Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Activity and Sedentary Behavior Patterns Across Weekdays and Weekend Days in Youth With Multiple Sclerosis and Controls.

Background This study quantified and compared weekday and weekend patterns of device-measured physical activity (PA) and sedentary behavior between youth with pediatric multiple sclerosis (MS) and controls for the purpose of informing future PA behavior change interventions. Methods Participant data were obtained from 3 ongoing observational studies, and the sample included 40 participants with pediatric MS and 41 controls. Light PA (LPA), moderate to vigorous PA (MVPA), and sedentary behavior data were collected using activity monitors (ActiGraph LLC) over 1 week. The main analysis involved a 2-way mixed factor analysis of variance with group as a between-subjects factor (pediatric MS vs control) and day as a within-subjects factor (weekday vs weekend day). Results There was no group by day interaction from the analysis of variance for percentage of activity monitor wear time spent in LPA, MVPA, or sedentary behavior. There was no effect of group for LPA, MVPA, or sedentary behavior. There was an effect of day of week on percentage of day spent in LPA, MVPA, and sedentary behavior. Conclusions These results suggest that youth with pediatric MS and controls were less physically active and more sedentary on weekends than on weekdays, but there were no differences between groups in PA and sedentary behavior overall or by day of the week. Physical activity interventions may be more successful by initially targeting weekend day activity.
Ultrastructural examination of testicular tissues and evaluation of ZO-1 protein levels obtained from azoospermic cases

Spermatogenesis is a process that involves cellular and biochemical processes. The purpose of this study is to understand the role of tight junctions in spermatogenesis by evaluating Zonula occludens-1 (ZO-1) protein levels of cells from the testicular sperm extraction (TESE) biopsies in patients with azoospermia. The study included 40 infertile men with azoospermia. They were divided into two groups, as spermatozoa positive (n=20) and spermatozoa negative (n=20). Testis tissues were examined morphologically, immunohistochemically and ultrastructurally by using transmission electron microscopy (TEM). The structure of seminiferous tubules was deteriorated, degenerated and hyalinized in spermatozoa negative group. ZO-1 expression level was normal in blood-testis barrier of spermatozoa positive group in comparing to lateral surfaces of Sertoli cells spermatozoa negative group. The ultrastructural results were also supported with light microscopy findings. These findings suggest that decrease of the ZO-1 protein expression level in Sertoli cells might be one of the factors involved in the impairment of spermatogenesis in spermatozoa negative group. Therefore, we suggest that tight junctions may have crucial roles in spermatogenesis.
Fog Computing Approach for Data Driven in Smart Agriculture

: A large part of these day’s global population is absolutely structured upon agriculture enterprise for its supply of livelihood. Smart agriculture is an improvement which emphasizes the use of statistics and conversation era. Fog computing, cloud computing and information pushed are the unique strategies to offer a notable opportunity for smart agriculture to boom within the productiveness with the aid of getting actionable insights to improve farming activities and increase within the performance and yield. Data driven is typically used to refer a manner or pastime this is spurred on by means of information, in place of being pushed by means of mere instinct or depending on the collection or analysis of data. Data pushed is the collection of actual time records associated with soil, environmental factors, planting, intercultural management and harvesting, value and pest management. The existing systems which might be primarily depends on traditional cloud models are insufficient to deal with a lot of information produced by the Internet of Things (IoT) gadgets which is associated. After decreasing latency in assisting the real time selections which is primarily based at the statistics produced. To be the most important issue, the facts processing closer to the supply of its production. This can be passed off with the aid of adopting the fog based mechanism. Fog computing which is dwells among cloud and Internet of Things (IoT), was proposed. In the Fog figuring environment, IoT gadgets are associated with fog gadgets. Smart agriculture based totally on IoT-Fog may be extra in a position in phrases of greatest utilization of bandwidth or latency for real time decision making. In this research paper, we had to provide the facts exploration of Fog Computing (FC) function above Cloud Computing (CC) towards observing smart agriculture.
Diazoresin modified monodisperse porous poly(glycidylmethacrylate-co-divinylbenzene) microspheres as the stationary phase for high performance liquid chromatography

