Studying Active Transportation (AT) is widespread in America and Europe's research and stud-ies that include Latent variables (LV) are growing to identify exact results of finding what to do to increase the utility of AT. LVs help us to have more accurate research. LVs are defined as psy-chological factors like feeling safe while you ride at night and thus they are not subjective and hard to understand but very important to increase the utility of using AT modes. In this study, most of the previous studies about bicycling have been reviewed. In this research, different var-iables including subjective and LVs are conducted for maximizing the use of bicycle utility and introduced to have better sight for future researchers to deal with modeling AT mode choice. Results represent the importance of having 'will' for using a bicycle, especially in difficult situa-tions and cultural barriers that affect the cycling of women.

Considering the significant advancements in autonomous vehicle technology, research in this field is of interest to researchers. To drive vehicles autonomously, controlling steer angle, gas hatch, and brakes need to be learned. The behavioral cloning method is used to imitate humans’ driving behavior. We created a dataset of driving in different routes and conditions and using the designed model, the output used for controlling the vehicle is obtained. In this paper, the Learning of Self-driving Vehicles Based on Real Driving Behavior Using Deep Neural Network Techniques (LSV-DNN) is proposed. We designed a convolutional network which uses the real driving data obtained through the vehicle’s camera and computer. The response of the driver is during driving is recorded in different situations and by converting the real driver’s driving video to images and transferring the data to an excel file, obstacle detection is carried out with the best accuracy and speed using the Yolo algorithm version 3. This way, the network learns the response of the driver to obstacles in different locations and the network is trained with the Yolo algorithm version 3 and the output of obstacle detection. Then, it outputs the steer angle and amount of brake, gas, and vehicle acceleration. The LSV-DNN is evaluated here via extensive simulations carried out in Python and TensorFlow environment. We evaluated the network error using the loss function. By comparing other methods which were conducted on the simulator’s data, we obtained good performance results for the designed network on the data from KITTI benchmark, the data collected using a private vehicle, and the data we collected.

Aging associates with progressive loss of skeletal muscle function leading up to sarcopenia, a process characterized by impaired mobility and weakening of muscle strength. Molecular mechanisms underpinning sarcopenia are still poorly characterized. Since aging associates with profound epigenetic changes, epigenetic landscape alteration analysis in the skeletal muscle promises to highlight molecular mechanisms of age-associated sarcopenia. The study was conducted exploiting the short-lived turquoise killifish Nothobranchius furzeri (Nfu), a relatively new model for aging studies. The epigenetic analysis suggested for a less accessible and more condensed chromatin in old Nfu skeletal muscle. Specifically, an accumulation of heterochromatin regions was observed as consequence of increased levels of H3K27me3, HP1alpha, polycomb complex subunits and senescence associated heterochromatic foci (SAHFs). Consistently, euchromatin histone marks, including H3K9ac, decreased. The integrative bioinformatics analysis of RNASeq and ChIPSeq, related to skeletal muscle of Nfu at different ages, revealed a down-modulation of genes involved in cell cycle, differentiation and DNA repair and an up-regulation of inflammation and senescence genes. Undoubtedly, more studies are needed to disclose the detailed mechanisms, but this approach revealed an unprecedented specific features of Nfu skeletal muscle aging, potentially associated with sarcopenia onset and consequent impairment of swimming and mobility typical of old Nfu.

1. Background and Objective: Spontaneous Intracranial Hemorrhage (ICH) is a catastrophic medical condition associated with significant morbidity and mortality. As the accumulation of unbound iron following ICH contributes to secondary brain injury, deferoxamine, an approved chelation drug, has become the center of attention. At the same time, its therapeutic remains a matter of dispute. This double-blinded Randomized Controlled Trial (RCT) aims to investigate the therapeutic potential of deferoxamine in neurological and radiological aspects. 2. Methods and Materials: The study enrolled 42 participants diagnosed with spontaneous ICH and confirmed by CT scan, randomly assigning them to either the deferoxamine treatment group or the placebo control group. While the control group received the routine treatment plus a placebo, the treatment group received routine treatment conjugated with 7.5 mg/kg of deferoxamine per hour intravenously over the first three days. The study compared hematoma and edema volume, GCS score, and mortality rates between the two groups. Our study employed rigorous randomization and blinding procedures to ensure unbiased results. 3. Results: There was a significant (p<0.05) improvement in patients' GCS up until the fourth day, but no significant difference was noted afterward. In addition, the volume of both edema and hematoma was significantly lower in the intervention group, as well as the length of stay, intubation requirement, and mortality. 4. Discussion: Deferoxamine administration can, at least in a short timeframe, improve neurological and radiological parameters.

Population growth and increasing global demand for freshwater have raised a serious challenge for the depleting sources of freshwater in the 21st century. Desalination technologies can be a reliable technique for providing freshwater. Capacitive deionization is one of the innovative desalination methods that has received increasing interest. Flow-electrode capacitive deionization (FCDI) (a new architecture of capacitive deionization) is one of the efficient, cost-effective, and environmentally-friendly desalination methods for freshwater production. In this experimental research, the performance of an FCDI system was investigated and the influence of important parameters such as flow rate of flow-electrodes, electrolyte salt concentration of flow-electrodes, and initial feed water concentration will be assessed on the efficiency of desalination operation. In this study, the flow-electrodes operated in short-circuited closed-cycle operation (SCC) mode, and also the feed water operated similarly to the flow-electrodes in closed-cycle. Moreover, in all the experiments, the salt adsorption capacity (SAC) and salt removal efficiency (SRE) was calculated. Herein, by optimizing the above mentioned parameters, the salt removal efficiency of 83% and a SAC value of 29.12 mg/g dry carbon were achieved in 5 hours.

According to many researchers, Abstraction is the basis of mathematics, computing, counting devices, and computer science and engineering. What is more, all of the above deal with complexity management in some way, and abstraction is the most basic mechanism of complexity management.Generative software development - whether in the sense of empowering humans by machine to create software or in the sense of reusing products - has been and is one of the serious concerns and goals of software engineering. The interesting thing is that in both views of generativity, the main issue is still, in a way, complexity management: whether this complexity management is to achieve diversity and reuse management (Czarnecki’s approach) or to Structuring from existing structures (the approach of Alexander and his followers in an object-oriented society).In this article, we will first look at complexity and its various definitions. The definitions that show, despite the different perspectives on complexity in different disciplines and domains, all point in one direction. We will conclude that complexity is rooted in multiplicity. In the following, we will formally define complexity. In the following discussion, we will look at the generative patterns of software development, and then we will look at the complexity management patterns at seven levels.In this article, the author has tried to maintain a comprehensive approach to complexity and to consider the approaches of different domains to complexity.

COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We introduce a new dataset that contains 48260 CT scan images from 282 normal persons and 15589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel method for increasing the classification accuracy of convolutional networks. We implemented our method using the ResNet50V2 network and a modified feature pyramid network alongside our designed architecture for classifying the selected CT images into COVID-19 or normal with higher accuracy than other models. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient identification phase, the system correctly identified almost 234 of 245 patients with high speed. We also investigate the classified images with the Grad-CAM algorithm to indicate the area of infections in images and evaluate our model classification correctness.

Breast cancer is among the most common and fatal diseases for women, and no permanent treatment has been discovered. Thus, early detection is a crucial step to control and cure breast cancer that can save the lives of millions of women. For example, in 2020, more than 65% of breast cancer patients were diagnosed in early-stage of cancer, from whom all survived cancer. Although early detection is the most effective approach for cancer treatment, breast cancer screening conducted by radiologists is very expensive and time-consuming. More importantly, conventional methods of analyzing breast cancer images suffer from high false detection rates. Different breast cancer imaging modalities are used to extract and analyze the key features affecting diagnosis and treatment of breast cancer. These imaging modalities can be divided into subgroups such as mammograms, ultrasound, magnetic resonance imaging, histopathological images, or any combination of them. Radiologists or pathologists analyze images produced by these methods manually that leads to increase the risk of wrong decisions for cancer detection. Thus, utilization of new automatic methods to analyze all kinds of breast screening images to assist radiologists to interpret images is required. Recently, artificial intelligence (AI) has been widely utilized to automatically improve the early detection and treatment of different types of cancer, specifically breast cancer, thereby enhancing the survival chance of patients. Advances in AI algorithms, such as deep learning, and availability of datasets obtained from various imaging modalities have opened an opportunity to surpass limitations of current breast cancer analysis methods. In this article, we first review breast cancer imaging modalities, and their strengths and limitations. Then, we explore and summarize the most recent studies that employed AI in breast cancer detection using various breast imaging modalities. In addition, we report available datasets on the breast cancer imaging modalities which are important in developing AI-based algorithms and training deep learning models. In conclusion, this review paper tries to provide a comprehensive resource to help researchers working in breast cancer imaging analysis.

In the previous work, the pure fatigue behavior of AM60 magnesium alloy (PF-AM60) was compared with the corrosion fatigue behavior of these specimens (CF-AM60). In this research, in continuation of the previous job, the pure fatigue behaviors of AM60 with polylactic acid (PLA) coating (PF-AM60-PLA) and also, corrosion fatigue behaviors of magnesium alloy with PLA coating (CF-AM60-PLA) were evaluated. Polymer coating was made by fused deposition modeling (FDM) with a 3D printer and attached to standard fatigue test specimens with a glue. Then, they were immersed in the simulated body fluid (SBF) for 27 days. In the end, a high-cycle bending fatigue test was performed on samples. The fracture surface of the samples was also observed using the field emission scanning electron microscopy (FESEM). Due to corrosion, the weight of the specimens redcued by an average of 35%. The corrosion rate decreased in the first 7 days and then increased. PF samples with coating had an average of 49% increase in fatigue lifetime. Regarding the CF samples, despite the use of a 10 times stronger solution, the fatigue lifetime of these samples decreased by only 35%. FESEM results also showed cleavage plates and striations. In addition, the separation of the glue from the coating and Mg was observed. Corrosion products including microcracks and holes were seen on the fracture surface of CF specimens, which caused stress concentration and crack growth. Holes caused by the release of gases were also observed in polymer coatings.

Increase in the emission of Greenhouse Gases (GHS) is among the significant concerns of government, societies, and policymakers. Due to the highest share of carbon dioxide in the produced GHGs, it is necessary to assess the factors that influence its emission. Energy systems and economic activities noticeably influence the amount of carbon dioxide production of countries. In this article, Artificial Neural Network (ANN) in addition to a linear correlation used to predict carbon dioxide emission of four CIS countries, including Turkmenistan, Uzbekistan, Kazakhstan, and Azerbaijan based the consumption of various energy sources and GDP, as the economic indicator. According to the obtained data by the proposed models, carbon dioxide emission can be accurately estimated by utilizing the mentioned input data. Models’ R-squared value are 0.9997 and 0.9999 in the cases of applying the correlation and ANN-based model. Moreover, the average absolute relative deviations by utilizing the correlation and GMDH ANN are approximately 1.05% and 0.61%, respectively. These statistical values demonstrate more proper performance of the ANN-based model compared with the applied linear correlation.

This study will lead to the development of a numerical data set that will assist in the design of Savonius wind turbines. A major objective of this study is to develop a better design for Savonius turbine blades in order to increase their torque coefficients, rotational speeds, and pressure coefficients. As part of the experimental design methodology, a full dataset was generated by simulating three-dimensional scale models utilizing computational fluid dynamics (CFD) simulations that were validated by wind tunnel data. This process is multi-objective optimization for optimizing turbine performance. The twist angle, aspect ratio, and overlap ratio are all important factors in determining the optimal torque and power coefficients. The group method of data handling (GMDH) algorithm was utilized to model objective functions based on input-output data. The Pareto fronts were plotted using polynomial models obtained from the evolutionary Pareto-based optimization approach (modified NSGA-II), and the optimal commercial points were determined using TOPSIS. A comparison of three- and two-objective optimization data revealed that two-objective optimization data lie within the boundaries of a three-objective optimization problem. The torque coefficient, rotational speed, and power coefficient are all improved by 13.74%, 0.071%, and 5.32%, respectively, using multi-objective optimization. As a result of the multi-objective optimization of the turbine, some significant characteristics of objective functions were discovered.

