Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of the Most Important Cardiovascular Risk Factors Based on Cross-Sectional Studies in the Population of Latvia

Background and Objectives: The aim of the study was to analyze the prevalence of cardiovascular risk factors (RFs) in Latvia from the population-based cross-sectional study performed in 2019–2020 and to compare the results with a similar study done in 2009–2010. Materials and Methods: The target sample of 6000 individuals representing a cross-section of Latvia’s inhabitants (aged 25–74) was formed using stratified two-stage cluster sampling. The survey had two components: (1) an interview using a pre-specified questionnaire and (2) physical examination (height, weight, arterial pressure) and collection of venous blood samples to measure levels of fasting glucose (Glu), total cholesterol (TC), high and low-density lipoprotein cholesterol (HDL-C/LDL-C), and triglycerides (Tg). In total, 4070 individuals were interviewed (32% non-response), from which 2218 (55%) individuals underwent physical examination and collection of blood samples. Results: The most frequently observed RFs were high LDL-C (62.0%), smoking (45.3%), and arterial hypertension (36.8%), while the prevalence of self-reported high cholesterol and hypertension was 19.3 and 18.6%, respectively. A decrease in the prevalence of hypertension, high LDL-C, and Glu was noted. Smoking decreased in younger men. The mean number of five most important cardiovascular RFs was 2.0 (95% confidence interval (CI) 2.0, 2.1); 2.3 (95% CI 2.2, 2.4) for men and 1.8 (95% CI 1.7, 19) for women. The average number of RFs has decreased by 0.3 in 10 years, t(5883) = −7.2, p < 0.001. Conclusions: Although the prevalence of cardiovascular RFs remains noteworthy, an improvement in the risk profile of the Latvian population has been observed over the past decade. The study shows subjective self-underestimation of cardiovascular risk.
Ultra-wide varifocal imaging with selectable region of interest capacity using Alvarez lenses actuated by dielectric elastomer

A remarkable feature of Alvarez lenses is that a wide focal length tuning range can be achieved using lateral displacement rather than commonly used axial translation, thus, reducing the overall length of varifocal imaging systems. Here, we present novel lens elements based on Alvarez lenses actuated by a dielectric elastomer (DE). The proposed lens elements are composed of the varifocal component and the scanning component. Based on the proposed lens elements, an imaging system is built to realize ultra-wide varifocal imaging with a selectable region of interest. The lens elements have a variable focus function based on an Alvarez lens structure and a DE actuator and a scanning function based on the DE-based four-quadrant actuators. The large deformation generated by the DE actuators permits the lateral displacement of the Alvarez lenses up to 1.145 mm. The focal length variation of the proposed varifocal component is up to 30.5 times, where the maximum focal length is 181 mm and the minimum focal length is 5.94 mm. The rise and fall times of the varifocal component are 160 ms and 295 ms, respectively. By applying different voltages on four-quadrant actuators, the scanning component allows the varifocal component to move in different directions and endows the varifocal component with a selectable region of interest imaging capability. The scanning range of the scanning component is 17.57 ° . The imaging resolution of the imaging system is approximately 181 lp/mm. The system developed in the current study has the potential to be used in consumer electronics, endoscopy, and microscopy in the future
Innovating and the dynamics of temporal scaffolding

Despite the growing acknowledgement of temporal complexities associated with the process perspective on innovation, insights into how timing and temporal experiences shape innovating; remains nascent and under researched. Why might this be the case and how can we gain better insights into the temporal dynamics which unfold while innovating? In this paper, I address this puzzle by tracing the theoretical origins of current limitations in literature to the distinction between the 'substantialist' and 'processual' ontologies in process research. Specifically, I demonstrate two major implications of adopting the 'substantialist' perspective in process research. These are first, the false opposition between persistence and change resulting in theories such as the 'punctuated equilibrium model'; and second, the nature of 'substantialist' and 'processual' time. These insights are then woven into a conceptual framework which informs the process research methodology used to investigate, two new product development projects at a Scottish high value manufacturing firm. Analysis of the data illuminates the unfolding of three distinct yet intertwined processes which I’ve called the process of setting temporal boundaries, the process of temporal prioritizing and the process of temporal sequencing. Taken together, these processes constitute a dynamic process, I call the 'Dynamics of temporal scaffolding'. I conclude by outlining the theoretical and practical implications of the 'dynamics of temporal scaffolding' for innovation research and practice. Such an approach, I believe, would allow us to integrate the temporal experience of organising while innovating with process theories in innovation research.
A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data

