Background: This practice guideline was developed by the Chronic Kidney Disease (CKD) Task Force, which was composed of clinical and methodological experts. The Saudi Arabian Ministry of Health and its Health Holding Company commissioned this guideline project to support the realization of the Vision 2030's healthcare transformation pillar. Methods: The guideline synthesis was guided by the GRADE-ADOLOPMENT methodology. Results: The final adoloped guideline addressed 12 clinical questions on blood pressure management in patients with CKD through a set of recommendations and performance measures. The recommendations included antihypertensive agents in children, non-renin angiotensin system inhibition (Non-RASi) vs RASi in adults, intensive vs standard blood pressure targets, early vs late assessment for kidney replacement therapy (KRT), late vs early preparation strategy for KRT, CKD symptoms during assessment for KRT or conservative management, initiation of KRT in patients with deteriorating CKD, choice of KRT modality or conservative management in certain CKD patient groups, changing or discontinuing KRT modalities, review frequency for KRT or conservative management, and Information, education and support. Conclusions: These conditional recommendations were based on low to very low certainty of evidence that highlights the need for high-quality randomized trials comparing different antihypertensive agents in patients with CKD.

The Impact of Event Scale-Revised (IES-R) is the most popular measure of post-traumatic stress disorder (PTSD), which has been recently validated in Arabic. This instrumental study aimed to determine optimal cutoff scores of the IES-R and its subscales in Arab samples of psychiatric patients (N = 168, 70.8% females) and healthy adults (N = 992, 62.7% females) from Saudi Arabia during the COVID-19 pandemic as an ongoing collective traumatic event. Based on a cutoff score of 14 of the Depression Anxiety Stress Scale 8-items (DASS-8), receiver operator curve (ROC) analysis revealed two optimal points of 39.5 and 30.5 for the IES-R in the samples (area under the curve (AUC) = 0.86 & 0.91, p values = 0.001, 95% CI: 0.80-0.92 & 0.87 to 0.94, sensitivity = 0.85 & 0.87, specificity = 0.73 & 0.83, Youden index = 0.58 & 0.70, respectively). Different cutoffs were detected for the six subscales of the IES-R, with numbing and avoidance expressing the lowest predictivity for distress. Meanwhile, hyperarousal followed by the irritability expressed stronger predictive capacity for distress than all subscales in both samples. In path analysis, pandemic-related irritability resulted from direct and indirect effects of key PTSD symptoms (intrusion, hyperarousal, and numbing). Irritability contributed to traumatic symptoms of sleep disturbance in both samples while the opposite was not true. The findings suggest usefulness of the IES-R at a score of 30.5 for detecting adults prone to trauma related distress, with higher scores needed for screening in psychiatric patients. Various PTSD symptoms may induce dysphoric mood, which represents a considerable burden that may induce circadian misalignment and more noxious psychiatric problems/ co-morbidities (sleep disturbance) in both healthy and diseased groups.

Fusion protein therapeutics engineering is advancing to meet the need for novel medicine. Herein, we further characterize the development of novel RTA & PAP-S1 antiviral fusion proteins. In brief, RTA/PAP-S1 and PAP-S1/RTA fusion proteins were produced in both cell free and E. coli in vivo expression systems, purified by His-tag affinity chromatography, and protein synthesis inhibitory activity assayed by comparison to the production of a control protein, CalmL3. Results showed that the RTA/PAP-S1 fusion protein is amenable to standardized production and purification and has both increased potency and less toxicity compared to either RTA or PAP-S1 alone. Thus, this research highlights the developmental potential of novel fusion proteins with reduced cytotoxic risk and increased potency.

This review is dedicated to sustainable practices in liquid chromatography. HPLC and UHPLC methods contribute significantly to routine analytical techniques. Therefore, the transfer of classical liquid chromatographic methods into sustainable ones is of utmost importance in moving toward sustainable development goals. Among other principles to render a liquid chromatographic method green, substitution of the organic solvent component in the mobile phase with a greener one received great attention. This review concentrates on choosing the best alternative green organic solvent to replace the classical solvent in the mobile phase for easy rapid transfer to a more sustainable normal phase or reversed-phase liquid chromatography. The main focus of this review will be on describing the transfer of non-green to green and white chromatographic methods in an effort to elevate the sustainability best practice in analytical chemistry. The greenness properties and greenness ranking in addition to the chromatographic suitability of seventeen organic solvents for liquid chromatography are mentioned to have a clear insight into the issue of rapidly choosing the appropriate solvent to transfer a classical HPLC or UHPLC method into a more sustainable one. A simple guide is proposed for making the liquid chromatographic method more sustainable.

Abstract Several studies have been conducted to strengthen weak road layers, regardless of whether they are un-der construction or are undergoing maintenance. Using substrates filled with different materials has proven effective for increasing the strength of these layers. In this study, I evaluated the coefficient of lateral soil pressure under various conditions when using reinforced and unreinforced piles filled with in-expensive material and the extent of their contribution to strengthening road layers. The results con-firmed that there was a difference in the coefficient of lateral soil pressure when the sand-filled piles were reinforced. The sand-filled piles were divided into several parts by arming. The maximum coeffi-cient of lateral soil pressure was 0.38 in the case of sand (1 mm) with reinforcement, whereas it was 0.29 in the same case without reinforcement as shown in Figure 1. The maximum coefficient of lateral soil pressure was 0.27 in the case of granite grain (2 mm) with reinforcement, whereas it was 0.17 in the same case without reinforcement. Moreover, the maximum lateral pressure coefficient was 0.26 in the case of granite grain (3 mm) with reinforcement, and it was 0.30 in the same case without reinforce-ment.

Construction of Pontoons is based on multiple elements, dimensions and weight. The study has addressed about how the industry of the floating reinforcement concrete precast (pontoons) installs in the factory with the combinations of utility, electricity services, and Internet service. The pontoon bridges are successfully installed in the road for transport or sea for shops. The installation process for pontoons is successfully attempted in a balanced situation above surface of the sea to the resistant of floating precast (pontoons) to any ambient effects such as weather conditions, the movement of the waves or any others effects. The findings elaborate that it is not just a military solution. Pontoon installation can significantly serve for civil purposes.

The branding of cities through their historical and cultural assets has become a pivotal strategy in urban development and tourism. This study focuses on Erbil Citadel, a UNESCO World Heritage Site, and its potential as a brand for Erbil, a city with a rich historical backdrop and flourishing urban landscape. The study aimed to explore the perceptions of Erbil's residents regarding the cultural significance of the Citadel and its potential as a city brand. A mixed-method survey questionnaire was conducted, collecting data from around 440 residents through both manual distribution around the Citadel and an online platform. The findings were analysed using SPSS to provide both descriptive and inferential statistical insights.

The integration of sign language recognition systems into digital platforms has the potential to bridge communication gaps between the deaf community and the broader population. This paper introduces an advanced Israeli Sign Language (ISL) recognition system designed to interpret dynamic motion gestures, addressing a critical need for more sophisticated and fluid communication tools. Unlike conventional systems that focus solely on static signs, our approach incorporates both Deep Learning and Computer Vision techniques to analyze and translate dynamic gestures captured in real-time video. We provide a comprehensive account of our preprocessing pipeline, detailing every stage from video collection to the extraction of landmarks using MediaPipe, including the mathematical equations used for preprocessing these landmarks and the final recognition process. The dataset utilized for training our model is unique in its comprehensiveness and is publicly accessible, enhancing the reproducibility and expansion of future research. The deployment of our model on a publicly accessible website allows users to engage with ISL interactively, facilitating both learning and practice. We discuss the development process, the challenges overcome, and the anticipated societal impact of our system in promoting greater inclusivity and understanding.

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two’s limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

The cross-linked microspheres were prepared and loaded with Favipiravir SARS-CoV-2 antiviral drug, by copolymerization of chitosan (CS) with a polysaccharide extracted from fresh pomegranate peels. Moreover, glutaraldehyde (Glu) has been used as chemical cross-linker ,and sodium hexametaphosphate (SHMP) as physical cross-linker. The extracted polysaccharide was analyzed and different techniques have been used and the analyses leads to the fact that it is pectin .The surface morphology of the prepared microspheres was studied use scanning electron microscope where the size and the shape factor (S) of Glu microspheres have shown high values(74.27μm) and (0.852) respectively means their surfaces are tends to roughness, whereas the SHMP microspheres have shown size particle(20.47μm)and shape factor (0.748) which gives indication that the SHMP microspheres have smooth surfaces. The swelling studies have shown that Glu microspheres have higher degree of swelling which means SHMP microspheres are more compact. The prepared microspheres have shown more Loading percentage of Favipiravir antiviral drug in SHMP microspheres(37%w/w)in comparison with Glu microspheres(35%w/w) where the electrostatic interaction between the Favipiravir ions and SHMP anions help for more loading. The microspheres prepared under different types of cross-linking have shown initially burst release of Favipiravir and followed by a step of controlled release for a certain time where its period depends on the pH of the release media. Both Glu and SHMP cross-linked microspheres have shown high controlled release time in buffered release solution of pH 7.4 and for a less periods in pH 1.3 and pH 9.4 which may related to the type of electrostatic interactions between drug and polymer system and their reactions with release solution ions.

The perception in pair trading is to recognize two stocks that move together, and their prices will converge to a mean value in future. However, finding the mean-reverted point at which the value of the pair will converge, and optimal boundaries of the trade is not easy. As uncertainty and model misspecifications may lead to losses. To cater for the problems, this study employs the novel entropic approach that utilizes entropy as penalty function for the misspecification of the model. The use of entropy as a measure of risk in pair trading is a nascent idea and this study utilizes daily data for 64 companies listed on PSX for the years 2017, 2018, and 2019, respectively to compute the returns based on the entropic approach. These companies cover the major sectors including Cement, Chemical, Automobile Assembler, Food and Personal Care Products, Oil and Gas Marketing Companies, Oil and Gas Exploration Companies Ltd, Power Generation and Distribution, Refinery and Pharmaceuticals. The returns to these stocks are then evaluated and compared with the Buy and Hold strategy. The results show positive and significant returns from pair trading using an entropic approach.

Prostate cancer (Pca) is a highly heterogeneous disease and the second more common tumor in males. Molecular and genetic profiles have been used to identify subtypes and guide therapeutic intervention. However, roughly 26% of primary Pca are driven by unknown molecular lesions. We use Principal Component Analysis (PCA) and custom RNAseq-data normalization to identify a gene expression signature which segregates primary PRAD from normal tissues. This Core-Expression Signature (PRAD-CES) includes 33 genes and accounts for 39% of data complexity along the PC1-cancer axis. The PRAD-CES is populated by protein-coding (AMACR, TP63, HPN) and RNA-genes (PCA3, ARLN1) sparsely found in previous studies, validated/predicted biomarkers (HOXC6, TDRD1, DLX1), and/or cancer drivers (PCA3, ARLN1, PCAT-14). Of note, the PRAD-CES also comprises six over-expressed LncRNAs without previous Pca association, four of them potentially modulating driver’s genes TMPRSS2, PRUNE2 and AMACR. Overall, our PCA capture 57% of data complexity within PC1-3. GO enrichment and correlation analysis involving major clinical features (i.e., Gleason Score, AR Score, TMPRSS2-ERG fusion and Tumor Cellularity) suggest that PC2 and PC3 gene signatures might describe more aggressive and inflammation-prone transitional forms of PRAD. Of note, surfaced genes may entail novel prognostic biomarkers and molecular alterations to intervene. Particularly, our work uncovered RNA genes with appealing implications on Pca biology and progression.

Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit based on shape analysis is presented. Color and shape analysis was utilized to segment the images of different fruits like apple, pomegranate obtained under different lighting conditions. First the input sectional tree image was converted from RGB colour space into the colour space transform (i.e., YUV, YIQ, or YCbCr). The resultant image was then applied to the algorithm for fruit segmentation. After it is applied Morphological Operations which is enhanced image then execute Blob counting method which identify the object and count the number of it. Accuracy of this algorithm used in this thesis is 82.21% for images that have been scanned.

The prevalence of internet gaming disorders (IGD) is considerably high among youth, especially with social isolation imposed by the ongoing COVID-19 pandemic. IGD adversely affects mental health, quality of life, and academic performance. The Internet Gaming Disorder Scale (IGDS9-SF) is designed to detect IGD according to DSM-IV diagnostic criteria. However, inconsistent results are reported on its capacity to diagnose IGD evenly across different cultures. To ensure the suitability of the IGDS9-SF as a global measure of IGD, this study examined the psychometric properties of the IGDS9-SF in a sample of Sri Lankan university students (N = 322, mean age =17.2 ± 0.6, range = 16-18 years, 56.5% males) and evaluated its measurement invariance across samples from Sri Lanka, Turkey, Australia, and the USA. Among Sri Lankan students, a unidimensional structure expressed good fit, invariance across different groups (e.g., gender, ethnicity, and income), adequate criterion validity (strong correlation with motives of internet gaming, daily gaming duration, and sleep quality), and good reliability (alpha = 0.81). Males and online multiplayers expressed higher IGD levels, greater time spent gaming, and more endorsement of gaming motives (e.g., Social and Coping) than females and offline players. Across countries, the IGDS9-SF was invariant at the configural, metric, and scalar levels, albeit strict invariance was not maintained. The lowest and highest IGD levels were reported among Turkish and American respondents, respectively. In conclusion, the IGDS9-SF can be reliably used to measure IGD among Sri Lankan youth. Because the scale holds scalar invariance across countries, its scores can be used to compare IGD levels in the studied countries.

