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Background: A meta‐analysis study was conducted to determine how to predict the effect of postoperative atrial fibrillation after cardiac surgery. Hypothesis: Long‐term mortality and cardiovascular morbidity are linked to postoperative atrial fibrillation. Method: Until August 2024, a comprehensive literature study was completed, and 3486 connected studies were revised. The 38 selected studies included 241 299 cardiac surgery participants at the beginning of the study. The odds ratio (OR) and 95% confidence intervals (CIs) were used to look at the effect of atrial fibrillation after heart surgery using two‐sided methods and either a fixed or random model. Results: Individuals with cardiac surgery with postoperative atrial fibrillation had significantly higher mortality at 1 year (OR, 1.39; 95% CI, 1.12–1.72, p < 0.001), mortality at 5 years (OR, 1.61; 95% CI, 1.33–1.94, p < 0.001), mortality at 10 years (OR, 1.61; 95% CI, 1.39–1.87, p < 0.001), and overall stroke (OR, 1.61; 95% CI, 1.34–1.94, p < 0.001) compared to without postoperative atrial fibrillation. Conclusions: Individuals with cardiac surgery with postoperative atrial fibrillation had significantly higher mortality at 1 year, mortality at 5 years, mortality at 10 years, and overall stroke compared to those without postoperative atrial fibrillation. To validate this discovery, more research and caution must be implemented when interacting with its values. Summary: Postoperative atrial fibrillation is the most frequent side effect following heart surgery. Although postoperative atrial fibrillation occurs in 20%–40% of individuals following heart surgery, its effect on long‐term results following heart surgery is not fully established.Individuals with cardiac surgery with postoperative atrial fibrillation had significantly higher mortality at 1 year, mortality at 5 years, mortality at 10 years, and overall stroke compared to those without postoperative atrial fibrillation.To validate this discovery, more research and caution must be implemented when interacting with its values. [ABSTRACT FROM AUTHOR]

Organophosphates (OPs) refers to a diverse group of phosphorus-containing organic compounds; they are widely used all over the world and have had an important beneficial impact on industrial and agricultural production and control of vector transmission. Exposure to OPs of different toxicities (high, moderate, slight, and low toxicity) can all have negative consequences on the nervous system, such as nausea, vomiting, muscle tremors, and convulsions. In severe cases, it can lead to respiratory failure or even death. Notably, OPs induce neuropathy in the nervous system through specific interactions with nicotinic or muscarinic receptors, phosphorylating acetylcholinesterase, or neuropathic target esterases. This review summarizes the possible toxicological mechanisms and their interplay underlying OP pesticide poisoning, including cholinesterase inhibition and non-cholinesterase mechanisms. It outlines the possible links between OP pesticide poisoning and neurological disorders, such as dementia, neurodevelopmental diseases, and Parkinson's disease. Additionally, it explores OP interactions' potential therapeutic implications that may help mitigate the deleterious impact of OPs on the nervous system. [ABSTRACT FROM AUTHOR]

Magnetic microrobots and nanoparticles offer unique capabilities for medical applications by granting unprecedented access to intricate and delicate anatomical structures. Nevertheless, an intuitive manipulation approach remains a challenge due to their small size and limited feedback. This study presents a new method for magnetic microrobot and nanoparticle control that employs virtual reality (VR), creating an immersive and realistic view of the bodily anatomy and the microrobot within. This study compares three manipulation modes: a traditional mode using 2D displays, VR mode using a VR headset and touch controllers, and VR autonomous programmed maneuvering. It is shown that VR‐assisted modes reduce the manipulation time by improving spatial awareness. Nanoparticles in a VR environment are also manipulated. The proposed method will find applications in terms of intuitive, immersive microrobots or magnetic nanoparticle control in complex biological environments, thus in many medical procedures and for drug and cell delivery. The immersive nature of this approach enhances the ability of the user to perceive and understand complex anatomical structures, facilitating better navigation within delicate environments; both dexterity and spatial awareness are improved. Thus, it is shown how microrobots and magnetic nanoparticles can be controlled using immersive simulations to improve both visualization and manipulation. [ABSTRACT FROM AUTHOR]

The aim of current study was to prepared zinc oxide nanofertilzers by ecofriendly friendly, economically feasible, free of chemical contamination and safe for biological use. The study focused on crude extract of Withania coagulans as reducing agent for the green synthesis of ZnO nano-particles. Biosynthesized ZnO NPs were characterized by UV–Vis spectroscopy, XRD, FTIR and GC–MS analysis. However, zinc oxide as green Nano fertilizer was used to analyze responses induced by different doses of ZnO NPs [0, 25, 50,100, 200 mg/l and Zn acetate (100 mg/l)] in Triticum aestivum (wheat). The stimulatory and inhibitory effects of foliar application of ZnO NPs were studied on wheat (Triticum aestivum) with aspect of biomass accumulation, morphological attributes, biochemical parameters and anatomical modifications. Wheat plant showed significant (p < 0.01) enhancement of growth parameters upon exposure to ZnO NPs at specific concentrations. In addition, wheat plant showed significant increase in biochemical attributes, chlorophyll content, carotenoids, carbohydrate and protein contents. Antioxidant enzyme (POD, SOD, CAT) and total flavonoid content also confirmed nurturing impact on wheat plant. Increased stem, leaf and root anatomical parameters, all showed ZnO NPs mitigating capacity when applied to wheat. According to the current research, ZnO NPs application on wheat might be used to increase growth, yield, and Zn biofortification in wheat plants. [ABSTRACT FROM AUTHOR]