Asynchronous Video Interviewing (AVI) is considered one of the most recent and promising innovations in the recruitment process. Using AVI in combination with AI-based technologies enables recruiters/employers to automate many of the tasks that are typically required for screening, assessing, and selecting candidates. In fact, the automated assessment and selection process is a complex and uncertain problem involving highly subjective, multiple interrelated criteria. In order to address these issues, an effective and practical approach is proposed that is able to transform, weight, combine, and rank automated AVI assessments obtained through AI technologies and machine learning. The suggested approach combines Cumulative Belief Structures with the Weighted Bonferroni-OWA operator, which allows (i) aggregating assessment scores obtained in different forms and scales; (ii) incorporating interrelationships between criteria into the analysis (iii) considering accuracies of the learning algorithms as weights of criteria; and (iv) weighting criteria objectively. The proposed approach ensures a completely data-driven and efficient approach to the personnel selection process. To justify the effectiveness and applicability of the suggested approach, an example case is presented in which the new approach is compared to classical MCDM techniques.
A Simulation Enhanced VSM Approach for high-Mix Manufacturing Environment

As market requirements change, manufacturers are experiencing the transition from low-mix to high-mix production, handling a larger number of product variants to stay competitive and avoiding reduction of system performance. Value stream mapping (VSM) is a preferred method of implementing lean manufacturing principles in various industries with the aim of improving system performance. However, most applications are limited to low-mix environment. This paper combines VSM and discrete event simulation (DES) to model and improve the performance of a high-mix production system. The as-is model based on VSM is verified using current state production data. Accordingly, the simulation result shows the potential of improving system performance by implementing lean manufacturing principles, which provides a reference to the case company. Keywords—Value stream mapping; high-mix; discrete event simulation
Women in Nontraditional Occupations: a mixed methods qualitative case study on women in the U.S. concrete-construction industry

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Distribution and Pattern of an Insurance Health Claim System: A Time Series Approach

There is a continuous increase in health costs, thereby increasing pressure on individuals and consequently making the amounts claimed by the insured to be on the increase. In this study, data was collected from a large local insurance company in Zimbabwe for the period from January 2012 to December 2016. The aim of this study was to analyse the distribution and future pattern of insurance health claim system using time series approach. Akaike information criterion and Schwarz Bayesian criterion were used to select the adequate model through maximum likelihood estimation methods. ARIMA (0, 0, 0) (1, 0, 1) [12] is the model that was chosen to forecast claim amounts. The use of ARIMA models proves to be an excellent instrument for predicting and capturing the cost trend of health claims which can help in decision making to insurance companies. Keywords: ARIMA; Box-Jenkins; health insurance; time series.
The Effect of Financial Technology on the Performance of Micro, Small, and Medium Businesses

Micro, small, and medium enterprises dominate the number of entrepreneurs in developing countries like Indonesia. Even though the scale enterprises are small, MSM entrepreneurs can’t be separated from tech- nology in the current era. Therefore, this study aims to analyze how finan- cial technology can affect the performance of Micro Small. and Medium Enterprises in Jakarta, Bogor, Depok, Tangerang and Bekasi. The data taken for this study is primary data obtained through the distribution of online questionnaires to MSM entrepreneurs in Jakarta, Bogor, Depok, Tangerang, and Bekasi. The number of samples in this study was 130 respondents with a non-probability sampling method with purposive sampling technique. The research data that has been obtained were analyzed using SPSS 26 software. The results showed that the use of financial technology did not significantly affect the performance of MSMEs. Meanwhile, financial tech- nology funding, cash back, or promos on products sold affects the perfor- mance of MSMEs. Maybe, it should be Micro, small, medium.
Motility Mapping Quantification Using the Classical Optical Flow Algorithm for Small Bowel Crohn’s Disease: Comparison with Balloon-assisted Enteroscopy Findings

Purpose To quantify bowel motility shown on cine MRI using the classical optical flow algorithm and compare it with balloon-assisted enteroscopy (BAE) findings in patients with Crohn’s disease (CD). Methods This retrospective study included 29 consecutive patients with CD who had undergone MR enterocolonography (MREC) and BAE between March and May 2017. We developed computer software to present motion vector magnitudes between consecutive cine MR images as bowel motility maps via a classical optical flow algorithm using the Horn-Schunck method. Cine MR images were acquired with a balanced steady-state free precession sequence in the coronal direction to capture small bowel motility. The small bowels were divided into three segments. In total, 63 bowel segments were assessed via BAE and MREC. Motility scores on the maps, simplified MR index of activity (sMaRIA), and MREC score derived from a 5-point MR classification were assessed independently by two radiologists and compared with the CD endoscopic index of severity (CDEIS). Correlations were assessed using Spearman’s rank coefficient. The areas under the receiver-operating characteristic curve (AUCs) of motility score for differentiating CDEIS was calculated; a P value < 0.05 was considered statistically significant. Results Motility score was negatively correlated with CDEIS (r = −0.59 [P < 0.001] and −0.54 [P < 0.001]), and the AUCs of motility scores for detecting CDEIS ≥ 3 were 88.2% and 78.6% for observers 1 and 2, respectively. There were no significant differences in the AUC for detecting CDEIS ≥ 3 and CDEIS ≥ 12 between motility and sMaRIA or MREC score. Conclusion The motility map was feasible for locally quantifying the bowel motility. In addition, the motility score on the map reflected the endoscopic inflammatory activity of each small bowel segment in patients with CD; hence, it could be used as a tool in objectively interpreting cine MREC to predict inflammatory activity in CD.
A charging management-based intelligent control strategy for extended-range electric vehicles