Porous poly(glycidylmethacrylate-co-divinylbenzene) (PGMA-co-DVB) microspheres with an average size of 4.6 μm were prepared using a multistage emulsion polymerization method successfully and were subsequently modified by diazoresin (DR). Three kinds of porogens (toluene, cyclohexanol and dodecanol) were applied and porous microspheres with different morphologies were obtained. Porous PGMA–DVB microspheres resulting from toluene were selected for further modification with DR due to their large specific surface area and good pore structure. These microspheres were modified through the hydrolysis of epoxy groups and a photocuring reaction with DR. After treatment with UV light, the hydrogen bonding between hydrolyzed microspheres and DR was converted into covalent bonding through a unique photochemistry reaction of DR. Porous PGMA–DVB–DR microspheres were used as the stationary phase for high performance liquid chromatography (HPLC). Depending on the chemical structure of DR, the DR modified PGMA–DVB stationary phase can be used to perform mix-mode separation mechanisms, including reversed phase (RP) and hydrophilic interactions. Therefore, baseline separation of benzene analogs was achieved by using the porous PGMA–DVB–DR particles as packing materials, and the by-product of hydrophilic acetic acid was rapidly separated from the N-vinyl-1,2,4-triazole product within 5 minutes. In addition, the DR-modified particles may be expected to be an alternative tool for organic acid separation due to the presence of secondary amino groups.
MicroRNAs as Potential Markers Involved in Erythroid Differentiation: A Systematic Literature Review

As a family of small non-coding RNAs, microRNAs (miRNAs) negatively modulate gene expression via directly targeting mRNAs in a sequence-specific pattern. Accumulated evidences have indicated that miRNAs involved in erythroid differentiation. Some experimental systems used for study the association of miRNAs with erythroid differentiation: 1) embryonic stem cells (hESCs) forced to erythropoiesis, 2) hematopoietic progenitor cells and erythroid-like cell lines induced to erythropoiesis by hypoxia and chemical substances, 3) and in vivo mice, zebrafish embryo systems. Based on the literatures, miR-451, miR-144, miR-486, miR-126-3p, miR-107, miR-199b-5p, miR-362, miR-188, miR-210, miR-125a, miR-146b, miR-22, miR-23a / miR-27a / miR-24, miR-16-2, miR-34a exhibit promotion role in erythropoiesis, while, miR-218, miR-320a, miR-221 / 222, miR-433, miR-200a, miR-223, miR-150, miR-34a-5p, miR-124, miR-Let-7d, miR-376a, miR-155, miR-126 / 126*, miR-103, miR-15a, miR-30a-5p, miR-26a-5p, miR-669m, miR-9 show suppression role in erythropoiesis. Nonetheless, the clear functional role of miR-24 is controversial in erythropoiesis. This article summarized the relationships between miRNAs and erythroid differentiation as well as potential target genes and action mechanisms. These discovered erythroid associated miRNAs stand for the starting point to develop novel approaches for miRNA treatment, miRNAs to be used as novel potential biomarker and target for diagnosis, therapeutics, prognosis of certain blood diseases, leading to promising prospects in blood diseases therapeutics.
Nutritional status and anxiety-depression relationship in hemodialysis patients

