function in young children. Integrating current research, the paper highlights the challenges faced by children from low SES backgrounds in terms of language comprehension and executive functioning. Studies indicate a close relationship between SES and a child's receptive language abilities and executive functions, which are crucial for overall learning and development. The article also explores how SES influences cognitive development in children through various pathways, such as home language environment, stress levels, and access to resources. Additionally, the paper discusses early intervention measures and policy recommendations for children from low SES backgrounds to bridge the developmental gap associated with SES.
What does Web 4.0 Promise for Tourism Ecosystem? A Qualitative Research on Tourism Ecosystem Stakeholders’ Awareness

The major motivation of this study is stemmed from the fact that web 4.0 will reveal new structures in consumer, service, stakeholder and business models in the tourism ecosystem. Technologies such as intelligent agents, big data, internet of objects and augmented reality will be important factors in this change. The main purpose of the research is to determine the stakeholders' awareness about the changes that the web 4.0 arguments may have on the tourism products and services, tourist profiles, business models and stakeholders in the tourism ecosystem. The study also aims to explore the stakeholders' predictions about this issue. The research was conducted through semi-structured interview with 18 participants including hotel enterprise directors, owners of travel agencies, public institution managers, non-governmental organization managers and academicians that play a supporting role in the tourism ecosystem in Izmir destination. The results revealed that the majority of stakeholders are aware of web 4.0 and its potential impacts. In addition, participants believe that web 4.0 will create new business models in which technology-producing stakeholders are involved, new tourist services that benefit from augmented reality and similar technologies and new tourist consumer profiles that will demand these tourist services.
Computer Vision-Based Position Estimation for an Autonomous Underwater Vehicle

Autonomous Underwater Vehicles (AUVs) are currently one of the most intensively developing branches of marine technology. Their widespread use and versatility allow them to perform tasks that, until recently, required human resources. One problem in AUVs is inadequate navigation, which results in inaccurate positioning. Weaknesses in electronic equipment lead to errors in determining a vehicle’s position during underwater missions, requiring periodic reduction of accumulated errors through the use of radio navigation systems (e.g., GNSS). However, these signals may be unavailable or deliberately distorted. Therefore, in this paper, we propose a new computer vision-based method for estimating the position of an AUV. Our method uses computer vision and deep learning techniques to generate the surroundings of the vehicle during temporary surfacing at the point where it is currently located. The next step is to compare this with the shoreline representation on the map, which is generated for a set of points that are in a specific vicinity of a point determined by dead reckoning. This method is primarily intended for low-cost vehicles without advanced navigation systems. Our results suggest that the proposed solution reduces the error in vehicle positioning to 30–60 m and can be used in incomplete shoreline representations. Further research will focus on the use of the proposed method in fully autonomous navigation systems.
Further Results on the Input-to-State Stability of a Linear Disturbed System with Control Delay

In this paper, a theorem is obtained that gives sufficient input-to-state stability conditions for linear systems with control delay and additive disturbances. Stabilizing feedback is considered available in the absence of delay and disturbances. The mathematical tools are the Lyapunov–Krasovskii functional, the Jensen inequality and the double Hadamard inequality. The critical delay is highlighted.
Advances in 3D Culture Models to Study Exosomes in Triple-Negative Breast Cancer