To fully take advantage of external charging conditions and reduce fuel consumption for extended-range electric vehicles, a charging management-based intelligent control strategy is proposed. The intelligent control strategy is applied to different driving patterns based on the various characteristics of urban roads. When the vehicle is driving on arterial roads, a constant power control strategy is applied. When the driver decides to go to a charging station, the extender-off time can be determined based on the current state of the vehicle and the distance to the charging station. When the vehicle is driving on an expressway, a power follower control strategy is applied. The range-extender engine is controlled to work over a wide variety of regions to obtain optimum fuel economy. The simulation results indicate that as the vehicle arrives at the charging station, the proposed charging management-based intelligent control strategy has made the state of charge reach the lowest permissible level after the driver made the decision to charge at the charging station. Therefore, the driver can charge the vehicle with as much clean electric energy as possible from the charging station. 中文概要目 的为了充分利用外界充电条件, 减少现有增程式电动汽车燃油消耗, 结合当前运行工况、整车运行状态以及相距充电站距离等信息, 通过合理调整整车需求功率在增程器与动力电池之间的分配, 使得增程式电动汽车在到达充电站时荷电状态(SOC)降低到理想充电范围, 提高了整车从充电站获取清洁电能的效率。 创新点1. 根据车辆当前状态, 建立电池需求电量估算模块和増程器输出功率计算模块;2. 在司机决定进入充电站充电后, 控制电池SOC 在车辆进入充电站时降到最低。 方 法1. 通过对使用环境进行分析, 建立智能控制策略, 在不同的运行工况下对增程器采用不同的控制方式。 通过理论推导, 建立动力电池需求电量估算模块(公式2);2. 通过仿真计算, 将所提出的智能控制策略与初始控制策略进行对比。 结 论1. 与整车原策略相比, 本文提出的智能控制策略能够根据车辆当前运行工况, 控制增程器采用不同的工作方式;2. 在司机决定到充电站充电时, 根据当前SOC值, 确定最佳增程器关闭时刻, 可使增程式电动汽车在到达充电站时, SOC 降低到理想充电范围, 提高动力电池从充电站获取清洁电能的能力。
Novel Water-Soluble Poly(terephthalic-co-glycerol-g-fumaric acid) Copolymer Nanoparticles Harnessed as Pore Formers for Polyethersulfone Membrane Modification: Permeability–Selectivity Tradeoff Manipulation

This work presents poly(terephthalic-co-glycerol-g-fumaric acid) (TGF) as a novel water-soluble polymeric nano-additive for the modification of a polyethersulfone ultrafiltration membrane. The TGF was harnessed as a pore former, aiming to improve the membrane surface porosity and hydrophilicity. Modified membranes were characterized to observe the influence of varying the TGF content on their hydrophilicity, porosity, morphological structure, and composition, as well as their entire performance. The results disclosed that porosity and hydrophilicity of the modified membrane prepared using 4 wt. % TGF content recorded an enhancement by 24% and 38%, respectively. Herein, the lower contact angle was mainly a reflection of the improved porosity, but not of the hydrophilic nature of water-soluble TGF. Furthermore, upon increasing the TGF content in the polymeric matrix, a more porous structure with longer finger-like micropores was formed. Moreover, a sponge-like layer clearly appeared near the bottom surface. Nevertheless, at optimum TGF content (4%), a clear enhancement in the water flux and BSA retention was witnessed by values of 298 LMH and 97%, respectively. These results demonstrate that the obtained permeation and separation behavior of the PES/TGF membrane could stand as a promising choice for water and wastewater treatment applications.
Raincheck: A new diachronic series of rainfall maps for Southwest Asia over the Holocene