Background/Aim: Malnutrition is one of the determinants of most morbidity and mortality in end-stage renal failure (ESRD) patients receiving hemodialysis (HD). Depression is the most common psychological complication among these patients. This study aimed to determine the nutritional status and anxiety-depression level in hemodialysis patients and evaluate the relationship between the two. Methods: This cross-sectional study included 55 routine hemodialysis patients over 18 years of age who were treated in the Department of Internal Diseases of a university hospital between November 2019 and January 2020. Two patients were excluded from the study due to renal transplantation. All patients filled out a two-part Hospital-Anxiety Depression Scale (HAD) and a two-part Mini Nutritional Assessment (MNA) questionnaire. The MNA-short form (MNA-SF) was first used to evaluate the malnutrition status of patients. Those who were identified as at-risk or malnourished with the MNA-SF were also asked to complete the long form. The HAD scale was used to evaluate the levels of depression and anxiety. SPSS 20 statistical package program for statistical analysis. P<0.05 was considered statistically significant. Results: The mean age of the patients was 56.2 (15.9) years; 36 (66%) were female and 18 (34%) were male. Among all, 55.8% and 26.9% of the patients were at risk in terms of depression and anxiety, respectively. Depression prevalence was higher in patients with low MNA-SF scores (P=0.001) and comorbidities (P=0.007). In those with a low MNA-SF score (P=0.001), comorbidities (P=0.008), and high urea levels (P=0.003), anxiety was more common. In patients with an elevated risk of anxiety (P=0.001) and depression (P=0.007), malnutrition risk was significantly higher. Conclusion: Depression is closely related to nutritional status in patients receiving chronic hemodialysis therapy and considered an independent risk factor for malnutrition. Early diagnosis and treatment of hemodialysis patients' psychological problems and regulation and control of nutrition programs can be practical interventions to improve the quality of life of these patients.
On the Up-to-date Course of Mathematical Logic for the Future Math Teachers

All-round development of the everyday logic of students should be considered as one of the most important tasks of general secondary education on the whole and general secondary mathematics education in particular. We discuss the problem of organization in teachers' training institutions of higher education and the expedient training of the future math teachers at institutions of general secondary education. The main goal is to ensure their ability to realize all their future professional activities and the necessary participation in forming the everyday logic of their pupils. The authors think that vocational educational program of training is that the future secondary school math teachers must contain a separate course of mathematical logic including at least 90 training hours (3 credits ECTS). Although the content filling of the course cannot be irrespective of the general level of arrangement of mathematics education in the corresponding country, it ought to be a subject of discussion of the international mathematics community and managers in the sphere of higher mathematics education. Simultaneously, the role, the place, and the expedient structure of such a course in the corresponding training programs should be under discussion. The article represents the authors' point of view on the problems indicated above. The research has a qualitative characteristic as a whole. Only some of its conclusions have statistical corroboration.
Mobile Authentication using Hybrid Modalities (MAHM) in Pervasive Computing

Cloud computing facilities using mobile phones has become a necessity more than being an alternative. Cloud storage, social networks and email communications using mobile phones allows for mobility and on the go access to these cloud services. Despite providing such conveniences to the users, cloud access via mobile devices is vulnerable to security breaches especially when a third party gets hold of the mobile phone. A third party may have access to the applications and features of the mobile phone provided that the unauthorized user managed to break the security login of the phone. This gives avenue for the unauthorized user to gain access to the cloud services without further verification. Because most of the cloud services provide a single sign-on features whereby the password is used by cloud services (gmail for example) for the first time only. After the first authentication, an authentication token which is downloaded to the mobile phone is used for subsequent authentications. Although this may sound secure without the use of password, the possibility for an unauthorized user access to the cloud services is still possible because the authentication token is stored in the phone itself and does not require further validations. Moreover, the authentication token is stored as plaintext inside the mobile phone and may be susceptible to security breach. Therefore, an identity management system based on user behavior patterns can be used to further validate the authorized user of the cloud services. The main aim of the research is to design MAHM, for cloud service identity management using human behavior patterns classification. There are various biometrics-based authentication using physiological and psychological have been in place but, environmental and human factors can influence these. In this research, unique behavior patterns will be used to identify distinct characteristics of certain individual. The framework will consist of various user behavior such as keypad tapping behavior, keystroke dynamics and phone swiping behavior as authentication scheme to the cloud applications
Learning Management Model to Promote Growth Mindset of Student Teachers