Tension pneumoventricle is a rare but potentially life threatening condition affecting the central nervous system. The majority of the reported cases are iatrogenic, seen after surgery for posterior fossa tumours, particularly in sitting position and pituitary and skull base tumours. Tension pneumoventricle following head injury is very rare with only seven reported cases till date. We report a case of untreated tension pneumoventricle, resulting from head injury due to road traffic accident leading to encephalomalacia of both the frontal lobes. [ABSTRACT FROM AUTHOR]

This research paper proposes an innovative Energy-Efficient Cooperative Virtual Multiple-Input Multiple-Output (MIMO) Communication Protocol to address the growing demand for energy-efficient communication in wireless networks. The protocol combines the OLEACH (Optimized Energy-Efficient Cluster Head) Protocol and a Greedy Approach to enhance energy efficiency, data rates, and interference mitigation in cooperative communication. The paper provides a comprehensive analysis, including equations and models, to demonstrate the superior performance of the proposed protocol compared to existing schemes. By integrating the OLEACH protocol with the Greedy Approach, the proposed protocol achieves optimal communication and minimizes energy consumption in wireless sensor networks. Simulation results show that the proposed protocol, called greedy-OLEACH, exhibits a high Packet Delivery Ratio (PDR) in low signal-to-noise ratio scenarios, indicating its effectiveness. Furthermore, comparisons with other clustering protocols such as LEACH, greedy-LEACH, and OLEACH reveal that greedy-OLEACH outperforms in terms of data delivery performance and remaining energy levels. This indicates efficient energy management and increased network longevity. The proposed protocol is scalable, robust, and secure, making it a promising choice for future wireless sensor network deployments. Overall, the Energy-Efficient Cooperative Virtual MIMO Communication Protocol presented in this research paper addresses the need for sustainable and green communication solutions in wireless networks, providing enhanced energy efficiency, throughput, and network performance compared to existing protocols. [ABSTRACT FROM AUTHOR]

On May 25, 2023, the Biden Administration released The U.S. National Strategy to Counter Antisemitism--America's first national strategy of this kind. In early November 2023, the White House announced the establishment of the firstever U.S. National Strategy to Counter Islamophobia. These historic commitments respond to increases in identity-based bias incidents and expression against Jews and Muslims. Antisemitic incidents, which were already rising even before the pandemic, increased by almost 400% since the start of the Israel-Hamas war. The war also triggered a sharp upturn in Islamophobic incidents in the U.S., including the shooting of three college students and the murder of a child. Although there has been fresh contestation in the U.S. over the Israeli-Palestinian conflict, this is also a particularly pressing moment for the effective implementation of the national strategies to combat antisemitism and Islamophobia here. United States makes that clear. By recognizing this, the National Strategy implicitly highlights the risks posed both by those conservatives who downplay associations with antisemites and those progressives who discount antisemitism. In centering anti-antisemitism as a national goal, the National Strategy additionally makes three key contributions: (1) by focusing on antisemitism as a broad social challenge rather than principally a problem on college campuses; (2) by its recognition of the role of social media in disseminating and amplifying antisemitism; and (3) by emphasizing the need for more empirical research aimed at the idiosyncrasies and impacts of antisemitism. To be sure, as the Article points out, some of the National Strategy's recommendations to reverse the normalization of antisemitism--its specific proposals regarding social media, its slant on "speaking out" and public condemnation, and its reliance on voluntary corporate sanctions--could benefit from further consideration, refinement, and empirical study. Nevertheless, it would be regrettable for American democracy if some under-analyzed policy recommendations, partisan politics, or concerns about disagreements over the Middle East were to cause the White House's important antiantisemitism commitment for the U.S. to be discounted as mere political theater. [ABSTRACT FROM AUTHOR]

Background: The thickness of extraocular muscles (EOMs) is important in the management of several conditions associated with EOM enlargement. This study determined the normative values of EOM diameters in adult patients seen at a teaching hospital in Nigeria. Materials and Methods: The study measured the thickness of the EOMs and the interzygomatic line (IZL) on brain images of 300 patients with non-orbital conditions (150 computed tomography [CT] and 150 magnetic resonance imaging [MRI]) archived in the radiological database of Delta State University Hospital, Nigeria, after ethical clearance. The Statistical Package for the Social Sciences (version 23) was used to obtain descriptive statistics and further compare the variables based on gender, age groups and laterality. The association between parameters was tested using Pearson's correlation test. A probability value of <5% was considered significant. Results: The thickest muscles were the medial rectus (0.42 ± 0.08 cm) and superior muscle group (0.42 ± 0.33 cm) on CT and the inferior rectus (0.40 ± 0.08 cm) on MRI. The diameters were symmetrical with sexual dimorphism in the superior muscle group on CT, medial and lateral recti on MRI and sum of all EOMs on both imaging groups (P < 0.05). The superior muscle group and the sum of all EOMs showed significant age group variations and a positive correlation with age. We noted a positive correlation between each EOM diameter and the sum of all EOMs besides the IZL (P < 0.05). Conclusion: This study offers normative data regarding EOMs that radiologists and ophthalmologists can use to diagnose disease conditions that cause EOM enlargement and further assess their response to treatment. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia is one of the leading countries and the initiator of enacting systems that respect and preserve the sanctity of personal data and criminalise its violation in any illegal manner. Royal Decree No. (19) dated 2021 was issued to establish the personal data protection system in the Kingdom of Saudi Arabia, and to begin a new era in improving the handling of personal data. With personal data and the necessary legal guarantees to protect it and to preserve the privacy of individuals, protect their rights, and enhance responsibility among individuals and other entities. This article examines the criminal law protection of individual’s personal data in cyberspace by analysing the legal framework applied in Saudi Arabia. With the analysis of the nature of individuals’ personal data and the forms of abuse against it, this article pursues effective means of protection regarding service providers, processors, and third parties. Highlighting the most prominent efforts made by the Saudi Data and Artificial Intelligence Authority (SDAIA), which is represented by the National Data Management Office, in the protection of personal data, this article identifies shortcomings by comparing the Saudi personal data protection policy with the European Union’s General Data Protection Regulation (GDPR). The findings of this article are useful for legislators in Saudi Arabia to review the new Personal Data Protection Law and to develop a proactive policy in detecting and dealing with incidents and breaches of data before they occur. [ABSTRACT FROM AUTHOR]