Background: Lung cancer is one of the common causes of death worldwide. Although the incidence rate of lung cancer in Western countries is decreasing, it presents a growing trend in developed countries. Since there is no accurate enough information about the epidemiological and Histopathologic features of lung cancer in central Iran, Isfahan, we were motivated to conduct this research. Materials and Methods: This was a descriptive, cross-sectional study carried out in central Iran, Isfahan. All demographic, histopathological and clinical data of the lung cancer patients registered in MACSA, a referral charity-based cancer center in central Iran, was analyzed within 2012-2018 using SPSS v.22 software. Results: Altogether 260 patients with lung cancer were included in this study from 6127 cancer patients registered within 2012-2018 (4.2%). Out of them, 66.2% were men, and 18.8 % of the patients were alive at the time of the study. The mean age of the patients at diagnosis was 61.56 (SD=14.11, range: 9-93). Altogether, 63.1% of patients had metastasis of whom 57.6% were in stage IV at diagnosis. The Frequency of different types of lung cancer was 36.9% adenocarcinomas, 14.2% squamous cell carcinoma, 9.6% bronchogenic carcinoma and 8.1% small cell lung cancer, respectively. Altogether, 128 cases were smokers with an average 35.45 ± 14 pack- years. Only in 36.2% of the patients, the diagnostic and therapeutic biomarkers had been checked, and CK7 was positive in 88.9% of the cases in which the biomarker had been checked. Conclusion: Despite to similar Iranian studies, the most common histopathologic type of lung cancer among the patients was adenocarcinoma that it may be attributed to the lower consumption of smoking in our population and their different genetic context. Molecular biomarkers had been checked in a small portion of the patients. More education of the clinicians along with the development of cancer molecular testing may lead to promote the personalized-based approach.

Introduction: Circulating tumor DNA (ctDNA) is newly diagnosed tumor DNA that can easily represent a tumor’s genetic and epigenetic change. Pheochromocytomas (PCCs) and Paragangliomas (PGLs) are rare tumors of adrenal gland tissue that have the potential to be detected by ctDNA. We aimed to study the potential of the methylation status of RDBP, SDHB, and SDHC genes in ctDNA of PCCs/PGLs patients as a diagnostic biomarker. Materials and Methods: Clinical data, fresh frozen tissue, the blood of 12 PCCs/PGL patients, and the blood of 12 age/sex-matched normal patients were collected. The methylation status of RDBP, SDHB, and SDHC was compared between cases and controls by MS-HRM analysis. Results: Amongst six promoter regions of RDBP, SDHB, and SDHC, promoter methylation quantification of SDHCa and RDBPb was significantly different between PCCs/PGLs and controls. SDHCa was methylated in 49.93% of PCCs/PGLs cases vs. 8.33 % of control samples, p-value: 0.026, area under curve AUC=0.757, and RDBPb in 74.9% of PCCs/PGLs cases vs. 25.0% of control samples, p-value: 0.032, AUC=0.750. Conclusions: This study suggests the ctDNA potential for a less invasive source of tumor epigenetic modification in PCCs/PGLs malignancies. The SDHCa and RDBPb hypermethylation warrant further exploration as diagnostic tools for PCCs/PGLs.

With the global increase of photovoltaic (PV) modules deployment in recent years, the need to explore and realize their reported failure mechanisms has become crucial. Despite PV modules being considered reliable devices, failures and extreme degradations often occur. Some degradations and failures can be minor and cause no critical harm if within the expected range. Others, may start mildly and then deteriorate faster to become catastrophic, especially in harsh environments. This paper conducts a state-of-the-art literature review to scan PV failures, types, and their root cause based on PV’s constructed components (from protective glass to junction-box). It outlines the hazardous consequences beyond PV module failures, describing what harm they can bring to the PV system. As we delve into the literature, it becomes clear that every component is vulnerable to certain types of failures; some can deteriorate within themselves, and others infect further PV components resulting in emerging more severe failures. In the end, the review briefly summarises PV failure detection techniques, emphasising electrical characterization techniques, and disclosing the need to engage more electrical parameters. Most importantly, this review can prepare the stage for the PV research community to identify the most prevalent degradation processes. This, in turn, encourages researchers to investigate them throughout modelling and experimental studies to forecast them at the early onset in order to protect the PV systems from hazardous malfunctions.

The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

Among endocrine cancers, thyroid carcinoma is the most prevalent type of cancer. It's prevalence has been increased throughout the world during the last decades, which shows great regional variations. Considering the increasing prevalence and occurrence of thyroid cancer cases, in this study we: Among endocrine cancers, thyroid carcinoma is the most prevalent type of cancer. It's prevalence has been increased throughout the world during the last decades, which shows great regional variations. Considering the increasing prevalence and occurrence of thyroid cancer cases, in this study we decided to evaluate the clinical and pathological charactristics of this endocrine system cancer in the population of thyroid cancer patients reffered to imam Khomeini Hospital in Sari between March 2014 and March 2021. decided to evaluate the clinical and pathological charactristics of this endocrine system cancer in the population of thyroid cancer patients reffered to imam Khomeini Hospital in Sari between March 2014 and March 2021.

An in-depth study of the failure of granular materials, which is known as a mechanism to generate defects, can reveal the facts about the origin of the imperfections such as cracks in the carbon anodes. The initiation and propagation of the cracks in the carbon anode, especially the horizontal cracks below the stub-holes, reduce the anode efficiency during the electrolysis process. In order to avoid the formation of cracks in the carbon anodes, the failure analysis of coke aggregates can be employed to determine the appropriate recipe and operating conditions. In this paper, it will be shown that a particular failure mode can be responsible for the crack generation in the carbon anodes. The second-order work criterion is employed to analyze the failure of the coke aggregate specimens and the relationships between the second-order work, the kinetic energy, and the instability of the granular material are investigated. In addition, the coke aggregates are modeled by exploiting the discrete element method (DEM) to reveal the micro-mechanical behavior of the dry coke aggregates during the compaction process. The optimal number of particles required for the failure analysis in the DEM simulations is determined. The effects of the confining pressure and the strain rate as two important compaction process parameters on the failure are studied. The results reveal that increasing the confining pressure enhances the probability of the diffusing mode of the failure in the specimen. On the other hand, the increase of strain rate augments the chance of the strain localization mode of the failure in the specimen.

In the current study, the failure behavior of retrofitted steel structures was studied experimentally and theoretically with steel/CFRP double strap joints (DSJs) under quasi-static tensile loading. A series of DSJs with different bonding lengths are also considered and examined to experimentally assess the effective bond length. To predict the failure load values of the tested specimens, a new stress-based criterion, namely the point stress (PS) criterion is proposed. Although some theoretical predictive modelling for the strength between steel/CFRP joints under various loading conditions has been presented, in this work by using the new proposed approach, one can calculate rapidly and conveniently the failure loads of the steel/CFRP specimens. Furthermore, to assess the validity of the new proposed criterion, further experimental data on steel/CFRP DSJs available in the open literature are predicted using the PS criterion. Finally, it was found that a good agreement exists between the experimental results and the theoretical predictions based on the PS criterion.

As 180-degree meanders are observed in abundance in nature, a meandering channel with two consecutive 180-degree bends was designed and constructed to investigate bed topography variations. These two 180-degree mild bends are located between two upstream and downstream straight paths. In this study, different mean velocity to critical velocity ratios have been tested at the upstream straight path to determine the meander's incipient motion. To this end, bed topography variations along the meander and the downstream straight path were addressed for different mean velocity to critical velocity ratios. In addition, the upstream bend's effect on the downstream bend has been investigated. Results indicated that the maximum scour depth at the downstream bend has increased as a result of changing the mean velocity to critical velocity ratio from 0.8 to 0.84, 0.86, 0.89, 0.92, 0.95, and 0.98 by respectively 1.5, 2.5, 5, 10, 12, and 26 times. Moreover, increasing the ratio increased the maximum sedimentary height by 3, 10, 23, 48, 49, and 56 times. The upstream bend's incipient motion was observed for the mean velocity to critical velocity ratio of 0.89, while the downstream bend was equal to 0.78.

Today, due to recent developments in technology, children devote plenty of time for screen viewing. However, its harmful effects are not yet clear. The purpose of present study was to examine the associations among screen viewing and sleep duration, and body mass index (BMI) in under-five years old children. This cross-sectional study was conducted with 322 under-five healthy children that were selected using multistage stratified cluster sampling method in 2017. The data that were gathered by time-use diary method were analyzed using Kolmogorov-Smirnov test, Spearman correlation tests, multiple linear regression analysis, one-way ANCOVA, two-way ANCOVA. There was a negative correlation between screen time and sleep duration (rs = -0.42, p = 0.00), positive correlation between screen time and BMI (rs = 0.38, p = 0.00) and sleep duration negatively correlated with BMI (rs = -0.22, p = 0.00). screen viewing was a predictive factor for both sleep duration (β = -0.26, p = 0.00) and BMI (β = -0.26, p = 0.00). screen viewing had a significant impact on sleep duration (4, 314) = 5.02, P = 0.001) and BMI (F (4, 314) = 1.16, P=0.298). Results of this study indicated that screen viewing is related to sleep duration and BMI in under-five children. furthermore, screen time has an impact on sleep duration and BMI scores of children. findings of our study suggest that sleep duration negatively is associated with BMI in under-five-year-old children.

Introduction Hydroxychloroquine (HCQ) is an antimalarial agent that has been tried out in the treatment of COVID-19, however, evidence of efficacy remains limited. Although Hydroxychloroquine overdose is not common, growing cases of poisoning with HCQ have been reported during recent years. HCQ toxicity is characterized by life-threatening symptoms which require immediate medical intervention. This report presents a suicide attempt in a hyperglycemic patient, massive ingestion of HCQ manifested by hypokalemia and acidosis.Case summaryA 47-year-old man presented at the hospital hours after massive ingestion of HCQ (100 tablets), with generalized weakness and dizziness which had led to a fall. He was drowsy and had experienced episodes of nausea/vomiting. His past medical history was remarkable for uncontrolled diabetes mellitus, confirmed by the blood glucose of 345 mg/dL, and a previous history of hospitalization a few months ago, due to a suicide attempt. He developed marked hypokalemia accompanied by acidosis, plasma potassium of 2.8 mmol/L and pH 7.34, and hypotension, blood pressure of 80/51 mm Hg, but survived with close cardiac monitoring and immediate intervention including aggressive potassium replacement, bicarbonate infusion, and charcoal administration. ConclusionConsidering the significantly increased off-label use of HCQ during the COVID-19 pandemic, this report alerts the potential for HCQ to be associated with severe electrolyte disorders, especially in predisposing conditions like diabetes. Clinicians should keep in mind the possibility of hypoglycemia in diabetic patients under hypoglycemic medications and concurrent use of chloroquine/HCQ. This therapeutic approach also suggests the benefit of even a delayed activated charcoal administration in the treatment of HCQ poisoning.

The aim of this study is to identify the effective institutional factors on the exploitation of entrepreneurial opportunities of the sports tourism industry in developing countries. This research is a qualitative study, the systematic method of Strauss and Corbin (1990) has been used to analyze the data. Interviewing is the main method of collecting data in this research, which semi-structured interviews were done with 45 members of the research community. According to Shane and Venkataraman individual-opportunity nexus framework (2000), interview questions were drafted and simultaneously with data collection from interviews, data analysis was performed. Based on the research results, 75 indicators affecting the exploitation of entrepreneurship opportunities in sports tourism were identified. Our research findings show that the necessary institutional arrangements in regulatory/legal/administrative dimensions (rule of law, government policies), normative/cultural (social norms, values and beliefs), cognitive/educational (promotion of elite knowledge, promotion of social knowledge) and guidance measures/supporter (public sector support, private sector support, complementary attraction and information technology) can improve the rate of entrepreneurial behavior in this area by increasing the ability and willingness of entrepreneurs to take advantage of entrepreneurial opportunities in the field of sports tourism. Finally, according to the research results, it can be suggested that for the growth of the sports tourism industry in developing countries, The existence of a legal, normative, supportive and educational environment will affect the ability and desire of market participants to identify and exploit the entrepreneurial opportunities of this emerging industry.

SARS-CoV-2 was detected in China in December 2019. Myocardial injury is a crucial presentation of COVID-19, based on the association of ACE-2 and SARS-CoV-2. Down-regulating ACE-2 decreases the cardioprotective effects of angiotensin, leading to a higher TNF-α activation. TNF-α causes the inflammatory response in the myocardial damage as an apoptotic inducer. Moreover, as an inducer of necroptosis, TNF-α binds to a part of TNF receptor 1, which involves receptor-interacting protein 1 (RIP1) and causes cell death through RIP1 inhibition and NF-κB stimulation, which are also done through Tpl-2. Calcineurin controls the Tpl-2-driven NFAT stimulation. Bcl-2 or Bcl-X_L entirely blocks these pathways. Bcl-2 overexpression reduces FasL expression with a mechanism based on Bcl-2 inhibiting the NFAT. Moreover, the Fas/FasL system activates apoptosis in various cells. Bcl-XL stimulates Fas-related cell death. Additionally, TNF-α, as a part of inflammatory cytokine storms, indirectly interacts with NFAT/Bcl-2 through Tpl-2/NF-κB. Diversely, TNF-α and IL-1ẞ, the basis of inflammatory cytokine storms in COVID-19, can stimulate generating NO. Also, IL-2 is highly up-regulated in COVID-19 patients and stimulates NO generation in patients. TNF-α can provoke the generation of superoxides in neutrophils. A well-determined mechanism is the intracellular production of NO via calcium-calmodulin-dependent NO synthase (NOS). NO enhances NFAT’s calcium-dependent activity. Also, Intra/extracellular calcium exchange activates calcineurin and its related molecule, NFAT. Nitration provokes RIP1 necroptosis cascade, with respiratory complex I. Nitrites converse protection against ischemia-reperfusion injuries in the myocardium. Regulating this intrinsic molecular pathway can prevent the necroptosis of cardiomyocytes.

