Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-cycle Washing of Cotton and the Results in Manner of DP

Washing processes, detergant agents, washing cycles and temperatures can often cause damage on fabrics. The aim of this work was to determine chemical and physical changes on cotton fabrics with different washing conditions. A Box–Bhenken statistical design was used to evaluate the effect of washing temperature (40 -50-60°C), number of washing (10, 30, 50) and washing agent (only water, base detergent, detergent with bleaching agent) on the average degree of polymerization. The effect of multiple washes on cotton fabrics was evaluated by means of average polymerization degree, tensile strength, whiteness index and scanning electron microscopy. Whiteness index decreased significantly using with base detergent and bleaching agent containing detergent, whereas washing with only water did not affect significantly to whiteness index, with increasing number of washing. However, temperature (p > 0.05) individually were not found statistically significant for whiteness index. As number of washing and temperature increased, tensile strength values decreased. Also, washing agent (p > 0.05) individually were not found statistically significant for tensile strength. When evaluated in terms of average polymerization degree values, after the washings with base detergent and bleaching agent containing detergent, there is a greater decrease in the average polymerization degree relative to the only water washings. While the temperature increased in washing process, the average polymerization degree decreased and the lowest average polymerization degree was obtained at 60 ˚C and 50 washes. SEM images indicate that number of washing and the content of detergent is an important parameter in the washing process. The worst image in this study was obtained with 50 washes using detergent containing bleach. Washing processes cause undesirable results on the surface of fabrics.
Analyzing the Effect of Economic and Demographic Factors on Digital Divide: The Case of Transition Economies

With the widespread use of information communication technologies, many people and countries with a lack of technology are growing. The term digital divide is a multifaceted phenomenon. It means the gap between people and countries with access to digital technologies and those with very limited or no access at all. The main purpose of this study is to investigate the factors affecting digital divide in selected transition countries. In the empirical analysis, The Panel Quantile Regression proposed by Machado and Silva (2019) has been applied. Using panel data for 20 countries for the period 1998 – 2014, the findings of this study revealed that economic and socio-demographic factors are the main predictors of the digital divide.
Dynamic Evolution of Traveler’s Bounded-Rational Route Choice Behavior

Travelers’ route choice shows bounded-rationality because of different perceptions of route attributes. Based on the bounded-rationality, the paper proposes the dynamic evolution rules and route choice model, and simulation method is applied to study the evolution process and results. The model includes three parameters reflecting the bounded-rationality of travelers. First, simulation results show that the bounded-rationality affects the evolution process. The switching threshold or the perception deviance is larger, convergence rate is faster, and shorter time is needed to reach equilibrium state. Also, fewer perfect rational travelers will lead to similar results. Second, the system can reach equilibrium and the final equilibrium volume of every route is almost unaffected by bounded-rationality. The equilibrium volume of every route is an approximately fixed value under all simulation scenes. At last, it is found that equilibrium volume of every route obeys normal distribution. That is, bounded-rationality affects the equilibrium convergence rate, but volume equilibrium results will not be influenced.
Insidious Attentional Deficits in Patients With Cerebral Small Vessel Disease Revealed by Attention Network Test

Background Several reports have indicated potential cognitive decline for cerebral small vessel disease (CSVD), especially in attention domain, whereas the attentional function at network level is still elusive. In this study, we used the attention network test (ANT) paradigm to characterize the efficiency of the alerting, orienting, and executive control networks in patients with CSVD and explore possible correlations between attention network efficiencies and obtained CSVD total score. Methods A total of 31 patients with CSVD and 30 healthy controls matched for age, gender, and education level were recruited. After neuropsychological and anxiety/depression/somatization assessments, an original version of ANT containing different cue conditions and target stimuli was used to investigate independent attentional components, and then, behavioral performance (accuracy and reaction time) and network efficacy were recorded and analyzed. Results Assessed by traditional neuropsychological scale (MoCA), we did not find difference between groups on general cognition. Nevertheless, the overall reaction time to targets of ANT was markedly prolonged in patients with CSVD, and similar phenomenon was observed for overall accuracy on ANT. Moreover, patients showed significantly lower orienting and executive control network efficiencies compared with controls, while not for alerting network. These impairments were correlated with total CSVD burdens, but not with anxiety, depression, or somatization. Conclusions Although general and almost all individual cognitive function evaluated by MoCA seemed to remain intact, the orienting and executive control function was impaired in individuals with CSVD, which was modulated by lesion grades. Our observations implied insidious attentional deficits regarding CSVD. Given this, considering its simplicity and sensitivity, ANT could serve as an attractive tool for early diagnosis of cognitive dysfunction. Further investigations on the availability of ANT detection for CSVD are warranted.
Effects of ω-3 Polyunsaturated Fatty Acids on Coronary Atherosclerosis and Inflammation: A Systematic Review and Meta-Analysis