Simple Summary Breast cancer comes in different types, making it hard to treat effectively. One particularly aggressive type, called triple-negative breast cancer, is tough to target with current treatments. Scientists use advanced methods like 3D cultures, which mimic human tissue better than traditional lab methods, to study breast cancer. These 3D cultures help understand how tiny communication structures called exosomes affect cancer growth, spread, and response to therapy. Exosomes are like messengers between cells and can influence cancer’s behavior and response to therapy. In this the review, we seek to discuss the effect of 3D cultures on the function of exosomes, which we believe could play an important role in improving exosome-mediated cancer treatment by delivering drugs more precisely and studying how cancer becomes resistant to treatment. This research could lead to better therapies and help us understand how cancer spreads and resists treatment. Abstract Breast cancer, a leading cause of cancer-related deaths globally, exhibits distinct subtypes with varying pathological, genetic, and clinical characteristics. Despite advancements in breast cancer treatments, its histological and molecular heterogeneity pose a significant clinical challenge. Triple-negative breast cancer (TNBC), a highly aggressive subtype lacking targeted therapeutics, adds to the complexity of breast cancer treatment. Recent years have witnessed the development of advanced 3D culture technologies, such as organoids and spheroids, providing more representative models of healthy human tissue and various malignancies. These structures, resembling organs in structure and function, are generated from stem cells or organ-specific progenitor cells via self-organizing processes. Notably, 3D culture systems bridge the gap between 2D cultures and in vivo studies, offering a more accurate representation of in vivo tumors’ characteristics. Exosomes, small nano-sized molecules secreted by breast cancer and stromal/cancer-associated fibroblast cells, have garnered significant attention. They play a crucial role in cell-to-cell communication, influencing tumor progression, invasion, and metastasis. The 3D culture environment enhances exosome efficiency compared to traditional 2D cultures, impacting the transfer of specific cargoes and therapeutic effects. Furthermore, 3D exosomes have shown promise in improving therapeutic outcomes, acting as potential vehicles for cancer treatment administration. Studies have demonstrated their role in pro-angiogenesis and their innate therapeutic potential in mimicking cellular therapies without side effects. The 3D exosome model holds potential for addressing challenges associated with drug resistance, offering insights into the mechanisms underlying multidrug resistance and serving as a platform for drug screening. This review seeks to emphasize the crucial role of 3D culture systems in studying breast cancer, especially in understanding the involvement of exosomes in cancer pathology.
Factors Affecting the Migration Decision of Tsunami Survivors from the Relocation Area

The government has undertaken a relocation program to address the housing problems caused by the earthquake and tsunami of December 26, 2004 in Aceh. However, the relocation of tsunami survivors also caused other impacts after the relocation was carried out. If the relocation site is not as desirable, it can cause tsunami survivors to decide to out-migrate the relocation area. This study was conducted to determine factors that significantly affect the decision of migration of tsunami survivors from the relocation area. This research is expected to provide information on post-disaster relocation for consideration in making relocation policy in the future. We use classification tree, which is part of the CART (Classification and Regression Trees) method. The data used is from The Aftermaid of Aid (AoA) survey conducted by International Center for Aceh and Indian Ocean Studies (ICAIOS) and Earth Observatory of Singapore (EOS) during 2014-2015. The results of the research indicate the factors that significantly affect the migration decision of tsunami survivors from a relocation area are gender, age, and job before relocation, total assets, and the distance of relocation house to central market, house modification, and concerns about possible of future tsunami. Most affecting factor of migration decision, however, is the distance of relocation house to the central market, confirming the impact of sosio-economic factor of post-disaster relocation. The optimal classification tree obtained has a classification accuracy rate of 85, 64%.
Design and Study the Performance of a CMOS-Based Ring Oscillator Architecture for 5G Mobile Communication

Oscillator circuits are used to make accurate and reliable clock signals for systems as simple as a wristwatch and as complicated as satellites, which are important for long-distance communication. There are many ways to build an oscillator circuit, using either passive or active parts. Each option has pros and cons, but at the current level of mobile communication development, the most important things are interoperability and low power use. This need has driven the development of compact, battery-operated electronics, and Very Large-Scale Integration (VLSI)-based ring oscillators provide the ideal solution. These oscillators ought to dissipate less power, have a large tuning range, and be compact. The paper presents a novel Complementary Metal Oxide Silicon (CMOS) ring oscillator that serves as a Voltage Controlled Oscillator. The suggested architecture utilizes the advantages of both a current-starved ring oscillator and a negative-skewed delay by combining their constituent parts. The proposed architecture has a control voltage of 1.15 V and a supply voltage of 2 V, generating a 9.35 GHz dominant frequency with a 13.82% harmonic distortion between the inputs and outputs. The proposed architecture can implement 5G-based applications that require high frequency and low power by carefully selecting the passive components within the design. Doi: 10.28991/ESJ-2024-08-01-020 Full Text: PDF