Leadership performance by village leaders is essential to promote sustainable life among rural communities, especially fisheries community who living along coastal villages. Otherwise, previous studies found that performance issues among village’s leaders remain as serious problems, and need to find the best solution. This study was conducted to profile the job performance among village leaders based on demographic factors such as educational level, age and experiences as village leader. The data of this cross-sectional survey were collected by questionnaires on 300 respondents consist of members of village organization through stratified sampling’s technique, while the data was analysed by SPSS using items of mean, standard deviation, independent-sample t-test and anova. The finding shown that there were differences in job performance among village leaders on educational level, age and experiences. Interestingly, the finding told the best on job performance among village leaders are (i) the age between 41 to 50 years old; (iii) the experience between 11 to 20 years; and (iii) the higher educational level the higher job performance among them. This result can be using by government or any responsible parties to improve job performance among village leaders, especially for recruitment selection and for in-service training.

Human activities and natural events alter the earth’s surface and pose a constant threat to the environment. Thus, accurately monitoring and predicting these changes in a timely manner is crucial to provide solutions and mitigate the environmental consequences beforehand. This research introduces a novel framework, called HCD-Net, for change detection using bi-temporal hyperspectral images. The framework is based on double-stream deep feature extraction and an attention mechanism. The first stream focuses on deep feature extraction through 3D convolution layers and 3D Squeeze-and-Excitation (SE) blocks. The second stream focuses on deep feature extraction through 2D convolution and 2D SE blocks. The extracted deep features are then concatenated and fed to dense layers for decision-making. The efficiency of HCD-Net is compared to the state-of-the-art change detection methods. Additionally, the bi-temporal Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) hyperspectral dataset was used for further evaluation of the change detection results. The results show that HCD-Net has a higher accuracy and the lowest false alarm rate, where the overall classification accuracy is above 96%, and the kappa coefficient is over 0.9.

Due to their wide range of uses in modern technology, nanomaterial’s of silver metallic (Ag-NPs) have engaged considerable concern, driving significant research with development efforts. This study focuses on investigating the antimicrobial properties of Ag-NPs, encompassing their production, characterization, and biological aspects. The eco-friendly extracellular biosynthetic method employed in this work utilized extracts from the marine fungus Aspergillus flavus MK4 as reducing agents for nanoparticle synthesis. Analyzing the colloidal Ag-NPs using UV-visible spectroscopy revealed a peak in absorbance at 460 nm, indicating the presence of plasmonic properties. The electrons imaging of internal structure (TEM) elucidated spherical shape of the Ag-NPs by 15 nm size. Testing against bacterial diversities (Gr-ve & Gr+ve) revealed potent antibacterial and antifungal efficacy. Cytotoxicity versus HepG-2 cell line was assessed using the MTT assay, and antioxidant properties were examined through the radical scavenging (DPPH) assay. In wise of their conceivable applications in the fields of antibacterial, anticancer, and wound-healing, the Ag-NPs that were synthesized exhibit promising features. With its powerful ability to synthesize silver nanoparticles (Ag-NP), Aspergillus flavus MK4 Aspergillus flavus MK4 can generate nanoparticles extensively characterized, demonstrating their antibacterial, antioxidant, anticancer, and wound-healing properties.

In this paper, precise examination of multi-port antennas with large mutual coupling between the ports is studied. For this purpose, some vital parameters such as active reflection coefficients and realised gain are emphasized. The main motivation of this research is the ignorance of this issue in several recently published papers. Hence, corrections and criticisms to some recently reported results are presented. At first, a microstrip patch consisting of two inverted U-slots is re-examined, which has been proposed in a recently published paper for wideband applications. However, the authors did not present satisfactory results to indicate the performance of the proposed structure. In reverse, some important parameters such as the antenna gain appear to be incorrectly reported. In this paper, the characteristics of the antenna are compared with a simple 50 Ω microstrip line excited by two probes, indicating no significant differences. In the remainder of this paper, some corrections are provided on two examples of wide-beam circularly polarised multi-fed antennas for satellite applications. The first example is the multi-fed spiral antennas with folded arms, which have been proposed as the widebeam antennas at 435 MHz. It is indicated that the antenna height should be increased for better performance. The second example is the quadrifilar square helical antennas with folded arms, which have been proposed as the widebeam antennas for 435 MHz with minor responses at 145 MHz. Some corrections are presented on the previously reported minor responses at 145 MHz.

This comprehensive review delves into gold market business management, covering historical perspectives, market dynamics, mining models, investment strategies, technology, regulations, global trends, and sustainability. Starting with a historical overview, it traces the gold market's evolution and analyzes supply-demand dynamics, price fluctuations, and geopolitical influences. The article scrutinizes gold mining models, evaluating environmental and social responsibilities, and explores financial management strategies, emphasizing risk and gold's role in portfolios. Examining technology's role, it highlights innovations in exploration, mining, and processing for improved efficiency and sustainability. The regulatory landscape analysis encompasses compliance challenges, environmental regulations, and ethical considerations, emphasizing global impacts. Global market trends are explored, identifying potential opportunities and challenges, offering strategic insights. The review concludes by evaluating sustainability practices, emphasizing environmental conservation, community engagement, and ethical sourcing.

This article provides a comprehensive exploration of the electric vehicle (EV) business, investigating its current state, market dynamics, and pivotal role in sustainable transportation. It delves into factors driving EV adoption, challenges faced by the industry, and the landscape of key players. The discussion extends to investments, infrastructure development, consumer trends, and the technological innovations shaping the future. The article concludes with insights into the anticipated growth and transformative impact of EVs, emphasizing their significance in fostering a cleaner, more sustainable future for global transportation.

This exploration delves into the intricacies of decision-making in business management. It covers decision-making models, influencing factors, real-world case studies, and strategies for effectiveness. Emphasizing the role of data-driven approaches, the exploration highlights the transformative impact of effective decisions on organizational success. Challenges and pitfalls are addressed, providing insights for overcoming obstacles. The importance of mastering decision-making is underlined as a strategic advantage in the competitive landscape of business management. In summary, this exploration offers a nuanced understanding, empowering leaders to make informed choices that shape organizational destinies.

Olfactory system is a vital sensory system in mammals, giving them the ability to connect with their environment. Anosmia, or the complete loss of olfaction ability, which could be caused by injuries, is an interesting topic for inspectors with the aim of diagnosing patients. Sniffing test is currently utilized to examine if an individual is suffering from anosmia; however, functional Magnetic Resonance Imaging (fMRI) provides unique information about the structure and function of the different areas of the human brain, and therefore this noninvasive method could be used as a tool to locate the olfactory-related regions of the brain. In this study, by recruiting 31 healthy and anosmic individuals, we investigated the neural BOLD responses in the olfactory cortices following two odor stimuli, rose and eucalyptus, by using a 3T MR scanner. Comparing the two groups, we observed a network of brain areas being more active in the normal individuals when smelling the odors. In addition, a number of brain areas also showed an activation decline during the odor stimuli, which is hypothesized as a resource allocation deactivation. This study illustrated alterations in the brain activity between the normal individuals and anosmic patients when smelling odors, and could potentially help for a better anosmia diagnosis in the future.

Preterm infants have increased body adiposity at term equivalent age and risk for adverse metabolic outcomes. The aim of the study was to define how nutrient intake may impact body composition (BC) of very low birth weight infants fed with early progressive enteral feeding and standard fortification. Eighty-six infants with

Although different assessments and evaluations of Dual-Miller cycle performed, specified output power and thermal performance associated with engine determined. Besides, multi objective optimization of thermal efficiency, Ecological Coefficient of performance ( ) and Ecological function ( ) by the mean of NSGA-II technique and thermodynamic analysis performed. The Pareto optimal frontier obtaining the best optimum solution is chosen by fuzzy Bellman-Zadeh, LINMAP, and TOPSIS decision-making techniques. Based on the results, performances of dual-Miller cycles and their optimization are improved.

The neural system has limited resources to interact with the environment, and this is where attention comes into play. Attention is a complex process that provides numerous benefits, but there has been a longstanding debate about the mechanisms involved in attentional orientation. Two widely proposed mechanisms are top-down and bottom-up, which relate to the organism's current behavioral goal and the salience of environmental stimuli, respectively. However, distinguishing between these mechanisms can be challenging in both behavioral and neural studies. This review introduces a new conceptualization in which both top-down and bottom-up mechanisms are viewed as aspects of the same process. This unified approach aims to prepare the organism to face stimuli and events based on its prior experiences, immediate (the current task that he/she is aware of), and innate (to be alive) demands.

Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer's demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network.

Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-meter physical distancing as a mandatory safety measure in shopping centres, schools and other covered areas. In this research, we develop a Deep Neural Network-based Model for automated people detection, tracking, and inter-people distances estimation in the crowd, using common CCTV security cameras. The proposed DNN model along with an inverse perspective mapping technique leads to a very accurate people detection and social distancing monitoring in challenging conditions, including people occlusion, partial visibility, and lighting variations. We also provide an online infection risk assessment scheme by statistical analysis of the Spatio-temporal data from the moving trajectories and the rate of social distancing violations. We identify high-risk zones with the highest possibility of virus spread and infection. This may help authorities to redesign the layout of a public place or to take precaution actions to mitigate high-risk zones. The efficiency of the proposed methodology is evaluated on the Oxford Town Centre dataset, with superior performance in terms of accuracy and speed compared to three state-of-the-art methods.

The proposal of novel drugs and approaches for effective treatment of the novel coronavirus is a necessity after the quick outbreak of the disease. Since the commencement of the coronavirus spread, enormous efforts have been made to protect, alleviate and cure the disease, though no specific treatment has been approved. While there have been convincing results in the use of chemical drugs and interferon therapy, such therapeutic approaches have various drawbacks and lack the required performance for the treatment of the new coronavirus. Medicinal plant species can provide a solution as a source of natural antiviral compounds by the accumulation of secondary metabolites and lectins as well as acting as a platform to express the viral immunogenic proteins. This study reviews the advantages and the results of previous research for the treatment of the novel coronavirus disease and previous generations of similar coronaviruses. Several plant-derived anti coronavirus compounds have been nominated that could be targeted for further research due to the similarity of the coronavirus disease in 2003 and the current coronavirus. This review regards plant species such as Scutellaria baicalensis (Baikal skullcap), and Utrica dioica (Stinging nettle) as suitable candidates for the new coronavirus antiviral research. Furthermore, the use of plants such as Nicotiana tabacum (Tobacco) for the expression of the coronavirus viral antigens can be a target for the future vaccinal research of the new coronavirus due to the efficiency of expression and intrinsic antiviral properties.

Heat transfer enhancement and hydrodynamic characteristics of nanofluid use in a micro heat exchanger is investigated for cooling electronic components working in hot climatic conditions. The cooling fluid employed was water and TiO2 nanoparticles at concentrations of 1% and 5%, Reynolds numbers ranged from 400 to 2000, and inlet temperatures ranged between 35ºC and 65ºC. At a nanofluid inlet temperature of 55ºC and a nanoparticle concentration of 1%, the Nusselt number increased by 23% up to 54% as the Reynolds number varied between 400 and 2000. At a nanoparticle concentration of 5%, the percentages which correspondingly enhanced the Nusselt number were 32% and 63%. The temperature of the electronic heating component decreased by 4.6-5.2ºC when the nanofluid concentration was increased from 0 to 5% at a Reynolds number of 400 and a nanofluid inlet temperature of 35ºC. Small increments in pressure drop of about 6% and 13% were observed at nanofluid concentrations of 1% and 5%, respectively. With nanoparticle concentrations of 1% and 5%, a Reynolds number of 2000 and a nanofluid inlet temperature of 35ºC, performance evaluation criterion (PEC) values of 1.36 and 1.45 were obtained. When the nanofluid inlet temperature was increased to 65ºC, the PEC parameter decreased to 1.02-1.10 for both concentrations.

