Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press

The accuracy of a predictive system is critical for predictive maintenance and to support the right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable to describe the stochastic nature of the data. Neural networks, such as long short-term memory (LSTM) and the gated recurrent unit (GRU), are good predictors for univariate and multivariate data. The present paper describes a case study where the performances of long short-term memory and gated recurrent units are compared, based on different hyperparameters. In general, gated recurrent units exhibit better performance, based on a case study on pulp paper presses. The final result demonstrates that, to maximize the equipment availability, gated recurrent units, as demonstrated in the paper, are the best options.
Natural Phytochemicals, Luteolin and Isoginkgetin, Inhibit 3C Protease and Infection of FMDV, In Silico and In Vitro

Foot-and-mouth-disease virus (FMDV) is a picornavirus that causes a highly contagious disease of cloven-hoofed animals resulting in economic losses worldwide. The 3C protease (3Cpro) is the main protease essential in the picornavirus life cycle, which is an attractive antiviral target. Here, we used computer-aided virtual screening to filter potential anti-FMDV agents from the natural phytochemical compound libraries. The top 23 filtered compounds were examined for anti-FMDV activities by a cell-based assay, two of which possessed antiviral effects. In the viral and post-viral entry experiments, luteolin and isoginkgetin could significantly block FMDV growth with low 50% effective concentrations (EC50). Moreover, these flavonoids could reduce the viral load as determined by RT-qPCR. However, their prophylactic activities were less effective. Both the cell-based and the fluorescence resonance energy transfer (FRET)-based protease assays confirmed that isoginkgetin was a potent FMDV 3Cpro inhibitor with a 50% inhibition concentration (IC50) of 39.03 ± 0.05 and 65.3 ± 1.7 μM, respectively, whereas luteolin was less effective. Analyses of the protein–ligand interactions revealed that both compounds fit in the substrate-binding pocket and reacted to the key enzymatic residues of the 3Cpro. Our findings suggested that luteolin and isoginkgetin are promising antiviral agents for FMDV and other picornaviruses.
A Comprehensive Review on Smart Grids: Challenges and Opportunities

Recently, the operation of distribution systems does not depend on the state or utility based on centralized procedures, but rather the decentralization of the decisions of the distribution companies whose objectives are the efficiency of interconnectivity. Therefore, distribution companies are exposed to greater risks, and due to this, the need to make decisions based on increasingly reliable models has grown up considerably. Therefore, we present a survey of key aspects, technologies, protocols, and case studies of the current and future trend of Smart Grids. This work proposes a taxonomy of a large number of technologies in Smart Grids and their applications in scenarios of Smart Networks, Neural Networks, Blockchain, Industrial Internet of Things, or Software-Defined Networks. Therefore, this work summarizes the main features of 94 research articles ranging the last four years. We classify these survey, according Smart Grid Network Topologies, because it can group as the main axis the sensors applied to Smart Grids, as it shows us the interconnection forms generalization of the Smart Networks with respect to the sensors found in a home or industry.
Blending agile methodologies to support automotive SPICE compliance

Currently, agile methodologies are widely used as a light‐weight development process model based on short development cycles, which can satisfy frequent change requests from customers and stakeholders, and reach an efficient product delivery. On the other hand, most suppliers in the automotive industry are currently facing a challenge to comply to automotive SPICE (ASPICE) standard, which is a domain‐specific model of ISO/IEC 15504. Moreover, original equipment manufacturers (OEMs) have increasingly requested ASPICE compliance from their suppliers to accurately assess their process quality capability. This paper analyzes to what extent the ASPICE process areas were covered by agile and aims to propose a model based on integrating agile methodologies, as well as customize some agile practices so that it can fit in the Automotive SPICE process model and support automotive suppliers to achieve the required ASPICE rating. MAN.03, which is the process area for project management, was selected from the process reference model (PRM). Then, each base practice (BP) was mapped to the suitable agile methodology. Moreover, MAN.03 consists of 10 BPs, and each BP rating was measured to be N, P, L, or F. For Level 1, we applied Kanban on BP.4 and Scrum on the remaining BPs. For Level 2, we applied Scrum on all generic practices. We presented our results after deploying Kanban, and a restructured version of Scrum, which makes it in compliance with the automotive industry. The approach taken in this study could be applied in other process areas in the PRM afterwards.
Data Fusion For Intelligent Decision Making in Agriculture Resource Management