Importance of studying Brinkman–Navier–Stokes flow under the influence of electric and magnetic fields lies in its relevance to fundamental physical phenomena, its applications in various fields of science and engineering and its potential for technological advancements. The study of Brinkman–Navier–Stokes flow under the influence of electric and magnetic fields, along with additional factors such as Joule heating, fractional derivatives and convection, represents a multifaceted and challenging problem in fluid dynamics and applied mathematics. In this study, we explore the combined effects of Joule heating due to electric current passing through the fluid and fractional derivatives that describe nonlocal behaviors. The fractional formulation leads to a relaxation mechanism that exhibits delay and recollection of the fluid motion. The organization of direct temperature and concentration changes in MHD flow is made possible by this formalization. A finite difference/finite element method is used to calculate the flow dynamics issue and fractionally linked fields. The physical factors explain how the topic under examination is relevant. [ABSTRACT FROM AUTHOR]

Food intake is a basic need to sustain life, but foodborne pathogens and food-related xenobiotics are also the main health concerns regarding intestinal barrier homeostasis. With a predominant role in the well-being of the entire human body, intestinal barrier homeostasis is strictly regulated by epithelial and immune cells. These cells are also the main intervenients in oxidative stress and inflammation-related diseases in the intestinal tract, triggered, for example, by genetic/epigenetic factors, food additives, pesticides, drugs, pathogens, and their metabolites. Nevertheless, the human diet can also be seen as a solution for the problem, mainly via the inclusion of functional foods or nutraceuticals that may act as antioxidant/anti-inflammatory agents to prevent and mitigate acute and chronic oxidative damage and inflammation. A literature analysis of recent advances in this topic highlights the significant role of Nrf2 (nuclear factor erythroid 2-related factor 2) and NF-kB (nuclear factor kappa-light-chain-enhancer of activated B cells) pathways in these biological processes, with many natural products and phytochemicals targeting endogenous antioxidant systems and cytokine production and balance. In this review, we summarized and discussed studies using in vitro and in vivo models of the intestinal tract used to reproduce oxidative damage and inflammatory events, as well as the role of natural products as modulators of Nrf2 and NK-kB pathways. [ABSTRACT FROM AUTHOR]

Pristine depositions of beach sediments containing heavy minerals (HM) along the shorelines of Mangalore, south–west coast of India is reported in the study. Primordial radionuclide concentrations in the beach sediments collected were determined by high purity germanium (HPGe) gamma spectrometry method. The mineral identification and counting were performed using polarizing microscope. Geometric mean values (GM) [Geometric Standard Deviation (GSD)] of concentrations of 40K, 232Th and 226Ra are obtained to be 139 (2), 482 (5) and 110 (4) Bq kg−1 respectively and total heavy mineral weight percentage (TM%) of Monazite, Zircon, Ilmenite and Lithic fragments are obtained to be 0.17 (3.5), 0.51 (2.9), 5.3 (3.2) and 2.3 (2.5)% respectively. Seasonal variation studies and statistical analysis of the data are also performed to examine correlations between the origins of the radionuclides and elevated percentage of HM in these sediment depositions. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter (PM) can be considered as a factor affecting human health. The aim of this study was to investigate the concentration of PM2.5 and heavy metals and their influence on survival of A549 human lung cells in exposure to PM2.5 breathing air of Ahvaz city. In order to assess the levels of PM2.5 and heavy metals, air samples were collected from 14 sampling stations positioned across Ahvaz city during both winter and summer seasons. The concentration of heavy metals was determined using ICP OES. Next, the MTT assay [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] was employed to ascertain the survival rate of A549 cells. The findings from this research demonstrated that average PM2.5 of the study period was (149.5 μg/m3). Also, the average concentration of PM2.5 in the urban area in winter and summer was (153.3- and 106.9 μg/m3) and in the industrial area this parameter was (191.6 and 158.3 μg/m3). The average concentration of metals (ng/m3) of urban areas against industrial, Al (493 vs. 485), Fe (536 vs. 612), Cu (198 vs. 212), Ni (128 vs. 129), Cr (48.5 vs. 54), Cd (118 vs. 124), Mn (120 vs. 119), As (51 vs. 67), Hg (37 vs. 50), Zn (302 vs. 332) and Pb (266 vs. 351) were obtained. The results of the MTT assay showed that the highest percentage of cell survival according to the exposure concentration was 25 > 50 > 100 > 200. Also, the lowest percentage of survival (58.8%) was observed in the winter season and in industrial areas with a concentration of 200 μg/ml. The carcinogenic risk assessment of heavy metals indicated that except for Cr, whose carcinogenicity was 1.32E−03, other metals were in the safe range (10–4–10–6) for human health. The high concentration of PM2.5 and heavy metals can increase respiratory and cardiovascular diseases and reduce the public health level of Ahvaz citizens. [ABSTRACT FROM AUTHOR]