Gas embolism is a medical condition leading to the blockage of blood flow in the microvasculature by gas bubbles. While reported as rare, gas embolism often has devastating, fatal physiological consequences. Despite this acute importance, the genesis and evolution of air bubbles in blood vessels under different physiological conditions, such as blood viscosity and blood flow rate, is still understudied, largely because of difficult experimentation and in situ visualization. The objective of this work was to study the gas embolism phenomenon in vitro, using a microfluidic system that mimicked the architecture of microvasculature. The microfluidic systems comprised linear channels with two different air inlet types, namely, T- and Y-junctions with three different widths (20 µm, 40 µm, and 60 µm), and a 30 µm width honeycombed network with three bifurcation angles (30°, 60°, and 90°). Three synthetic liquids equivalent to 0%, 20%, and 46% hematocrit that mimicked the physiological blood viscosity and hematocrit concentrations were used. Our results show that: (i) 20 µm and 40 µm width channels had an elevated risk of gas embolism due to wide fluctuations in the total slug sizes; (ii) the resistance to the flow of air bubbles increased with the increase in the equivalent concentration of hematocrit; (iii) gas bubbles causing blockages and dampening of the flow velocity were frequently observed in 20 µm channels, and lastly (iv) increased risk of gas embolism was observed in the honeycomb architecture with 60° and 30° bifurcations. This work suggests that in vitro experimentation using microfluidic devices with microvascular tissue-like structures opens the possibility of studying this medical condition with high reproducibility and impacts the fact-based medical guidelines for preventing or mitigating iatrogenic occurrences.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

Background: COVID-19 is a respiratory illness caused by SARS-CoV-2 that has become a global pandemic. Although children can contract the virus, they are generally less likely than adults to develop severe symptoms. Parents and caregivers should monitor their children for symptoms and seek medical attention if their child becomes ill. Practicing good hygiene and social distancing can help prevent the spread of the virus. Vaccines are available for children and can provide additional protection against COVID-19. Understanding the impact of COVID-19 on children is crucial for developing effective public health strategies to control the pandemic.Objectives: The current study aims to determine the prevalence of Covid-19 in pediatric age group in Duhok province and Zakho city, in Kurdistan region. among the children who tested positive for IgG test. If IgG antibodies are detected in a person's blood sample, it suggests that they have been infected with SARS-CoV-2 at some point in the past and their immune system has responded by producing antibodies against the virus.Methods: A cross-sectional investigation was undertaken involving youngsters aged 5 to 12 years. The study encompassed a total of 330 participants, selected between October and December 2022. The children underwent testing to detect IgG antibodies. Moreover, a questionnaire was employed to gather demographic and individual information from each contributor.Results: Among the studied sample, 302/330 (91.5%) of children were positive to IgG antibody test. No gender difference for COVID-19 was found in pediatric age group. Case fatality rate was 0%. 22/302 (6.6%) cases were symptomatic during the infection. However, 282(93.4%) cases were asymptomatic. Conclusions: Covid-19 infection in pediatric age group has good prognosis compared to adults. Intensive care unit (ICU) and death are rare. High-risk groups should be targeted for education and immunization/vaccination. Furthermore, more studies are needed to be conducted in order to investigate the risk factors of the infection and to assess the awareness among the general population about the risk of infection.

This paper reports on the optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation systems for cattle farming in rural areas of Bangladesh. Bangladesh is a lower middle-income country with declining rates of poverty among its 160 million people due to persistent economic growth in conjunction with balanced agricultural improvements. Most of the rural households adopt a mixed farming system by cultivating crops and simultaneously rearing livestock. Among the animals raised, cattle are considered as the most valuable asset for the small/medium-scale farmers in terms of their meat and milk production. Currently, along with the major health issue, the COVID-19 pandemic is hindering the world’s economic growth and has thrust millions into unemployment; Bangladesh is also in this loop. However, natural disasters such as COVID-19 pandemic and floods, largely constrain rural smallholder cattle farmers from climbing out of their poverty. In particular, small and medium-scale cattle farmers face many issues that obstruct them from taking advantage of market opportunities and imposing a greater burden on their families and incomes. An appropriate measure can give a way to make those cattle farmers’ businesses both profitable and sustainable. Optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation system for cattle farming is a new and forward-looking approach for sustainable development of the livestock sector. In this study, we design and optimize a thin-film coating assisted hybrid (photovoltaic-battery-generator) power system by using the Hybrid Optimization of Multiple Energy Resources (HOMER, Version 3.14.0) simulation tool. An analysis of the results has suggested that the off-grid hybrid system is more feasible for small and medium-scale cattle farming systems with long-term sustainability to overcome the significant challenges faced by smallholder cattle farmers in Bangladesh.

Plant species with anti-inflammatory properties might play an essential role in combatting COVID-19 via reducing cytokine storms. We aimed to review the extant evidence of the potential therapeutic efficacy of natural products against cytokine storms by inhibiting interleukin-6 (IL-6) as a major pathological mediator. Data were collected following an electronic search in major databases (Pubmed, Scopus, Web of Science, Google Scholar) and also preprint articles on preprint and medRxiv servers by using a combination of relevant keywords. Seventeen active compounds and medicinal plants were found and reviewed in the present review. Results of both in-vivo and in-vitro experiments conducted on these compounds showed that Phillyrin, SMFM, Qiangzhi decoction, curcumin, Shen-Fu, Forsythia, and Alpha-Mangostin inhibit the production of IL-6. Andrographolide and Liu Shen Wan have an inhibitory effect on releasing this agent, while Ilex Asprella and Deoxy-11,12-didehydroandrographolide and naringin reduce the expression of IL-6. Theaflavin and Cholorogenic acid inhibit the secretion of IL-6, Xuebijing, and Chai-Hu-Gui-Zi-Gan-Jiang-Tang and Lipanpaidu prescription can reduce the serum level of IL-6. These agents also effectively improve infected lungs, increase survival rates, and minimize tissue damage. Medicinal plants and their phytochemical ingredients with down-regulatory effects on the expression of IL-6 have a potential influence on the inhibition of cytokine storms during viral infection caused by COVID-19. Therefore, phytochemicals could be regarded as promising candidates for managing cytokine storm inflammatory responses due to COVID-19 infection.

Many inflammatory mechanisms are involved in the pathophysiology of COVID-19 infection. COVID-19 inhibits IFN antiviral responses, so we should expect an out-of-control viral replication. “Cytokine storms” occur due to the over-production of pro-inflammatory cytokines after an influx of neutrophils and monocytes/macrophages and may be responsible for the immunopathology of the lung involvement. Several cascades have been reported in the activation process of NF-κB. In this paper, to find new therapeutic options for COVID-19 infection, we reviewed some natural products that could potentially inhibit the NF-κB pathway. We found that sevoflurane, quercetin, resveratrol, curcumin, KIOM-C, bergenin, garcinia kola, shenfu, piperlongumine, wogonin, oroxylin, plantamajoside, naringin, ginseng, kaempferol, allium sativum L, illicium henryi, isoliquiritigenin, lianhua qingwen, magnoflorine, and ma Huang Tang might be effective in inhibiting the NF-KB pathway. These natural products could be helpful in the control of COVID-19 infections. However, larger clinical trials are needed to ascertain the efficacy of these products fully.

Colpodella species are free-living opportunistic pathogens that cause human and animal infections and use ticks and flies as vectors. Trophozoite and cyst stages of Colpodella species can be distinguished from stages of the prey Parabodo caudatus using Sam-Yellowe’s trichrome staining. Colpodella species obtain nutrients by attaching to their prey, aspirating the prey’s cytoplasmic contents into a posterior food vacuole and encysting. It is unclear whether both trophozoite and cyst stages are present during infection. Molecular techniques identified Colpodella species in all reported infections. However, no morphological information was reported to aid life cycle stage identification in hosts. This review discusses the increased incidence of Colpodella infection in animals and in vectors and the need to identify stages used for transmission and pathogenesis. The potential for zoonotic infections through tick and fly bites is a public health concern. We previously used Sam-Yellowe’s trichrome staining to identify life cycle stages of Colpodella sp. In order to gain a better understanding of transmission and pathogenesis, identifying Colpodella life cycle stages in infected tissue and in vectors will provide important insights regarding nutrient uptake in hosts by determining whether attachment of trophozoites to host cells occurs, and identifying trophozoites and cysts in infected hosts.

Agriculture uses a lot of fuel, fertilizers, pesticides and other substances, while emitting large amounts of GHGs. It is important to optimize these inputs and outputs. One such way is increas-ing crop biodiversity. For this reason, single crops and mixtures of maize, hemp and faba bean as binary and ternary crops were investigated at the Experimental Station of Vytautas Magnus Uni-versity, Lithuania. Results showed that consumption of diesel fuel was by the 31-46% higher than in single and 22-35% higher than in binary cultivations was found in a ternary crop. This influenced on the highest energy input or near twice higher than in maize and hemp single crops and maize+hemp binary crop, but similar with binary crops with faba bean. Despite this, the productivity of the trinary crop and, at the same time, the energy output were 2-5 times higher than in other treat-ments. This compensated for higher energy inputs and the energy efficiency ratio. In ternary crop, energy productivity was from 1.1 to 2.8 times higher and net energy was by 1.9-5.3 times higher than in other tested cultivations. The highest total GHG emissions were obtained in binary maize+hemp and maize+faba bean cultivations (1729.84 and 2067.33 CO2eq ha-1). Ternary cultiva-tion with the highest energy inputs initiated average GHG emission - 1541.90 kg ha-1 CO2eq. For higher efficiency, ternary crop could be sown and harvested in one machine pass. Faba beans should be included in the ter-nary crops, as their biomass takes a significant part of the total biomass produced. We recommend to review the inter-cropped faba bean seeding rates as faba bean seeds have a high energy input equivalent.

This study investigated the impact of seven-strain probiotic supplementation on the frequency of T helper 17 (Th17) cells, regulatory T (T-reg) cells, Treg/Th17 ratio, and their gene expression in individuals with severe traumatic brain injury (STBI). Probiotics can influence the gut microbiota, modulate the immune response, and prevent or alleviate certain immune diseases. However, it is necessary to clarify whether probiotics can effectively impact Th cells in STBI patient. Despite the great attention to improving the immune system in most diseases, there is currently no accurate mechanism for the use of probiotics in diseases with damage to the head injury, which can be a basis for the use of probiotics. The primary objective of this study is to address this research gap. The present study was a randomized, double-blind, placebo-controlled trial that enrolled 48 STBI patients. They were treated with probiotics or placebo: 4 capsule/day for 14 days. The pre- and post-study evaluation included examining the frequency of Treg, Th17 cells, as well as the expression of associated immunological parameters (Foxp3 and RORγt) and Treg/Th17 ratio in both groups. No significant differences were found between the two groups in terms of subject characteristics (P>0.05). GCS scores at 14 days were significantly higher in the probiotic compared to the placebo group. The probiotic group showed a significant decrease in Th17 cell and RORγt gene expression (P = 0.022 and P< 0.001, respectively), a notable increase in T-reg and FoxP3 gene expression (P= 0.025 and P< 0.001, respectively), and a higher Treg/Th17 ratio compared to the placebo group. Our study provides promising evidence of the beneficial effects of seven-strain probiotic supplementation on Th cells in individuals with STBI.

On the basis of the golden ratio and the compasseses, every angle was divided into three equal parts. In general, it has been proven that the problem of triangulation of an angle cannot be solved on the basis of the golden ratio and the expanding of the angle. The relationship of golden relativity with Pi number and Euler's number has not been investigated to solve impossible problems. According to the investigation of events in six-dimensional space-time, with the simultaneous movement of two arms of the compasses based on the golden ratio, every angle was divided into three equal parts. The growth rate based on the golden ratio is the key to solving the most intractable mathematical and physical problems.

Consciousness results from comprehending the living creature from its existence in time and space. Thought and consciousness are distinguishing factors between humans and machines having artificial intelligence. No algorithm has been offered for artificial self-awareness based on Thinking. Previous studies have not studied the relationship between consciousness, thinking and time. In this study, the relationship between consciousness, thinking, memories and speech over time has been studied. A deep logical connection exists between consciousness, thinking, and time. An algorithm can be designed for artificial consciousness based on this research findings.