Although vaccinating the world is adopted by the WHO to limit COVID-19 transmission, people’s worries about vaccines may suppress their desire for vaccination despite vaccine availability. This study aimed to evaluate the levels of stress and anxiety among 250 Jordanians who received their first vaccine dose at a local community health center. The respondents completed the stress and anxiety subscales of the Depression Anxiety and Stress scale 21 (DASS-21) pre- and post-vaccination. The respondents expressed more moderate-severe levels of stress pre than post vaccination (20.8% and 13.2%, respectively). Meanwhile, 37.2% and 45.2% of the respondents expressed moderate-severe anxiety pre and post vaccination, respectively. Wilcoxon signed-rank test revealed that the drop in the level of stress from pre (median (IQR) = 5 (1-8)) to post vaccination (median (IQR) = 3 (1-7)) was statistically significant (z = -3.81, p = 0.001, r = 0.17) while the increase in anxiety was not. Anxiety median significantly dropped among individuals experiencing mild to severe anxiety pre vaccination. Similarly, stress and anxiety significantly increased among individuals expressing normal anxiety pre vaccination (z = -3.57 and -8.24, p values = 0.001, r = 0.16 and 0.37, respectively). Age positively correlated with post vaccination anxiety among respondents with mild pre vaccination anxiety, and it negatively correlated with pre vaccination level of stress in the normal anxiety group. Gender, marital status, respondents’ level of education, and history of COVID-19 infection had no significant correlation with anxiety or stress at either point of measurement. Overcoming their hesitancy to receive COVID-19 vaccine, individuals with normal levels of anxiety experienced a rise in their distress symptoms following immunization. On the contrary, vaccination seemed to desensitize anxious individuals. Policymakers need to formulate a population-specific plan to increase vaccine preparedness and promote psychological well-being over all during the pandemic.

Target 9.c of the 2015 United Nations (UN) sustainable development goals (SDGs) specifically addresses increasing access to information and communication technology (ICT) resources, and striving for universal access to the internet by 2020. The present study seeks to evaluate the effectiveness of the youth related national strategies implemented in this regard by a select number of countries in the Middle East region. The study does so, by relying on a spatial bivariate copula regression analysis of data on youth respondents from five countries, extracted from the 2018 Program for international students’ assessment (PISA). Focusing specifically on evaluating the availability of ICT resources to the youth population, and also identifying the impact of ICT resources on youth subjective well-being in the region, we find that except for the UAE and Qatar that have above OECD average youth performance on the ICT resource index, youth from the remaining countries reported below OECD level average access to ICT resources. The within region cross-country comparative analysis of ICT resources availability to the youth population at home, also highlighted significant heterogeneity across the five countries, post 2015 SDG adoption by UN country members. Furthermore, looking at the impact of ICT resources on youth well-being, controlling for not only cross-country spatial correlations, and factors such as home educational resources, cultural possessions at home, parental occupation status, youth expected occupation status, economic and socio-cultural status, age, gender, and grade level in school; we found that every standard deviation increase in ICT resources to the youth population in the region raises their self-expressed sense of belonging in school by 1.88% standard deviations. Given the empowering nature of ICT resources to youth, and the potential of both to support national as well as regional economic development initiatives, a concerted effort to ease ICT resources diffusion by member countries in the middle east region could assist not only each country in its own development path, but also the region as a whole to live up to its growth potential by the 2030.

This article discuss the effects of heat treatment and lubrication modes on the machinability of an A356 alloy (Al-Si-Mg); the alloy is studied as-received, with solution heat-treated alloy (SHT) as well as with an alloy that is solution heat-treated and then aged at 155, 180 and 220 °C. In the course of machinability evaluation, several criteria including cutting force, surface roughness, tool wears and burr analysis (chip) were studied. The results and analysis in this work indicated that the selected machinability criteria are important and necessary to effectively evaluate the machinability of A356 alloys. The machinability of both materials and tools were estimated in terms of cutting force, chip thickness ratio and burr formation, flank wear and roughness. The effects of different cutting parameters (cutting speed and feed rate) and lubrication modes (dry, mist and wet) on the machinability of the A356 cast alloy were also examined. The influence of heat treatments on the burr formation and surface quality was clearly revealed by the experimental results. Experimental work revealed that cutting forces were influenced significantly by aging and cutting speed. However, the different aging at 155, 180, and 220 °C and the cutting speed significantly affected the machinability of the A356 cast alloy. The results obtained show that a better drilling performance in terms of surface quality occurs at a high feed rate, with dry drilling and artificial aging at T6.

Medical implants made of biodegradable materials could be of advantage for temporary applications such mechanical support during bone-healing or as vascular stents to keep blood vessels open. After completion of the healing process the implant would disappear, avoiding long-term side effects or the need for surgical removal. Various corrodible metal alloys based on magnesium, iron or zinc have been proposed as sturdier and potentially less inflammatory alternative to degradable organic polymers, in particular for load-bearing applications. Despite the recent introduction of magnesium-based screws the remaining hurdles to routine clinical applications are still challenging, such as limiting mechanical material characteristics or unsuitable corrosion characteristics. Here, salient features and clinical prospects of currently investigated biodegradable implant materials are summarized with a main focus on magnesium alloys. A mechanism of action for the stimulation of bone growth due to the exertion of mechanical force by magnesium corrosion products is discussed. To explain divergent in vitro and in vivo effects of magnesium a novel model for bacterial biofilm infections is proposed which predicts crucial consequences antibacterial implant strategies.

Dementia patients express a set of problematic and deteriorating symptoms, along self-care dependency. Overtime, the mental health of family caregivers of persons with dementia may suffer, putting them at a high risk for psychopathology, which may be associated with endangered wellbeing of demented people. This cross-sectional study examined the psychometric properties of the Depression Anxiety Stress Scale 8-items (DASS-8), DASS-12, DASS-21 in a convenient sample of 571 caregivers from northern Italy and southern Switzerland (Mean age = 53, SD = 12, range = 24–89 years). A bifactor structure of the three measures had the best fit; some items of the DASS-12/DASS-21 failed to load on their domain-specific factors. The three-factor structure was invariant across various groups (e.g., gender, education, etc.), expressed adequate reliability and convergent validity, and had strong positive correlation with the 3-item UCLA Loneliness Scale (UCLALS3). Dementia type had no effect on distress scores, which were higher among females, adult children caregivers, those caring for dependent patients, and those who received help with care. For 54.9 and 38.8% of the latter, care was provided by relatives and health professionals, respectively. Since the DASS-8 expresses adequate psychometrics comparable with the DASS-21, it may be used as a brief measure of distress in this population.

Malaria is one of the life-threatening disease caused by the Anopheles mosquitoes affecting the human red blood cells. It is the global health concern which is quite common in tropical as well as sub-tropical parts of the World. Therefore, it is an important to have an effective computer aided system in place for early detection and treatment. State of the art machine learning techniques are used to detect the infected malaria cells from the pool of images. As the visual heterogeneity of the malaria dataset is highly complex and dynamic, therefore higher number of images are needed to train the machine learning models effectively. However, hospitals as well as medical institutions do not share the medical image data for collaboration due to general data protection regulation (GDPR) and data protection act (DPA). To overcome this collaborative challenge, our research is inspired to use the real-time medical image data while using the framework of federated learning (FL) framework that will ensure the data privacy while mutual collaboration of hospitals and medical institutes. We have used the state of the art machine learning models that include the Resnet50 and densenet in a federated learning framework. We have experimented both models in different settings and our preliminary results showed that the densenet model performed better in accuracy (75%) in contrast to resnet50 (72%) while considering 8 clients, while the trend is observed common in 4 clients with the similar accuracy of 94% and 6 client showed that the densenet model performed quite well with the accuracy of 92% while resnet50 achieving only 72%.

Background. TRPA1-related drugs alter sensation, particularly in conditions of inflammation. To further characterize the role of these drugs in bladder sensation, the TRPA1 agonist cinnamaldehyde (CMA) and oral true cinnamon spice were examined in preclinical models of bladder pain. Methods. Female, adult rats with and without acute zymosan-induced cystitis, were anesthetized and visceromotor (VMR) and cystometric responses to urinary bladder distension (UBD) determined following either the intravesical administration of CMA/vehicle solutions or the oral administration of true cinnamon/vehicle. ELISA measures of bladder TRPA1 content were also determined. Results. Acute cystitis resulted in increases in bladder TRPA1 content and produced an increased vigor of the VMRs to UBD and a lowering of micturition volume thresholds for activation of a micturition response. Intravesical CMA produced a robust inhibition of VMRs to UBD in rats with cystitis, but not in those without. Micturition volume thresholds were lowered by CMA in rats without cystitis, but had no additional effect in rats with cystitis. Oral cinnamon also produced a robust inhibition of VMRs to UBD in rats with cystitis and a mild augmentation of VMRs to UBD in rats without cystitis. Conclusions. A potentially analgesic effect of the spice, true cinnamon, in the treatment of the pain of acute cystitis was suggested by these preclinical studies. Human studies are indicated.

Cyrene was evaluated for the first time as a potential sustainable mobile phase solvent in re-versed-phase chromatography. As a benign biodegradable solvent, Cyrene is an attractive re-placement to classical non-green organic chromatographic solvents such as acetonitrile and a modifier, co-eluent to known green solvents such as ethanol. Compared to ethanol, Cyrene is less toxic, non-flammable, bio-based, biodegradable and cheaper solvent. A fire safety spider Chart was generated to compare the properties of Cyrene to ethanol and show its superiority as a greener solvent. Cyrene's behaviour, advantages, and drawbacks in reversed-phase chromatography, including cut-off value, elution power, selectivity, and effect on the column, were investigated using a model drug mixture of moxifloxacin and metronidazole. A monolithic C18 (10 x 4.6 mm) column was used as a stationary phase. Different ratios of Cyrene: ethanol with an aqueous portion of sodium acetate buffer mobile phases were tested. A mobile phase consisting of Cyrene: ethanol: 0.1 M sodium acetate buffer pH 4.25 (8:13:79, v/v) was selected as most suitable mobile phase system for separating and simultaneously determining metronidazole and moxifloxacin. The greenness and whiteness of the method were evaluated using the qualitative green assessment tool AGREE and the white analytical chemistry assessment tool RGB12. Further potentials of Cyrene as a solvent or modifier in normal phase chromatography, liquid chromatography-mass spectrometry, and supercritical fluid chromatography are discussed.

Drought is treated as a key natural disaster that affects numerous segments of the natural environment and economy throughout the world. Drought indices (DIs) were computed for Potwar region (PR) in Punjab-Pakistan, using DrinC software which are deciles, Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Drought situation of 12, 9, 6 and 3 months was estimated on temporal basis. DIs obtained by deciles technique showed that for the last 39 years, 8-years are with drought severity in a cycle and are occurring every 2 to 7-years just the once repetitively. The RDI and SPI index showed the analogous trends as of deciles. Though, for RDI and SPI, the extremely dry and severely dry class was merely two years and rest of the drought affected years with respect to deciles were normally and intermediately dry. SPI is better as compared to deciles as the severity is better understood in the context of SPI. Regression analysis revealed that the RDI and SPI indices are mutually interrelated and if first 3 month precipitation is obtainable one can forecast yearly RDI. This investigation is valuable to devise future development plans to contest vulnerable drought incidents, its mitigation and impacts on socio-economic sectors.

A sustainable reversed-phase chromatographic method has been developed and validated for the simultaneous determination of three active pharmaceutical ingredients, dorzolamide, brinzolamide, and timolol, used to treat glaucoma. The eco-friendly solvent isopropanol has been used as an organic mobile phase constituent. According to the Hansen space green solvent selection tool, isopropanol has a G score of 6.5, comparable to ethanol, which has a G score of 6.6. The mobile phase consists of isopropanol: aqueous sodium acetate buffer (0.1 M, pH 4.25) in the ratio of 10:90 (v/v). The flow rate was maintained at 1 mL/min. Dorzolamide and brinzolamide were detected at 254 nm, and timolol was detected at 295 nm. A high-purity silica with a polymeric C18 modification column (5 µm,150 x 4.6 mm) was used for this separation. The three compounds were eluted within 8 min. The method was validated according to ICH guidelines. The calibration curves were linear in the range of 20-70 µg/mL, 40-140 µg/mL, and 20-70 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. The LODs were found to be 1.61 µg/mL, 1.60 µg/mL, and 3.16 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. Good accuracy and precision were obtained for the three compounds. The greenness and whiteness of the method were indicated using the AGREE and RGB12 tools, respectively.

This qualitative study aims at identifying the essence of personal experiences of accounting partners in Saudi Arabia. For this phenomenology approach employs to understand the lived experience of accounting partners and how would such experience affect their career. It mainly aims to explore the different experiences of fifteen (15) Saudi partners working in various accounting companies in Saudi Arabia. The interviews conducted to explore the most important challenges and difficulties for accountants to become a partner, and the most important job skills that the partners must have. This study found that there is urgent need for a number of things, including the required number of years of experience to become a partner, and to make sure that the partners are having the right education and professionally qualified. In addition, other different skills that the partner must have include responsible leadership, professional communication, good marketing skills and excellent command of English. Moreover, this research is vital for the concerned parties to identify the current challenges in the accounting profession in Kingdom of Saudi Arabia.

As the number of ships for marine transportation increases with the advancement of global trade, encountering multiple ships in marine traffic becomes common. This situation raises the risk of collision of the ships; hence this paper proposes a novel Fuzzy-logic based intelligent conflict detection and resolution algorithm, where the collision courses and possible avoiding actions are analyzed by considering ship motion dynamics and the input and output fuzzy membership functions are derived. As a conflict detection module, the Collision Risk (CR) is measured for each ship by using a scaled nondimensional Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) as inputs. Afterwards, the decisions for collision avoidance are made based on the calculated CR, encountering angle and relative angle of each ship measured from others. In this regard, the rules for the Fuzzy interface system are defined in accordance with the COLREGs, and the whole system is implemented on the MATLAB Simulink platform. In addition, to deal with the multiple ship encounters, the paper proposes a unique maximum-course and minimum-speed change approach for decision making, which has been found to be efficient to solve Imazu problems, and other complicated multiple-ship encounters.

