The textile industry produces high volumes of colored effluents that require multiple treatments to remove non-adsorbed dyes which could be recalcitrant due to their complex chemical structure. Most of the studies have dealt with the biodegradation of mono or diazo dyes but rarely with poly-azo dyes. Therefore, the aim of this paper was to study the biodegradation of a four azo-bond dye (Sirius grey) and to optimize its decolorization conditions. Laccase-containing cell free supernatant from the culture of a newly isolated fungal strain, Coriolopsis gallica strain BS9, was used in the presence of 1-hydroxybenzotriazol (HBT) to optimize the dye decolorization conditions. A Box-Benken design with 4 factors namely: pH, enzyme concentration, HBT concentration and dye concentration, was performed to determine optimal conditions for the decolorization of Sirius grey. The optimal conditions were pH 5, 1 U/mL of laccase, 1 mM of HBT, and 50 mg/L of initial dye concentration ensuring a decolorization yield and rate of 87.56 % and 2.95 %/min respectively. Decolorized dye solution showed a decrease of its phytotoxicity (Germination index GI = 80 %) compared to the non-treated solution (GI = 29 %). This study suggests that laccase-mediator system could be a promising alternative for dyes removal from textile wastewaters.

We obtain some generalised Minkowski-type integral formulas for compact Riemannian (resp. spacelike) hypersurfaces in Riemannian (resp. Lorentzian) manifolds admitting an arbitrary vector field that we assume to be timelike in the case where the ambient space is Lorentzian. Some of these formulas generalize existing formulas in the case of conformal and Killing vector fields. We apply these integral formulas to obtain interesting results concerning the characterization of such hypersurfaces in some particular cases such as when the ambient space is Einstein admitting an arbitrary (in particular, conformal or Killing) vector field, and when the hypersurface has constant mean curvature.

The deposition of dust particles on solar panel modules constitutes a significant challenge, leading to a potential reduction in solar cell performance. This work tackles this issue by investigating the surface modification of a layer of transparent indium tin oxide (ITO), with a detailed analysis of the influence of its characteristics via different annealing conditions/processing. The ITO layer has been studied to enhance its characteristics for dust removal applications. Of particular note is that the developed ITO layer can be applied to dust removal using electrostatic or magnetic-based approaches. Thus, the correlation between annealing gas (using Argon, Oxygen, and Nitrogen), annealing temperature, and annealing ramping rate is explored with the obtained surface topography, as well as electrical and optical properties. The developed ITO layers annealed in the Argon medium at 600°C with an annealing ramping rate of 50°C/s showed smooth surface roughness, the highest electrical conductivity, and a relatively low refractive index. Such findings can play a crucial role in the future implementation of using the enhanced ITO layer for dust mitigation in solar panels, thus improving their long-term performance.

The over use of pharmaceutical compounds, essentially antibiotics, led to an increase of their concentrations in aquatic ecosystems. In this study, the white-rot fungus Coriolopsis gallica (high-laccase-producing fungus) was investigated for the biodegradation of ampicillin (AMP) under different cultivation conditions. The biotransformation of the antibiotic was confirmed by means of high-performance liquid chromatography (HPLC), and the antibacterial activity was evaluated via the bacterial growth inhibition agar well diffusion method using Escherichia coli as an ampicillin-sensitive test strain. The results showed that AMP (50 mg L-1) was totally removed by C. gallica after 6 days of incubation in a liquid medium. The antibiotic removal rate was maximal with a fungal culture aged 9 days. Such a culture achieved the removal of a higher concentration of up to 500 mg L-1 of ampicillin in 3 days. This higher antibiotic removal rate was concomitant with the maximal laccase production in culture supernatant. In addition, four consecutive doses of 500 mg L-1 of ampicillin were transformed by the same fungal culture in 24 days. After that, the fungus was unable to remove the antibiotic. The measurement of ligninolytic enzyme activity showed that laccase of C. gallica might participate in the biotransformation of AMP.

