Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithm of Holding Time Control Using Delay-Tolerant Packet for Energy-Efficient Transmission

ABSTRACT This paper proposes an energy transmission method to maximize energy efficiency of a based station. This method makes use of classification of service type to solve an inefficient use of transmission power, which is from exponential relationship between the legacy data throughput and transmission power. The proposed one is a way to find the most energy-efficiency points with the transmitted optimal amount of data on users in a base station of wireless network environment. For this, we propose EETA (Energy-Efficient Transmission Algorithm) which can control the amount of data and the holding time at the base station. As a result, the proposed method can improve the energy efficiency of about 10% compared to the legacy base station.Keywords:Wireless Data Transmission, Energy-Efficiency, Base Station, Next Generation Network, Type of Service 에너지 효율적인 전송을 위한 지연 허용 패킷의 유지시간 제어 알고리즘 류 승 민 † ⋅최 원 석 †† ⋅최 성 곤 ††† 요 약 제안된 논문은 기지국의 에너지 효율을 최대화하기 위한 에너지 전송 방식에 관한 것으로, 기존의 데이터 처리량과 송신전력 사이의 지수 함수적 관계에 따른 비효율적 문제를 해결함으로써 서비스의 유형에 따른 데이터를 분류하고, 무선 네트워크 환경의 기지국에서 사용자들에게 전송 되는 최적의 데이터 량에 따른 에너지 최적화 지점을 찾아내는 방법이다. 이를 위해, 기지국에서 사용자에게 전송되는 데이터의 양 및 유지시간을 조절하여 데이터 전송의 에너지 효율 최적화 지점을 찾을 수 있는 EETA 알고리즘(Energy-Efficient Transmission Algorithm)을 제안한다. 결과적으로 제안한 방식은 기존 기지국 대비 에너지 효율이 약 10% 향상됨을 알 수 있다. 키워드:무선 데이터 전송, 에너지 효율, 기지국, 차세대 네트워크, 서비스 타입
A comprehensive characterization of alternative splicing events related to prognosis and the tumor microenvironment in lung adenocarcinoma

Background Alternative splicing (AS) is a critical mechanism of post-transcriptional regulation and has been widely reported to be associated with the tumor progression and tumor microenvironment (TME) formation. However, the role of AS in lung adenocarcinoma (LUAD) has not been clearly elucidated. This study presents a comprehensive analysis exploring the impact of AS on prognosis and TME in LUAD. Methods The gene expression transcriptome profiles and survival data were obtained from The Cancer Genome Atlas (TCGA) database, and the splicing profiles were obtained from the TCGA SpliceSeq database. Base on prognostic AS events, a prognostic signature was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) regression followed by multivariate Cox regression analysis. Survival outcomes was analyzed using the Kaplan-Meier method and the predictive performance of the signature was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, the landscape of the TME was assessed by ESTIMATE, Microenvironment Cell Population (MCP)-counter, and single-sample Gene-Set Enrichment Analysis (ssGSEA) algorithms. Results A total of 127 prognostic AS events with P value <0.001 from 89 genes in LUAD were confirmed. A prognostic signature was constructed based on 20 prognostic AS events. Kaplan-Meier survival analysis demonstrated that higher risk scores were associated with poorer overall survival (OS). The area under the ROC curve of risk scores predicting the 1-, 3-, and 5-year survival probability were 0.791, 0.847, and 0.832, respectively. Furthermore, significant relationship was observed between the prognostic signature and the landscape of the TME. High-risk patients had lower stromal/immune scores, higher tumor purity, and significantly decreased abundance of majority immune cells, and immune-related signatures (P<0.05). Finally, a potential regulatory mechanism of the AS events is displayed in a regulatory network. Conclusions This research highlights the prognostic value of AS events for patients with LUAD and provide new insight into the regulation of the TME by AS. Notably, AS may affect the patient’s prognosis by altering the TME. Our findings provide important guidance for the development of novel biomarkers and therapeutic targets in patients with LUAD.
Changes in Upper-Body Muscular Strength and Power in Paralympic Swimmers: Effects of Training Confinement during the COVID-19 Pandemic