Asthma causes chronic coughing, wheezing, dyspnea, and chest pressure. This study assessed asthmatic patients' knowledge, attitudes and awareness of bronchial asthma and proper education on its meaning, risk factors, symptoms, diagnosis, management, and prevention practice. We performed a cross-sectional interventional asthma KAP survey in Erbil, Iraq. We adapted a validated study questionnaire from KAP studies in other nations to the Erbil situation and culture. In Erbil, Kurdistan, Iraq, two major hospitals' asthma clinics were studied. We chose 250 asthmatic ICU patients from October 2018 to July 2019. Health education was comprehensive. The health education program used a Kurdish PowerPoint with a printout. 25 groups got two-weeks of one-hour health education pre-intervention. Each group was questioned before, 2 and 12 weeks after health education. All data were analyzed by SPSS v26. The mean age of the respondent was 37.52±15.16 with 48.7 % respondent having a positive family history of asthma. After 2weeks of health education intervention, respondent have a higher knowledge score, positive attitudes compared to pre-education and after 12 weeks of education with a significant difference (P < 0.001) with improvised prevention practice. Health education programs led to considerable improvements in asthmatic patients' knowledge, attitudes, and practices regarding their condition. After receiving health education for a period of two weeks, the majority of the participants answered correctly regarding asthma, its causes, and the elements that trigger asthma attacks.

Exact sequential state estimation of orbiting objects in space can be found by predicting the state using Fokker Planck Kolmogorov Equation (FPKE) and measurement correction using Bayes’ conditional/posterior Probability Density Function (PDF). Posterior PDF can be expressed as Gaussian density expanded in terms of Hermite polynomials named as Gram Charlier Series (GCS). This research is an extension of an earlier work on second order linearized solution to nonlinear Bayesian filtering using Taylor series and third order GCS expansion of posterior PDF. In this new extension, Bayes’ posterior PDF is approximated by a mixture of GCS functions for which the parameters are propagated using linear propagation theory. The update of weights of different components of GCS mixture model uses the FPKE error as feedback to adapt for the amplitude of different GCS components while solving a quadratic programming problem earlier used for Gaussian Mixture Model (GMM) PDF. Proposed filtering method is applied on tracking of space debris. The simulation results for the filter shows performance is moderately better than single GCS filter, Extended Kalman Filter (EKF) and Gaussian Sum Filter (GSF) under space debris’ highly uncertain initial conditions and sparse measurement availability.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive impairment and memory loss. Oxidative stress (OS) has emerged as a central element in the pathophysiology of AD, linking various pathological features including amyloid-β (Aβ) plaque formation, tau hyperphosphorylation, and synaptic dysfunction. This review comprehensively examines the role of OS in AD, focusing on the mechanisms of reactive oxygen species (ROS) production, mitochondrial dysfunction, and their impact on neuronal integrity. Additionally, the review highlights recent advances in antioxidant therapy. Elevated ROS levels in the aging brain exacerbate oxidative damage to lipids, proteins, and DNA, contributing to neuronal atrophy and synaptic loss. Mitochondrial dysfunction further amplifies OS, disrupting cellular energy metabolism and promoting neurodegeneration. Despite the strong association between OS and AD, antioxidant therapies have shown inconsistent clinical outcomes. Emerging strategies targeting offer promising avenues for therapeutic intervention. This review highlights the need for a multifaceted approach in understanding and mitigating OS-related damage in AD, aiming to pave the way for more effective treatments and improved patient outcomes.

This article aims to delve into the Equity, Diversity and Inclusivity (EDI) issues prevalent in the engineering disciplines in Canada and Spain, shedding light on the common obstacles faced by underrepresented individuals and highlighting potential strategies to foster a more inclusive and diverse engineering community in these nations. Two strategic lines have been identified: (a) facilitating university education access to underrepresented and minority groups, and (b) Accompanying and guiding such students during university training, setting them up for successful future careers. The article also shows the sets of strategies employed in Canada and Spain, clearly distinguishing the approach taken in the two countries. While in Canada, there is a more decentralized approach wherein the universities device their strategies and agenda to address EDI issues, in Spain there is a stronger and direct involvement of the government to ensure a comprehensive, system-wide approach to tackling EDI issues in academia.

The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E) and packet delivery ratio (PDR). The adverse effects of channel may cause data loss. Reducing delay up to possible extend improves the reliability of the network, also increasing the number of nodes in a particular network increase reliability. Besides, increasing the number of nodes improve reliability but also increase power consumption. In order to overcome these shortcomings, the two routing protocols are proposed in this paper, namely Delay and Reliability Aware Routing (DRAR) protocol and Cooperative Delay and Reliability Aware Routing (Co-DRAR) protocol for UWSNs. In DRAR protocol, network is divided into two equal regions where two sink nodes(SNs) are positioned at upper region of the network and two SNs are placed at the mid region of the network. The protocol choose the relay node based on residual energy (RE), distance and Bit Error Rate (BER). These parameters protect the data packets from corruption and also provide stable path (where nodes remain active for longer period and do not die quickly). The protocol uses single link and may get worse sometimes while changing channel circumstances. To address this problem, cooperative routing scheme is added to DRAR protocol in order to developed its enhanced version known as Co-DRAR protocol. The protocol works by allowing the destination to receive multiple copies of data packets in order to decide the quality of packets. The proposed protocols DRAR and Co-DRAR perform routing irrespective to geographical position of sensors nodes conversely to the some of conventional routing protocols that's way our propose protocol better perform than the well-known protocol i.e. Depth base routing (DBR) in terms of EC, E2E, PDR, dead nodes, packet drop ratio and number of alive nodes (ANs).

Keywords: Green human resource management1; Green supply chain management2; Regulation and legislation3; Sustainable development goals4.

Necrotizing pneumonia due to Methicillin-Resistant Staphylococcus Aureus (MRSA) is devastating and difficult to treat in preterm infants. We report a case of severe MRSA necrotizing pneumonia in a preterm infant. As an add-on rescue therapy to vancomycin, linezolid rapidly cured this case after the failure of vancomycin plus rifampicin. This rapid cure suggests that adjunctive rather than rescue linezolid may be considered in such cases.

Cell-penetrating peptides (CPPs) have been evaluated as enhancers in drug delivery, their addition in medical formulations favors absorption allowing obtaining the pharmacological effect with lower drug doses. In vaccine formulations their inclusion has been also explored with interesting results. Currently mucosal vaccination constitutes a promising alternative with the main advantage of inducing both systemic and mucosal immune responses, which are crucial for control tumors and infections at mucosal tissues. The known CPP Penetratin was recently evaluated in vaccine formulations designed for nasal administration. The authors demonstrated that this non-covalent linked CPP could improve the antigen-specific systemic and mucosal antibody responses. In the present work we evaluate in Balb/C mice the nasal immune-enhancing effect of four CPPs. Animals were intranasally immunized with CPP and the recombinant hepatitis B surface protein (HBsAg) as model antigen. The IgG antibody response in sera and the mucosal IgA response were measured by ELISA. The IFN-g secretion response at spleen was also evaluated by ELISPOT and ELISA. Among the CPPs studied one novel peptide stand out by its ability to potentiate the humoral and cellular immune response against the co-administered antigen. Considering that the use of mucosal routes is a promising strategy in vaccination against infectious diseases and cancer, which are gaining special relevance nowadays in the development of novel candidates against SARS-CoV-2 and other potential emerging respiratory virus, the searching and development of safe mucosal adjuvants constitute a current need.

In the Kingdom of Saudi Arabia (KSA), residential buildings’ energy consumption accounts for almost 50% of the building stock electricity consumption. The electricity generation consumes over one-third of the daily oil production. KSA was ranked as one of the highest countries in fossil fuel consumption per capita in 2014. Moreover, the KSA’s economy heavily relies on fossil fuel sources, namely oil reservoirs, whereby depletion will negatively affect the future development of the country. The total electricity consumption is annually growing by approximately 5-8%, which would lead to identical oil consumption to oil production in 2035. Currently, the KSA government is concerned to generate more renewable energy using large renewable energy plants. The government is investing in energy generation through renewable sources, by financing large scale photovoltaic farms to stop an economic crisis that may occur in 2035. The existing building stock consumes around 80% of the total current Saudi electricity that is generated. According to the Saudi energy efficiency report, the primary energy consumption per capita is over three times higher than the world average. Therefore, the residential buildings need further assessment as to their current energy consumption. This research used a survey to explore current user behaviour in residential buildings energy performance in the city of Jeddah, KSA. The findings of the survey showed: • The buildings thermal properties were found to be poorly designed • The majority of users within the buildings prefer a room temperature of below 24 °C, which requires a massive amount of cooling • Due to the climate conditions and the cultural aspects of KSA, housing units are occupied for more than 18 hours per day • An increase in user awareness has helped to slightly improve residential buildings energy efficiency Knowing the current high energy consumption sources and causes and being able to define available opportunities for further developments on building thermal properties enhancements and how to increase user awareness to reach self-sustaining buildings is essential.

In this paper we designed system for smart university building based on artificial intelligence (AI) and internet of things (IOT). Our idea can be summarized in smart security system that has different sensors to detect the surrounding environment of the class room in campus which keep everyone and everything on campus safer. By using (IOT), (AI) technologies and applications and by using microcontroller programming we can make the university building safer, secure and more energy saves.

Cancer treatment with specific chemotherapeutic agents has been well documented to have an adverse impact on female fertility leading to premature ovarian failure (POF). The objective of this study was to investigate if chemotherapeutic induced POF can be reversed with an infusion of autologous nucleated peripheral blood cells (PBMC). To reach our goal, mice were treated with a single intraperitoneal injections of busulfan and cyclophosphamide to induce POF. This was followed by transfusion of PBMC. The ovarian morphology and functional parameters were monitored by radioimmunoassay, real-time PCR, immunofluorescence and immunohistochemistry analysis. Our study showed that chemotherapy (CTX) protracted estrous cycle period and repressed E2 production. CTX decreased the expressions of steroidogenesis markers- CYP-17 synthesis, StAR and Connexin-43 protein expression from the ovarian follicles. We also observed reduced numbers and sizes of the primordial and primary follicles in CTX-treated mice compared to untreated controls (P < 0.05). When both CTX and untreated –control groups were stimulated with gonadotrophin, the control group produced ten times more ova than the CTX group. Finally, the treatment of premature ovarian failure induced by CTX with autologous PBMC transfusion resulted in over-expression and a statistically significant increase in several stem cell markers and restoration of fertility. Infusion with PBMC in CTX further decreased the estrous cycle length by 2.5 times (P < 0.01). We found that transfusion of autologous PBMC to mice with chemotherapy induced POF was very effective at restoring fertility. These results are similar to other studies using bone marrow derived mesenchymal stem cells.

Fossil fuels and carbon origin resources are affecting our environment. Therefore, alternative energy sources have to be established to co-produce energy along with fossil fuels and carbon origin resources until it is the right time to replace them. Microbial Fuel Cell (MFC) is a promising technology in the field of energy production. Compared to the conventional power sources it is more efficient and not controlled by the Carnot cycle. Its high efficiencies, low noise, and less pollutant output could make it revolutionize in the power generation industry with a shift from centrally located generating stations and long-distance transmission lines to dispersed power generation at load sites. In this review, several characteristics of the MFC technology will be highlighted. First, a brief history of abiotic to biological fuel cells and subsequently, microbial fuel cells is presented. Second, the focus is then shifted to elements responsible for the making MFC working with efficiency. Setup of the MFC system for every element and their assembly is then introduced, followed by an explanation of the working machinery principle. Finally, microbial fuel cell designs and types of main configurations used are presented along with scalability of the technology for the proper application.

In the quest for robust and efficient digital communication, this paper introduces cutting-edge key exchange protocols leveraging tropical semirings’ computational prowess and block matrices’ structural resilience. Moving away from the conventional use of finite fields, these protocols deliver markedly faster processing speeds and heightened security. We present two implementations of our concept, each utilizing a different platform for the set of commuting matrices: one employing tropical polynomials of matrices and the other employing Linde-de la Puente matrices. The inherent simplicity of tropical semirings leads to a decrease in operational complexity, and using block matrices enhances our protocols’ security profile. The security of these protocols relies on the Matrix Decomposition Problem. We also provide a comparative analysis of our protocols against existing matrix block-based protocols in finite fields. This research marks a significant shift in cryptographic protocol design, specifically tailored for demanding engineering applications, and sets a new standard in secure and efficient digital communication.

Green Stormwater Infrastructure (GSI), a sustainable engineering design approach for managing urban stormwater runoff, has long been recommended as an alternative to conventional conveyance-based stormwater management strategies to mitigate the adverse impact of sprawling urbanization. Hydrological and hydraulic simulations of small-scale GSI measures in densely urbanized micro watersheds require high-resolution spatial databases of urban land use, stormwater structures, and topography. This study presents a highly resolved Storm Water Management Model developed under considerable spatial data constraints. It evaluates the cumulative effect of the implementation of dispersed, retrofitted, small-scale GSI measures in a heavily urbanized micro watershed of Costa Rica. Our methodology includes a high-resolution digital elevation model based on Google Earth information, whose accuracy was sufficient to determine flow patterns and slopes, as well as to approximate the subsurface stormwater structures. The model produced satisfactory results in event-based calibration and validation, which ensured the reliability of the data collection procedure. Simulating the implementation of GSI shows that dispersed, retrofitted, small-scale measures could significantly reduce impermeable surface runoff (peak runoff reduction up to 40%) during frequent, less intense storm events and delay peak surface runoff 5-10 minutes. The presented approach can benefit stormwater practitioners and modelers conducting small scale hydrological simulation under spatial data constraint.