Background and Purpose Multiple guidelines suggest the ω-3 polyunsaturated fatty acids (ω-3 PUFAs) help to prevent major vascular events of coronary heart disease (CHD), but the data on large trials of ω-3 fatty acids are controversial. We reviewed the available evidence to determine the effect of ω-3 PUFAs on coronary atherosclerosis. Materials and Methods Literature were from online databases. Randomized controlled trials (RCTs) or observational studies were acceptable. Quantitative data synthesis was conducted using R version 4.1. 2. Each outcome was calculated using standardized mean difference (SMD) in a random-effect model. Sensitivity analysis was conducted for each outcome. A total of 21 RCTs and 1 observational study with 2,277 participants were included. Results Meta-analysis indicated a benefit of ω-3 PUFAs on coronary atherosclerosis, namely, (1) ω-3 PUFAs can reduce the atherosclerotic plaque volume (SMD −0.18; 95% CI −0.31 to −0.05); (2) ω-3 PUFAs can help reduce the loss of the diameter of the narrowest segments of coronary arteries in patients with CHD (SMD 0.29; 95% CI, 0.05–0.53); (3) ω-3 PUFAs do not have significant effect on volume of lipid plaque in coronary arteries (SMD −1.18; 95% CI −2.95 to 0.58), volume of fiber plaque (SMD 0.26; 95% CI −0.81 to 1.33), and calcified plaque (SMD 0.17; 95% CI −0.55 to 0.89); and (4) ω-3 PUFAs had no significant effect on endothelial inflammatory factors in peripheral blood. Conclusions We confirmed that ω-3 PUFAs benefit patients with CHD by reducing the progression of coronary atherosclerosis. We indicated that the benefits were not caused by reducing endothelial inflammations of coronary arteries. Systematic Review Registration https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42021285139, identifier: CRD42021285139. Graphical Abstract In order to increase the exposure of our work, we made a graphical abstract: ω-3 PUFAs (ω-3 polyunsaturated fatty acid) reduce coronary atherosclerotic plaques growth and relieve the lesions process of the most stenotic segment of the coronary artery. However, the effects on all main compositions of atherosclerotic plaques (fiberboard, calcified plaque, and lipid plaque) are not statistically significant. Serum soluble vascular cell adhesion molecule-1 (sVCAM-1) level and activation percentage of von Willebrand factor (VWF%) are not significantly affected. The mechanism of ω-3 PUFAs on coronary atherosclerosis may need further studies.
THE EFFECTS OF DIFFERENT SOWING TIMES AND HARVEST STAGES ON FORAGE YIELD AND QUALITY IN BUCKWHEAT (FAGOPYRUM ESCULENTUM MOENCH)

This study was carried out to determine the effects of different sowing times and harvest stages on the yield and forage quality of buckwheat in Marmara conditions. The experiment was carried out in Bursa Uludag University Agricultural Application and Research Area in 2018 and 2019 years using Gunes variety as plant material. The experiment was established in a split-plot randomized complete blocks design with three replicates. Four different sowing times (15 April, 1 May, 15 May and 1 June) were considered in the main plot and three different harvest stages (flowering, milk, and dough) in the sub-plot. Results showed that higher plant height, stem diameter, and dry matter yield values were obtained from the plants sown on 15 April and harvested during the milk or dough stages. The highest crude protein ratio, crude protein yield and relative feed value, and the lowest acid detergent fiber and neutral detergent fiber values were determined in plants, which were sown early and harvested during flowering. In general, the delayed harvest stage increased the yield of buckwheat but negatively affected the forage quality.
Effectiveness of Calming Techniques on Children's Outcomes regarding Magnetic Resonance Imaging and Mothers' Satisfaction Level

Background: Psychological preparation for children undergoing magnetic resonance imaging can be achieved through applying different calming techniques that help anxious children to cope with the threatening situation and increased image quality. Aim of study: Was to evaluate effectiveness of calming techniques on children's outcomes regarding magnetic resonance imaging and mothers' satisfaction level. Design: A quasi-experimental design was utilized to conduct this study. Setting: The study was conducted at magnetic resonance imaging unit at Benha University Hospital. Subjects: Purposive sample of 159 children accompanied with their mothers were selected and divided equally into three groups (control group, study group1 and study group 2). Results: There is a significant decrease in level of anxiety and fear among children in study group1 compared with those in control group and study group2 30 minute after intervention and 1hr after performing magnetic resonance imaging. Also, there is improvement in level of knowledge and level of anxiety among mothers in study group 1 compared with those in control group and study group2 with increased level of satisfaction in study group1 1hr after applying magnetic resonance imaging. Conclusion: Applying calming techniques for children undergoing magnetic resonance imaging has positive effect in lowering children's anxiety, fear, mother's anxiety and increase mother's satisfaction level among study group1. Recommendations: Conducting continuous periodical education for nurses in MRI setting about the different methods of calming techniques that can be used for children before and during magnetic resonance imaging.
A convenient synthesis, anticonvulsant screening and neurotoxicity study of novel quinoline incorporated thiazolidin-4-one derivatives as potential anticonvulsant agents