This paper presents a method for producing a gravity field through an electromagnetic field. The electromagnetic field can produce a positive or negative gravity field. The relationship between gravity force and electromagnetic is unknown. Former studies by theoretical physics predict the relationship between these two forces. Based on the general balance theory in six dimensions of space and time, the electromagnetic field was studied from this viewpoint. Three-dimensional waves oscillate in the fourth dimension and electromagnetic waves distort space-time. Aggregating these distortions can behave like a positive or negative gravity field. Consequently, the production of energy is possible from gravitational fields.

A human brain can communicate with another one’s brain using quantum entanglement. Similar particles can entangle without interaction. Sensory communication between two individuals from far distances is still not known. Former studies primarily have been performed regarding brain neurons' quantum behavior. The test was performed on two individuals far from each other. These individuals were put under the same music on the basis of brain neuroplasticity property. By activating the brain reward system, aligned thinking was time scheduled in these individuals’ brains. On the basis of entanglement, compressed information was sent and received between these two individuals.

On the basis of the findings of this paper, the theories of quantum mechanics and general relativity can be expressed in a comprehensive theory. The events were surveyed length of the time, in the Euclidean six-dimensional space-time (R6=x1+x2+x3+t1+t2+t3). Previous studies have not studied the relationship between the origin of matter's inherent properties, fundamental constants, and quantum mechanics phenomenon with space-time geometry. This theory prediction the with certainty obtained probabilistic results of quantum mechanics. This prediction is on the basis of metric resulting from the Eccentricity of the Ellipse due to the object density, in the length of time. The cause and nature of dark matter and dark energy are the findings of this article.

Bangladesh's railway system mostly uses typical manual railway crossing technique or boom gates through its 2,955.53 km rail route all over the country. The accidents are frequently happening in the railway crossings due to not having obstacle detectable and quickly operating gate systems, and also for fewer safety measures in the railway crossing. Currently, there are very few automatic railway crossing systems (without obstacle detectors) available, however, all of them are dependent on the national power grid without a backup plan for any emergency cases. Bangladesh is still running a bit behind in the power generation of its consumption, hence it is not possible to have a continuous power supply at all times all over the countryside. We aim to design and develop a smart railway crossing system with an obstacle detector to prevent common types of accidents in the railway crossing points. We design to use two infrared (IR) sensors to operate the railway crossing systems which will be controlled by the Arduino Uno. This newly designed level crossing system will be run with the help of sustainable renewable energy which is cost-effective, eco-friendly, and apply under the national green energy policy towards achieving sustainable development in Bangladesh as a part of the global sustainable goal to face climate change challenges. We have summarized the simulated results of several renewable energy sources including a hybrid system and optimized the Levelized Cost of Energy (LCOE), and the payback periods.

Dysregulation of the angiotensin-II Type-I receptor (AT1R) and its pathway was reported to associate with poor-prognosis in several malignancies, including colorectal-cancer (CRC). We have explored the therapeutic-potential of targeting AT1R using valsartan, and its pharmacological-interaction with Fluorouracil (5-FU) in CRC. Anti-proliferative function was evaluated in 2-/3-dimensional cells and in vivo models. Anti-proliferative, anti-migratory, apoptotic function and effect on cell-cycle was assessed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), wound-healing test, and Fluorescence-activated cell sorting (FACS), respectively, while gene-expression was determined at mRNA/protein levels. By histogical analysis and measuring of oxidative/antioxidant markers, we evaluated the anti-inflammatory properties of valsartan. Valsartan suppressed cell-growth and impacted the anti-tumor-activities of 5-FU by apoptosis-induction. Valsartan inhibited the cells migration by perturbation of Matrix metalloproteinase (MMP1). Furthermore, valsartan inhibited tumor-growth and metastasis, and this was more notable in valsartan/5-FU combination-treated-group. The mechanism was plausible to be via the induction of Reactive-oxygen-species (ROS) and down-regulation of Superoxide-dismutase (SOD), thiol/catalase (CAT) as well as Vascular endothelial growth factor (VEGF) and Transforming growth factor beta (TGF-β). Valsartan may protect cells against intestinal fibrosis by modulation of pro-fibrotic and pro-inflammatory components include fibronectin, Interleukin) IL-1β (, Tumor necrosis factor alpha) TNF-α (, Interferon gamma) INF-γ (, and Monocyte Chemotactic Protein 1 (MCP-1). Our findings demonstrated that targeting the AT1R receptor may inhibit tumor-growth and ameliorate fibrosis and inflammation associated with CRC via modulation of AT1 and TGF-β pathways.

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system. According to recent studies, cellular senescence caused by telomere shortening may contribute to the development of MS. Aim of the study: to determine the associations of TEP1 rs1760904, rs1713418, TERC rs12696304, rs35073794 gene polymorphisms with the occurrence of MS. Methods: The study included 200 patients with MS and 230 healthy controls. Genotyping of TEP1 rs1760904, rs1713418 and TERC rs12696304, rs35073794 was performed using RT-PCR. Statistical analysis of the obtained data was performed using the program "IBM SPSS Statistics 29.0". Haplotype analysis was performed using the online program "SNPStats". Results: The TERC rs12696304 G allele of this SNP is associated with a 1.4-fold lower odds of developing MS (p=0.035). TERC rs35073794 is associated with an approximately 2.4-fold reduced odds of MS occurrence in the codominant, dominant, overdominant, and additive models (p < 0.001; p < 0.001; p < 0.001; p < 0.001, respectively). Haplotype analysis shows that the rs1760904-G - rs1713418-A haplotype is statistically significantly associated with a 1.75-fold increased odds of developing MS (p=0.006). The rs12696304-C - rs35073794-A haplotype is statistically significantly associated with a 2-fold decreased odds of developing MS (p=0.008). In addition, the rs12696304-G - rs35073794-A haplotype was found to be statistically significantly associated with a 5.3-fold decreased odds of developing MS (p&lt;0.001). Conclusion: Current evidence may suggest a protective role of TERC SNP in the occurrence of MS, while TEP1 has the opposite effect.

Memory is probably one of the most complex cognitive functions of the human, and in many years, thousands of studies have helped us to better recognize this brain function. One of the reference textbooks in neuroscience, which has also elaborated on the memory function, is written by Prof. Kandel and his colleagues. In this book, I encountered a number of ambiguities when it was explaining the memory system. Here, I am sharing those points, either to find an answer for them, or to let them be a suggestion for our future works. Prof. Kandel has spent most of his meritorious lifetime on studying the memory system; however, the brain is extremely complex, and as a result, we still have many years to comprehensively understand the neural mechanisms of brain functions.

Despite the 12-lead electrocardiogram (ECG) being the gold standard in evaluating clinical presentations of arrythmias of various kinds, several notable limitations, namely in accuracy and localization, have recently garnered concern with respect to administering appropriate therapeutic measures. The following text puts these limitations under the spotlight, highlighting the difficulty and challenging nature of standard ECG analysis and therapeutic measures, while simultaneously showing a novel body surface electrocardiographic mapping system that utilizes 3D spatial imaging and pinpoint localization algorithms in order to compensate for the shortcomings of the standard ECG, thereby providing higher precision data collection. We provide a brief overview of the novel device in a selection of arrhythmic demographics, along with its validity and reliability, while illustrating the benefits and positive outcomes of its utility.

Although lithium-ion batteries have extensively been used in various applications because of their high energy capacity, fracture and failure, the by-products of large strains and stresses caused by fast charging and discharging need yet to be addressed. The size effects on the mechanical behavior of the nano-sized structures are significant; however, the classical elasticity theory may not consider such effects. On the other hand, surface stress theory, as a robust and potential theory, is suitable in considering size effects in nano-scale structures. Therefore, in this paper, in order to involve the surface stress effects on the fracture behavior of Li-ion batteries, the following steps are taken. Firstly, a phase-field model is used to determine the evolution of the concentration profile. Subsequently, the stress distribution is obtained by using the surface stress theory combined with chemical equations for a planar electrode. Afterward, by using the weight function method for an edge crack in the plate, the stress intensity factor is derived for all time steps and possible crack lengths during the process. It is found that with increasing phase boundary thickness parameter or decreasing phase-separation phenomenon, the surface mechanics parameters become more influential. Furthermore, in the presence of positive surface stress, the diffusion-induced stress distribution decreases, which in turn reduces the stress intensity factor. In addition, in this paper, the two states of surface stress are compared either for elastic or total strain. Concerning stresses and concentrations, the results indicate a big difference at the beginning of the deintercalation process showing, in particular, 2% for stresses, but the differences diminish gradually.

Interactions of different factors in differently tilled faba bean agrosystem is still insufficiently studied and evaluated. For these reasons we studied the results of long-term field experiment, which was carried out in the Research Station of Vytautas Magnus University, Agriculture Academy (Lithuania). The aim of this study is comprehensively evaluating the effect of the deep and shallow ploughing, deep cultivation-chiseling, shallow cultivation-disking, and no-tillage systems for faba bean cultivation on the much-interacted factors, relations between them and strength of impact by the integrated evaluation method using complex evaluation index (CEI). Calculations showed that the influence of the no-tillage system was the greatest on the faba bean agrosystem than other system used. Shallow cultivation was more efficient than deep and shallow ploughing and deep cultivation systems. In the deep ploughing system, there were calculated more minimal, i.e. close to 1 as the CEI value, which showed DP ineffectiveness.

At the time of tillage, properties of the soil change, thereby changing the conditions of crop development and ultimately their productivity and quality. The effect of non-inversion tillage or no till on faba bean development is stills not widely investigated. For this reason, investigations of tillage systems from deep and shallow ploughing, chiselling, disking to no tillage were tested in Vytautas Magnus University, Agriculture Academy, Lithuania. The results showed that different tillage methods had less influence on faba bean development than meteorological conditions during the growing seasons. Soil chiselling generally showed better faba bean canopy development rates than other treatments. Faba bean roots developed somewhat better in not tilled plots. Vegetative conditions had a significant influence on faba bean development indicators. The effects of vegetative conditions during all four years of the experimentation were significantly different from each other. This shows that, due to rapid climate change, the conditions of each vegetative season become unique and require precise attention.

The alkylation of 1,1,2-trimethyl-1H-benzo[e]indole with 2-chloroacetamide, followed by work-up of the reaction mixture with a base and the subsequent treatment of a crude product with acetic acid gives 10a,11,11-trimethyl-10a,11-dihydro-8H-benzo[e]imidazo[1,2-a]indol-9(10H)-one. The structure assignments were based on data from ¹H, ¹³C and ¹⁵N NMR spectroscopy. The optical properties of the obtained compound were studied by UV-vis and fluorescence spectroscopy.

Directed energy deposition (DED) parameters were determined for near-β alloy Ti-55511 by employing statistical design of experiments (DOE) methods. Parameters resulting in fully dense freeform deposits were identified using two sequential DOEs. Single laser tracks were printed with several laser power, traverse rate, and powder feed rate settings in an initial DOE to identify promising build parameters. Capture efficiency and effective deposition rate were used to characterize and rank the single track deposits. The best parameters were then used to print solid cube with various X-Y and Z-overlaps (different hatch spacing, HS, and layer thickness, ZS) in a second DOE. Suitable deposition parameters were selected based on cube density and microstructure and were used to fabricate larger tensile samples for mechanical testing. Multiple parameter sets were found to provide dense Ti-55511 deposits with acceptable mechanical properties and parametric models showed statistical significance.

The fundamental challenge for the structural design of complicated shapes and lightweight structures such as Tensile Membrane Structures (TMS) is a reliable estimation of lateral loading such as wind load. Wind pressure coefficients can’t be correctly calculated by standards for a large range of intricate forms of structures. Computational Fluid Dynamics (CFD), a strong computational technique for evaluating wind pressure distribution on complicated geometry, can be used to determine wind-related parameters. The average wind related-distributions for the tensile membrane surface are validated with a few contributions from prior studies, which are important to validate with benchmarks in experimental wind tunnel experiments. For the double-curved surface, the results show good agreement between experimental tests and CFD simulations. In this study, CFD simulation was used to calculate the mean surface pressure coefficient (Cp) for generic shapes and tensile membrane forms using the steady Reynolds-Averaged Navier-Stokes (RANS) technique. Wind force coefficients and the effect of wind directions are also explored across a wide range of classical and tensile forms. The purpose of the current research is to look at the effect of wind assault angle on the Cp distribution for tensile membrane structures and general shapes.