Aim: In individuals with COVID-19, the study assessed the relationship between cytokine expression and pulmonary dysfunction. These correlations may help to suggest strategies for prevention and therapies of coronavirus disease outbreak. Patients and methods: 50 healthy participants and 100 COVID-19 patients participated in this study. COVID-19 participants were subdivided into moderate and severe groups based on the severity of their symptoms. In both patients and controls, measurements of white blood cells (WBCs), lymphocytes, C-reactive protein (CRP), interleukin (IL)-1, IL-4, IL-6, IL-18, and IL-35 were estimated. All the patients performed chest CT and CO-RADS score was assessed. Results: All patients had increased WBCs count and CRP, IL-1, IL-4, IL-6, IL-18, and IL-35 levels than healthy controls. While WBCs, CRP, and cytokines like IL-1β and IL-6 showed significantly higher levels in the severe group as compared to moderate patients, IL-4, IL-35, and IL-18 showed comparable levels in both disease groups. Furthermore, CO-RADS score was positively connected with WBCs, CRP, and cytokine levels (IL-35, IL-18, IL-6, IL-4 and IL-1β) in both groups, and lymphocyte levels in all patient groups considerably decreased as compared to the controls. CO-RADS score, also demonstrated a positive correlation with lymphocytes in the moderate COVID-19 patients, whereas in the severe patients, it demonstrated a negative correlation with lymphocytes. Conclusion: Severe COVID-19 patients, compared to individuals with moderate illness and healthy controls, patients had lower lymphocyte counts and increased CRP with greater WBCs counts. In contrast to moderate COVID-19 patients, severe COVID-19 patients had higher levels of IL-1β and IL-6, but IL-4, IL-18, and IL-35 between both illness categories at close levels. CO-RADS 5 was the most frequent category in both moderate and severe cases. Patients with a typical CO-RADS involvement had a higher CRP and white blood cell count with a lower lymphocyte count than the others. Cytokine levels were considered a surrogate markers of severe lung affection in COVID 19 patients.

To face the high tolerance of biofilms to antibiotics, it is urgent to develop new strategies to fight against these bacterial consortia. We describe here an innova-tive antibiofilm nano vector, consisting of a Dispersin B-permethylated-β-cyclodextrin/ciprofloxacin adamantly (DspB-β-CD/CIP-Ad). For this purpose, complexation assays between CIP-Ad and (i) unmodified β-CD and (ii) different derivatives of β-CD, that are 2,3-O-dimethyl-β-CD, 2,6-O-dimethyl-β-CD, and 2,3,6-O-trimethyl-β-CD were tested. A stoichiometry of 1/1 was obtained for the β -CD/CIP-Ad complex by NMR analysis. ITC experiments were carried out to determine Ka, ΔH, ΔS thermodynamic parameters of the complex between β-CD or its different derivatives in the presence of CIP-Ad. A stoichiometry 1/1 of β-CD/CIP-Ad complexes was confirmed with variable affinity according to the type of methylation. A phase solubility study showed increased CIP-Ad solubili-ty with CDs concentration, pointing out complex formation. The evaluation of the antibacterial activity of CIP-Ad and the 2,3-O-dimethyl-β-CD/CIP-Ad or 2,3,6-O-trimethyl-β-CD/CIP-Ad complexes was performed on S.epidermidis strains. MIC studies showed that the complex of CIP-Ad and 2,3-O-dimethyl-β-CD exhibited similar antimicrobial activity to CIP-Ad alone, while the interaction with 2,3,6-O-trimethyl-β-CD increased MIC values. Antimicrobial assays on S. epidermidis biofilms demonstrated that the synergistic effect observed with the DspB/CIP association was partly maintained with the 2,3-O-dimethyl-β-CDs/CIP-Ad complex. To obtain this "all in one" nano vector, able to destroy the biofilm matrix and release the antibiotic simultaneously, we covalently grafted DspB on three carboxylic permethylated CD derivatives with different length spacer arms. The strategy was validated by demonstrating that a DspB-permethylated-β-CD/ciprofloxacin-Ad nanovector exhibited efficient antibiofilm activity.

Osteoarthritis is a painful, disabling condition which is increasing in prevalence as a result of an ageing population. With no recognised disease limiting therapeutics, arthroplasty of the hip and knee is the most common and effective treatment for lower limb osteoarthritis, however lower limb arthroplasty has a finite life-span and a proportion of patients will require revision arthroplasty. With increasing life expectancy and an increasing proportion of younger (<65 years) patients undergoing arthroplasty, the demand for revision arthroplasty after implant failure is also set to increase. Statins are cholesterol modulating drugs widely used for cardiovascular risk reduction which have been noted to have pleiotropic effects including potentially influencing arthroplasty survival. In vitro studies have demonstrated pleiotropic effects in human bone cells, including enhancement of osteoblastogenesis following simvastatin exposure, and in vivo studies have demonstrated that intraperitoneal simvastatin can increase peri-implant bone growth in rats following titanium tibial implant insertion. There is evidence also that statins may also influence osseointegration, enhancing bone growth at the bone-implant interface, subsequently improving the functional survival of implants. Data from the Danish Hip Arthroplasty Registry and Clinical Practice Research Datalink in the UK suggest a reduction in the risk of lower limb revision arthroplasty in statin ever-users vs never users, and a time dependent effect of statin administration on reduction in risk of revision. In this article we review the clinical and scientific evidence linking statins and risk of revision arthroplasty.

This study examines the role of using algorithmic HRM to make strategic decisions pertaining to HR activities in organizations. The study develops a scale to measure algorithmic HRM usage in its first phase, and in the second phase, it finds that algorithmic HRM having significant impact on the strategic HR decision making that helps and enables organization in creating the competitive advantage. Utilizing the author’s LinkedIn profile, 234 final participants considered for this research. Collected data analyzed by applying PLS SEM. It evaluates the mediation role of the HR strategic decision making, and the HR digital maturity as a moderator in seeing the impact of algorithmic HRM on the competitive advantage of the firm. The study finds a strong relationship between the algorithmic HRM usage and competitive advantage, a significant relationship between algorithmic HRM usage and the strategic HR decision making, and lastly, a significant relationship between strategic HR decision making and the competitive advantage. The moderating role of HR digital maturity was found to be insignificant in this research which paves the way for further research. This research, the model, and its findings contribute to the theory and implicate the practicality of algorithmic HRM. It's one of few papers that address the algorithmic HRM usage in the transitioning economy like Saudi Arabia.

Climate change and development have increased urban flooding, requiring modernization of stormwater infrastructure. Retrofitting standard passive systems with controllable valves/pumps is promising, but requires real-time control (RTC). One method of automating RTC is reinforcement learning (RL), a general technique for sequential optimization and control in uncertain environments. The notion is that an RL algorithm can use inputs of real-time flood data and rainfall forecasts to learn a policy for controlling the stormwater infrastructure to minimize measures of flooding. In real-world conditions, rainfall forecasts and other state information, are subject to noise and uncertainty. To account for these characteristics of the problem data, we implemented Deep Deterministic Policy Gradient (DDPG), an RL algorithm that is distinguished by its capability to handle noise in the input data. DDPG implementations were trained and tested against a passive flood control policy. Three primary cases were studied: (i) perfect data, (ii) imperfect rainfall forecasts, and (iii) imperfect water level and forecast data. Rainfall episodes (100) that caused flooding in the passive system were selected from 10 years of observations in Norfolk, Virginia, USA; 85 randomly selected episodes were used for training and the remaining 15 unseen episodes served as test cases. Compared to the passive system, all RL implementations reduced flooding volume by 70.5% on average, and performed within a range of 5%. This suggests that DDPG is robust to noisy input data, which is essential knowledge to advance the real-world applicability of RL for stormwater RTC.

Pneumonia kills over two million children under-age of five every year. Oral amoxicillin was recommended by WHO as the first drug of choice for treatment of non-severe pneumonia. The study aimed to determine the clinical failure rate of amoxycillin for the treatment of childhood non-severe pneumonia at Primary Health Care Centers (PHCCs). A randomized controlled multicenter-trial study was conducted in Sana’a. IMCI strategy was used to enrollments the cases where randomly allocated to receive amoxicillin or co-trimoxazole orally for five days. Multivariate logistic regression was used for identified risk factors associated with clinical failure. A total of 254 children were enrolled, of whom 128 cases were treated with amoxicillin while 126 with co-trimoxazole. The clinical failure for amoxicillin was significantly more than co-trimoxazole (30% vs 10%) p value > 0.001. the most risk factor which significantly associated to amoxicillin failure were pre-infection in the last 6 months, while abnormal CBC and literate mothers were associated with clinical failure of co-trimoxazole (p value > 0.05). The use of co-trimoxazole as an alternative to amoxicillin for the treatment of non-severe pneumonia in the PHCCs and conducting further studies to determine the appropriate antibiotic as the first line of defense are recommended.

Artificial insemination (AI) is considered as the most efficient feasible tool to improve the dairy cows’ profitability and productivity. In bovines, AI helps to promote genetic improvement and can positively impact the rural economy. The achievement of education in rural populations was one of the Millennium Development Goals (MDGs), made by the United Nations. During the last World Summit on Sustainable Development (WSSD), it was concluded that most of the world’s poor, illiterate and undernourished population lives in rural areas; therefore, access to education is considered one of the greatest challenges for governments in countries with developing economies. To determine the effects of a theoretical-practical training program related to rural management and leadership, AI, and bovine genetic improvement, on the perception and level of knowledge in a rural Colombian population that has been affected by the armed conflict. Phase 1. Included the practical and theoretical training of undergraduate animal sciences students in three dimensions rural management; leadership (D-ML), AI in bovines (D-AI), and genetic improvement (D-GI) after training students were evaluated and selected according to their skills, characteristics, solidarity skills, and their social sensitivity was identified. Phase 2. Included the socioeconomic characterization and training of rural residents by students and field experts in three dimensions D-ML, D-AI, and D-GI. After training we evaluated the perception and level of knowledge before and after training in 63 rural residents using an evaluative instrument. The data before and after (post-test) of the theoretical-practical training, were analyzed to obtain a statistical significance. The perception of knowledge in rural residents was low for general knowledge (2.48±0.76, p ˂ 0.05), D-ML (2.89±1.18, p ˂ 0.05) and D-AI and D-GI (2.17±0.83, p ˂ 0.05). On the other hand, before the theorical-practical training the level of general knowledge was 45.9%, however, after the training increased at 77.6% (p<0.01), while the level of knowledge for the D-AI was increased from 38.5 % to 80.6 % (p ˂ 0.05) after training. Regarding the level of knowledge for the D-GI pre-training was 50.8 and increased to 73.0% (p<0.01) then after. Finally, the level of knowledge for the D-ML was increased (p<0.01) from 54.8 before training to 75% after training. Altogether, the rural extension programs contribute to the closing of knowledge gaps in relation to the use of reproductive biotechnologies and bovine management in rural areas affected by armed conflict.

Magnetorheological elastomers (MREs) are a type of smart material that can change their mechanical properties in response to external magnetic fields. These unique properties make them ideal for various applications, including vibration control, noise reduction, and shock absorption. This paper presents an approach for modeling the impact behavior of MREs. The proposed model uses a combination of exponential functions arranged in a multi-layer Preisach model to capture the nonlinear behavior of MREs under impact loads. The model is trained using particle swarm optimization (PSO) and validated using experimental data from drop impact tests conducted on MRE samples under various magnetic field strengths. The results demonstrate that the proposed model can accurately predict the impact behavior of MREs, making it a useful tool for designing MRE-based devices that require precise control of their impact response. The model's response closely matches the experimental data, with a maximum prediction error of 10% or less. Furthermore, the interpolated model's response shows good agreement with the experimental data, with a maximum percentage error of less than 8.5%.

Neuronal timing is critical for many brain functions such as perception and learning. At the level of the chemical synapse, the synaptic delay is determined by the presynaptic release probability (Pr) and the waveform of the presynaptic action potential (AP). Depolarization-induced analogue-digital facilitation (d-ADF) is a form of context-dependent synaptic facilitation that is induced by constant depolarization of the presynaptic neuron and is mediated by voltage inactivation of presynaptic Kv1 channels. Whether synaptic delay is modulated during d-ADF remains unclear. We show here that despite Pr is elevated during d-ADF at L5-L5 synapses, the synaptic delay is surprisingly unchanged, suggesting that both Pr- and AP-dependent changes in synaptic delay compensate for each other. We conclude that in contrast with other short- or long-term modulation of presynaptic release, timing is not affected during d-ADF because of the opposite interaction of Pr- and AP-dependent modulations of synaptic delay.

In addition to identifying and prosecuting cyber attackers, attack attribution activities can provide valuable information guiding the defenders’ security procedures and giving them greater confidence in incident response and remediation. However, technical analysis involved in cyberattack attribution requires high skills, experience, access to up-to-date Cyber Threat Intelligence, and significant investigators’ effort. Attribution results are not always reliable, and skilful attackers often work hard to cover their traces and mislead or confuse investigators. In this article, we present a tool designed to support technical attack attribution and implemented as a machine learning model extending the OpenCTI platform. We also discuss the tool’s performance in the investigation of a recent cyberattack.

Almost all modern inorganic light-emitting diode (LED) designs are based on double heterojunctions (DHJs) whose structure and current injection principle have remained essentially unchanged for decades. Although highly efficient devices based on the DHJ design have been developed and commercialized for energy-efficient general lighting, the conventional DHJ design requires burying the active region (AR) inside a pn-junction. This has hindered the development of emitters utilizing nanostructured ARs located close to device surfaces such as nanowires or surface quantum wells. Modern DHJ III-N LEDs also exhibit resistive losses which arise from the DHJ device geometry. The recently introduced diffusion-driven charge transport (DDCT) emitter design offers a novel way to transport charge carriers to unconventionally placed ARs. In a DDCT device, the AR is located apart from the pn-junction and the charge carriers are injected into the AR by bipolar diffusion. This device design allows the integration of surface ARs to semiconductor LEDs and offers a promising method to reduce resistive losses in high power devices. In this work, we present a review of the recent progress in gallium nitride (GaN) based DDCT devices, and an outlook of potential DDCT has for opto- and microelectronics.