The Agricultural Resource Management System (ARMS) is an information system that geographically permits farmers to classify their field and farm animals’ for making services in terms of setting up resources, increasing their ecological Farm Plan, food traceability, and animal physical condition. It is a tough task of planning the agricultural resources and making use of them effectively such as farm construction, tools utilization, fertilizer processing, management amenities, and use facilities which adds to the production, training, and marketing of crops. Apart from the fundamental property sunlight, soil, and water, the seeds and animal breeds, and human Endeavour also should be given more priority as agricultural resources. On the other hand, Agriculture Management System is the administration website to assist farmers in achieving high productivity and profitability to furnish efficient agricultural procedures through online selling of products. In order to attain the benefits and profits through agricultural resources, the Data fusion technique is used to integrate data and knowledge impending from several sources to acquire exact outcomes remotely. The purpose of this paper is to construct an intelligent decision-making Data fusion algorithm for proficient agriculture resource management. In addition, the analysis of challenges of the resource management and solutions also are rendered by taking agriculture land’s natural resources like water, air, and temperature level in winter and autumn seasons.
Preoperative Differentiation of Pancreatic Cystic Neoplasm Subtypes on CT-Based Radiomics: SCN, MCN And IPMN

Background:The serous cystic neoplasm (SCN), mucinous cystic neoplasm (MCN), intraductal papillary mucinous neoplasm (IPMN) comprise the large proportion of pancreatic cystic neoplasm (PCN). The appropriate clinical management of MCN and IPMN isextremely essential to improve the 5-years survival rate for the early detection of pancreatic cancer. However, the differential diagnosis of patients with PCN before the treatment is still a tough challenge for all surgeons. Therefore, a reliable diagnosis tool is urgently required to be established for the improvement of precision diagnostics.Method:Between February 2016 and December 2020, 143 consecutive patients with PCN who were confirmed by postoperative pathology were retrospectively included in the study cohort, randomized into development and test cohort at the ratio of 7:3. The predictors of preoperative clinical-radiologic paraments were evaluated by the use of univariate and multivariable logistic regression analysis. A total of 1218 radiomics features were computationally extracted from the enhanced computed tomography (CT) of tumor region and a radiomics signature was established by the random forest algorithm. In the development cohort, the multi-class and binary-class radiomics models integrating preoperative variables and radiomics features were constructed to distinguish between the three types of PCN. The independent internal test cohort was applied to validate the classification models.Result:All preoperative prediction models were built by integrating the radiomics signature with thirteen diagnosis-related radiomics features and three important clinical-radiologic parameters of age, sex and tumor diameter. The multi-class prediction model presented an overall accuracy of 0.804 in the development cohort and 0.707 in the test cohort. The binary-class prediction models displayed the higher overall accuracy of 0.853, 0.866, 0.928 in the development dataset and 0.750, 0.839, 0.889 in the test dataset. In the test cohort, the binary-class radiomics models showed better predictive performances (AUC = 0.914, 0.863 ,0.926) than the multi-class radiomics model (AUC = 0.850), with a large net benefit in the decisive curve analysis. The radiomics-based nomogram provided the correct predicted probability for the diagnosis of PCN.Conclusion: The proposed radiomics models with clinical-radiologic parameters and radiomics features helped predict the accurate diagnosis among SCN, MCN, and IPMN to advance personalized medicine.
Mitochondrial Quality Control in Cardiac-Conditioning Strategies against Ischemia-Reperfusion Injury

Mitochondria are the central target of ischemic preconditioning and postconditioning cardioprotective strategies, which consist of either the application of brief intermittent ischemia/reperfusion (I/R) cycles or the administration of pharmacological agents. Such strategies reduce cardiac I/R injury by activating protective signaling pathways that prevent the exacerbated production of reactive oxygen/nitrogen species, inhibit opening of mitochondrial permeability transition pore and reduce apoptosis, maintaining normal mitochondrial function. Cardioprotection also involves the activation of mitochondrial quality control (MQC) processes, which replace defective mitochondria or eliminate mitochondrial debris, preserving the structure and function of the network of these organelles, and consequently ensuring homeostasis and survival of cardiomyocytes. Such processes include mitochondrial biogenesis, fission, fusion, mitophagy and mitochondrial-controlled cell death. This review updates recent advances in MQC mechanisms that are activated in the protection conferred by different cardiac conditioning interventions. Furthermore, the role of extracellular vesicles in mitochondrial protection and turnover of these organelles will be discussed. It is concluded that modulation of MQC mechanisms and recognition of mitochondrial targets could provide a potential and selective therapeutic approach for I/R-induced mitochondrial dysfunction.
A new data-driven robust optimization approach to multi-item newsboy problems