Because of the essential role of PLpro in the regulation of replication and dysregulation of the host immune sensing, it is considered a therapeutic target for novel drug development. To reduce the risk of immune evasion and vaccine effectiveness, small molecular therapeutics are the best complementary approach. Hence, we used a structure-based drug-designing approach to identify potential small molecular inhibitors for PLpro of SARS-CoV-2. Initial scoring and re-scoring of the best hits revealed that three compounds NPC320891 (2,2-Dihydroxyindene-1,3-Dione), NPC474594 (Isonarciclasine), and NPC474595 (7-Deoxyisonarciclasine) exhibit higher docking scores than the control GRL0617. Investigation of the binding modes revealed that alongside the essential contacts, i.e., Asp164, Glu167, Tyr264, and Gln269, these molecules also target Lys157 and Tyr268 residues in the active site. Moreover, molecular simulation demonstrated that the reported top hits also possess stable dynamics and structural packing. Furthermore, the residues' flexibility revealed that all the complexes demonstrated higher flexibility in the regions 120–140, 160–180, and 205–215. The 120–140 and 160–180 lie in the finger region of PLpro, which may open/close during the simulation to cover the active site and push the ligand inside. In addition, the total binding free energy was reported to be − 32.65 ± 0.17 kcal/mol for the GRL0617-PLpro, for the NPC320891-PLpro complex, the TBE was − 35.58 ± 0.14 kcal/mol, for the NPC474594-PLpro, the TBE was − 43.72 ± 0.22 kcal/mol, while for NPC474595-PLpro complex, the TBE was calculated to be − 41.61 ± 0.20 kcal/mol, respectively. Clustering of the protein's motion and FEL further revealed that in NPC474594 and NPC474595 complexes, the drug was seen to have moved inside the binding cavity along with the loop in the palm region harboring the catalytic triad, thus justifying the higher binding of these two molecules particularly. In conclusion, the overall results reflect favorable binding of the identified hits strongly than the control drug, thus demanding in vitro and in vivo validation for clinical purposes. [ABSTRACT FROM AUTHOR]

Cystic lesions are common lesions of the sellar region with various pathological types, including pituitary apoplexy, Rathke's cleft cyst, cystic craniopharyngioma, etc. Suggested surgical approaches are not unique when dealing with different cystic lesions. However, cystic lesions with different pathological types were hard to differentiate on MRI with the naked eye by doctors. This study aimed to distinguish different pathological types of cystic lesions in the sellar region using preoperative magnetic resonance imaging (MRI). Radiomics and deep learning approaches were used to extract features from gadolinium-enhanced MRIs of 399 patients enrolled at Peking Union Medical College Hospital over the past 15 years. Paired imaging differentiations were performed on four subtypes, including pituitary apoplexy, cystic pituitary adenoma (cysticA), Rathke's cleft cyst, and cystic craniopharyngioma. Results showed that the model achieved an average AUC value of 0.7685. The model based on a support vector machine could distinguish cystic craniopharyngioma from Rathke's cleft cyst with the highest AUC value of 0.8584. However, distinguishing cystic apoplexy from pituitary apoplexy was difficult and almost unclassifiable with any algorithms on any feature set, with the AUC value being only 0.6641. Finally, the proposed methods achieved an average Accuracy of 0.7532, which outperformed the traditional clinical knowledge-based method by about 8%. Therefore, in this study, we first fill the gap in the existing literature and provide a non-invasive method for accurately differentiating between these lesions, which could improve preoperative diagnosis accuracy and help to make surgery plans in clinical work. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) remains a global health concern. Emerging clinical trial (CT) evidence suggests that probiotic intervention may promote a healthy gut microbiome in individuals with T2DM, thereby improving management of the disease. This systematic literature review summarizes thirty-three CTs investigating the use of oral probiotics for the management of T2DM. Here, twenty-one studies (64%) demonstrated an improvement in at least one glycemic parameter, while fifteen studies (45%) showed an improvement in at least one lipid parameter. However, no article in this review was able to establish a uniform decrease in glycemic, lipid, or blood pressure profiles. The lack of consistency across the studies may be attributed to differences in probiotic composition, duration of probiotic consumption, and probiotic dose. An interesting finding of this literature review was the beneficial trend of metformin and probiotic co-administration. Here, patients with T2DM taking metformin demonstrated enhanced glycemic control via the co-administration of probiotics. Taken together, the overall positive findings reported across the studies in combination with minimal adverse effects constitute ground for further quality CTs. This review provides recommendations for future CTs that may address the shortcomings of the current studies and help to extract useful data from future investigations of the use of probiotics in T2DM management. [ABSTRACT FROM AUTHOR]

The ocean environment monitoring system is of great significance to the researchers because the ocean is the storehouse of natural resources. It is critical to comprehend and assess the ocean's environmental conditions. Several studies have been conducted over the last several decades that use sophisticated information and communication techniques to ensure the ocean ecosystem. Wireless sensor networks (WSNs) are a promising technology to monitor the ocean environment, which delivers significant benefits such as enhanced accuracy and real-time observations. The advancements in sensor technology such as micro electromechanical systems (MEMS), integrated systems, distributed processing, wireless communications, and wireless sensor applications have contributed to the development of WSNs. This paper describes the utilization of WSN and analyzes the previous and existing project works and technologies used for ocean environment monitoring through WSNs, and also includes the MEMS sensor technology used for monitoring various ocean parameters such as ocean wave monitoring, water conductivity, temperature, and depth of ocean. [ABSTRACT FROM AUTHOR]

Minimum information models are reporting frameworks that describe the essential in-formation that needs to be provided in a publication, so that the work can be repeated or compared to other work. In 2016, Minimum Information about Tolerogenic Antigen-Presenting cells (MITAP) was created to standardize the reporting on tolerogenic antigen-presenting cells, including tolerogenic dendritic cells (tolDCs). tolDCs is a generic term for dendritic cells that have the ability to (re-)establish immune tolerance; they have been developed as a cell therapy for autoimmune diseases or for the prevention of transplant rejection. Because protocols to generate these therapeutic cells vary widely, MITAP was deemed to be a pivotal reporting tool by and for the tolDC community. In this paper, we explored the impact that MITAP has had on the tolDC field. We did this by examining a subset of the available literature on tolDCs. Our analysis shows that MITAP is used in only the minority of relevant papers (14%), but where it is used the amount of metadata available is slightly increased over where it is not. From this, we conclude that MITAP has been a partial success, but that much more needs to be done if standardized reporting is to become common within the discipline. [ABSTRACT FROM AUTHOR]