Understanding how the public perceives various risks and hazards associated with our well-being and health is crucial for government and policymakers. The present research aimed to assess the public's perception of various risks and hazards associated with their well-being and health. The study combined two well-known approaches to risk assessment, namely, the analytical hierarchical process (AHP) and the psychometric paradigm. Seven risk attributes were chosen from the risk perception literature to evaluate 27 risks and hazard activities using a survey questionnaire developed based on the psychometric paradigm literature. The collected data was then analyzed using AHP to determine the priority weight for each risk attribute. The results showed that the most important risk attribute was voluntariness of risk, followed by chronic-catastrophic and newness of risk. Furthermore, the study found that natural hazards were ranked the highest, followed by refugee influx and fire hazards. In contrast, the mobile phone was perceived as the lowest type of risk. The findings can be used by policymakers to develop effective and sustainable risk communication strategies. Policymakers can use the research findings to create effective and sustainable risk communication strategies that help the government to inform and educate the public about potential risks, improve coordination among agencies and stakeholders, and enhance public trust in government decision-making.

The present work focuses on developing miniaturized, light weight electrochemical sensors for detection of chemical warfare agents (CWAs) like sarin and tabun simulants, i.e., diisopropyl fluorophosphate (DFP), and O,S-diethyl methyl phosphonothioate (O,S-DEMPT). Differential pulse voltammetry (DPV) was employed to examine the redox properties of capturing molecular probe CE2 with the nerve agent stimulants. Coupling of a portable potentiostat with the drone technology could allow on-situ and remote detection of analytes such CWAs to be realized, which can be crucially important to the national and global securities.

Avian Metapneumovirus (aMPV) is a significant poultry pathogen with a global presence, primarily causing respiratory issues in turkeys. It also affects chickens, although the severity of its impact is often lessened in this species. In Morocco, aMPV has been detected in broiler flocks, prompting the need to deeply analyze circulating strains to understand better the epidemiology and develop control measures accordingly. This research focuses on the sequencing and molecular characterization of aMPV in these flocks. Additionally, aMPV isolated from turkeys displaying Turkey Rhinotracheitis (TRT) signs, were included in the study to compare the findings. RNA extracted from positive swabs was subjected to nested PCR, targeting the attachment protein of the G gene, followed by gel electrophoresis. Amplicons were purified and sequenced using the Sanger method. Bioinformatics tools facilitated sequence analyses, including BLAST for similarity searches and Mega® for phylogenetic analysis using the maximum likelihood method with 1000 bootstrap replicates. The investigation unveiled the existence of three distinct clades of the same aMPV/B strain, two of which originated from used vaccines and one from field recombination, all circulating in broilers and turkeys and indicating potential virus transmission between both poultry species. This article presents the first-ever molecular characterization of aMPV isolated from Moroccan broilers and turkeys, encompassing comprehensive investigations on its presence and subtype, and genetic characterization.

The present study focuses on the synthesis, characterization, and investigation of a p-n heterojunction photocatalysis. Titanium dioxide (TiO2) can’t alone induce the photocatalytic water splitting due to its wide bandgap, which decreases its catalytic activity in the visible light. To make redshift of absorptivity for the TiO2, Nickel (Ni)-doped Graphene (rGO) supported TiO2 was synthesized. Several characterization techniques have been employed to validate the composition and the light absorption ability of the prepared photocatalysts including TEM, SEM, EDS, XRD, XPS, and UV-Vis spectroscopy. The characterization revealed successful doping of the Ni and TiO2 on the rGO nanosheet. Moreover, the UV-Vis spectroscopy indicated a significant shift of light absorption toward the visible spectrum. The photon-induced evolution of H2 was remarkably enhanced using the prepared Ni-rGO/TiO2 nanocomposite. Furthermore, the optimum ratio of rGO: TiO2: Ni in the hybrids was 10:1:4, while the higher Ni ratio would decrease the photocatalytic activity. The stability of the photocatalyst was also verified during 8 cycles of photocatalytic reactions. The kinetic study revealed the nature of the integrated reaction and the controlling step governing the reaction sequence. .

This study aimed to develop chitosan-based apigenin spray dried solid dispersion using 1:1,1:1.5,1:2 w/w ratios. The results of process yield and drug assay were found to be (87.5%, 94.2%, and 95.86%), (95.2 ±1.34%), (99.5 ±0.85%), and (97.6 ±2.42%), respectively, for AC1, AC2, and AC3. Flow properties indicate the free flow of powders. FTIR revealed compatibility among chitosan and apigenin, and DSC and XRD showed prepared solid dispersion was on a molecular level and available in amorphous. In contrast, SEM images reflect irregular block and near-spherical shape elongated particles in the selected AC2. The antimicrobial examination reflects that AC2 was more effective against Gram-positive, negative, and fungal strains. AC2 SDSDs has more anti-oxidant property compared to pure flavonoid (AGN). Anti-proliferative activity against A549 lung cancer cell lines showed better anti-cancer activity by AC2 SDSDs. The selected AC2 SDSD filled in a 3D shell pill and further characterized for 3D shell pill for dissolution profiles and stability studies. The product has sustained release and similar release profiles after three months of storage. The findings suggest that the AC2 SDSDs may be a promising candidate for further development as a 3D printed drug delivery system for treating multiple disease conditions using model flavonoid- apigenin.

Water pollution is regarded as a dangerous problem that needs to be resolved right away. This is largely due to the positive correlation between the increase in global population and waste production, especially food waste. Hydrogel beads based on sodium alginate (Alg) and pomegranate fruit peels (PP) were developed for the adsorption of Safranin O dye (SO) in aqueous solutions. The obtained Alg-PP beads were widely characterized. The effects of the contact time (0-180 min) and initial concentration (10-300 mg/l), the initial pH (2-10), the adsorbent dosage (1-40 g/l) and the temperature (293-333 K) were investigated through batch tests. The data proved that the adsorption kinetics of SO reached equilibrium within 30 min and up to 180 min. The adsorption data of SO onto synthesized beads follow the pseudo second-order model. The experimental data fitted very well to both Freundlich and Langmuir models. The maximum adsorption capacity of Alg-PP could reach 8.99 mg/g at 293 K. Calculation of Gibbs free energy and enthalpy indicated that adsorption of SO onto Alg-PP is spontaneous and endothermic. Finally, analysis of diffusion and mass transport phenomena were presented. The reported results revealed that the Alg-PP beads could be used as a novel natural adsorbent for the removal of cationic dye pollutants from aqueous environments.

Generative artificial intelligence (GenAI) has been developing with many incredible achievements like ChatGPT and Bard. Deep generative model (DGM) is a branch of GenAI, which is preeminent in generating raster data such as image and sound due to strong points of deep neural network (DNN) in inference and recognition. The built-in inference mechanism of DNN, which simulates and aims to synaptic plasticity of human neuron network, fosters generation ability of DGM which produces surprised results with support of statistical flexibility. Two popular approaches in DGM are Variational Autoencoders (VAE) and Generative Adversarial Network (GAN). Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. In this research, VAE and GAN is unified into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is good at generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. In other words, AVA aims to improve accuracy of generative models, besides AVA extends function of simple generative models. In methodology this research focuses on combination of applied mathematical concepts and skillful techniques of computer programming in order to implement and solve complicated problems as simply as possible.

Fault detection is an important step for subsurface interpretation and reservoir characterization from 3D seismic images. Due to the numerous and complicated faulting structures of seismic images, manual seismic interpretation is time taking and need intensive work. To overcome this problem, geoscientists are coming up with productive computer-aided techniques for assisting in interpreter science for many years. However, in this paper, we used a pre-trained CNN model to predict faults from the 3D seismic volume of the Poseidon field of Browse Basin, Australia. Basically, this field is highly structured with complex normal faulting throughout the targeted Plover Formations. So, our motivation for this work in this field is to compare machine learning-based fault prediction to user interpreted faults identification with supported by seismic variance attribute. We found very satisfying result using DL with having an improved fault probability volume that outperform variance technology. Therefore, we propose that this workflow could reduce time and able to predict fault quite accurately in any field area.

Aquathermolysis is a promising method to upgrade heavy oil in reservoir conditions. However, application of catalysts can significantly promote transformation of the heavy fragments (resins and asphaltenes) and heteroatom-containing compounds of crude oil mixture into low-molecular-weight hydrocarbons. In this paper, the comparison study of the catalytic performance of the water-soluble metal salts such as NiSO4 and FeSO4 on the aquathermolytic upgrading of heavy oil samples produced from Ashal’cha reservoir was carried out at a temperature of 300 °C for 24 hours. Iron nanoparticles contributed to the highest viscosity reduction degree - 60% in contrast to the viscosity of the native crude oil sample. The viscosity alteration is reasoned by the changes in the group composition of heavy oil after catalytic (FeSO4) aquathermolysis, where the content of resins and asphaltenes were reduced by 17% and 7%, respectively. Moreover, the aquathermolytic upgrading of heavy oil in the presence of FeSO4 led to an increase in the yield of gasoline fraction by 13% and diesel fraction by 53%. The H/C ratio, which represents the hydrogenation of crude oil, increased from 1.52 (before catalytic upgrading) to 1.99 (after catalytic upgrading). The results of Chromatomass (GC-MS) and Fourier-infrared (FT-IR) spectroscopies confirmed the intensification of destructive hydrogenation of resins and asphaltenes in the presence of the water-soluble catalysts. According to XRD and SEM-EDX results, the metal salts are thermally decomposed during the aquathermolysis process into the oxides of corresponding metals and particularly sulfided by the sulfur-containing aquathermolysis products.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

Nizatidine is a gastroprotective drug with a short biological half-life and narrow absorption window. This study aimed at developing floating tablets of nizatidine using various HPMC viscosity grades, namely K4M, E4M, K15 and K200M. Directly compressed tablets revealed an excellent uniformity in hardness, thickness and weight and nizatidine was evenly distributed within the matrix floating tablets. Buoyancy study revealed floating lag time as low as 18–38 s, and tablets remain buoyant for upto 24 h. However, the later depended upon viscosity grade of HPMC and that the higher the viscosity, the less was the total floating time. In vitro dissolution indicated viscosity dependent nizatidine release from the floating tablets. HPMC K4M and E4M based floating tablets released almost 100% drug in 12 h, whilst higher viscosity polymers such as K15 and K200M only released 81.88% and 75.81% drug, respectively. The drug release followed non-Fickian diffusion from tablets formulated with K4M, K15 and K200M, whilst super case II transport was observed with E4M based tablets. More interestingly, K4M and E4M polymers have similar viscosity yet exhibited different drug release mechanism. This was attributed to the difference in degree of substitution of methoxyl- and hydroxypropoxyl- groups on polymer backbone.

In this paper a novel and flexible solution for fault prediction based on data collected from Supervisory Control and Data Acquisition (SCADA) system is presented. Generic fault/status prediction is offered by means of a data driven approach based on a self-organizing map (SOM)and the definition of an original Key Performance Indicator (KPI). The model has been assessed on a park of three photovoltaic (PV) plants with installed capacity up to 10 MW, and on more than sixty inverter modules of three different technology brands. The results indicate that the proposed method is effective in predicting incipient generic faults in average up to 7 days in advance with true positives rate up to 95%. The model is easily deployable for on-line monitoring of anomalies on new PV plants and technologies, requiring only the availability of historical SCADA data, fault taxonomy and inverter electrical datasheet.

Climate change is affecting the planet, compromising survival and altering forest ecosystems. Investigating climatic variations in all regions is important. The aim of this research was to assess such variations in the W and Pendjari Biosphere Reserves in Benin from 1985 to 2015 and predict climate up to 2045. Drought frequency was assessed by using the Standardized Precipitation and Evapotranspiration Index (SPEI) and correlation was performed between climatic variables. Then a predictive analysis was computed. From 1985 to 2015, there was change in the climate with few severe dry and wet years while no extreme climatic condition was noticed. Most of the years showed nearly normal climatic conditions. The predicted climate indicates an absence of extreme conditions up to 2045 but an increase in the annual humidity is expected. A low decrease in annual mean temperature with high confidence is expected. Decision-makers can better organize adaptation programs and sensitize people in the reserves on their role in environmental conservation and mitigation of climate change using these outputs.

Chronic Myeloid Leukemia, resulting due to chromosomal aberration t(9;22) through formation of oncogenic BCR-ABL fusion oncogene. Modern BCR-ABL inhibitors, called TKIs, have revolutionized CML treatment. CML has three stages: chronic, accelerated, and blast crisis. TKIs work well in CP-CML, where patients survive as long as the normal population, but they don't work in AP- and BC-CML. Even with advances in treatment, BC-CML has an average overall survival of less than a year, giving oncologists little time to clinically intervene. Oncologists can delay or prevent CML advancement by detecting patients at risk of disease progression early and making timely treatment decisions, especially with third and fourth generation TKIs. However, no universal molecular biomarkers exist to diagnose CML patient groups at risk of disease progression. A recent study found that all BC-CML patients have mutant FANCD2. Our study was designed to detect mutant FANCD2 in AP-CML (early progression phase) to investigate its potential as a novel biomarker of early CML progression from chronic phase to accelerated phase due to the urgent need for such a biomarker. Our study comprised of 123 CP-CML (control group) and 60 AP-CML patients (as experimental group) from Hayatabad Medical Complex, Peshawar, Pakistan, from Jan 2020 to July 2023. DNA was extracted from the patients and FANCD2 gene was sequenced using Illumina next generation sequencer (NGS) Illumina MiSeq sequencer. NGS analysis revealed a unique splice site mutation in FANCD2 gene (c. 2022-5C>T). This mutation was detected in all CP-CML patients but in none of CP-CML. The mutation was confirmed by Sanger sequencing. FANCD2 is member of Fanconi anemia (FA-) pathway gene involved in DNA repair and genomic instability. Therefore, our studies show that FANCD2 (c. 2022-5C>T) mutation as a very specific molecular biomarker for early CML progression. We recommend to clinical validate this biomarker is prospective clinical trials.

In conclusion, the present study demonstrated the safety of practicing WFM at different TOD. Furthermore, it appears that practicing WF in the evening is safer, as indicated by HRR60s, [Gl], and MBP findings. The utilization of digital biomarkers for monitoring health status during WFM has been shown to be efficient.