Colorectal cancer prognosis get worse with advancement of disease into metastatic stage. There is a pertinent need to develop prognostic biomarkers that can be used for personalized and precision medicine. Alternative splicing provides an insight into understanding of changes at isoform expression level which may not be evident at gene level. In this direction, we utilized our prior knowledge about significant alternatively spliced genes and chose ADAM12 and MUC4 for further characterization in a metastatic cell line model. These genes were found to be good prognostic indicators in The Cancer Genome Atlas database. We studied the gene organization and designed primers to specifically amplify a group of isoforms. Differential expression of these group of isoforms was observed in normal, primary and metastatic colorectal cancer cell lines. We further validated the results using sanger sequencing. Isoform expression was found to respond to the 5-fluorouracil treatment. RNAseq analysis of the cell lines further validated the differential expression of gene isoforms. Successful detection of ADAM12 and MUC4 in cell lysates varied according to the antibody used which may reflect differential expression of isoforms. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their probable used as prognostic or predictive biomarkers.

In this study, we aim to evaluate how cyclodextrin molecules affect the hydrophilicity and selec-tivity of PVDF membrane. Herein, we prepared PVDF-PVP(1-x) β-CDx membranes, with x rang-ing from 0 to 1 wt%. The membranes were deeply characterized by means of X-ray diffraction (XRD), attenuated total reflectance infrared (ATR-IR), Raman spectroscopies, Thermal gravimet-ric analysis (TGA), Contact angle measurement (CA), scanning electron microscopy (SEM) and atomic force microscopy (AFM). The study unequivocally demonstrates the effectiveness of the addition of β-CD molecules on membranes' structural, morphological, and dielectric properties. Adding 0.25wt% β-CD enhanced hydrophilicity, with CA decreasing from 72.6° to 56° and roughness decreasing from 81 to 29 nm. The PVDF-PVP(1-x) β-CDx membranes were then fully characterized using electrochemical impedance spectroscopy (EIS) to determine their dielectric properties, which clearly showed that the presence of β-CD induced polarization of the mem-brane. The separation of various dyes with different sizes and charges was utilized. These dyes included methylene blue (MB, positive, 0.504 nm), methyl red (MR, neutral, 0.487 nm), rose Bengal (RB, negative, 0.588 nm), and brilliant blue (BB, negative, 0.798 nm). Based on our re-search, we found that the membrane's selectivity is determined by both exclusion factors (such as size and dielectric properties) and inclusion inside the β-CD cage. We found that using alpha-CD instead of beta-CD led to the disappearance of dye inclusion. These findings strongly sug-gest that β-CD molecules can be a viable solution for dye removal from wastewater.

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.

Reliable prediction of infectious disease is an essential need for public health organizations to minimize or prevent the disease's spread. With the increase of data growth in the healthcare sector, accurate analysis of such data helps for early disease detection and better patient care. With the availability of huge data, it is a great deal for predicting and handling an epidemic occurrence. To control the epidemic disease, a new Artificial Intelligence called Manhattan Hessian Linear Feature Embedding Based Tucker Congruence Deep Convolutional Network (MHLFE-TCDCN) is introduced with higher accuracy and minimum time consumption. The MIoT device is used to collect the data from the patient body. The proposed MHLFE-TCDCN includes two major processes namely feature selection and classification with multiple layers such as input, two hidden layers, and one output layer. First, the feature selection process is performed using the Manhattan Hessian Locally Linear Embedding technique in the first hidden layer to minimize the dimensionality and time complexity. After selecting the feature, the classification is performed using the Tucker coefficient of congruence regression. The Tucker coefficient of congruence measures the similarity between the training and testing disease data. A positive similarity level is used to accurately identify the disease at the output layer based on the similarity measure. Experimental assessment is carried out with various parameters such as accuracy, precision, recall, F-measure, and computational time concerning several numbers of patient data. The quantitative results and discussion that the proposed MHLFE-TCDCN technique achieves higher accuracy with minimal computation time as compared to the conventional methods.

Remote work as a new working pattern is considered of high importance in determining the competitiveness of the institutions that adopt this form of work. This trend toward remote working has benefited workers greatly in terms of flexibility and work-life balance and has had unanticipatedly positive effects on sustainability. The issue has grown in importance considering recent development of digitalization and high concern of countries to achieve the sustainable goals. This study attempts to examine the effect of three explanatory variables: remote work, institutional efficiency, and work management on the competitiveness of finance institutions in Saudi Arabia. To collect the primary data, a survey was conducted on a stratified random sample that comprised 1270 respondents. The sample covers the three finance sector segments: banks, insurance, and finance companies. Correlation analyses, one-sample t-tests, and multi-regression analyses are applied to analyze the data. The results of the study showed that there is a positive significant relationship between the three explanatory variables of the study and institutional competitiveness. Besides, the regression model revealed that the two explanatory variables; remote work and institution efficiency are statistically significant at 95% confidence intervals, while work management is not statistically significant. The study recommends promoting remote work to increase the finance institution's competitiveness by restructuring the work policies, designing work strategies, and introducing a new management system compatible with remote work.