The aim of this case series was to evaluate the effectiveness of a dry-land home-training program conducted during the COVID-19 pandemic period in Paralympic swimmers. Previous evidence showed the importance of muscular strength and power training for Paralympic swimmers due to the positive relationship between severity of impairment, swimming technique and biomechanics parameters. Specifically, we aimed to analyze: (i) the effects of a customized training regime conducted pre, during and post restrictions on upper-body muscular strength and power (one repetition maximum, mean propulsive velocity, and mean relative propulsive power) compared to a regular gym-based program; (ii) the associations between mean propulsive velocity and load during two upper body exercises in order to estimate the one repetition maximum. Four elite Paralympic swimmers were retrospectively analyzed in upper-body muscular strength, mean propulsive velocity and mean relative propulsive power in bench press and lat pull-down exercises at three time points: T0 (prior the Lockdown period), T1 (immediately after the Lockdown confinement), T2 (sixteen weeks after returning to gym training). Our findings suggest a very likely decrement in one repetition maximum, mean propulsive velocity, and mean relative propulsive power during the Lockdown period compared with the T0 period with a subsequent very likely increment in one repetition maximum after returning to gym training (T2) compared with the lockdown period (T0). Conversely, mean relative propulsive power showed an unclear improvement in all athletes in T2 compared with T1. These results were also corroborated by the Friedman’s test followed by the Dunn’s pairwise comparison that mainly showed a decrement from T0 to T1 (p < 0.05). At the same time, it appears that muscle strength and power could be rapidly restored close to the pre-lockdown levels following an adequate training program in the gym, albeit without significance (p > 0.05). Finally, the close relationship between mean propulsive velocity and load in bench press and lat pull-down exercises was also confirmed in para swimming, making a possible estimation of one repetition maximum.
Sound insulation performance optimization of lightweight sandwich panels

Optimization of lightweight sandwich panels has been intensively studied, but optimization in terms of the acoustic objective is still a hot topic, and the influence on optimization results caused by sandwich panel geometric constraints is also rarely investigated. In this study, the optimization on lightweight sandwich panel designs is investigated by maximizing the sound insulation performance and minimizing the panel mass simultaneously. Firstly, the acoustic model of sandwich panels is discussed, which provides basic formulas to model the acoustic objective function. Secondly, the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided. Finally, the numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate the tradeoff between two objectives, the panel transmission loss corresponding to the three typical points in the Pareto front, and how the geometric constraints impact the optimization results for lightweight sandwich panels.
Predictive Factors of Functioning Adrenal Incidentaloma: A 15-Year Retrospective Study

Background and Objectives: Adrenal incidentaloma is an adrenal mass that is found incidentally in abdominal imaging studies. It is important to categorize whether the mass is a functioning or non-functioning incidentaloma to determine the appropriate management and follow-up. Our study aimed to identify predictive factors for functioning adrenal incidentaloma that could assist in early detection and in determining which patients may require hormonal investigations. Materials and methods: This 15-year retrospective study was performed in a tertiary care medical center. A total of 244 patients with adrenal incidentaloma were identified, of whom 88 had functioning adrenal incidentaloma. The patients’ clinical biochemical factors and radiographic parameters were reviewed. Multivariable analysis using logistic regression with backward stepwise selection analysis was performed. Results are presented as odds ratios (ORs) with 95% confidence interval (CI). Statistical significance was set at p < 0.05. Results: A significant clinical predictor for functioning adrenal incidentaloma is a history of hypertension (OR 2.72, 95% CI(1.53, 4.82)), while significant radiological predictors include mass size >4 cm (OR 2.20, 95% CI(1.20, 4.02)) and Hounsfield units (HU) < 10 (OR 2.47, 95% CI(1.23, 4.94)). Conclusions: These easy-to-obtain clinical and radiological predictors can be used to help identify functioning adrenal incidentaloma. In clinical practice, taking these factors into consideration could potentially reduce the number of investigations required to diagnose functioning adrenal incidentaloma.
DuraCloud™ and Flexible Digital Preservation at the Texas Digital Library