Fluctuations in climate have been associated with significant societal changes, both in the modern day and in the past. In dryland environments such as much of Southwest Asia, rainfall is often used as a proxy for soil moisture available for crop production, and in pre-industrial societies this is assumed to directly relate to food production capacity and security. However, rainfall values are commonly quoted in archaeological literature without further context. Variability between values arising from different methods and timescales are rarely considered. This is important as small changes in rainfall can have profound effects on the interpretation of sites and landscapes. Here, we present a novel set of snapshot precipitation maps for Southwest Asia between the years 10,240 BP and 300 BP, based on previously published natural archive data by Bar-Matthews and Ayalon (2004) from Soreq Cave, and a newly derived modern rainfall map. The modern map was created using station data from the years 1960–1990 and a geostatistical interpolation technique applied across 14 separate zones. We outline the steps involved in the creation of the maps and provide access to, and clear explanations of, the data and methods used. Using the hindcasted maps, two case studies to highlight why a nuanced approach to rainfall is required in the study of ancient societies are examined. Changes to the spatial extent of the so-called ‘Zone of Uncertainty’ through time, as well as land suitable for rainfed agriculture throughout time using a simple model are calculated. It is demonstrated that relatively small fluctuations in rainfall can have a significant impact on the distribution of moisture availability for the region. It is argued that archaeologists need to be aware of the sources and limitations of the rainfall data used in their interpretations, and our map series is offered as a baseline dataset.
Offloading strategy in internet of vehicle based on edge cache

To reduce the delay of task offloading in edge computing of the internet of vehicle and adapt the delay sensitivity and task repeatability of vehicle network, this paper presents a task offloading algorithm which utilizes the edge cache. When a task uploaded to the edge server and get corresponding results, Edge server evaluate factors including task total latency, size of result and popularity of the task to decide store the result in edge caching or not. If it is determined to be yes ,the following same task uploaded to the edge server will get the result from edge cache directly, reducing calculate delay of the task and operating cost of the entire system. The simulations show that this algorithm can reduce the latency and improve the availability of edge caching. In the ideal case. Compared with the original algorithm, the proposed algorithm can save 49% of the average latency and improve 31% availability of edge cache.
Adaptive RISE Feedback Control for Robotized Machining With PKMs: Design and Real-Time Experiments

The development of high-precision tasks, such as machining, needs a positioning device for the cutting tool with the smallest possible error. Multiple design factors need to be considered to ensure a mechatronic device successfully performs such tasks. One of these factors may be attributed to the control scheme, which is responsible for controlling the position of the machine. In view of the importance of designing a good control scheme for a robotic system, in this article, we propose a new extension of the robust integral sign of the error (RISE) for the positioning device a parallel kinematic machine (PKM). This extension consists in including a nominal feedforward term based on the inverse dynamic model of the robot and replacing the RISE fixed feedback gains with adaptive ones. The RISE part of the proposed controller ensures semiglobal asymptotic stability. Moreover, it can accommodate sufficiently smooth bounded disturbances. The feedforward part cancels the nonlinearities of the system, improving the tracking performance of the controller. The adaptive feedback gains produce corrective actions when an increase in the tracking errors is due to the contact forces that occur during the machining process. A Lyapunov-based stability analysis is conducted to prove the semiglobal asymptotic stability of the proposed control solution. To show its effectiveness, real-time experiments are performed for two case studies; the first one is on a free motion trajectory and the second on machining experiments under three different forward speeds on SPIDER4, a redundantly actuated PKM.
123I-BMIPP, a Radiopharmaceutical for Myocardial Fatty Acid Metabolism Scintigraphy, Could Be Utilized in Bacterial Infection Imaging

In this study, we evaluated the use of 15-(4-123I-iodophenyl)-3(R,S)-methylpentadecanoic acid (123I-BMIPP) to visualize fatty acid metabolism in bacteria for bacterial infection imaging. We found that 123I-BMIPP, which is used for fatty acid metabolism scintigraphy in Japan, accumulated markedly in Escherichia coli EC-14 similar to 18F-FDG, which has previously been studied for bacterial imaging. To elucidate the underlying mechanism, we evaluated changes in 123I-BMIPP accumulation under low-temperature conditions and in the presence of a CD36 inhibitor. The uptake of 123I-BMIPP by EC-14 was mediated via the CD36-like fatty-acid-transporting membrane protein and accumulated by fatty acid metabolism. In model mice infected with EC-14, the biological distribution and whole-body imaging were assessed using 123I-BMIPP and 18F-FDG. The 123I-BMIPP biodistribution study showed that, 8 h after infection, the ratio of 123I-BMIPP accumulated in infected muscle to that in control muscle was 1.31 at 60 min after 123I-BMIPP injection. In whole-body imaging 1.5 h after 123I-BMIPP administration and 9.5 h after infection, infected muscle exhibited a 1.33-times higher contrast than non-infected muscle. Thus, 123I-BMIPP shows potential for visualizing fatty acid metabolism of bacteria for imaging bacterial infections.