A newsboy problem is a typical stochastic inventory management problem and has extensive applications in the fields of operational research, management sciences and marketing sciences. One of the challenges underlying such problems is to handle the uncertainty of demands. In the existing results, it is often to assume that the demand distribution is given to facilitate solution of the problems. In this paper, a novel data-driven robust optimization model for solving multi-item newsboy problems is proposed by combining the absolute robust optimization with a data-driven uncertainty set, and the latter is leveraged to address the uncertainty of demands. For the single-item situation, a closed-form solution is obtained and influences of parameters on the optimal solutions are analyzed. Owing to complexity of the multi-item situation, a uniform smoothing function is leveraged to smooth the proposed model. Then, an algorithm, called a modified Frank-Wolfe feasible direction algorithm, is developed to solve a series of smooth subproblems. Numerical simulation demonstrates that the proposed model in this paper can reduce over-conservation of robust optimization methods and is more robust than other similar well-established methods in the literature. By numerical simulation and sensitivity analysis, it is concluded that: (1) The proposed method can provide more stable optimal order policy and profits than the existing ones; (2) For a product with a higher unit purchase price, the optimal order quantities are more sensitive to its change; (3) In view of profitability, the newsboy should not to be too risk-averse.
Machine learning approach towards remote diagnostics and repair of electric vehicle charging processes

Electric vehicles have become a focus technology, promising a sustainable future mobility. Besides sufficient availability of charging infrastructure, ensuring functioning charging plays a crucial role for the success of e-mobility. This faces several challenges as related processes are more complex compared to refilling fuel of a conventional vehicle. Worldwide, different charging technologies, infrastructures and standards are being developed continuously. Realistically, not all can be considered during production. Besides, deviations from standards alongside implementation failures can cause incompatibility of vehicle and infrastructure. However, over-the-air updates enable the adaption of connected cars during their usage. Therefore, this paper firstly suggests using machine learning to allow vehicles to deal with certain unknown charging behaviour through automated parameterisation. Various system parameters on both sides can cause states which lead to an incomplete charging sequence. An intelligent agent shall learn parameters aiming for a complete charging process. Secondly, this paper proposes using data-driven digital twins of vehicles and infrastructure to perform backend simulations. The approach is demonstrated based on an exemplary use case and is evaluated via first simulation results. Future work will focus on expanding and improving the method, as well as implementing a real vehicle prototype.
Antitumor effect of radiation therapy on orthotopic PDX models of human esophageal adenocarcinoma

As a rule, esophageal adenocarcinoma develops in the lower esophagus. Life expectancy and survival rates depend on the cancer stage and the general health of the patient. Chemoradiotherapy is the most successful treatment approach to this type of cancer. The choice of optimal radiation doses for achieving the best possible therapeutic effect is still a challenge. The aim of this paper was to study effective radiation doses and assess response of human esophageal adenocarcinoma to radiation using a PDX model. The study was conducted in female Balb/c nude mice (n = 25). Fragments of the donor tumor were implanted into the cervical esophagus of immunodeficient mice. Effects of radiation on the obtained orthotopic xenografts were studied after each of 3 irradiation sessions (4, 6, 8, and 10 Gy in each of the experimental groups, respectively). First-passage xenografts reproduced the morphology of the donor tumor. The mean tumor volume differed significantly between the control group and the experimental groups exposed to 6, 8 or 10 Gy (р ≤ 0.01) after each irradiation session. Tumor growth delay was significant after exposure to the total dose of 18 Gy. The further radiation dose increase was ineffective. The reduction of tumor volume in the xenografts was correlated to the increase in the one-time radiation dose. The total dose over 18 Gy produced a detrimental effect on the hematopoietic system and blood biochemistry of the experimental mice.
Microbiological features of Pseudomonas aeruginosa in children with Cystic Fibrosis

The purpose of the study was to determine the frequency rate of Pseudomonas aeruginosa infection among children with cystic fibrosis (CF) in Dnipro region and to provide microbiological characteristics of the obtained isolates. The study was conducting from January 2019 to December 2020. Children with genetically confirmed CF diagnosis were enrolled. The main research method was bacteriological with identification of microorganisms by biochemical properties; antimicrobial susceptibility was determined by disk-diffusion method. Biological material: mucus from a deep smear from the posterior pharyngeal wall, sputum and tracheobronchial lavage waters. The Leeds criteria were used to define persons with chronic infection. The study involved 21 children. We collected 183 respiratory samples with 49 isolates of P. aeruginosa. The most important co-existing pathogens were Staphylococcus aureus, Aspergillus spp. and Candida spp. In our study, P. aeruginosa was associated with Aspergillus spp. (χ2=20.952; df=1; p˂0.001). Mucoid isolates were found in 24.49% of cases. P. aeruginosa showed variable sensitivity to different groups of antimicrobial agents, but the highest resistance was to penicillins. Mucoid P. aeruginosa was more resistant to penicillins (p˂0.001) and cephalosporins (p=0.036). Infection P. aeruginosa is frequent among children with CF; there were three children with chronic bronchopulmonary infection P. aeruginosa in Dnipro region in the end of 2020. The likelihood of Aspergillus spp. infection was higher in the case of current P. aeruginosa infection. P. aeruginosa showed variable susceptibility to different groups of antimicrobial agents, but mucoid isolates were more resistant.
GREATER ZAB RIVER BASIN PLANNING (2050)