The Texas Digital Library is now offering preservation service via DuraCloud™, an open source technology developed by DuraSpace. In 2014, the membership of the TDL formed a Working Group to explore the software and define best practices, given the diverse approaches to the issue of preservation. In January 2015 we first announced the service and made the service available in Spring of 2015. In this presentation, the Texas Digital Library will describe how our implementation of the DuraCloud™ software provides multiple upload options for preservationists through a selection of interfaces and tools intended to serve a variety of audiences, from librarians at their desktop to server administrators working at the command line. We will describe how DuraCloud™@TDL fits in to varying environments as a primary or third party preservation solution, and we will also define the array of options for durable, reliable storage infrastructure for preservationists in the care of the unique collections of their institutions. Looking forward, TDL will discuss the issues regarding preservation management and challenges we are addressing with users such as format management and metadata management within DuraCloud™@TDL. TDL will present planned next steps for additional services such as integration of DuraCloud™@TDL with DSpace, using DuraCloud™ as a platform for utilization of the Digital Preservation Network, and the potential for using DuraCloud™ to serve content to the public. We will be joined by representatives of DuraSpace who will present information about the ongoing development of DuraCloud™as well as future plans for DuraCloud features/functionality and integrations. In addition, TDL and DuraSpace will discuss how TDL community activities tie to the broader trends of DuraCloud customer use and the joint efforts between the two organizations to create resources and best practices around preserving content in a cloud environment. Lastly, ways in which TDL and others can assist development as part of the DuraCloud user-base and the overall DuraSpace community will be highlighted.
Performance Evaluation of Nonacosan-10-ol-Based Polyethylene Packaging Material Using Molecular Dynamics Simulations

Packaging material has a significant role in maintaining or altering the shelf life of different products. Polymer materials are extensively used as packaging materials for different perishable and non-perishable products both during transportation and storage. This article aims at developing a new polymer composite which can be used as packaging material. This new composite addresses the challenge of controlling oxygen diffusion rates during the storage of perishable goods such as vegetables, meat and produce, etc. The proposed new composite primarily consists of nonacosan-10-ol and polyethylene. Molecular dynamics simulations (MDS) are performed by mixing 5.2%, 17.1%, 29.2%, 40.8% and 45.2% (wt/wt) of nonacosan-10-ol to amorphous polyethylene. Mechanical properties such as Young’s modulus/glass transition temperature, and gas transport properties such as diffusion coefficient and diffusion volume are estimated from the MDS and diffusion related simulations consisting of different oxygen concentrations in polyethylene-alone system and polyethylene- nonacosan-10-ol blends. The impact of adding different weight percent of nonacosan-10-ol to polyethylene is quantitatively assessed and optimal composition of the proposed additive is suggested corresponding to minimal oxygen diffusion rate, high elastic modulus and good thermal stability.
Big Data in Vehicular Cloud Computing: Review, Taxonomy, and Security Challenges

Modern vehicles equipped with various smart sensors have become a means of transportation and have become a means of collecting, creating, computing, processing, and transferring data while traveling through modern and rural cities. A traditional vehicular ad hoc network (VANET) cannot handle the enormous and complex data that are collected by modern vehicle sensors (e.g., cameras, lidar, and global positioning systems (GPS)) because they require rapid processing, analysis, management, storage, and uploading to trusted national authorities. Furthermore, the integrated VANET with cloud computing presents a new concept, vehicular cloud computing (VCC), which overcomes the limitations of VANET, brings new services and applications to vehicular networks, and generates a massive amount of data compared to the data collected by individual vehicles alone. Therefore, this study explored the importance of big data in VCC. First, we provide an overview of traditional vehicular networks and their limitations. Then we investigate the relationship between VCC and big data, fundamentally focusing on how VCC can generate, transmit, store, upload, and process big data to share it among vehicles on the road. Subsequently, a new taxonomy of big data in VCC was presented. Finally, the security challenges in big data-based VCCs are discussed.
Abnormal neutrophil polarization in chronic obstructive pulmonary disease and how cigarette smoke extracts attract neutrophils