Currently, narrowband Power line communication (PLC) is considered as an attractive communication system in smart grid environments for applications such as advanced metering infrastructure (AMI). In this paper, we will present a comprehensive comparison and analysis in time and frequency domain of noise measured in China and Italy. In addition, impulsive noise in these two countries are mainly analyzed and modeled using two probability based models, Middleton Class A (MCA) model and \(\alpha\) stable distribution model. The results prove that noise measured in China is rich in impulsive noise, and can be modeled well by \(\alpha\) stable distribution model, while noise measured in Italy has less impulsive noise, and can be better modeled by MCA model.

This study evaluates the effectiveness of Darknet53 and VGG16 pretrained models to develop a hybrid ensemble model named HybridPlantNet23 deep learning model for effective plant disease classification, using the publicly available dataset ‘A Dataset of Leaf Images’ from Mendeley webpage. The preprocessing of the dataset involved resizing the images to the respective requirements of the pretrained models to develop a combined datastore which served as the input. All experiments were conducted using MATLAB R2023b deep network designer interface. Model performances were evaluated based on the conventional accuracy, precision, recall, and F1-score. VGG16 achieved the highest accuracy (97.25%), precision (96.30%), recall (96.96%), and F1-score (96.55%), outperforming both Darknet53 and the ensemble HybridPlantNet23 model. Despite the advanced architecture of the ensemble model, its performance (accuracy: 95.37%, precision: 93.56%, recall: 94.20%, F1-score: 93.74%) was not significantly superior, thus highlighting scientific reasons behind this development. Recommendations for future works were provided accordingly.

Purpose: The study aimed to investigate if there were any links between liver function biomarkers and immunoglobulins levels in serum, and Toll-like receptors (TLRs) and neuropilin-1 (NRP1) in COVID-19 patients. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) by the receiver operator curve (ROC) analysis for immunoglobulins levels and TLRs expressions. Patients and Methods: This study included 150 patients (100 patients with confirmed COVID-19 and 50 healthy volunteers as a control group). Patients with COVID-19 were subdivided into two groups according to the severity of symptoms (moderate and severe, with 50 patients each). Serum C-reactive protein (CRP), alanine aminotransaminase (ALT), aspartate aminotransaminase (AST), albumin, lactate dehydrogenase (LDH), immunoglobulin (Ig) G, and IgM levels were estimated. TLRs (TLR2 and TLR4) and NRP1 gene expression in blood samples were investigated using quantitative real-time polymerase chain reaction (qRT-PCR). ROC analysis was also applied to determine the accuracy of various detected parameters in predicting the possibility of COVID-19 infection. Results: In COVID-19 patients, serum parameters related to liver function, except serum albumin, CRP, IgG, IgM, and TLR2, TLR4, and NRP1 mRNA expression levels, significantly elevated compared to controls. Severe COVID-19 patients exhibited significantly higher liver enzymes (ALT, AST and LDH), CRP, and TLR2 mRNA expression levels and lower albumin levels than the moderate group. In the moderate and severe groups, ALT, CRP, TLR2, and TLR4 had a significant positive correlation with IgM levels. ALT, AST, LDH, CRP, TLR2, and TLR4 showed a significant positive correlation with IgG levels in both groups. In both the moderate and severe groups, NRP1 expression was found to be significantly correlated with CRP, IgG, IgM, TLR2, and TLR4. In contrast, serum albumin levels exhibited a significant negative correlation with IgG and IgM levels only in the severe group, but they showed a significant negative correlation with TLR2, TLR4, and NRP1 expression in both moderate and severe groups. Serum ALT and AST activities were positively correlated with NRP1 expression in the moderate group but not in the severe group and as well as TLR2 and TLR4 expression in both the moderate and severe groups. ROC analysis indicated that AUC was higher than 0.800 for serum IgM level and TLR4 gene expression in moderate COVID-19 group. Conclusions: The increased liver function biomarkers in serum and NRP1 expression are closely correlated with sustained activations in humoral and innate immune responses during COVID-19 infection. As a result, TLR2, TLR4, and NRP1 could be targets for limiting COVID-19 infection and impairment effects on liver function. Moreover, detection of IgM level in serum and TLR4 expression in blood have a good accuracy in predicting the possibility of infection with COVID-19 in moderate cases.

Abstract Background: Most cardiac metastases emerge from primary lung, breast, and hematologic malignancies. The clinical manifestations of cardiac metastasis vary depending on tumor location and size. Cardiac metastasis from cervical squamous cell carcinoma is extremely rare and is mostly found on autopsy. We report a case of cervical cancer metastasis to the interventricular septum. Case Summary. This report discusses the case of a 48-year-old woman with interventricular septal metastases, originating from squamous cell carcinoma of the cervix. The woman came to our hospital after experiencing a fainting spell. Her hospital stay was notable for a brief syncopal event during a 30-second asystole episode, which ended spontaneously. Upon awakening, she reported severe chest pain. In response, she was quickly taken to the catheterization laboratory. There, a coronary angiography revealed an 80% blockage in her left anterior descending artery. Two years prior, our patient was diagnosed with invasive squamous cell cervical carcinoma with PET/CT showing no evidence of metastatic disease. A repeat PET/CT scan was done following cardiac catheterization and was significant for a mass along the interventricular septum of the heart. Discussion. Cardiac metastasis from primary cervical squamous cell carcinomas is scarcely reported in medical literature. Among these rare cases, the majority involved the right ventricle, with only three involving the left ventricle. There are no documented instances of metastasis to the interventricular septum. To our knowledge, this would be the first such case.

Objective Ovarian pregnancy is a rare but well-known pathology. However, pathophysiology, diagnosis and treatment are not clearly established. Data sources. All case reports published in Pubmed from Nov 2011 till Nov 2022. Study eligibility criteria. A systematic review and 2 case reports of ovarian pregnancy Study appraisal and synthesis methods. Not applicable Results Ovarian pregnancies occur in 8% of women without or blocked oviducts and in 23% on the other side than the corpus luteum and the symptoms of ovarian pregnancies are not specific. Therefore ovarian pregnancy has to be suspected in all women with abdominal bleeding. As for extrauterine pregnancies, the presence of an intrauterine pregnancy does not rule out an ovarian pregnancy. Surgical excision is the preferred treatment. Important is that in women with both an intra-uterine and an ovarian pregnancy, care should be taken not to damage the corpus luteum. Conclusions Ovarian pregnancies can occur in women with blocked tubes, on the other side of the corpus luteum, in the presence of an intrauterine pregnancy, and even when pregnancy tests or tranvaginal ultrasonography are negative. The diagnosis being difficult to exclude, a laparoscopy is indicated in all women with intra-abdominal bleeding, keeping in mind that an intra-uterine pregnancy cannot be exluded and that a corpus luteum need to be respected.

Structural DNA nanotechnology provides an excellent foundation for diverse nanoscale shapes that can be used in various bioapplications and materials research. From all existing DNA assembly techniques, DNA origami has proven to be the most robust one for creating custom nanoshapes. Since its invention in 2006, building from the bottom up using DNA has drastically advanced, and therefore, more and more complex DNA-based systems have become accessible. So far, vast majority of the demonstrated DNA origami frameworks are static by nature, but interestingly, there also exist dynamic DNA origami devices that are increasingly coming into view. In this review, we discuss DNA origami nanostructures that perform controlled translational or rotational movement triggered by predefined DNA strands, various molecular interactions and/or other external stimuli such as light, pH, temperature and electromagnetic fields. The rapid evolution of such dynamic DNA origami tools will undoubtedly have a significant impact on molecular scale precision measurements, targeted drug delivery and diagnostics, but they can also play a role in development of optical/plasmonic sensors, nanophotonic devices and nanorobotics for numerous different tasks.

Integrating numerous renewable resources has been extensively researched and studied to create a dependable energy system. This study investigated the best techno-economical hybrid energy system configuration while using hydrogen energy to keep the system's energy balanced. Additionally, this study aims to determine the best hybrid system configuration for the location under investigation. A novel technique of DBM (Deterministic Balanced Method) was introduced to determine the total annual energy output for the project's lifetime. This approach is used to contrast the outcomes of other HOMER software tools. Then, using HOMER, it is possible to confirm the sizing optimization results for the suggested method by comparing the power ratings and yearly energy output. A detailed comparison between our proposed method and HOMER Pro has been conducted for validation and verification. Our method has been rigorously tested in various hybrid off-grid energy systems, ensuring its applicability and reliability across different scenarios and configurations. The results of our study indicate a high degree of similarity between the proposed approach and HOMER pro for computing annual energy power for the studied energy systems. Specifically, our analysis revealed that the difference between the approaches was within a range of 5%, indicating a high level of consistency and reliability in our method. These findings suggest that our approach can be confidently applied to determine the appropriate size of hybrid energy systems accurately. Overall, our study provides valuable insights into the development of effective sizing methodologies for hybrid energy systems. After considering the amount of solar radiation and wind speed gathered by global weather data platforms like NASA and METEONORM, this paper has also included a real case study of the Cairo International Airport's hybrid renewable energy production systems. To guarantee the viability of this study, the system design was founded on an actual load that was researched and simulated. A cluster of distributed networks was finally proposed to use the excess energy and enable energy conversion processes to be used in industry and transportation applications.

This study aimed at assessing the extent to which the Saudi general population has embraced digital health medical applications to meet their health-related needs so that the Saudi Ministry of Health and government can appropriately be guided on scaling up of digital health across the country. As such, this study was guided by the question of to what extent do the Saudi people use digital health mobile-based applications?. This was a cross-sectional study utilizing snowballing sampling approach. Frequencies, Chi-square, and Spearman rank correlation statistics were used to offer descriptive and inferential analysis of the variables. The majority of the participants were economically able to afford smart devices that have medical apps, had at least an app on such devices, and highly regarded the benefits of the apps. Unfortunately, their understanding of how to use such apps was limited and this posed a barrier to embracing digital health alongside difficulty downloading apps, and medical ethical concerns. Although there is a willingness, extra effort is needed from the Saudi Ministry of Health and government to promote the uptake of digital health in Saudi Arabia.

Long unpunctuated texts containing complex linguistic sentences are a stumbling block to processing any low-resource languages. Thus, approaches that attempt to segment lengthy texts with no proper punctuation into simple candidate sentences are a vitally important preprocessing task in many hard-to-solve NLP applications. In this paper, we propose (PDTS) a punctuation detection approach for segmenting Arabic text, built on top of a multilingual BERT-based model and some generic linguistic rules. Furthermore, we showcase how PDTS can be effectively employed as a text tokenizer for unpunctuated documents (i.e., mimicking the transcribed audio-to-text documents). Experimental findings across two evaluation protocols (involving an ablation study and a human-based judgment) demonstrate that PDTS is practically effective in both performance quality and computational cost.

In this study, the temporal variation in soil salinity dynamics was monitored and analyzed using Electromagnetic Induction (EMI) in an agricultural area in Port Said, Egypt, which is at risk of soil salinization. To assess soil salinity, repeated CMD2 soil apparent electrical conductivity (ECa) measurements were taken and inverted to generate electromagnetic conductivity imaging (EMCI), representing soil electrical conductivity (σ) distribution through time-lapse inversion. This process involved converting EMCI data into salinity cross sections using a site-specific calibration equation that correlates σ with the electrical conductivity of saturated soil paste extract (ECe) for the collected soil samples. The study was performed from August 2021 to April 2023, involving six surveys during two agriculture seasons. The results demonstrated the accurate prediction ability of soil salinity with R2 value of 0.81. The soil salinity cross sections generated on different dates observed changes in the soil salinity distribution. These changes can be attributed to shifts in irrigation water salinity resulting from canal lining, winter rainfall events, and variations in groundwater salinity. This approach is effective for evaluating agricultural management strategies in irrigated areas where it is necessary to continuously track soil salinity to avoid soil fertility degradation and a decrease in agricultural production and farmer’s income.

Bread wheat (Triticum aestivum L.) is staple of Pakistani people. However, its yield at farmer field is low as compared with its genetic potential. Integration of various crop and soil management strategies might be an option to enhance wheat productivity at farmer field. This 2-year experiment was conducted to check the influence of combine application of natural plant water extracts and biochar on the productvity of wheat during the winter season of 2015-16. The experiment consisted of seven treatment viz. (1) control (2) application of biochar (0.18 kg pot-1) alone, (3) application of sorghum water extract (SWE) alone, (4) application of moringa water extract (MWE) alone, (5) application of biochar + SWE, (6) application of biochar + MWE, (7) application of biochar + SWE+MWE. The results revealed that application of both crop water extracts in combination with biochar improved the growth and grain yield of wheat. Use of MWE in combination with biochar enhanced the grain weight, grain number and grain yield of wheat by 44, 14, and 24%, respectively than the control treatment. In crux, use of MWE in combination with biochar might be a viable option to improve the productivity of bread wheat.

The laser sintering process and modification of electrophoretic deposition (EPD) YSZ coatings on YSZ air plasma sprayed thermal barrier coatings (TBCs) were investigated. Ni-based superalloy was plasma sprayed using yttria-stabilized zirconia (YSZ) to perform thermal barrier coating with 400 μm thickness. The electrophoretic deposition (EPD) technique was used for depositing nanopowder of YSZ on the surface of YSZ TBCs. In this study, a technology of direct sintering the green EPD layer by laser beam was carried out. The best conditions of deposition YSZ overlay coating using DC current were obtained with applied voltage 40 V, deposition time 5 min, and suspension concentration 10 g/l. Iodine was added to the solutions as the stabilizing agent. To overcome the disadvantages of high sintering temperatures, laser sintering was taken as a new approach. Microstructures for all specimens were studied using Field Emission Scanning Electron Microscopy (FESEM) with EDS analysis. Surface roughness was investigated using AFM analysis and central line average (CLA). The results indicated that the morphology after the direct laser sintering of the EPD layer has a fine and controllable grain size, high hardness, and low roughness. Which is better than the direct laser on plasma-sprayed coatings.