Climate change is the most serious causes and has a direct impact on biodiversity. According to the world's biodiversity conservation organization, reptile species are most affected since their biological and ecological qualities are directly linked to climate. Due to a lack of time frame in existing works, conservation adoption affects the performance of existing works. The proposed research presents a knowledge-driven Decision Support System (DSS) including the assisted translocation to adapt to future climate change to conserving from its extinction. The Dynamic approach is used to develop a knowledge-driven DSS using machine learning by applying an ecological and biological variable that characterizes the model and mitigation processes for species. However, the framework demonstrates the huge difference in the estimated significance of climate change, the model strategy helps to recognize the probable risk of threatened species translocation to future climate change. The proposed system is evaluated using various performance metrics and this framework can comfortably adapt to the decisions support to reintroduce the species for conservation in the future. [ABSTRACT FROM AUTHOR]

The existing research on emotion recognition commonly uses mel spectrogram (MelSpec) and Geneva minimalistic acoustic parameter set (GeMAPS) as acoustic parameters to learn the audio features. MelSpec can represent the time-series variations of each frequency but cannot manage multiple types of audio features. On the other hand, GeMAPS can handle multiple audio features but fails to provide information on their time-series variations. Thus, this study proposes a speech emotion recognition model based on a multi-input deep neural network that simultaneously learns these two audio features. The proposed model comprises three parts, specifically, for learning MelSpec in image format, learning GeMAPS in vector format, and integrating them to predict the emotion. Additionally, a focal loss function is introduced to address the imbalanced data problem among the emotion classes. The results of the recognition experiments demonstrate weighted and unweighted accuracies of 0.6657 and 0.6149, respectively, which are higher than or comparable to those of the existing state-of-the-art methods. Overall, the proposed model significantly improves the recognition accuracy of the emotion "happiness", which has been difficult to identify in previous studies owing to limited data. Therefore, the proposed model can effectively recognize emotions from speech and can be applied for practical purposes with future development. [ABSTRACT FROM AUTHOR]

Lung transplantation is the preferred treatment method for patients with endstage pulmonary disease. However, several factors hinder the progress of lung transplantation, including donor shortages, candidate selection, and various postoperative complications. Electrical impedance tomography (EIT) is a functional imaging tool that can be used to evaluate pulmonary ventilation and perfusion at the bedside. Among patients after lung transplantation, monitoring the graft’s pulmonary function is one of the most concerning issues. The feasible application of EIT in lung transplantation has been reported over the past few years, and this technique has gained increasing interest from multidisciplinary researchers. Nevertheless, physicians still lack knowledge concerning the potential applications of EIT in lung transplantation. We present an updated review of EIT in lung transplantation donors and recipients over the past few years, and discuss the potential use of ventilation- and perfusion-monitoring-based EIT in lung transplantation. [ABSTRACT FROM AUTHOR]

Organophosphates (OPs) are inhibitors of acetylcholinesterase and have deleterious effects on the central nervous system. Clinical manifestations of OP poisoning include convulsions, which represent an underlying toxic neuro-pathological process, leading to permanent neuronal damage. This neurotoxicity is mediated through the cholinergic, GABAergic and glutamatergic (NMDA) systems. Pharmacological interventions in OP poisoning are designed to mitigate these specific neuro-pathological pathways, using anticholinergic drugs and GABAergic agents. Benactyzine is a combined anticholinergic, anti-NMDA compound. Based on previous development of novel GABA derivatives (such as prodrugs based on perphenazine for the treatment of schizophrenia and nortriptyline against neuropathic pain), we describe the synthesis and preliminary testing of a mutual prodrug ester of benactyzine and GABA. It is assumed that once the ester crosses the blood–brain-barrier it will undergo hydrolysis, releasing benactyzine and GABA, which are expected to act synergistically. The combined release of both compounds in the brain offers several advantages over the current OP poisoning treatment protocol: improved efficacy and safety profile (where the inhibitory properties of GABA are expected to counteract the anticholinergic cognitive adverse effects of benactyzine) and enhanced chemical stability compared to benactyzine alone. We present here preliminary results of animal studies, showing promising results with early gabactyzine administration. [ABSTRACT FROM AUTHOR]

High-speed parallel robots have been extensively utilized in the light industry. However, the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system's dynamic response and stable operation cannot be ignored during the high-speed reciprocating motion. Thus, trajectory planning is essential for efficiency and stability from pick-and-place (PAP) actions. This paper presents a method for planning the equal-height pick-and-place trajectory considering velocity constraints to improve the PAP efficiency and stability of high-speed parallel robots. The velocity constraints in the start-and-end points can reduce vibration from picking and placing, making the trajectory more suitable to complex beltline situations. Based on velocity constraints, trajectory optimization includes trajectory smoothness and joint torque to optimize cycle time is carried out. This paper proposes an online trajectory optimization solution. By using back propagation (BP) neural networks, the solution is simplified and can be solved in real-time. Simulation and experiments were carried out on the SR4 parallel robot. The results show that the proposed method improves the efficiency, smoothness, and stability of the robot. This paper proposes an online trajectory planning method which is velocity constraints based and can improve the efficiency and stability of high-speed parallel robots. The work of this research is conducive to finely applying high-speed parallel robots. [ABSTRACT FROM AUTHOR]