Background Airway inflammation produced by neutrophils is a critical factor in the development of chronic obstructive pulmonary disease (COPD). Poor or excessive neutrophil polarization and chemotaxis may lead to pathogen accumulation and tissue damage. However, it is unclear how cigarette smoke extract (CSE) attracts neutrophils and to what extent COPD is affected by the improper polarization of these abnormal neutrophils. This study sought to assess the polarization and migration dynamics of neutrophils isolated from patients with different severities of COPD compared to healthy smoking and non-smoking control subjects, and to detect how CSE triggers the polarization of neutrophils. Methods The neutrophils were freshly isolated using standard isolation protocol. The polarization of the neutrophils was observed using a Zigmond chamber when stimulated by a linear concentration gradient of CSE or N-formyl-methionine-leucine-phenylalanine (fMLP). Confocal laser-scanning microscopy was used to observe the intracellular calcium of the neutrophils. The experimental data are presented as the mean ± standard deviation. SPSS 20.0 software was used for the statistical analysis. A P value <0.05 was considered statistically significant. Results The neutrophils from the COPD patients showed a higher frequency of spontaneous polarization and a lower prevalence of directionality polarization than those from the healthy control (HC) and smoker subjects. The abnormal polarization of the neutrophils from the COPD patients was altered by the influence of store-operated calcium entry (SOCE) component matrix interaction molecules 1 and 2 and calcium release-activated calcium channel protein 1 [stromal interaction molecule 1 (STIM1), Stromal interaction molecule 2 (STIM2), and calcium release-activated calcium modulator 1 (ORAI1)]. Conclusions The COPD neutrophils exhibited unique polarization and migration patterns compared to those of the cells examined from other populations. The attraction of CSEs to neutrophils was mediated by the SOCE/Akt/Src pathway.
New Young Voters’ Decision to Vote: Impact of Access, Analysis and Evaluate, Create and Act

The development of technology in media provides advanced communication processes and sources of information conventionally provided by news agencies but today, media users are capable to create information. The ability to create media content is a benefit of the exposure to social media use and affects the Government's decision to lower the voting age in Malaysia (Undi18). The implementation of Undi18 is based on the judgment that new young voters have high political interests and greater political knowledge that led to the decision to vote. The purpose of this study is to measure the impact of media literacy competency on the decision to vote among new young voters and to develop the decision to vote model from a media literacy perspective. By using simple random sampling for a quantitative survey among 323 respondents among higher education institutions in Malaysia. This study deploys Structural Equation Modelling for descriptive and inferential analysis apart from model development evaluation. This study found that media literacy competency has significantly influenced the decision to vote among new young voters. The decision to vote model from media literacy theory developed in this study found that analysis and evaluation are strong predictors of the decision to vote among new young voters followed by access and act dimensions. Surprisingly, create dimension reported a negative influence on the decision to vote among new young voters. Young people did not create political updates through their social media accounts due to socioeconomic, psychological, and social factors that have been discussed in this article.
Automated People Movers with rope traction: engineering and modelling an innovative hybrid solution to optimise energy use / Automated People Mover con trazione a fune: progettazione e modellizzazione di una soluzione ibrida innovativa finalizzata al risparmio energetico

At the beginning of the 21st century, several scientific studies drew attention to the unsustainability of the massive use of fossil fuels as the main global source of energy and this led to international public organisations starting numerous projects aimed at containing the resulting greenhouse gas emissions. In this context, Automated People Movers can play an important role, as they are fully automated transport systems operating on a fixed track, along which the vehicles can be pulled by one or more steel wire ropes. This feature makes it possible to manufacture lighter and less energy consuming vehicles because of the on-board absence of propulsion, transmission and energy accumulation elements, with a consequent lightening of the structural parts. The use of electric energy to power these transport systems makes it possible to take advantage of energy sources that are not necessarily black-oil dependent. The energy aspect has been analysed using an original simulation model, developed with MATLAB®, in which several variables, including the vehicle load factor, have been considered. The results, expressed in terms of gep/(pass·km), have been compared with the specific energy consumption of alternative urban transit systems, according to the most recent technical literature
Unveiling the nature of a miniature world: a horizon scan of fundamental questions in bryology