Received: July 10, 2021/ Accepted: August 19, 2021/ Published online: 20 August 19, 2021 Abstract: Epilepsy is a neurological disorder involving a local body to the whole body part. The disease is not fatal, but the consequences are very grave. There is no final and permanent cure for the disease. Moreover, drug-resistant epilepsies are evolving, making the healthcare giver a limited space to treat the disease. Therefore, new drug molecules are continuously needed to treat drug-resistant epilepsies. Herein, the authors report the synthesis and antiepileptic screening of a series of quinoline-incorporated thiazolidin-4-ones. The synthesized compounds were characterized and subjected to maximal electroshock seizure (MES) and subcutaneous pentylenetetrazol (scPTZ)-induced seizure tests. Neurotoxicity was evaluated via rotarod and ethanol potentiation tests. Among the compounds tested, 19c, 20b, 20c, 21band 21f showed maximum protection against MES test model. In scPTZ test, compounds 20c, 20d, 21b and 21f showed maximum activity. In rotarod and ethanol potentiation tests only one compound that is 21b showed neuromotor toxicity. More research is needed to validate the safety and efficacy of these compounds.
Evaluation of Spatial and Temporal Performance of Deep Learning Models for Travel Demand Forecasting: Application to Bike-Sharing Demand Forecasting

Deep learning approaches are widely employed for forecasting short-term travel demand to respond to real-time demand. Although it is critical for demand forecasting to be evenly distributed in the spatial and temporal views to support real-time mobility service operations, in related studies, the predictive performance of models has been evaluated only in terms of aggregated errors. Therefore, the present study was conducted to investigate the distribution of errors to explore spatiotemporal correlations. Six deep learning models with the same architecture, except for the base module, consisting of three stacked layers, were constructed. These models were used to forecast demands for a station-based bike-sharing service in Seoul, South Korea. To attain our goals, global and local Moran’s I of the errors was introduced to evaluate the spatial and temporal performances of the deep learning approaches. The results showed that the model with convolutional long short-term memory layers, which are effective at predicting spatiotemporal data, outperformed the other models in terms of aggregated performance. However, the global Moran’s I of the errors in the model reflects spatial dependency over the regions. This suggests that the best predictive performance of the model does not necessarily imply that it performs well in demand forecasting in all regions. Furthermore, cluster and outlier analyses of the errors indicated that excessive or insufficient predictions were clustered or dispersed throughout the regions. These results can be used to enhance the model by introducing the spatial correlation index into the loss function or by incorporating additional features for handling spatial correlations.
History of the Flipped Classroom Model and Uses of the Flipped Classroom Concept

Flipped Classroom (FC) Model is an approach based on learning the simple and theoretical parts of a subject in extracurricular time through educational technologies and performing higher-level studies during class time. With the development and spread of educational technologies, the interest in the FC Model has increased. In the present study, we aimed to reveal the historical development of the FC Model, which is a current teaching model, and what kind of uses it has as a concept. The findings, which were put forward in line with this purpose, were reached by the document analysis method. With reference to the results of the research, although the ideas and practices that paved the way for the emergence of the FC Model are older, it could be said that the approach was expressed as a concept in its present form in 2000. In addition, it was revealed that the interest in the FC Model continued to increase over the years and it was expressed with several concepts. As a result of the investigation, it was determined that flipped classroom was the one used most among these concepts. Based on the results of the study, certain suggestions were made. It is expected that this research will contribute to the field in terms of revealing the historical development of the FC Model and the concepts in which the concept of FC is used in the literature.
Rashevsky’s dream: A physico-mathematical foundation of history and culture

The popular science fiction series Foundation penned by Isaac Asimov explores the idea that the course of the future of societies is not only predictable but can be engineered as well. In Asimov’s fictional world, a multidisciplinary science called psychohistory combines mathematics, psychology, and history to predict future events. Nicolas Rashevsky, the father of mathematical biology, lent credibility to the existence of universal principles underpinning human cultural evolution using mathematical models. His vision remains to be fully realized, as our capacity to predict and even engineer is very fragmented. Two main obstacles are a misunderstanding of the role of mathematical models and the limitations of current datasets. Recent advances in complex systems research, computer-based simulations, and large-scale databases, are paving the way towards fully developing a mathematical theory of human history.
Study on the SOC estimation method for Lithium power battery based on tomographic images