The increasing reliance on foods sweetened with fructose is of great concern due to its leading role in development of obesity and other related metabolic disorders. Since oxidative stress is one of the pathogenic processes for development of these disorders, this research evaluated the inclusion of antioxidant-rich spices in diet as means of ameliorating dyslipidaemia and liver dysfunction in metabolic syndrome-induced Wistar rats. Thirty rats were induced with metabolic syndrome using 55.43% high-fructose diet, divided into six groups and fed on diets supplemented with 2 % inclusions of ginger, black pepper, garlic, turmeric and a mixture of the spices. Serum lipid profiles, atherogenic indices and indices of liver function were determined. Compared with the control, metabolic syndrome-induced rats fed the spices-supplemented diets had significantly (p<0.05) higher levels of serum cholesterol, triglyceride and low-density lipoprotein cholesterol which were significantly lower in comparison with the metabolic syndrome-induced rats fed standard diet. The atherogenic index and coronary risk index as well as activities of aspartate aminotransaminase, alanine aminotransaminase, alkaline phosphatase and gamma glutamyl aminotransaminase were significantly (p<0.05) higher in the groups treated with spices-supplemented diets compared with the control, but lower in comparison with the metabolic syndrome-induced rats fed standard diet. There were no significant (p>0.05) variations among groups in levels of serum bilirubin. It is evident that including these spices in diets could alleviate dyslipidaemia and lower serum enzyme activities in metabolic syndromeinduced rats, and could therefore, enhance restoration of heart and liver damages caused by consuming metabolic syndrome-causing diets. [ABSTRACT FROM AUTHOR]

Protein corona composition and precise physiological understanding of differentially expressed proteins are key for identifying disease biomarkers. In this report, we presented a distinctive quantitative proteomics table of molecular cell signaling differentially expressed proteins of corona that formed on iron carbide nanoparticles (NPs). High-performance liquid chromatography/electrospray ionization coupled with ion trap mass analyzer (HPLC/ESI-Orbitrap) and MASCOT helped quantify 142 differentially expressed proteins. Among these proteins, 104 proteins showed upregulated behavior and 38 proteins were downregulated with respect to the control, whereas 48, 32 and 24 proteins were upregulated and 8, 9 and 21 were downregulated CW (control with unmodified NPs), CY (control with modified NPs) and WY (modified and unmodified NPs), respectively. These proteins were further categorized on behalf of their regularity, locality, molecular functionality and molecular masses using gene ontology (GO). A STRING analysis was used to target the specific range of proteins involved in metabolic pathways and molecular processing in different kinds of binding functionalities, such as RNA, DNA, ATP, ADP, GTP, GDP and calcium ion bindings. Thus, this study will help develop efficient protocols for the identification of latent biomarkers in early disease detection using protein fingerprints. [ABSTRACT FROM AUTHOR]

Text similarity is critical in a variety of applications, including word processing, signal processing, imagery, data mining, wireless sensor networks, etc., where text similarity measurements can detect whether texts are lexical or semantic similar. Semantic text similarity is the term that uses to describe similarities based on meaning. Although this function is very challenging, it remains an active subject of study due to the complexities of natural language. The second type is lexical similarity whereby this type can be used to eliminate repetition by grouping similar texts together provided that two texts are very similar. It is important to remember that traditional text similarity approaches only look at the actual words in a phrase to compare two texts. Depending on the use case, it's easier to build and manage and offers a better trade-off. This paper examines current work on text similarity and divides it into four categories. Techniques based on strings, Corpus, knowledge, or hybrid similarities, these categories are all comparable. There are also examples of different combinations of these techniques for matching text and finding similarities between two texts. A smart method is proposed to find out the similarity between two texts called the fuzzy data similarity (FDS), and to prove the efficiency of the proposed method, it was compared with the most famous methods, where the results showed an accuracy of the FDS about 93%. [ABSTRACT FROM AUTHOR]

Reducing uncertainty in 3D carbonate rock type distribution is a critical factor that profoundly impacts field development for hydrocarbon or carbon capture and storage (CCS) projects. Miocene carbonate reservoirs in the Central Luconia offshore region are economically important global gas reservoirs. The nature of these carbonate rocks can be visually distinct in the core and the multiscale reservoir heterogeneity might vary in scale from the 100-m scale to the sub-millimeter scale. This work presents a series of steps workflow to obtain spatial information about the organization scheme of carbonate rock types, and capture the most important petrophysical and sedimentary controls on rock property distribution in the E11 field, a carbonate buildup, located in Central Luconia Province, offshore Malaysia. The spatial data were generated from a supervised neural Kohonen algorithm. The rock types predicted with this workflow were propagated using IPSOM probabilized self-organizing maps SOM. This tool is used for classifying multivariate data samples according to "patterns" or multivariate responses. The workflow includes several steps: A Step 1—Core data description, B Step 2—Thin section description, C Step 3—Well log interpretation, and D Step 4—IPSOM probabilized self-organizing maps for facies prediction SOM. The depth plots of the predicted rock type showed close correspondence to the core-based rock types in terms of the stratigraphic organization of tight and reservoir layers, proportions, and juxtaposition. This result is sufficient to merit the application of the rock type logs into a future porosity model of the E11 field, and to understand the lateral and vertical distribution of tight and reservoir rock types of distribution. The results can be used to build a future realistic digital twin of the subsurface, and in digital geological modeling. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) is one of the renowned ad hoc network technology that has vast varieties of applications such as in computer networks, bio-medical engineering, agriculture, industry and many more. It has been used in the internet-of-things (IoTs) applications. A method for data collecting utilizing hybrid compressive sensing (CS) is developed in order to reduce the quantity of data transmission in the clustered sensor network and balance the network load. Candidate cluster head nodes are chosen first from each temporary cluster that is closest to the cluster centroid of the nodes, and then the cluster heads are selected in order based on the distance between the determined cluster head node and the undetermined candidate cluster head node. Then, each ordinary node joins the cluster that is nearest to it. The greedy CS is used to compress data transmission for nodes whose data transmission volume is greater than the threshold in a data transmission tree with the Sink node as the root node and linking all cluster head nodes. The simulation results demonstrate that when the compression ratio is set to ten, the data transfer volume is reduced by a factor of ten. When compared to clustering and SPT without CS, it is reduced by 75% and 65%, respectively. When compared to SPT with Hybrid CS and Clustering with hybrid CS, it is reduced by 35% and 20%, respectively. Clustering and SPT without CS are compared in terms of node data transfer volume standard deviation. SPT with Hybrid CS and clustering with Hybrid CS were both reduced by 62% and 80%, respectively. When compared to SPT with hybrid CS and clustering with hybrid CS, the latter two were reduced by 41% and 19%, respectively. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs), one of the fundamental technologies of the Internet of Things (IoT), can provide sensing and communication services efficiently for IoT-based applications, especially energy-limited applications. Clustering routing protocol plays an important role in reducing energy consumption and prolonging network lifetime. The cluster formation and cluster head selection are the key to improving the performance of the clustering routing protocol. An energy-efficient routing protocol based on multi-threshold segmentation (EERPMS) was proposed in this paper to improve the rationality of the cluster formation and cluster heads selection. In the stage of cluster formation, inspired by multi-threshold image segmentation, an innovative node clustering algorithm was developed. In the stage of cluster heads selection, aiming at minimizing the network energy consumption, a calculation theory of the optimal number and location of cluster heads was established. Furthermore, a novel cluster head selection algorithm was constructed based on the residual energy and optimal location of cluster heads. Simulation results show that EERPMS can improve the distribution uniformity of cluster heads, prolong the network lifetime and save up to 64.50%, 58.60% and 56.15% network energy as compared to RLEACH, CRPFCM and FIGWO protocols respectively. [ABSTRACT FROM AUTHOR]