This study examines the relationship between firm-level and macroeconomic variables and stock prices (SP) in Iran, Saudi Arabia (KSA), and Iraq, where economic conditions are uncertain. The sample consists of all firms listed on these countries' stock exchanges between 2015 and 2019, yielding a comprehensive dataset from 154 Iranian firms, 82 KSA firms, and 33 Iraqi firms. Using a fixed effect model, intriguing relationships are uncovered between firm-level and macroeconomic factors on SP. The findings indicate that, at a 1% significance level, there is a strong link between Iran and Iraq's GDP and their respective SP. In KSA, the association between GDP and SP is positive and significant at a 5% level. In addition, there is a positive and statistically significant correlation between the inflation rate and SP in all three countries. Moreover, the association between exchange rates and SP is significant and positive in KSA and Iraq but negative and significant at the 1% significance level in Iran. Furthermore, in KSA, the connection between oil prices and SP is positive and significant, whereas, in Iran, the relationship is negative at the 1% level. Surprisingly, there is no association between the price of oil and Iraqi SP. Regarding intangible assets, their impact on SP in Iran and KSA is negligible. In Iraq, however, there is a negative and significant relationship at the 5% level, indicating that intangible assets have a detrimental impact on SP. These findings highlight the complex link among macroeconomic factors, intangible assets, and SP in the examined countries. Policymakers and governments should prioritize implementing measures to foster sustainable economic growth, manage inflation, and stabilize exchange rates. These actions can boost investor confidence and contribute to the stock market's overall development.

In this paper, we proposed the fusion of two projection based face recognition algorithms: local binary Patterns in DCT domain and singular value decomposition (SVD) characterized by its simplicity and efficiently. Standard databases ORL are used to test the experimental results which prove that proposed system achieves more accurate face recognition as compared to individual method.

Chemical and mechanical properties of plasma-assisted nitrided (PAN), TiN cathodic arc coated, and PAN with TiN coated samples were thoroughly evaluated on tool steel samples of 1.2379. The evaluation involved SEM, nano-indentation, profilometer, micro scratch, and corrosion tests. The results revealed that PAN treatment alters the roughness of the surface, while it has minimal impact on the coefficient of friction. However, it increases the substrate's hardness, making it twice as hard and three times more resilient against scratch tests, along with improved corrosion resistance. TiN-coated samples are four times harder than untreated ones, but they exhibit a higher elastic modulus (E), leading to a lower H/E index. The most promising results were obtained with PAN+TiN treatment, combining high hardness (H) with lower E, resulting in a high H/E index, a crucial criterion for wear resistance. These samples also demonstrated superior scratch hardness and corrosion resistance, despite being thinner and rougher.

Aims: Adolescence is a critical period because the brain is involved in the process of maturation that entails cognitive functions. On the way of maturation, an individual’s inhibitory control undergoes many changes and becomes vulnerable to different thrill-seeking like smoking, drinking, and so on. Smoking is highly prevalent among teenagers that are trying to take control of their behaviors in order to join society. They experience antisocial behavior too which is a trait that can lead adolescents to addiction. This trait is an inevitable part of psychopathy. Inhibitory deficits and psychopathy have been widely reported in addiction studies. The current study tried to investigate the relationship between psychopathic traits and behavioral inhibition between male smokers and non-smoker teenage students.Materials & Methods: Statistical sample of this research is 62 teenage students aged 17 years that are divided into smoker and non-smoker groups. The participants have been chosen through random sampling from the population of 10 high schools. The data have been gathered in Kordkoy and Gorgan in Golestan province. Behavioral bias has been measured by Go/NoGo task and psychopathic traits through youth psychopathic traits inventory. Also, the short form of Wechsler Adult Intelligence Scale test has been executed and used as a control variable.Findings: A meaningful difference has been found between the performance of smoker and non-smoker groups in Go/No Go task and psychopathic traits that are smokers performed weaker in comparison with non-smokers and psychopathic traits of smokers were meaningfully higher than non-smokers. On the other hand, there was no significant difference between these two groups in their Wechsler Adult Intelligence Scale scores.Conclusion: The results have shown that smokers have higher psychopathic traits and lower behavioral inhibition when compared with their non-smoker peers. According to the results of current research, smoking can decline the cognitive functions.

Background: The important periodontal disease pathogen Porphyromonas gingivalis produces large biofilms that increase its pathogenicity. Finding natural antimicrobial agents is crucial because of the rise in antibiotic resistance. Objective: The purpose of this study was to determine if plant extracts such as Symphytum officinale (S) and Panax ginseng (G) were effective against P. gingivalis separately and in combination with a common antibiotic Metronidazole (F). Materials and Procedures: Six different dilutions were produced the plant extracts and antibiotic separately and in combination with G and F and S and F using two-fold serial dilution technique. To evaluate the effects of these substances biofilm inhibition experiments were conducted. Plaque samples were collected from periodontitis patients to isolate P. gingivalis and standard strain of P. gingivalis (ATCC 33277) were bought. Additionally, Acylated Homoserine Lactones (AHLs) detection was carried out to look for any activity that would interfere with quorum sensing. GraphPad prism was used for statistical analysis with p value &lt; 0.05. Results: The combinations of Symphytum Officinale and Metronidazole (S+F) showed the maximum effectiveness in biofilm inhibition (98.7%), which was better than G+F (98.2%) with substantial variations in biofilm inhibition levels in different treatment regimes. Notably, the isolate from the patient was more active than the standard strain. Additionally, the plant extracts and their combinations at particular dilutions had notable inhibitory effects on the generation of AHL (p &lt;0.05). Conclusion: The study highlights the possibility of Symphytum Officinale and Panax Ginseng as effective treatments for P. gingivalis biofilm and AHLs, both on their own and in combination with Metronidazole. These organic substances may open the door to cutting-edge methods of treating periodontal disorders.

The Myc gene, widely studied in numerous cancer types, serves as a pivotal regulator of crucial cellular processes implicated in tumorigenesis, such as cell growth, proliferation, invasion, metastasis, and therapy resistance. LncRNAs have been identified as relevant partners of Myc. LncRNAs modulate chromatin structure and function, transcription, splicing, stability, and translation of mRNAs, thereby emerging as pivotal regulators in cell differentiation, metabolism, signaling. An intricate crosstalk exists between Myc and lncRNAs in a wide range of cancers, wherein they can physically and functionally interact through direct and indirect mechanisms. Some lncRNAs can regulate Myc activity at post-transcriptional level, affecting its stability, translation, or interactions with other proteins, thus acting as oncogenes, while others act as tumor suppressors. On the other hand, Myc can target numerous lncRNA genes and modulate their expression, affecting the expression of downstream targets involved in tumorigenesis. Given the significant role of the Myc-lncRNA network in various cancer types, exploring therapeutic strategies targeting these crucial cellular regulators is of utmost importance. This review article focuses on breast cancer, analyzing those lncRNAs influencing Myc as well as the Myc-regulated lncRNAs.

One of the major problems caused by repeated subcutaneous insulin injections in diabetic patients is insulin amyloidosis. Understanding the molecular mechanism of amyloid fibril formation of insulin and finding effective compounds to its inhibit or eliminate is very important and extensive research has been done on it. In this study, the anti-amyloidogenic and destabilizing effects of the pyrogallol, as a phenolic compound, on human insulin protein were investigated by CR absorbance, ThT and ANS fluorescence, FTIR spectroscopy and atomic force microscopy. According to the obtained results, the formation of amyloid fibrils at pH 2.0 and 50 °C was confirmed by CR, ThT, ANS, FTIR assays. Microscopic images also showed the twisted and long structures of amyloid fibrils. Simultaneous incubation of the protein with pyrogallol at different concentrations reduced the intensities of CR, ThT and ANS in a dose-dependent manner and no trace of fibrillar structures was observed in the microscopic images. FTIR spectroscopy also showed that the position of amide I band in the spectrum of samples containing pyrogallol was shifted. Based on the findings in this study, it can be concluded that pyrogallol can be effective in preventing and suppressing human insulin amyloid fibrils.

Systemic capillary leak syndrome (SCLS) is an uncommon, potentially life-threatening disorder defined as recurrent attacks of pseudo-shock. This syndrome occurs due to the disruption of endothelial cells, which leads to increased vascular permeability, causing intravascular fluid to leak into the extravascular space and albumin to be retained in the interstitial space. SCLS can lead to hypovolemia, peripheral hypoperfusion, and acute renal insufficiency. The syndrome is presented with fever, generalized edema, pleural effusions, dyspnea, hypovolemia, hemoconcentration, prerenal azotemia, shock, and syncope. After ruling out other causes of hypovolemic shock, the diagnosis of SCLS can be considered on the presence of the classical triad of hypotension, hemoconcentration, and hypoalbuminemia. Eliminating the precipitating factors is the cornerstone of SCLS management. It is advisable to be very cautious and weigh the risks and benefits of vaccination of people with a history of this condition. This review will discuss and compare different aspects of SLCS after SARS-CoV-2 infection and COVID-19 vaccination.

CO2 injection into geological formations is considered one way of mitigating the increasing levels of carbon dioxide concentrations in the atmosphere and its effect on and global warming. In regard to sequestering carbon underground, different countries have conducted projects at commercial scale or pilot scale and some have plans to develop potential formations for carbon dioxide storage. In this study, pure CO2 injection is examined on a model with the properties of bunter sandstone and then sensitivity analyses were conducted for some of the important parameters. The results of this study show that the extent to which CO2 has been convected in the porous media in the reservoir plays a vital role in improving the CO2 dissolution in brine and safety of its long term storage. We conclude that heterogeneity plays a crucial role on the saturation distribution and can increase or decrease the amount of dissolved CO2 in water. Furthermore, the value of absolute permeability controls the effect of the Kv/Kh ratio on the CO2 dissolution in brine. In other words, as the value of vertical and horizontal permeability decreases (i.e. tight reservoirs) the impact of Kv/Kh ratio on the dissolved CO2 in brine becomes more prominent. Additionally, reservoir engineering parameters, such as well location, injection rate and scenarios, also have a high impact on the amount of dissolved CO2.

This work attempted to fabricate superhydrophobic fabric via simple immersion technique. Textile fabrics were coated with silica nanoparticles prepared from tetraethoxysilane (TEOS) to obtain sufficient roughness with hydrophobic surface chemistry. Then the coated fabrics were treated with polydimethylsiloxane (PDMS) and aminopropyltriethoxysilane (APTES) to reduce the surface energy. The effects of PDMS concentration on the surface morphology and superhydrophobicity of as-prepared fabric were investigated. The morphology and the composition of superhydrophobic fabric was characterized by scanning electron microscopy (SEM), energy dispersive X-ray (EDS) and Fourier transform infrared (FTIR) spectroscopy. The results revealed the formation of spherical silica nanoparticles with average particle size of 250 nm throughout the fabric surface. The possible interactions between silica nanoparticles and APTES, as well as the fabrics were elucidated. Investigating the hydrophobicity of fabrics via water contact angle (WCA) measurement showed that the treated fabric exhibits excellent water repellency with a water contact angle as high as 151° and a very low water sliding angle. It also found that the treated fabric maintained most of its hydrophobicity against repeated washing. The comfort properties of the obtained superhydrophobic fabrics in term of air permeability and bending length did not reveal any significant changes.

Background and Aim: Cancer is a disease characterized by uncontrolled cell growth and invasion of tissues. It seems that personality differences and psychological factors are important factors that lead to different reactions to cancer. Therefore, the main purpose of the present study was to investigate the relationship between type D, stress level of life events, personality traits, and anxiety sensitivity in people with breast cancer attending to Tehran Bu-ali Hospital. Methods: The study was a correlational study in which 100 cancer patients referred to Bu-ali Hospital in Tehran, selected by the available sampling method from April to June 2018. The tools used included the Denollet DS-14 Type D Questionnaire, the Paykel Life events Questionnaire, the Eysenck Personality Questionnaire, the ASI Anxiety Scale, Floyd et al., Data analysis in this study is taken place by using SPSS software, two descriptive levels (percentage, frequency, etc.) and regression. Results: The study results showed that there is a relationship between type D personality with stress of life events, neurosis, extraversion, and psychopath dimensions of personality and anxiety sensitivity in breast cancer patients. Conclusion: Psychological factors play a role in the incidence and exacerbation of breast cancer, and ultimately patients with personality type D and personality traits such as psychosis and high anxiety sensitivity and more stress of life events show more symptoms.