This research was aimed to study the management of water resources within international basins, among which is the study of water authorities within the Greater Zab River Basin (GZRB) in the Kurdistan region - Iraq, where it is an international river shared by Iraq and Turkey, and aims to develop the river basin management and international cooperation between the authorities Shared water within the basin, as well as identifying factors that affect implementation, the principles, and joint projects. On the other hand, the interactions of water users competing for water inside the river basin were identified. For this reason, the Water Evaluation Analysis Planning (WEAP) model was applied to the basin to determine the optimal GZR planning system and plan optimum operating policy. The main issue with this planning is how the system meets future water needs. For this reason, optimal monthly water distribution policies have been simulated using the WEAP model using the past 33 years' debt, and the revaluated GZRB performance. An ideal simulation scheme has been developed and implemented for different scenarios such as domestic needs, irrigation water, and ecological water. This study compared to the official figures in the planning work that took place in the eighties. As a result of these comparisons, the average annual water supply was 368.1 million cubic meters in August 2032. Accordingly, it was proposed that the construction of the Bekhme Dam was completed because it understood that the water requirements could not be met in the current conditions.
Justice and equity in pragmatic clinical trials: Considerations for pain research within integrated health systems

Pragmatic clinical trials (PCTs) can overcome implementation challenges for bringing evidence‐based therapies to people living with pain and co‐occurring conditions, providing actionable information for patients, providers, health systems, and policy makers. All studies, including those conducted within health systems that have a history of advancing equitable care, should make efforts to address justice and equity.
Distribution of Sulfate-Reducing Bacteria in the Environment: Cryopreservation Techniques and Their Potential Storage Application

Sulfate-reducing bacteria (SRB) are a heterogeneous group of anaerobic microorganisms that play an important role in producing hydrogen sulfide not only in the natural environment, but also in the gastrointestinal tract and oral cavity of animals and humans. The present review was written with the inclusion of 110 references including the time period from 1951 to 2021. The following databases were evaluated: Web of Science, Scopus and Google Scholar. The articles chosen to be included in the review were written mainly in the English and Czech languages. The molecular mechanisms of microbial cryoprotection differ depending on the environment where microorganisms were initially isolated. It was observed that the viability of microorganisms after cryopreservation is dependent on a number of factors, primarily colony age, amount of inoculum, cell size or rate of cooling, and their molecular inventory. Therefore, this paper is devoted to assessing the performance and suitability of various cryopreservation methods of intestinal bacteria, including molecular mechanisms of their protection. In order to successfully complete the cryopreservation process, selecting the correct laboratory equipment and cryopreservation methodology is important. Our analysis revealed that SRB should be stored in glass vials to help mitigate the corrosive nature of hydrogen sulfide, which can affect their physiology on a molecular level. Furthermore, it is recommended that their storage be performed in distilled water or in a suspension with a low salt concentration. From a molecular biological and bioengineering perspective, this contribution emphasizes the need to consider the potential impact associated with SRB in the medical, construction, and environmental sectors.
Gluten-Free Cereal Products and Beverages: A Review of Their Health Benefits in the Last Five Years

In the past decades, food products and beverages made from gluten-free cereals were initially created for certain groups of people who experience gluten-related disorders such as wheat allergies, gluten ataxia, non-celiac gluten sensitivity, and the most well-known, celiac disease. Nowadays, the consumption of gluten-free products is not only restricted to targeted groups, but it has become a food trend for normal consumers, especially in countries such as the UK, the US, and some European countries, who believe that consuming a gluten-free product is a healthier choice compared to normal gluten-containing products. However, some research studies have disapproved of this claim because the currently available gluten-free products in the market are generally known to be lower in proteins, vitamins, and minerals and to contain higher lipids, sugar, and salt compared to their gluten-containing counterparts. The use of other gluten-free cereals such as sorghum, millet, and teff as well as pseudo cereals such as buckwheat and quinoa has gained significant interest in research in terms of their various potential health benefits. Hence, this review highlights the potential health benefits of some gluten-free cereals and pseudo cereals apart from corn and rice in the last decade. The potential health benefits of gluten-free products such as bread, pasta, crackers, and cookies and the health benefits of some other non-alcoholic beverages made from gluten-free cereals and pseudo cereals are reported.