The high flammability and lack of charrability of polystyrene (PS) pose significant limitations on its broader applications. Therefore, there is an urgent need for a straightforward and efficient method for the synthesis of flame-retardant PS, which still poses a considerable challenge. In this study, we present an efficient approach to enhance the flame-retardant properties of PS through direct phosphorylating aromatic C(sp2)-H bonds using commercially available and inexpensive manganese catalyst. A range of phosphonates served as reactive substrates to enable a tunable degree of polymer functionalization. The corresponding phosphorylated PS specimens were determined by means of 1H NMR, 31P NMR, FTIR spectroscopy and GPC. Microscale combustion calorimetry (MCC) tests indicate that this protocol indeed enhances the flame-retardant performance of PS. Moreover, other advantages associated with the incorporation of the phosphonate group have been observed, including improved thermal resistance and wettability. This cost-effective strategy of Mn-catalyzed C-H can also be utilized to directly obtain phosphonate modification of waste foamed PS and styrene acrylonitrile copolymer, providing a new method for the purpose of recycling and upgrading PS plastics.

To address the issue of reduced orbit estimation accuracy resulting from discrepancies between in-orbit measured geomagnetic field values and IGRF model values in autonomous orbit estimation of microsatellites based on geomagnetic field measurements, this study introduces an adaptive cubature H-infinity filtering algorithm. Firstly, it presents the low-altitude orbital dynamics model and geomagnetic field measurement model for microsatellites. Subsequently, within the adaptive cubature H-infinity filtering algorithm, a spherical simplex rule and a second-order Gaussian-Legendre quadrature criterion are employed to compute the spherical surface integral and radial integral. Additionally, a spherical simplex-radial quadrature rule is proposed to enhance the approximation accuracy of nonlinear Gaussian weighted integrals. Furthermore, by integrating extended H-infinity filtering based on game theory with the cubature quadrature rule, an inverse proportional relationship between constraint level and filtering innovation is established. This allows for adaptive adjustment of the constraint level to enhance robustness against model errors. Finally, through semi-physical simulation experiments, it is demonstrated that compared with traditional algorithms, the proposed algorithm improves autonomous orbit estimation position accuracy of microsatellites by 7.49%, while also enhancing velocity accuracy by 3.1%, thus validating its effectiveness.

Higher education equips youth with the requisite knowledge and skills for navigating environmental education and sustainability. The current study aims to test a comprehensive model for integrating environmental education and sustainability principles within the higher education ecosystem. The model emphasizes problem-based and service-learning approaches, technological integration, and behaviour change models to foster environmental education, and community engagement and enhance overall well-being. In this study, researchers examined the impact of curriculum, extracurricular activities, and community engagement as independent variables on dependent variables namely environmental education, sustainability, and well-being while also considering the mediating role of the undergraduates' awareness level. Data was collected from a higher education academic Institute in Riyadh, Saudi Arabia. The variance-based structural equation modeling (SEM) technique using Smart-Partial Least Squares (PLS) software was used to test these hypothesized relationships empirically. The study findings revealed a significant positive impact of curriculum development, extracurricular activities, and community engagement efforts on elevating undergraduates' awareness levels. Awareness levels mediated the effect of environmental education, sustainability, and well-being, highlighting the need to integrate environment-related topics into academic and extracurricular activities. This underscores higher education's potential to shape eco-conscious leaders by infusing environmental education into academic life. These findings have implications for higher education institutions, policymakers, and community organizers, emphasizing the importance of a holistic approach to environmental education for a sustainable society. By fostering environmental awareness among youth and integrating it into broader societal initiatives, educational institutions can play a crucial role in shaping a generation committed to sustainability and well-being.