ABSTRACT Introduction Half a century since the creation of the International Association of Bryologists, we carried out a review to identify outstanding challenges and future perspectives in bryology. Specifically, we have identified 50 fundamental questions that are critical in advancing the discipline. Methods We have adapted a deep-rooted methodology of horizon scanning to identify key research foci. An initial pool of 258 questions was prepared by a multidisciplinary and international working group of 32 bryologists. A series of online surveys completed by a broader community of researchers in bryology, followed by quality-control steps implemented by the working group, were used to create a list of top-priority questions. This final list was restricted to 50 questions with a broad conceptual scope and answerable through realistic research approaches. Key results The top list of 50 fundamental questions was organised into four general topics: Bryophyte Biodiversity and Biogeography; Bryophyte Ecology, Physiology and Reproductive Biology; Bryophyte Conservation and Management; and Bryophyte Evolution and Systematics. These topics included 9, 19, 14 and 8 questions, respectively. Conclusions Although many of the research challenges identified are not newly conceived, our horizon-scanning exercise has established a significant foundation for future bryological research. We suggest analytical and conceptual strategies and novel developments for potential use in advancing the research agenda for bryology.
Development and Validation of an Artificial Intelligence Electrocardiogram Recommendation System in the Emergency Department

The machine learning-assisted electrocardiogram (ECG) is increasingly recognized for its unprecedented capabilities in diagnosing and predicting cardiovascular diseases. Identifying the need for ECG examination early in emergency department (ED) triage is key to timely artificial intelligence-assisted analysis. We used machine learning to develop and validate a clinical decision support tool to predict ED triage patients’ need for ECG. Data from 301,658 ED visits from August 2017 to November 2020 in a tertiary hospital were divided into a development cohort, validation cohort, and two test cohorts that included admissions before and during the COVID-19 pandemic. Models were developed using logistic regression, decision tree, random forest, and XGBoost methods. Their areas under the receiver operating characteristic curves (AUCs), positive predictive values (PPVs), and negative predictive values (NPVs) were compared and validated. In the validation cohort, the AUCs were 0.887 for the XGBoost model, 0.885 for the logistic regression model, 0.878 for the random forest model, and 0.845 for the decision tree model. The XGBoost model was selected for subsequent application. In test cohort 1, the AUC was 0.891, with sensitivity of 0.812, specificity of 0.814, PPV of 0.708 and NPV of 0.886. In test cohort 2, the AUC was 0.885, with sensitivity of 0.816, specificity of 0.812, PPV of 0.659, and NPV of 0.908. In the cumulative incidence analysis, patients not receiving an ECG yet positively predicted by the model had significantly higher probability of receiving the examination within 48 h compared with those negatively predicted by the model. A machine learning model based on triage datasets was developed to predict ECG acquisition with high accuracy. The ECG recommendation can effectively predict whether patients presenting at ED triage will require an ECG, prompting subsequent analysis and decision-making in the ED.
Genome Mining of α-Pyrone Natural Products from Ascidian-Derived Fungus Amphichorda felina SYSU-MS7908

Culturing ascidian-derived fungus Amphichorda felina SYSU-MS7908 under standard laboratory conditions mainly yielded meroterpenoid, and nonribosomal peptide-type natural products. We sequenced the genome of Amphichorda felina SYSU-MS7908 and found 56 biosynthetic gene clusters (BGCs) after bioinformatics analysis, suggesting that the majority of those BGCSs are silent. Here we report our genome mining effort on one cryptic BGC by heterologous expression in Aspergillus oryzae NSAR1, and the identification of two new α-pyrone derivatives, amphichopyrone A (1) and B (2), along with a known compound, udagawanone A (3). Anti-inflammatory activities were performed, and amphichopyrone A (1) and B (2) displayed potent anti-inflammatory activity by inhibiting nitric oxide (NO) production in RAW264.7 cells with IC50 values 18.09 ± 4.83 and 7.18 ± 0.93 μM, respectively.