Wireless networks and the Internet of things (IoT) have proven rapid growth in the development and management of smart environments. These technologies are applied in numerous research fields, such as security surveillance, Internet of vehicles, medical systems, etc. The sensor technologies and IoT devices are cooperative and allow the collection of unpredictable factors from the observing field. However, the constraint resources of distributed battery-powered sensors decrease the energy efficiency of the IoT network and increase the delay in receiving the network data on users' devices. It is observed that many solutions are proposed to overcome the energy deficiency in smart applications; though, due to the mobility of the nodes, lots of communication incurs frequent data discontinuity, compromising the data trust. Therefore, this work introduces a D2D multi-criteria learning algorithm for IoT networks using secured sensors, which aims to improve the data exchange without imposing additional costs and data diverting for mobile sensors. Moreover, it reduces the compromising threats in the presence of anonymous devices and increases the trustworthiness of the IoT-enabled communication system with the support of machine learning. The proposed work was tested and analyzed using broad simulation-based experiments and demonstrated the significantly improved performance of the packet delivery ratio by 17%, packet disturbances by 31%, data delay by 22%, energy consumption by 24%, and computational complexity by 37% for realistic network configurations. [ABSTRACT FROM AUTHOR]

Several graphical methods have been developed to understand the stratigraphy observed in wells and assist experts in estimating rock quality, defining limits for barriers, baffles, and speed zones, and in particular, delineating hydraulic flow units. At present, there exists no computational tool that bundles the main graphical methods used for defining flow units. This paper introduces an add-on module to the MATLAB Reservoir Simulation Toolbox that contains computational routines to carry out such graphical analyses, both qualitatively and quantitatively. We also describe a new secondary method defined as the derivative of the stratigraphic modified Lorenz plot, which we use to classify depth ranges within the reservoir into barriers, strong baffles, weak baffles, and normal units, based on flow unit speed over those depths. We demonstrate the capabilities of the "Graphical Analysis for Well Placement Strategy" module by applying it to several case studies of both real and synthetic reservoirs. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy and society, the production of municipal solid waste is continuously increasing worldwide. Therefore, harmless treatments and the disposal of municipal solid waste should be improved. This study combined the concept of Internet of things and smart environment protection with a "cloud, network, end" platform architecture to construct a smart management platform for the planning and management of landfills. The platform was developed for the mechanical biological treatment (MBT) of landfills and was divided into seven modules, landfill design, municipal solid waste production prediction, MBT waste microbial volume reduction, stability analysis, result analysis, remote monitoring, and sharing and communication, which can effectively improve the operation and management of waste, enhance the effective storage volume of a landfill, extend its service life, and thereby improve the sustainable development of the city. This study can be used as a reference for applications in similar projects worldwide. [ABSTRACT FROM AUTHOR]

In this study, undoped and Magnesium doped TiO2 nanoparticles (Mg-TiO2 NPs) are successfully synthesized via a simple sol–gel method cost-effectively. The prepared Mg- TiO2 NPs is characterized by UV–Vis, FTIR, PL, XRD, FESEM, TEM, and EDAX. UV–Visible Spectroscopy showed that an increase in the optical bandgap concerning the concentration of dopant Mg increases. The bandgap values were found to be 3.57–3.54 eV. FTIR spectra shows that the presence of the characteristic stretching and bending vibrational band of Ti–O bonding at 468 cm−1 and shifts in vibrational bands were observed for Mg-TiO2 NPs. PL spectra of Mg- TiO2 NPs at different concentrations exhibit a strong UV emission band. X-ray diffraction confirmed the formation of the tetragonal anatase phase. The average crystallite size of synthesized samples was found to be 22–19 nm. The average crystallite size of Mg- TiO2 NPs decreases with increasing the concentration of dopant Mg. The FESEM and TEM analysis confirmed that the spherical morphology for both TiO2 and Mg-TiO2 NPs. SAED pattern confirms the crystalline nature of prepared samples. EDAX spectra confirm the presence of Ti, O, and Mg and confirm that Mg2+ ions are present in the TiO2 lattices. The prepared samples were investigated against gram-positive and gram-negative bacteria. The prepared samples exhibit potent antibacterial activity against gram-negative bacteria than the gram-positive bacteria. The prepared samples exhibit significant photocatalytic degradation for Methylene blue (MB). [ABSTRACT FROM AUTHOR]