Due to the common SOC estimation methods cannot accurately estimate the SOC of the battery in real time, it results in inaccurate SOC estimation. Therefore, the SOC estimation method for lithium power battery based on tomography images is proposed, it can be used to obtain tomographic images that reflect the structural morphology parameters density, area and thickness of the cathode and anode electrodes active materials in real time. Finally, a prediction model for the SOC with pixels of cathode and anode electrodes active materials is established. The result shows that the SOC can be calculated by the structural morphological parameters of the battery in real time, and the estimation results are more accurate and reliable.
The mechanism of action of platelet-rich plasma for knee osteoarthritis: a systematic review

Background: Platelet-rich plasma (PRP) is a biological intra-articular therapy that has shown good clinical outcomes in patients with knee osteoarthritis (OA) and has been widely studied from in vitro to pre-clinical animal models. We aimed to synthesize non-clinical evidence regarding the different effects related to PRP. Methods: A systematic literature review was conducted in the MEDLINE, EMBASE, and Google Scholar databases in December 2020. Studies were included if they were non-clinical basic science publications describing the effect of PRP treatment, studies focused on knee OA, and articles reporting the use of PRP or a similar platelet-derived product. Included articles were assessed and categorized based on the effect or the mechanism of the action described. The main findings of each study were obtained and analyzed. Results: A total of 41 articles were included to review the outcomes of interest. The most frequently reported mechanism was the modulation of genes involved in synthesizing and degrading the cartilage extracellular matrix (ECM), followed by ECM morphological analysis, inflammation, and cell proliferation. PRP preparations with low and high content of leukocytes were equally reported. Conclusions: The studies reviewed provide evidence for several ways in which PRP can act once it is present in the intra-articular environment. The vast majority of data support a beneficial effect of PRP therapy, especially for leukocyte-poor PRP formulations. The evidence collected gives us a clue as to what the mechanism of action could be. However, the great heterogeneity in the study formulations and models implies further investigation.
A Phase I, Randomized, Double-Blind, Placebo-Controlled Clinical Trial to Evaluate the Safety and Tolerance of Oil Palm Phenolics (OPP) in Healthy Volunteers

Background and aim: Oil palm aqueous by-products rich in phenolic content are known as oil palm phenolics (OPP), and pre-clinical research has shown that OPP has great potential to be further developed as an anti-hyperlipidemic agent. Hence, in order to introduce OPP into market, its safety profile needs to be established by undergoing a phase I clinical trial on healthy humans. Methods: A parallel, placebo-controlled, randomized, and double-blinded clinical trial was conducted for 2 months on 100 healthy subjects aged 20–40 years old. This trial was registered at clinicaltrials.gov (NCT04164446). The subjects were randomly allocated to four treatment arms with 25 participants each: placebo, 250, 1,000, and 1,500 mg of OPP. During the trial, subjects were required to consume four capsules simultaneously per day. Withdrawal of fasting blood for hematology, liver and renal function analysis, and medical examination were conducted at baseline (day 1), day 30, and day 60. For monitoring, vital signs (blood pressure and pulse rate) and weight measurements were taken during each visit. Results: Minor adverse events (AEs) were reported in all groups especially at high dose (1,500 mg) but none were serious adverse events (SAEs). Fasting blood parameters between control and all OPP-treated groups demonstrated no statistically significant difference from baseline to day 60. Conclusion: With no major AEs and SAEs reported and no abnormal findings in biochemistry and hematology results, OPP supplementation in capsule form is safe to be taken up to 1,500 mg a day.
Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note

Wearable devices are burgeoning, and applications across numerous verticals are emerging, including human performance monitoring, at-home patient monitoring, and health tracking, to name a few. Off-the-shelf wearables have been developed with focus on portability, usability, and low-cost. As such, when deployed in highly ecological settings, wearable data can be corrupted by artifacts and by missing data, thus severely hampering performance. In this technical note, we overview a signal processing representation called the modulation spectrum. The representation quantifies the rate-of-change of different spectral magnitude components and is shown to separate signal from noise, thus allowing for improved quality measurement, quality enhancement, and noise-robust feature extraction, as well as for disease characterization. We provide an overview of numerous applications developed by the authors over the last decade spanning different wearable modalities and list the results obtained from experimental results alongside comparisons with various state-of-the-art benchmark methods. Open-source software is showcased with the hope that new applications can be developed. We conclude with a discussion on possible future research directions, such as context awareness, signal compression, and improved input representations for deep learning algorithms.