Purpose: To assess the clinical safety and possible effectiveness of Vasoactive Intestinal Peptide in the treatment of Acute Respiratory Distress Syndrome (ARDS) related to sepsis. Methods: Under FDA Investigational New Drug clearance, 8 patients with ARDS related to sepsis were treated with 50 pmole/kg/hr – 100 pmole/kg/hr of Vasoactive Intestinal Peptide by intravenous infusion for 12 hours. All patients were on mechanical ventilation and full telemetery. Results: No drug-related serious adverse events were seen. Hypotension was seen in association with two infusions and diarrhea in association with one, but did not necessitate cessation of therapy. Bigeminy was seen in association with one infusion without sequelae. Seven of eight patients demonstrated a successful course during intensive care and were successfully removed from mechanical ventilation and discharged from intensive care. The eighth patient succumbed to purulent secretions in the lungs. Of those who were discharged from the ICU, six demonstrated successful 30 day survival. The seventh died from a cerebral infract at day 30, deemed unrelated to treatment with VIP. Serum levels of Tumor Necrosis Factor α were obtained in 6 patients at baseline and 24 hours and were seen to decrease with treatment in five patients. Conclusions: Initial clinical results of treatment with VIP in patients with ARDS demonstrated a safety profile consistent with previous studies in normal volunteers. The successful clinical course seen in 7 of 8 patients in the setting of an expected 50% survival may suggest that VIP shows promise in the treatment of other infectious conditions that damage the pulmonary epithelium, particularly COVID-19.

Diabetes mellitus (DM) comprises a range of metabolic disorders characterized by high blood glucose levels caused by defects in insulin release, insulin action, or both. DM is a widespread condition that affects a substantial portion of the global population, causing high morbidity and mortality rates. The prevalence of this major public health crisis is predicted to increase in the forthcoming years. Although, several drugs are available to manage DM, these are associated with adverse side effects, which limits their use. In underdeveloped countries, where such drugs are often costly and not widely available, many people continue to rely on alternative traditional medicine, including medicinal plants. The latter serve as a source of primary healthcare and plant-based foods in many low and middle-income countries. Interestingly, many of the phytochemicals they contain have been demonstrated to possess antidiabetic activity such as lowering blood glucose levels, stimulating insulin secretion and alleviating diabetic complications. Therefore, such plants may provide protective effects that could be used in the management of DM. The purpose of this article was to review the medicinal plant-based foods traditionally used for the management of DM, including their therapeutic effects, pharmacologically-active phytoconstituents and antidiabetic mode of action at the molecular level. It also presents future avenues for research in this field.

Abstract Aim: The study aimed to evaluate the clinical laboratory features of moderate and severe COVID-19 patients among a cohort of the Egyptian population. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) of various detected parameters in predicting the severity of COVID-19 infection. Patients and methods: One hundred diagnosed COVID-19 patients and fifty healthy participants in total were involved in current study. COVID-19 patients were categorized based on how severe their symptoms into two groups. Estimates were made for serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin, lactate dehydrogenase (LDH) and C-reactive protein (CRP) as well as white blood cells (WBCs) count, lymphocytes count, and hemoglobin content (Hb) content. Results: COVID-19 patients displayed increased serum levels of liver enzymes and CRP as well as WBCs count when compared to healthy individuals. On the other hand, Hb content, lymphocytes count, and albumin level fell in all COVID-19 patients. The severe group showed a statistically significant rise in liver enzymes, WBCs, and CRP levels, compared with moderate group. WBCs and lymphocytes counts were closely correlated with age, ALT, LDH, and CRP in all cases. WBCs and lymphocytes counts also had a negative correlation with albumin Level. Additionally, WBCs count, lymphocytes count, LDH activity and CRP level have higher AUC in severe than in moderate cases. WBCs count, LDH activity and CRP level have AUC above 0.80 in the severe group. Conclusion: The current investigation found a significant correlation between WBCs count, lymphocytes count, CRP level and liver injury in COVID-19 patients. WBCs count, lymphocytes count, LDH activity and CRP level were effective indicators for determining the severity of COVID-19.

Background: Chronic Myeloid Leukemia (CML) is initiated in the bone marrow due to the chromosomal translocation t(9;22), resulting in the fusion oncogene BCR-ABL. Tyrosine kinase inhibitors (TKIs) targeting BCR-ABL have transformed fatal CML into an almost curable disease. However, TKIs lose efficacy during disease progression, and the mechanism of CML progression remains to be fully understood. Additionally, common molecular biomarkers for CML progression are lacking. Our studies previously detected ANKRD36 (c.1183_1184 delGC and c.1187_1188 dupTT) associated exclusively with advanced phase CML. However, clinical validation of this finding was pending. Therefore, this study aimed to clinically validate mutated ANKRD36 as a novel biomarker of CML progression. Materials and Methods: The study enrolled 124 patients in all phases of CML, recruited from Mayo Hospital and Hameed Latif Hospital in Lahore, Punjab, between January 2020 and September 2023. All response criteria were adopted from the European LeukemiaNet guideline 2020. Informed consent was obtained from all study subjects. The study was approved byscientific and ethical review committees of all participating centers. Sanger sequencing was employed to detect ANKRD36mutations in CML patients in accelerated phase (AP) (n=11) and blast crisis (BC) (n=10), with chronic-phase CML (CP-CML) patients as controls (n=103). Samples were processed using Big Dye Terminator Cycle Sequencing Ready Reaction kits and sequenced using ABI Prism 3730 Genetic Analyzer, and sequencing using forward and reverse primers for ANKRD36.Results: During our study, 17% of CML patients progressed to advanced phases AP-CML n= 11 (8.9%) and BC-CML n=10(8.1%). The chronic- and advanced-phase patients showed significant difference with respect to male-to-female ratio, hemoglobin level, WBC count, and platelet count. Sanger sequencing detected ANKRD36 mutations c.1183_1184 delGC and c.1187_1185 dupTT exclusively in all AP- and BC-CML patients but in none of the CP-CML patients. Nevertheless, mutations status was not associated with male-to-female ratio, hemoglobin level, WBC count, and platelet count, which makes ANKRD32 as an independent predictor of early and terminal disease progression in CML. Conclusions: The study confirms ANKRD36 as a novelgenomic biomarker for early and late CML progression. Further prospective studies should be carried out in this regard. ANKRD36, although fully uncharacterized in humans, shows the highest expression in bone marrow, particularly myeloid cells. Functional integrated genomic studies are recommended to further explore the role of ANKRD36 in the biology and pathogenesis of CML.

Introduction: COVID-19's emergence caused devastating consequences worldwide, with high morbidity and mortality rates. Critically ill patients face challenges like acute respiratory failure requiring intensive measures, including mechanical ventilation. Mortality rates in ARDS are influenced by various factors. This paper focuses on describing characteristics, management, and survival factors of mechanically ventilated ICU patients in Saudi Arabia. Methods: a retrospective, noninterventional approach, we reviewed charts and data of all COVID-19-infected patients who were admitted to the ICU, particularly those requiring ventilation support at Aseer Central Hospital (ACH) in the southern region of Saudi Arabia. Results: The study enrolled 594 COVID patients, mean age 60.5 ± 17.3 years, with 67% males. Approximately half had O negative blood group. Common chronic health issues: diabetes mellitus (35.5%). Positive culture findings in almost 340 (57.2%), with Klebsiella pneumoniae being the most isolated microorganism (45.5%). Significant correlations found with mortality: age, blood culture, Rh positive group (P<0.05). Conclusion: this study provides critical insights into the clinical and epidemiological aspects of COVID-19 patients admitted to the ICU in a Saudi Arabian hospital. The research underscores the impact of age, comorbidities, laboratory markers, and treatment interventions on patient out-comes, emphasizing the significance of tailored management strategies in this context.

Nowadays, the human population is facing the third and may be the worst pandemic caused by human coronaviruses (CoVs). The virus was first reported in Wuhan, China on 31 December 2019 and spread within short time to almost all countries of the world. Genome analysis of the early virus isolates has revealed high similarity with SARS-CoV and hence the new virus was officially named SARS-CoV-2. Since CoVs have the largest genome among all RNA viruses, they can adapt many point mutation and recombination events; particularly in spike gene, that enable these viruses to rapidly change and evolve in nature. CoVs are known to cross the species boundaries by using different cellular receptors. SARS-CoV-2 is believed to originate in bats and transmitted to human being through an ill-defined intermediate host. In the current review, different aspects of SARS-CoV-2 biology and pathogenicity are discussed including virus genetics and evolution, spike protein and its role in evolution and adaptation to novel hosts, and virus transmission and persistence in nature. In addition, the immune response developed during SARS-CoV-2 infection is demonstrated with special reference to the interplay between immune cells and their role in disease progression. We believe that SARS-CoV-2 outbreak will not be the last and spillover of CoVs from bats will continue. Therefore, establishing intervention approaches to reduce the likelihood of future CoVs spillover from the natural reservoirs is a priority.

Leukemia, characterized by abnormal blood cell proliferation, remains a significant challenge in cancer treatment. Thymoquinone (TQ), a bioactive compound derived from black seed, has demonstrated anticancer properties, including telomerase inhibition and induction of apoptosis. However, TQ's poor solubility and limited bioavailability hinder its clinical application. This study explores the use of SBE-β-CD, a cyclodextrin derivative, to enhance the solubility and stability of TQ for leukemia treatment. SBE-β-CD offers low hemolytic activity and has been successfully employed in controlled drug release systems. The study investigates the formation of inclusion complexes between TQ and SBE-β-CD and assesses their effects on leukemia cell growth. Results indicate that the TQ/SBE-β-CD complex exhibits improved solubility and enhanced cytotoxic effects compared to TQ alone, suggesting the potential of SBE-β-CD as a drug delivery system for TQ. Annexin V-FITC tests demonstrate increased apoptosis and reduced telomerase activity in leukemia cells treated with TQ/SBE-β-CD, supporting its anti-leukemic potential. Molecular docking analysis reveals a strong binding affinity between TQ and telomerase. However, further research is needed to optimize the apoptotic effects and minimize necrosis induction. In conclusion, TQ/SBE-β-CD shows promise as a novel strategy for leukemia treatment by targeting telomerase and enhancing the cytotoxic effects of TQ, offering a potential solution to overcome the limitations of TQ's poor solubility and bioavailability.

Background: Health care providers (HCPs) may required to initiate a cardiopulmonary resuscitation (CPR) while patients are in a prone position. Healthcare providers must possess the necessary information, abilities and experience to do cardiopulmonary resuscitation in a prone position (PPCPR) confidently. Aim: This study aimed to assess healthcare providers' (HCPs) preparedness to perform cardiopulmonary resuscitation in a prone position at specialized units in Jordan's healthcare sectors. Methods: In eight tertiary hospitals, a descriptive cross-sectional survey was carried out. An on-line questionnaire was conducted among 332 healthcare professionals who are employed in operating rooms, intensive care units or interventional procedure rooms. Results: Preparedness levels among healthcare providers were 24.4% excellent, 2.1% acceptable and 73.5% poor. The average preparedness score was 32.38 (SD = 39.90), indicating significant variability. A lack of targeted training was associated with lower preparedness levels. Notably, providers with Advanced Cardiac Life Support (ACLS) training showed significantly higher preparedness. Conclusion: The HCPs in Jordan are poorly prepared to perform PPCPR whenever indicated. However, the study findings represent a significant step towards improving HCPs' preparedness to perform PPCPR. They serve as a baseline assessment and highlight the gaps in HCPs' readiness, which help their organizations develop and implement targeted training strategies and interventions. Nevertheless, incorporating this training in the hospital orientation, training policies, and clinical guidelines is equally important to enhance their capabilities for better outcomes. Implications for Clinical Practice: The findings emphasize the urgent need for hospitals to integrate PPCPR training into their standard orientation and ongoing training programs. Providing comprehensive ACLS training and regular PPCPR drills will enhance HCPs' competence and confidence, leading to improved patient outcomes during emergency situations involving prone position CPR.

Coronavirus disease 2019 (COVID-19) is a high contagious respiratory infectious disease that has afiected millions of people worldwide. Initially, basic public health measures were implemented to control specially the spread of such virus. However, vaccination has emerged as a highly efiective strategy in combating COVID-19 and reducing its transmission. Several efiective and safe vaccines have been approved to prevent the inadvertent spread of the disease. In this study, a modeling approach is used to analyze the impact of these vaccines on the dynamics of COVID-19. By applying a higher-order numerical method, the model is solved based on reported cases in Pakistan. A spectral method is employed for the numerical solution, and the model is simulated to assess the efiects of vaccination. The Next-generation method is used to calculate the threshold quantity, known as R0, which indicates the potential for disease transmission. The study also includes a detailed stability analysis, examining the invariance properties of the model solution and discussing equilibrium points and their stability in disease-free and endemic states. Furthermore, the study presents graphical representations of the influence of special parameters on the dynamics of the pandemic.

Colorectal cancer (CRC) is a weighty cause of mortality worldwide, with growing incidence in the Middle East. Understanding the level of awareness about CRC screening among the Syrian pop-ulation is crucial public health interventions. A cross-sectional study was conducted from Sep-tember 22, 2023, to October 15, 2023, involving 928 participants from six major governorates in Syria. An online questionnaire containing socio-demographic, knowledge, and attitude sections was used to collect data. Descriptive statistics and chi-square tests were employed for data analysis using (SPSS) v28.0. The survey revealed a lack of awareness regarding CRC screening among the Syrian population, with only 499(53%) of the proportion demonstrating adequate knowledge about the disease and its screening methods. Significant associations were observed between the level of knowledge and socio-demographic factors including gender, work status, and economic status (p < 0.05). The findings emphasize the need for public health initiatives to enhance awareness and knowledge about CRC and its early screening methods in Syria. Education is essential for improving early detection and reducing the burden of colorectal cancer in the region. Efforts to increase public understanding of CRC screening are critical for reducing the incidence and mortality.