This research aimed to develop the assessment of efficiency of a learning management model to promote growth mindset of student teachers. The samples consisted of 134 freshman student teachers at a university in Thailand. It is a quasi-experimental research. T-test for dependent sample was used for data analysis. The results revealed that the learning management model to promote growth mindset of student teachers was based on personalized learning, self-directed learning, internal coaching, authentic assessment, and reflection. There were 5 components of learning management, i.e., students as learning owners, activity design, creative learning, creative learning activity management, assessment for learning development, and creative feedbacks. Besides, growth mindset of student teachers in post-learning management was significantly higher than in pre-learning management (p < 0.01).
AN INVESTIGATION INTO THE PERFORMANCE OF THE MULTILAYER PERCEPTRON ARCHITECTURE OF DEEP LEARNING IN FORECASTING STOCK PRICES

A wide range of studies have been conducted on deep learning to forecast time series data. However, very few researches have discussed the optimal number of hidden layers and nodes in each hidden layer of the architecture. It is crucial to study the number of hidden layers and nodes in each hidden layer as it controls the performance of the architecture. Apart from that, in the presence of the activation function, diverse computation between the hidden layers and output layer can take place. Therefore, in this study, the multilayer perceptron (MLP) architecture is developed using the Python software to forecast time series data. Then, the developed architecture is applied on the Apple Inc. stock price due to its volatile characteristic. Using historical prices, the accuracy of the forecast is measured by the different activation functions, number of hidden layers and size of data. The Keras deep learning library, which can be found in the Python software, is used to develop the MLP architecture to forecast the Apple Inc. stock price. The developed model is then applied on different cases, namely different sizes of data, different activation functions, different numbers of hidden layers of up to nine layers, and different numbers of nodes in each hidden layer. Then, the metrics mean squared error (MSE), mean absolute error (MAE) and root-mean-square error (RMSE) are employed to test the accuracy of the forecast. It is found that the architecture with rectified linear unit (ReLU) outperformed in every hidden layer and each case with the highest accuracy. To conclude, the optimal number of hidden layers differs in every case as there are other influencing factors.
Relationship Between Nighttime Emergency Department Admission and Adherence to a Sepsis Treatment Bundle

Background: Nighttime hospital admission is often associated with increased mortality risk in various diseases. Following sepsis campaign implementation, this study investigated compliance rates with the Surviving Sepsis Campaign 3-h bundle for daytime and nighttime emergency department (ED) admissions and the clinical impact of compliance on mortality. Methods: We conducted an observational study using data from a prospective, multicenter registry for septic shock provided by the Korean Shock Society from 11 institutions from November 2015 to December 2017. The outcome was the compliance rate with the complete 3-hour treatment bundle according to the time of arrival in the ED. Mediation analysis was conducted to evaluate the proportion of the total effect that could be explained by hospital admission times.Results: A total of 2,247 patients were enrolled. Compared with daytime admission, nighttime admission was associated with higher compliance for the administration of antibiotics within 3-h (adjusted odds ratio (AOR), 1.276; 95% confidence interval (95% CI), 1.050–1.550, p=0.014), vasopressor within 3-h (AOR, 1.235; 95% CI, 1.009–1.512; P=0.031) and for the administration of the complete 3-h bundle (AOR, 1.231; 95% CI, 1.004–1.501; P=0.046), likely as a result of the increased volume of patients admitted during daytime hours. Consequently, daytime hospital admission adversely affected in-hospital and 28-day mortality rates, mediated by decreased compliance with the complete 3-h bundle. Conclusions: Septic shock patients admitted to the ED during the daytime exhibited lower sepsis bundle compliance than those admitted at night. Despite sepsis campaign implementation, factors that decrease bundle compliance should be reconsidered in patients with septic shock.
A Novel Approach to Model the Thermal-eletrical Behavior of Pyroeletric Infrared Sensors

The combined evaluation of the thermal and electrical domain of a pyroelectric system is a challenging task. The proposed approach precisely models the thermal system with FEM. The output data is approximated with a fit function and transferred to SPICE creating a universal and adaptable model for the whole pyroelectrical signal chain. For validation, the InfraTec detector LRM-244 is used.
Modeling Thermal Abuse in Transportation Batteries