The study explores antibacterial, antiinflammatory and cytoprotective capacity of Pelargonium sidoides DC root extract (PSRE) and proanthocyanidin fraction from PSRE (PACN) under conditions characteristic for periodontal disease. Following previous finding that PACN exerts stronger suppression of Porphyromonas gingivalis compared to the effect on commensal Streptococcus salivarius, the current work continues antibacterial investigation on Staphylococcus aureus, Staphylococcus epidermidis, Aggregatibacter actinomycetemcomitans and Escherichia coli. PSRE and PACN are also studied for their ability to prevent gingival fibroblast cell death in the presence of bacteria or bacterial lipopolysaccharide (LPS), to block LPS- or LPS+IFNγ-induced release of inflammatory mediators, gene expression and surface antigen presentation. Both PSRE and PACN were more efficient in suppressing Staphylococcus and Aggregatibacter compared to Escherichia, prevented A. actinomycetemcomitans- and LPS induced death of fibroblasts, decreased LPS-induced release of interleukin 8 and prostaglandin E2 from fibroblasts and IL-6 from leukocytes, blocked expression of IL-1β, iNOS, and surface presentation of CD80 and CD86 in LPS+IFNγ-treated macrophages, and IL-1β and COX-2 expression in LPS-treated leukocytes. None of the investigated substances affected either the level of secretion or expression of TNFα. In conclusion, PSRE, and especially PACN, possess strong antibacterial, antiinflammatory and gingival tissue protecting properties under periodontitis mimicking conditions and are suggestable candidates for treatment of the disease.

A novel educational platform called Shared Modeling and Simulation Environment (SMSE) was initiated in the ERASMUS+ “CybPhys” project. It integrates the Jupyter platform, including Ju-pyter Notebooks, for e-learning in the STEM field. A novel platform enhances e-learning by combining Moodle with Jupyter's capabilities to create virtual labs. A survey was conducted in the spring of 2023 among bachelor and master students of Chernihiv National Polytechnic Uni-versity aimed to gather feedback from students using SMSE in their e-learning process. Two student groups were involved: one of them consisted of students using SMSE in both the autumn and spring semesters and another represented the students starting with SMSE in the spring se-mester. The survey based on the adjusted Technology Acceptance Model (TAM) was conducted to understand the acceptance of this e-learning approach. A comprehensive analysis of students’ answers based on the TAM approach revealed the inside of the process of transformation of stu-dents’ perceptions during the acquisition of the SMSE platform. Our research demonstrates that SMSE effectively merges Moodle's online learning capabilities with Jupyter notebooks, provid-ing a flexible and interactive learning experience for both in-class and remote students. It pro-vides a web-based, multifunctional e-learning environment that combines a variety of tools and technologies, giving students the possibility to be involved in all sorts of teaching activities, such as lectures, exercises, simulations, etc., through the use of one single online environment.

Manufacturing environments, characterized by rapid, unpredictable changes, uncertainties, risks, and uncontrollable fluctuations, pose significant challenges to minimizing disruptions in processes. This study introduces an innovative approach that prioritizes curbing risk propagation among processes to enhance robustness. It emphasizes the integration of engineering management principles and modular design within manufacturing. Adopting a system engineering perspective, all manufacturing process activities are viewed as interrelated components within a unified system. By employing Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, manufacturing process architecture is modularized, yielding heightened robustness. The proposed mathematical model equips engineering and manufacturing managers with a potent tool for designing robust processes while adeptly managing system complexity. The study's outcomes underscore a substantial enhancement in modularization, leading to elevated overall robustness in manufacturing processes. To validate the methodology, the architectural design of manufacturing processes is examined in a real-case scenario, specifically the Barez Industrial Group in Iran. This verification substantiates the 'manufacturing processes' of the case, presenting an optimally modularized architecture. The results affirm the proposed approach's efficacy, demonstrating improved modularization that contributes to bolstered robustness in manufacturing processes.

Anhydrobiosis is the state of life when cells get into waterless conditions and gradually cease their metabolism. In this study, we determined the sequence of events in Saccharomyces cerevisiae energy metabolism during processes of dehydration and rehydration. The intensities of respiration and acidification of the medium, the amounts of Phenyldicarbaundecaborane (PCB-) bound to yeast membranes, and the capabilities of cells to accumulate K+ were assayed using electrochemical monitoring system, and intracellular content of ATP was measured using bioluminescence assay. Mesophilic, semi-resistant to desiccation S. cerevisiae strain 14 and thermotolerant, very resistant to desiccation S. cerevisiae strain 77 cells were compared. After 22 h of drying it was possible to restore the respiration activity of very resistant to desiccation strain 77 cells, especially when glucose was available. PCB- binding also indicated considerably higher metabolic activity of dehydrated S. cerevisiae strain 77 cells. Electrochemical K+ content and medium acidification assays indicated that permeabilization of the plasma membrane in cells of both strains started almost simultaneously, after 8-10 h of desiccation, but semi-resistant strain 14 cells were longer keeping K+ gradient and stronger acidifying the medium. For both cells, the fast rehydration in water was less efficient compared to reactivation in the growth medium, indicating the need for nutrients for the recovery. Higher viability of strain 77 cells after rehydration could be due to the higher stability of their mitochondria.

Aortic rupture is known as one of the potential causes of sudden cardiac death in athletes. Nevertheless, adaptation strategies for aortic root dilation in athletes vary. The purpose of this study was to investigate aortic root adaptation to physical workload and to determine if aortic root’s and left ventricle sizes are contingent upon the physical workload. Echocardiography was applied to 151 subjects to measure the aortic root at aortic valve annulus (AA) and at sinus of Valsalva (VS). 122 were athletes (41 females and 81 males) and 29 were non-athletes (14 females and 15 males). Of the 41 female athletes, 32 were endurance athletes, and 9 strength athletes. From 81 male athletes, 56 were endurance athletes, and 25 were strength athletes. AA and VS mean values for the body surface area were presented as rAA and rVS. Left ventricle (LV) meaures incuded LV end-diastolic diameter (LVEDD), interventricular septum thickness in diastole (IVSTd), LV posterior wall thickness in diastole (LVPWTd), LV mass (LVM), LV mass index, LV end-diastolic diameter index (LVEDDI). Results indicated that VS was higher in female athletes (28.9±2.36mm) than in non-athletes (27.19±2.87mm, p=0.03). On the other hand, rAA was higher in strength athletes (12.19±1.48mm/m2) than in endurance athletes (11.12±0.99mm/m2, p=0.04). Additionally, rVS and rAA were higher in female strength athletes (17.19±1.78mm/m2, 12.19±1.48mm/m2) than female basketball players (15.49±1.08mm/m2, p=0.03, 10.75±1.06 mm/m2, p=0.02). Statistically significant positive moderate correlations were found between VS and LVEDD, LVM, IVSTd, LVPWTd, rVS and LVEDDI parameters in all athletes. The diameter of Valsalva sinus was greater in female athletes compared to non-athletes. The rAA mean value for body surface area was greater in female athletes practising strength sports as compared to their counterparts who were practising endurance sports. The diameter of the aortic root at sinuses positively correlated with the LV size in all athletes. Trial was registered at ClinicalTrials.gov Identifier: NCT03656861, September 3, 2018 (retrospectively registered).

Soil tillage intensity influences the distribution of nutrients, and soil’s physical and me-chanical properties, as well as gas flows. The impact of reduced tillage on these indices in spring barley cultivation is still insufficient and requires more analysis on a global scale. This study was carried out at Vytautas Magnus University, Agriculture Academy (Lithu-ania) in 2022–2023. The aim of the investigation was to determine the effect of the tillage systems on the soil temperature, moisture content, CO2 respiration and concentration in spring barley cultivation limited by the semi-humid subarctic climate. Based on a long-term tillage experiment, five tillage systems were tested: deep and shallow mold-board ploughing, deep cultivation-chiselling, shallow cultivation-chiselling, and no-tillage. Shallow ploughing technology was found to be better at conserving soil moisture and maintaining a higher temperature. Deep cultivation had a lower moisture content and lower soil temperature. Shallow cultivation fields in most cases increased CO2 emissions and CO2 concentration. The results show that in direct sowing fields, most cases had a positive effect on crop density. Direct sowing fields resulted in significantly lower grain yields of spring barley in the years studied.

Multicropping can solve the energy and GHG balance problems, but the emergence, development and productivity of such mixed crops are at risk due to uneven distribution of precipitation. For this reason, investigations were performed at the Experimental Station of Vytautas Magnus University, Lithuania. Single maize crop was compared with Crimson/red clover, Persian clover, and alfalfa intercropped maize cultivations. Results showed that under arid conditions, the intercrops biomass was about 4 times less than under humid. Humid conditions were less suitable for maize and when growing with intercrops they produced about 3-5 t ha-1 less dried biomass, and when growing sole - about 6 t ha-1 less biomass than in arid conditions. Due to the higher yield of maize biomass in arid season, better energy indicators of the crop were obtained in arid conditions than in humid. The difference between net energy was about 122-123 MJ ha-1 in all treatments, except for the maize crop with intercropped alfalfa, where the difference was 62 MJ ha-1. All tested technologies were environmentally friendly, CO2 equivalent varied between treatments from 804 to 884 kg ha-1. Uneven distribution of precipitation during vegetative season makes us think about the improvement of intercropping technologies. Sowing intercrops at the same time with maize could improve its germination but increase the problem of weed spread.

In this paper a protection scheme is provided to protect microgrid by considering the problems that are generated by addition of distributed generators to distribution networks and change these networks from passive to active. At first, changes in microgrid conditions that can affect short-circuit current is explained. Then Based on these changes, an algorithm is proposed to update relays settings. The algorithm can be used for both instantaneous and inverse time relays. In this protection scheme, central unit has no place and relays are responsible for monitoring microgrid and update their settings. In other words, this protection scheme is an adaptive and decentralized microgrid protection scheme. Instantaneous overcurrent relays are used in this paper. To avoid storing large amounts of setting data in relays memory, a method for calculating pickup current of instantaneous relay is provided. Since digital relays used, a new characteristic curve for instantaneous relay for better performance in the field of backup protection is defined. This new characteristic curve has two peakup currents: one of them for main protection and the other one for backup protection. Then coordination of instantaneous relay using the new characteristic curve is explained. At the end, this protection scheme is implemented on a microgrid.

Olive fruits at different ripening stages give rise to various table olive products and oil qualities. Therefore, developing an efficient method for recognizing and sorting olive fruits based on their ripening stages can greatly facilitate postharvest processing. This study introduces an automatic computer vision system that utilizes deep learning technology to classify the `Roghani` Iranian olive cultivar into five ripening stages using color images. The developed model employs convolutional neural networks (CNN) and transfer learning based on the Xception architecture and ImageNet weights as the base network. The model was fine-tuned by testing multiple configurations of well-known CNN layers. To minimize overfitting and enhance model generality, data augmentation techniques were employed. By considering different optimizers and two image sizes, four final candidate models were generated. These models were then compared in terms of loss and accuracy on the test dataset, classification performance (classification report and confusion matrix), and generality. All four candidates exhibited high accuracies ranging from 86.93% to 93.46% and comparable classification performance. In all models, at least one class was recognized with 100% accuracy. However, by taking into account the risk of overfitting, two models were discarded. Finally, a model with an image size of 224 × 224 and an SGD optimizer, which had a loss of 1.23 and an accuracy of 86.93%, was selected as the preferred option. The results of this study offer robust tools for automatic olive sorting systems, simplifying the differentiation of olives at various ripening levels for different post-harvest products.

An investigation of compressible flow over two-dimensional obstacles is presented in this paper. When shock waves are formed on surfaces due to compressibility and these shocks interfere with the boundary layer, undesirable effects such as friction, separation, and flow instability occur. To weaken the shock and reduce its effects, various methods have been employed in the past, including surface suction, surface blowing, and vortex generators. Using numerical solutions, the present work attempts to reduce the negative effects of the shock generated by the obstacle by creating porosity on its surface. Numerical methods such as the finite volume method and the Navier-Stokes equations as well as the Spalart-Allmaras model are used. By creating suction and blowing and increasing the cross-sectional area of the flow, porous surfaces reduce the effects of shock. Achieving around 50% porosity on the obstacle weakened the shock and reduced the Mach number after it, according to this paper's results. Also, the area under the skin friction diagram has decreased by about 38% as a result of less interference between the shock and the boundary layer and blowing caused by the porous surface.

In this paper, we demonstrate a useful interaction between the theory of clique partitions, edge clique covers of a graph, and the spectra of graphs. Using a clique partition and an edge clique cover of a graph we introduce the notion of a vertex-clique incidence matrix for a graph and produce new lower bounds for the negative eigenvalues and negative inertia of a graph. Moreover, utilizing these vertex-clique incidence matrices, we generalize several notions such as the signless Laplacian matrix, and develop bounds on the incidence energy and the signless Laplacian energy of the graph. %The tight upper bounds for the energies of a graph and its line graph are given. More generally, we also consider the set $S(G)$ of all real-valued symmetric matrices whose off-diagonal entries are nonzero precisely when the corresponding vertices of the graph are adjacent. An important parameter in this setting is $q(G)$, and is defined to be the minimum number of distinct eigenvalues over all matrices in $S(G)$. For a given graph $G$ the concept of a vertex-clique incidence matrix associated with an edge clique cover is applied to establish several classes of graphs with $q(G)=2$.