Increased network lifetime is a desired property of low-powered and energy-constrained Internet of Things (IoT) devices that are deployed in wireless network environments. Clustering is used as a technique in multiple solutions to improve overall network lifetime. Further variants in the clustering process are defined to optimize the results. One such variant is equal clustering, where all the clusters have the same size. However, this approach suffers from the issue of nodes closer to the base station (BS) dying out earlier. As an alternative, unequal clustering is proposed, where clusters close to the BS are of smaller size; thus, cluster heads (CHs) consume a substantial proportion of their energy for being acting as data forwarding nodes. In this paper, we propose an unequal clustering approach with the BS at the center of a circular area. The size of each cluster is fixed and computed based on the node density of the area. The number of clusters increases from outwards to inwards towards the BS. The results show considerable performance gain over selected benchmark works. [ABSTRACT FROM AUTHOR]

Mobile chargers have greatly promoted the wireless rechargeable sensor networks (WRSNs). While most recent works have focused on recharging the WRSNs in an on-demand fashion, little attention has been paid on joint consideration of multiple mobile chargers (MCs) and multi-node energy transfer for determining the charging schedule of energy-hungry nodes. Moreover, most of the schemes leave out the contemplation of multiple network attributes while making scheduling decisions and even they overlook the issue of ill-timed charging response to the nodes with uneven energy consumption rates. In this paper, we address the aforesaid issues together and propose a novel scheduling scheme for on-demand charging in WRSNs. We first present an efficient network partitioning method for distributing the MCs so as to evenly balance their workload. We next adopt the fuzzy logic which blends various network attributes for determining the charging schedule of the MCs. We also formulate an expression to determine the charging threshold for the nodes that vary depending on their energy consumption rate. Extensive simulations are conducted to demonstrate the effectiveness and competitiveness of our scheme. The comparison results reveal that the proposed scheme improves charging performance compared to the state-of-the-art schemes with respect to various performance metrics. [ABSTRACT FROM AUTHOR]

The article argues for the official recognition of Arab Americans at the federal and state levels, including access to funding and protections from discrimination to empower the Arab American community. Topics discussed include history of Arab Americans in terms of their designation as white, discrimination experienced by Arab Americans, and their inability to access federal programs available to other minority groups.

Nowadays, the automotive industry still incorporates collaborative robots and their applications into the less traditional processes to automate them. The purpose is to make up for the skill gap, retain skilled staff, attract the younger generation, and increase quality. The paper brings a short overview of the automated collaborative workplace, including the PFL technique description and possibilities. Also, humanrobot collaboration (HRC) is elaborated together with the example of such an automated workplace (with dual-arm robotic system participation). The specific contact (transient, quasistatic) between the human body and robotic system is described to fulfill the HRC and PFL technique. It also summarizes and explains ISO / TS 15066 details to apply this technique at automated assembly process example. [ABSTRACT FROM AUTHOR]

In Surveillance Wireless Sensor Networks (SWSN), the nodes are distributed at the borders to detect unauthorized intrusions. In such applications, as the nodes are usually equipped with limited batteries and the network area is harsh to be accessible for humans, energy efficiency is considered as one of the main issues in designing the sensor networks. In the last years, Wireless Rechargeable Sensor Networks (WRSN) provides valuable insights into solving the energy constraint problem in WSNs. In a WRSN, Wireless Mobile Chargers (WMC) are responsible to recharge the batteries of the sensor nodes in order to enhance the operation time of the network. In most of the previous WRSN based schemes, the WMCs recharge the nodes singly and directly, which results in increasing the travel time of WMC and waiting time of sensor nodes. In addition, despite of using WMC, the permanent network lifetime has not been addressed in most of the previous schemes. Therefore, to overcome the limitations of existing literature, this research work focuses on the design and development of Broker-based Nodes Recharging Scheme (BNRS) which significantly contributes to improved lifetime and performance of SWSN. In the proposed scheme, power banks are employed as brokers between sensor nodes and WMC. The main duty of a power bank is to receive energy from WMC and transfer to the sensor nodes. Based on the simulation experiments the proposed BNRS achieves the permanent network operation which results in increasing security in the border of countries. [ABSTRACT FROM AUTHOR]

Presents the table of contents for this issue of this publication. [ABSTRACT FROM AUTHOR]

Energy constraint is one of the main design issues of wireless sensor networks. Over the past few years, the concept of the wireless mobile charger (WMC) has been proposed in order to improve the energy efficiency of the networks. In such schemes, optimizing the moving trajectory and charging time of WMC are considered as two main problems. Several schemes attempt to optimize the moving trajectory of WMC without considering the balanced energy depletion time of nodes, which leads to degrading the energy efficiency and network lifetime. Thus, a route optimization of WMC algorithm is proposed to determine the optimal trajectory of WMC to move along sensor nodes in such a way that the balanced energy depletion time of the nodes is achieved. Moreover, in most of the existing schemes, WMCs charge the nodes as long as their batteries are fully charged. However, not considering the remaining lifetime of the other nodes leads to premature network death and decreases the network performance. Therefore, a charge time optimization of WMC algorithm is proposed to overcome the mentioned problem. Simulation results demonstrate that the proposed scheme remarkably enhance the network performance in terms of different evaluation metrics. [ABSTRACT FROM AUTHOR]