Transition from fossil-fueled to electrified vehicles depends on developing economical, reliable batteries with high energy densities and long life. Safety, preventing premature or catastrophic failure, is of paramount importance in battery design. The largest gaps in our technical understanding of the safe operation of electrical energy storage devices involve the fundamental mechanisms, energetics, and inefficiencies of complex processes that occur during battery operation that can lead to thermal runaway: charge transfer, charge carrier and ion transport, both in the bulk and at various interfaces, and morphological and phase transitions associated with Liion transport between cathode and anode. We have developed a suite of modeling tools to consider phenomena related to battery safety, thermal management, and the onset of thermal runaway in transportation-based secondary Li-ion batteries, rooted in a first-principles description of the governing atomistic processes at the electrode-electrolyte interface, propagating chemical information through multiple scales to a continuum-scale description of thermal transport and failure capable of addressing a variety of operational and thermal excursion conditions. These tools enable the identification of potential safety and stability issues of new battery designs prior to experimental realization.
Characteristics of o/w emulsions containing lipophilic molecules with cyclodextrins as emulsifiers

Cyclodextrins are used in the formulations of cosmetic and pharmaceutical products in the form of an inclusion complex with molecules to modify their characteristics. Furthermore, the cyclodextrins themselves can function as additives in the formulation of emulsions to stabilize these preparations. The aim of this study is to prepare o/w emulsions with α-, β- or γ-cyclodextrin as emulsifier agent and to evaluate, by macro- and microscopic observations, centrifugation test and also rheological analysis, the influence of two lipophilic model molecules, benzophenone and camphor, on the formulation properties. Benzophenone and camphor are able to reduce the emulsion stability if the molecule forms an inclusion complex with the cyclodextrin used in the formulation.
Near-zero-refractive-index metasurface antenna with bandwidth, directivity and front-to-back radiation ratio enhancement

In this paper, a novel metasurface-based Fabry–Perot Cavity antenna is presented. The antenna is wideband, directive and has a high front-to-back ratio. The idea of the antenna is based on loading a microstrip narrow band patch antenna resonating at 4.6 GHz by a metasurface superstrate. The metasurface superstrate consists of an aperiodic array of holes in contrast to the periodic nature of unit cell previously explored in the literature. The metasurface is designed as a near-zero-refractive-index material (NZRIM). By controlling the phase reflection properties of the structure, improved radiation pattern, improved front-to-back lobe ratio (7–25 dB), improved directivity (by 3 dB) and antenna bandwidth (five times) are obtained compared to a conventional microstrip antenna. The enhancement in bandwidth and directivity simultaneously using just a single layer of metasurface superstrate demonstrated for the first time, to best to authors’ knowledge, are obtained.
Controlling The Root System Architecture In Rice: Impact of Genes, Phytohormones And Root Microbiota

BackgroundIn order to feed expanding population, new crop varieties were generated which significantly contribute to world food security. However, the growth of these improved plants varieties relied primarily on synthetic fertilizers, which negatively affect the environment as well as human health. Plants adapt to adverse environmental changes by adopting root systems through architectural changes at the root-type and tissue-specific changes and nutrient uptake efficiency. ScopePlants adapt and operate distinct pathways at various stages of development in order to optimally establish their root systems, such as change in the expression profile of genes, changes in phytohormone level and microbiome induced Root System Architecture (RSA) modification. Many scientific studies have been carried out to understand plant response to microbial colonization and how microbes involved in RSA improvement through phytohormone level and transcriptomic changes.ConclusionIn this review, we spotlight the impact of genes, phytohormones and root microbiota on RSA and provide specific, critical new insights that have been resulted from recent studies on rice root as a model. First, we discuss new insights into the genetic regulation of RSA. Next, hormonal regulation of root architecture and the impact of phytohormones in crown root and root branching is discussed. Finally, we discussed the impact of root microbiota in RSA modification and summarized the current knowledge about the biochemical and central molecular mechanisms involved.