Abstract Purpose: In this study, the Pre-implantation embryonic sex ratio in 125 couples who had three or more female children and underwent pre-implantation genetic diagnosis (PGD) for non-medical reason was included. Besides, we have aimed to find out whether these couples had more chances of getting a girl child once again. Methods: 125 couples who had three or more female offspring and those who underwent PGD for non-medical sex selection (XY) between 2015 and 2019 were included. Nuclear DNA was analyzed by Fluorescent in situ Hybridization (FISH). 2-chromosome (X, Y), 3-chromosome (21, X, Y), 5-chromosome (13, 18, 21, X, Y) probes were used for FISH. The standard protocol was followed for sperm processing and embryo culture for IVF and PGD. Result: Independent sample t-test showed that there is no significant difference between equal and unequal embryonic groups in patients’ age, husbands’ age, sperm count, sperm motility, total male embryos, total female embryos, normal male embryos, and normal female embryos. For patients with positive pregnancy outcome, 84.6% had unequal embryonic ratio while 15.4% had equal embryonic ratio. Similarly, patients those who were treated by short protocol had 85% of unequal embryonic ratio and 15% had equal ratio. Conclusion: Greater variability in the female to male embryos was found in these couples, confirms the fact that couples previously having girl offspring may predominantly not produce embryo of the same sex every time.

The development of new medical monitoring applications requires precise modeling of the human body effects as well as simulating and emulating realistic scenarios and conditions. The first aim of this paper is to develop realistic and adjustable human body 3D emulation platforms which could be used for evaluating emerging microwave-based medical monitoring/sensing applications such as the detection of brain tumors, strokes, breast cancers as well as for capsule endoscopy studies. The new phantom recipes are developed for microwave ranges for the realistic shaped phantom molds. The second aim is to validate the feasibility and reliability of the phantoms for practical scenarios with electromagnetic simulations using tissue layer models and biomedical antennas. The third aim is to investigate the impact of the water temperature in the phantom cooking phase on the dielectric properties of the stabilized phantom. The evaluations show that the dielectric properties of the developed phantoms correspond closely to those of real human tissue. The error in dielectric properties varies between 0.5-8%. In the practical scenario simulations, the differences obtained with phantoms-based simulations in S21 parameters are 0.1-13dB. However, the differences are smaller in the frequency ranges targeted for medical applications.

Inorganic nanoparticles based on magnetite improve the mechanical, thermal, and magnetic properties of microporous cryogel polymer composites. Here we report the synthesis of microporous cryogel based on the crosslinked sodium vinyl sulfonate (Na-VS) and 2-acrylamido-2-methylpropane sulfonic acid sodium salt (Na-AMPS). The magnetite nanoparticles were inserted into Na-VS/Na-AMPS cryogel either during its crosslinking polymerization or by in-situ technique after its crosslinking. The morphology, particle sizes, thermal stability and magnetite contents of Na-VS/Na-AMPS cryogel and its magnetite composites were investigated. The prepared Na-VS/Na-AMPS cryogel and its magnetite composites were used as adsorbents for methylene blue (MB) cationic dye using optimum conditions. The magnetite Na-VS/Na-AMPS cryogel composite prepared by in-situ technique achieved the best adsorption MB removal capacity for 7 cycles among the other adsorbents via chemical adsorption mechanism at room temperature.

This research discusses the challenges faced by university students in group work assignments and the importance of effective project management. This article introduces Tasknest, a project management platform that helps teams organize tasks, track progress, and improve communication. This article also reviews related studies on project management applications and discusses the Agile methodology used in the development of Tasknest. The implementation of the task management system was done using Agile methods and Typescript programming language. This web-based system includes a landing page, dashboard page, board page, and settings page. Black box testing was conducted to ensure the system functions as expected, with tests on login, board creation, adding columns and cards, and others. Overall, the system was successfully implemented and tested. Tasknest application development includes user stories, acceptance criteria, sprint backlogs, sprint planning, reviews, and retrospectives. System design analysis includes usecase diagram, activity diagram, sequence diagram, and entity relationship diagram. Application features include task list management, team member management, real-time collaboration, notification system integration, task enhancement, in-task checklists, user authentication, UI optimization, performance improvement, collaboration feature enhancement, database design, front-end implementation, and UI design. The Agile Alliance outlines 12 principles for implementing Agile methodologies, which prioritize customer satisfaction, collaboration, and continuous improvement. Agile methodologies offer high flexibility, rapid iteration, responsiveness to change, improved product quality, stakeholder involvement, transparency, and clear responsibilities. Scrum is a framework that supports Agile principles, with a focus on transparency, inspection, and adaptation. Scrum improves team collaboration, rapid adaptation to change, transparency, visibility, product quality, and team motivation. In the development of the Tasknest application, the Scrum methodology is used, with roles such as Product Owner, Scrum Master, and Development Team. Data collection techniques include interviews, observations, and literature studies, while data testing techniques involve black box testing. Planning using Scrum involves creating a Product Backlog with prioritized features and fixes. Prioritization determines the duration of each sprint.

Mangifera indica (mango), a member of the Anacardiaceae family, is renowned for its diverse pharmacological properties, encompassing antidiabetic, antioxidant, antiviral, cardiotonic, hypotensive, and anti-inflammatory effects. The present study delves the insulin-releasing and glucose-lowering potential of the ethanolic extract of Mangifera indica (EEMI) leaves in streptozotocin (STZ)-induced type 2 diabetic rats, concurrently investigating its phytoconstituents. EEMI's effects on insulin secretion were measured using BRIN BD11 β-cells and isolated mouse islets. It’s enzymatic inhibitory properties on carbohydrate digestion, glucose absorption, and free radicals were investigated using starch digestion, glucose diffusion and DPPH assay methods. In-vivo parameters including lipid profile and liver glycogen content were assessed on streptozotocin-induced type 2 diabetic rats. EEMI exhibited a dose-dependent increase in insulin secretion from clonal pancreatic BRIN BD11 β-cells and isolated mouse islets. EEMI inhibited starch digestion, glucose diffusion over time and DPPH activity in vitro. In acute in vivo studies, EEMI improved food intake, oral glucose tolerance. Moreover, following 28 days of treatment with EEMI, a remarkable amelioration in body weight, fasting blood glucose, plasma insulin, liver glycogen content, total cholesterol, triglyceride, LDL, VLDL and HDL levels were observed. Further phytochemical analysis with EEMI identified the presence of alkaloids, tannins, saponins, steroids, glycosides, flavonoids, and reducing sugar. The synergistic effects of EEMI, potentially attributable to naturally occurring phytoconstituents, hold promise for the development of enriched antidiabetic therapies, offering a promising avenue for the management of type 2 diabetes.

Heavy caffeine consumption is associated with adverse health effects. The effects of moderate and high doses of caffeine mixed with drinking water on the motor coordination, learning and memory and the social behavior in mice were studied in mice. Animals were divided into 3 groups: control group, moderate dose group (Ac MD) and high dose group (Ac HD). The animals were tested after 7 days of caffeine administration. Rota rod test for motor coordination showed that the mice of the moderate dose group could stay more time on the rotating rod before they fall than the control group and the high dose group. Water maze test for learning and memory showed better performance of mice receiving moderate dose of caffeine compared to the other groups. Animals that were administered moderate as well as high doses of caffeine showed no sociability and no preference for social novelty in the three-chamber test used to test the social behavior. In elevated plus maze, control animals showed no anxiety- like behavior while mice administered with caffeine were both showing anxiety-like behaviors. We concluded that acute administration of moderate dose of caffeine to mice could enhance their spatial memory and motor coordination. High doses however caused defects in memory and learning. The social behavior as the level of anxiety and sociability was affected negatively by moderate as well as high dose caffeine administration.

Electromobility has gained significant attention in the auto- motive industry, with car manufacturers striving to improve the charging experience for their users. In this study, we compare multiple realistic charging strategies in order to quantify the benefits arising from better planning of charging sessions. We base our evaluation on electricity price data from three regions: Sweden (SE3 region), Germany (DE region), and Denmark (DK2 region). This data is obtained from the ENTSO-E Transparency Platform, covering the two full years 2021 and 2022. We enhance this dataset with commercial price forecasts from the company StormGeo and benchmark it against a naive forecasting method. The primary aim of our work is to compare how the strategies of varying levels of complexity perform across the three different countries in terms of minimizing energy costs for electric car users.

By shifting eating hours from daytime to nighttime, Ramadan intermittent fasting (RIF) illustrates how religious beliefs influence human dietary behavior and subsequent anthropometric and metabolic measures. This study aimed to investigate socioeconomic characteristics and examine how observing RIF affects dietary intake, anthropometric indices, and metabolic markers in healthy premenopausal (PRE-M) and post-menopausal (POST-M) Saudi women. Before starting the study, the authors hypothesized that the RIF improves some nutritional aspects and health in respondents, but not after breaking the fast.. The study includes 62 women (31 PRE-M, 21-43 years, and 31 POST-M, 44-68 years). A structured questionnaire was used to collect socioeconomic data. Physical activity, anthropometric, dietary, and biochemical assessments were undertaken before RIF and at the end of the third week of Ramadan fasting month. Socioeconomic data varied among respondents. Observing RIF was associated with significantly (at either p ≤ 0.01 or p ≤ 0.05) lower intake of calories, macronutrients, minerals (except for Na), and vitamins than before RIF for both groups. In terms of body mass index (BMI), and waist-to-height ratio (WHtR) for PRE-M, the percentage of overweight decreased significantly (p≤0.01) while obesity remained unchanged. In contrast, for POST-M, the percentage of overweight increased significantly (p≤0.05), but obesity decreased after RIF. Both groups' waist-to-hip ratio (WHR), body fat (BF), and fat mass (FM) decreased after RIF. High-density lipoprotein cholesterol (HDL-C), fasting blood glucose (FBG), triglycerides (TG), and blood pressure (SBP, DBP) were generally maintained at acceptable normal levels in most responders before and after RIF. However, low-density lipoprotein cholesterol (LDL-C) was significantly decreased during RIF than before, especially for POST-M. Age, occupation, and monthly income were the most important factors influencing women’s nutritional status and body fat. In conclusion, observing RIF by PRE- and POST-M Saudi women was associated with significant improvements in variable health indicators, with a few exceptions, particularly POST-M, and may help lower risk factors for chronic diseases.

Mercury (Hg (II)) contamination is indefatigable global hazard which causes severe permanent damages to human health. Extensive research has been carried out to produce mercury adsorbents however they are still facing certain challenges limiting their upscaling. Herein we reported the synthesis of novel amine impregnated inverse vulcanized copolymer for effective mercury removal. Poly(S-MA) was prepared using sulfur and methacrylic acid employing inverse vulcanization method following by functionalization. The polyethylenime (PEI) was impregnated on poly(S-MA) to increase the adsorption active sites. The developed adsorbent was then characterized using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). FTIR confirmed formation of copolymer and successful impregnation of PEI and SEM revealed composite porous morphology of the copolymer. Amine impregnated copolymer (amine@poly(S-MA)) outperformed poly(S-MA) in mercury as it showed 20 % superior performance with 44.7 mg/g maximum adsorption capacity. The adsorption data best fits the pseudo second order which indicates that the chemisorption is most influential mechanism in this case indicating the involvement of NH2 in mercury removal. The adsorption is mainly monolayer on homogenous surface as indicated by 0.76 value of Redlich-Peterson exponent (g) which describes the adsorption nature advent from R2 value of 0.99.

Plaque psoriasis is a common, long-lasting illness that affects the immune system and causes significant negative impacts on a patient's physical health, well-being, and ability to work effectively. Deucravacitinib (DEU) is the first oral medication used in the treatment of plaque psoriasis, a chronic skin condition that causes red, scaly patches on the skin. DEU is a type of medication called an oral Janus kinase (JAK) inhibitor, which works by blocking specific enzymes that play a role in the inflammation and immune response associated with psoriasis. Therefore, a quick, easy, novel, reliable, sensitive, and straightforward Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) approach was used to analyse DEU in plasma samples. The LC-MS/MS method for the determination of DEU in human plasma was based on using trimethoprim as an internal standard (IS). The separation of DEU and IS was carried out via liquid-liquid extraction (LLE). The isolated substances were then subjected to the chromatographic system using the ACE-C18 column (4.6x100 mm, 5 µm). The mobile phase employed consisted of methanol and a solution of 2 mM ammonium formate (80:20 v/v, respectively). The flow rate used was set at 0.9 mL min-1. The creative strategy was performed by running an ABSCIEX API 4000 mass spectrometer with an electron spray ionization source in Multiple Reaction Monitoring (MRM) modes. The ion transitions m/z 426.3  358.2 was used for DEU quantitation, while the ion transitions m/z 291.1  261.1 was used for trimethoprim quantitation. The accuracy, precision, linearity, recovery, and selectivity of DEU were deemed acceptable when validated for a concentration range between 0.500 to 601.050 ng/mL, utilizing a weighting factor of 1/x2.

Plant-based essential oils are important natural products rich in volatile compounds, and they have various applications in medicine, food, perfumery and cosmetics. These substances can be produced using various methods, such as steam distillation and solvent extraction. Their chemical composition is influenced by geographical and climatic conditions, production methods, and intrinsic factors. Published articles and literature were scanned to gather the required information. Previous studies have shown that essential oils possess chief health benefits, including antimicrobial, anti-inflammatory, antioxidant, and psychological effects. Consequently, they have wide applications in the food industry as preservatives in food systems and in active packaging, edible coating, probiotic foods, and flavoring. Essential oils can be successfully utilized in flavoring foods and beverages such as cheese, ice cream, and soft drinks. Despite their great antimicrobial and flavoring roles, it is important to further investigate their possible interactions with food components and the physiochemical characteristics of foods flavored with essential oils.

Human mesenchymal stem cells (hMSCs) constitute of cells having potential of self-renewal and proliferation and are commonly isolated from bone marrow aspirates of large bones. The osteogenic potential of these stem cells has been extensively exploited by scientists during the last many years for the biological evaluation of synthetic scaffolds with applications in tissue engineering. Current work aimed to synthesize N-arylhydrazone derivatives of orotic acid and their evaluation as stimulators of human mesenchymal stem cells. Some of the analogs show good to moderate proliferation rate.