Although, promotion of urbanization culture in recent decades has made inevitable development of cities in the world, however, the development can be guided in a direction that leave, to the extent possible, minimum socioeconomic and environmental impacts. For this, it is required to first forecast auto-spreading orientation of cities and suburbs in rural areas over time and then avoid shapeless growth of cities. This paper is an attempt to develop a dynamic hybrid model based on logistic regression (LR), Markov chain (MC), and cellular automata (CA) for prediction of future urban sprawl in fast-growing cities. The model was developed using 12 widely-used urban development criteria, whose significant coefficient was determined by logistic regression, and validated by relative operating characteristic (ROC) analysis. The validated model was run in Guilan, a tourist province in northern Iran with a very high rate of urban development. For this, changes in the area of urban land use were detected over the period of 1989 to 2013 and then, future sprawl of the province was forecasted by the years 2025 and 2037. The analysis results revealed that the area of urban land use was increased by more than 1.7 % from 36012.5 ha in 1989 to 59754.8 ha in 2013, and the area of Caspian Hyrcanian forestland was reduced by 31628 ha. The results also predicted an alarming increase in the rate of urban development in the province by the years 2025 and 2037, during which urban land use is predicted to develop 0.9 % and 1.38 %, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban basements as well as around major roads and commercial areas. This development, if not controlled, will lead to the loss of 13863 ha of Hyrcanian forests and if the trend continues, 21013 ha of Hyrcanian forests and 20208 ha of Barren/open lands are expected to be destroyed by the year 2037. In general, the proposed model is an efficient tool for the support of urban planning decisions and facilitates the process of sustainable development of cities by providing decision-makers with an overview on future development of cities where the growth rate is very fast.

Worldwide the steel corrosion is one of the greatest deterioration problems for reinforced concrete structures. Comparing some literature experimental results with a complex FEM model, the present paper points out the principal aspects those characterize the static behavior of RC elements damaged by corrosion. Moreover, the non-dimensional abaci defined for some specific case studies finalized to the evaluation of the residual flexural strength of corroded elements highlight the dangerousness of the corrosion degradation if the failure of the element is governed by the steel

The importance of vertical jump in sport fields and rehabilitation is widely recognized. Furthermore, Force-Time variables of vertical jump are factors affecting jumping height. Exclusive review of each of this variables, in eccentric and concentric phases, can lead to a specific focus on them during jumping exercises. So, the aims of his study were to a) reviewing the relationship between force-time curve variables of eccentric and concentric phases with jump height and b) description of this variables in Iran national youth volleyball players society. This is an observational study. 12 elite volleyball player (Male, Iran national youth volleyball players, 17±0.7 years) have participated in this study. Correlation between Force-Time variables - included peak force (PF), relative peak force (RPP), peak power (PP), average power (AP), relative peak power (RPP), and Modified Reactive Strength Index (MRSI) - in eccentric and concentric phases and ultimate jump height has been studied. Results showed that the average power (r=0.7) and relative peak force (r=0.75) of concentric phase and MRSI (r=0.83) have significant correlation with ultimate jump height (JH). Relative peak power and average power of concentric phase can massively effect Jump Height in sports like volleyball, which vertical jump is an integral part of them. Focus on both of these factors, which has been studied in this research, in training programs, can improve athlete jump performance significantly.

Compton cameras detect scattered gamma rays and estimate the distribution of gamma-ray sources. Nonetheless, crafting a camera tailored to a specific application presents formidable challenges, often necessitating the implementation of diverse image reconstruction techniques. Delving into the factors influencing these cameras can pave the way for design optimization and performance enhancement. This study introduces an inventive detector design for Compton imaging systems, building upon the achievements of prior designs. The proposed system contains eight scatterer detectors and a semiconductor absorber detector, spaced at 1 mm and 30 mm intervals, respectively. The source-to-first-scatterer-detector distance is 5 mm, with scatterer and absorber detector plates measuring 70× 70× 2.125 mm³ and 70× 70× 10 mm³, respectively. Geant4 simulation toolkit models the Compton imaging system, and an analytical method reconstructs Compton camera images. Unlike more straightforward techniques, the analytical method directly reconstructs Compton camera images by solving the equation relating to the reflected image data. This approach is implemented in the C++ programming language. The study's findings reveal that the analytical method discerns optimal conditions and parameters that significantly influence efficiency, yielding a full width at half maximum (FWHM) of 3.7 mm with an angular uncertainty of approximately 2.7 degrees at an energy level of 0.662 MeV. Compared to another experimental design employing the analytical image reconstruction approach, the FWHM value decreased by 0.7 mm. This study presents an innovative detector design and an analytical reconstruction method for Compton imaging systems, showcasing improved efficiency and accuracy.

The main parameters for calculation of relative humidity are the wet-bulb depression and dry bulb temperature. In this work, easy-to-used predictive tools based on statistical learning concepts, i.e., the Adaptive Network-Based Fuzzy Inference System (ANFIS) and Least Square Support Vector Machine (LSSVM) are developed for calculating relative humidity in terms of wet bulb depression and dry bulb temperature. To evaluate the aforementioned models, some statistical analyses have been done between the actual and estimated data points. Results obtained from the present models showed their capabilities to calculate relative humidity for divers values of dry bulb temperatures and also wet-bulb depression. The obtained values of MSE and MRE were 0.132 and 0.931, 0.193 and 1.291 for the LSSVM and ANFIS approaches respectively. These developed tools are user-friend and can be of massive value for scientists especially, those dealing with air conditioning and wet cooling towers systems to have a noble check of the relative humidity in terms of wet bulb depression and dry bulb temperatures.

In large infrastructures such as dams, which have a relatively high economic value, ensuring the proper operation of the associated hydraulic facilities in different operating conditions is of utmost importance. To ensure the correct and successful operation of the dam's hydraulic equipment and prevent possible damages, including gates and downstream tunnel, to build laboratory models and perform some tests are essential (the advancement of the smart sensors based on artificial intelligence is essential). One of the causes of damage to dam bottom outlets is cavitation in downstream and between the gates, which can impact on dam facilities, and air aeration can be a solution to improve it. In the present study, six dams in different provinces in Iran has been chosen to evaluate the air entrainment in the downstream tunnel experimentally. Three artificial neural networks (ANN) based machine learning (ML) algorithms are used to model and predict the air aeration in the bottom outlet. The proposed models are trained with genetic algorithms (GA), particle swarm optimization (PSO), i.e., ANN-GA, ANN-PSO, and ANFIS-PSO. Two hydrodynamic variables, namely volume rate and opening percentage of the gate, are used as inputs into all bottom outlet models. The results showed that the most optimal model is ANFIS-PSO to predict the dependent value compared with ANN-GA and ANN-PSO. The importance of the volume rate and opening percentage of the dams' gate parameters is more effective for suitable air aeration.

In this paper, an offshore airborne wind energy (AWE) farm consisting of three non-reversing pumping mode AWE systems is modelled and simulated. The AWE systems employ permanent magnet synchronous generators (PMSG). A direct interconnection technique is developed and implemented for AWE systems. This method is a new approach invented for interconnecting offshore wind turbines with the least number of required offshore-based power electronic converters. The direct interconnection technique can be beneficial in improving the economy and reliability of marine airborne wind energy systems. The performance and interactions of the directly interconnected generators inside the energy farm internal power grid are investigated. The results of the study conducted in this paper, show the directly interconnected AWE systems can exhibit a poor load balance and significant reactive power exchange which must be addressed. Power control strategies for controlling the active and reactive power of the AWE farm are designed, implemented, and promising results are discussed in this paper.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.

Coarse-grained molecular dynamics simulations are employed to investigate the spatiotemporal evolution of vesicles (polymersomes) by the self-assembly of randomly distributed amphiphilic BAB triblock copolymers with hydrophilic A and hydrophobic B blocks in an aqueous solution. The vesiculation pathway consists of several intermediate structures, such as an interconnected network of copolymer aggregates, a cage of cylindrical micelles and a lamellar cage. The cage-to-vesicle transition occurs at a constant aggregation number and practically eliminates the hydrophobic interfacial area between the B block and solvent. Molecular reorganization under-lying the sequence of morphology transitions from a cage-like aggregate to a vesicle is nearly isentropic. The end-to-end distances of isolated copolymer chains in solution and those within a vesicular assembly follow log normal probability distributions. This is attributed to the pre-ponderance of folded chain configurations in which the two hydrophobic end groups of a given chain stay close to each other. However, the probability distribution of end-to-end distances is broader for chains within the vesicle as compared to that of a single chain. This is due to the swelling of the folded configurations within the hydrophobic bilayer. Increasing the hydropho-bicity of the B block reduces the vesiculation time without qualitatively altering the self-assembly pathway.

In this paper, we compile the fractional power series method and the Laplace transform to design a new algorithm for solving the fractional Volterra integro-differential equation. For that, we assume the Laplace power series (LPS) solution in terms of power q=1m,m∈Z+, where the fractional derivative of order α=qγ for which γ∈Z+. This assumption will help us to write the integral, the kernel, and the nonhomogeneous terms as a LPS with the same power. The recurrence relations for finding the series coefficients can be constructed using this form. To demonstrate the algorithm's accuracy, the residual error is defined and calculated for several values of the fractional derivative. Two strongly nonlinear examples are discussed to provide the efficiency of the algorithm. The algorithm gains powerful results for this kind of problem. Under Caputo meaning the obtained results are illustrated numerically, and graphically. Geometrically, the behavior of the solution declares that the changing of the fractional derivative parameter values' in their domain alters the style of the attained solution in a symmetrical meaning and fully coinciding to the ordinary derivative value'. From these simulations, the results report that the recommended novel algorithm is a straightforward, accurate, and superb tool to generate analytic-approximate solutions for Integral, and integro-differental equations of fractional order.

This study introduces a novel nanocomposite coating composed of PANI/CeO2 nanocomposite films, aimed at addressing corrosion protection needs. Analysis through FTIR spectra and XRD patterns confirms the successful formation of the nanocomposite films. Notably, the PANI/CeO2 nanocomposite films exhibit a hydrophilic nature. The bandgap energy of the PANI composite film measures at 3.74 eV, while the introduction of CeO2 NPs into the PANI matrix reduces the bandgap energy to 3.67 eV. Furthermore, the electrical conductivity of the PANI composite film is observed to be 0.40 S.cm-1, with the incorporation of CeO2 NPs leading to an increase in electrical conductivity to 1.07 S.cm-1. To evaluate its efficacy, electrochemical measurements were conducted to assess the corrosion protection performance. Results indicate a high protection efficiency of 92.25% for the PANI/CeO2 nanocomposite film.

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN) appeared to be dependent on the seasonal growth. Phragmites australis the most sensitive species in order the removal of nutrient from wastewater.

The speed-density or flow-density relationship is a fundamental aspect of traffic flow theory. Single-regime models often face challenges in consistently fitting empirical data under diverse traffic conditions. This paper addresses the inaccuracies of single-regime models, attributing them not only to their functional forms but also to data dispersion and sample selection bias. To mitigate these issues, the data is segmented into day and night periods, leading to the creation of separate models for each. Calibration results, conducted on data from two freeways, Tehran-Karaj and Tehran-Qom, reveal distinct challenges, with the former exhibiting high dispersion and the latter showing low dispersion. Surprisingly, single-regime models demonstrate notable effectiveness when applied to distinct day and night data. Further analysis, categorizing data into day and night, results in reduced errors (20-60% improvement in R-Square), emphasizing the potential for enhanced accuracy by considering distinct regimes. Overall, the study underscores the significance of regime-specific considerations for accurate traffic flow modeling. Upon thorough evaluation, the study highlights the superiority of the neural network Multi-layer Perceptron (MLP) over traditional models. The research discusses the implications of incorporating day and night parameters into the models, emphasizing their potential for accuracy enhancement.

The current study focused on reviewing the rapid growing of using magnetic water in different fields of science and measure the influence of several intensities of magnetization on the chemical and electrical properties of tap water treated by reverse osmosis. The work includes circulation of water for 24 h. in magnetic fields of intensity 500, 1000, 1500, and 2000 G. The magnetization of water causes increasing some positive and negative ions in water such as (Mg, K, Na, Cl¯, Alkaline and SiO₂) and decreasing some positive and negative ions (Ca and SO₃). In the near future, the application of concepts of sustainability development in civil engineering have the to produce structures in harmony with these concepts through using of high-performance materials with less impacts on the environmental and have low cost. The main application of using magnetic water is improvement the geotechnical properties of soil through precipitation of calcite which increases the bond between soil particles and then strength of soil.