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec². The main ideas of H-Rec² include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec² framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

Abstract: This paper aimed to investigate the entrepreneurial intentions of female students in Saudi Arabia, utilizing the Theory of Planned Behavior (TPB) as the theoretical framework. Employing a quantitative research methodology, data was collected through a questionnaire administered to female students at Princess Nourah University. The results revealed a positive inclination towards entrepreneurship, with over 64% expressing a desire to pursue entrepreneurial ventures in the future. This optimistic trend among female students suggests a potential pool of future entrepreneurs. Interestingly, a small percentage (3.21%) categorically rejected entrepreneurship as a career option, indicating a relatively low level of disinterest in entrepreneurial pursuits. However, many respondents (32%) remained undecided, presenting a valuable opportunity for mentorship and support to cultivate their entrepreneurial intentions. These findings underscore the significance of providing guidance and education to encourage entrepreneurship among female students. The TPB analysis highlighted that attitudes and perceived behavioral control towards entrepreneurship were favorable among female students, indicating a positive mindset and belief in their ability to embark on entrepreneurial endeavors. However, societal norms still exert a negative influence on some student’s entrepreneurial intentions, suggesting a need to address cultural barriers that might hinder female students' willingness to pursue entrepreneurship. The study suggests enhancing female entrepreneurship through societal encouragement and support from personal networks. It highlights the importance of fostering entrepreneurial aspirations in female students. Crucially, the study underscores the role of universities in cultivating entrepreneurial intentions by proposing the implementation of entrepreneurship-focused curricula and the creation of university-based training units or incubators.

The Quantum-Cosmos Nexus Theory delves into the intricate web of relationships that tie together fundamental constants, cosmological properties, and the boundaries of our comprehension in the realm of physics. It unveils a profound interconnection between the gravitational constant (G), the speed of light (c), and the parameters of the observable universe. It introduces a unification equation that hints at a connection between the fundamental constants. It also introduces a new constant, , which is similar to the Planck constant but, on a large scale, signifies the ultimate unit of action or energy on a cosmic scale. With this new constant, new units similar to Planck units have been introduced. They are the equivalence of Planck units in the sense that they represent the limits of our current understanding of physics on the largest scale. The theory also shows that most of the fundamental constants of nature, including the gravitational constant (G), the speed of light (c), vacuum permittivity (ε₀) vacuum permeability (u₀), the Boltzmann constant (K_B), and the fine-structure constant (α), can be derived from these new units and Planck units. The first derived equation suggests a potential weakening of the gravitational constant over time, assuming the density remains relatively constant. Although this is a matter of speculation, it has the potential to explain observations related to dark matter. The theory also makes use of the Planck force, defining it as the maximum force on the quantum and cosmic scales. It also emphasizes that the Planck scale is not the ultimate limit and reveals our observational constraints, offering a unique perspective on the universe's fundamental workings. The Quantum-Cosmos Nexus Theory reveals how fundamental constants, cosmic dynamics, and the limits of our understanding converge, opening the door to fresh perspectives on the underlying principles of the universe.

Many techniques have been and are being made to find alternatives to water-saving practices. Among them, Partial root drying (PRD), one of the effective approaches, plays a major role in reducing the harmful effects of water deficit stress. An experiment was carried out using irrigation strategies [I1 (100% full irrigation “FI”), I2 (75%FI), I3 (50%FI), and I4 (PRD (50%FI)] and soil organic mulch [L0 (Zero layer organic soil mulch” control”), L1 (Single layer organic soil mulch), L2 (Two layers of organic soil mulch), and L3 (Three layers of organic soil mulch)] to inspect the impact of those treatments for increasing yield, water productivity and saving energy under arid region conditions. To meet the study's objective, two field experiments were carried out at a private farm. Our results demonstrated a general decrease in water stress and salt accumulation inside root-zone area with PRD with L3. The PRD strategy increased fruit yields by 3.7 and 7.3% and water productivity by 51.9 and 53.1% compared with I1 during 2020/2021 and 2021/2022, respectively, while reducing the applied irrigation water by 50 %. The PRD strategy showed superior results in increasing mango yield and water productivity. In general, PRD can be used as good technique to save water and energy up to 50% and enhance productivity along with using organic mulching, ultimately improving mango yield under arid climatic regions. It may prove a good adaptation strategy for current and future water shortage scenarios of climate change.

Objective Objective of the study was to evaluate the public perception and acceptance of community pharmacists in providing mental health support in Saudi Arabia during COVID-19. Methods An online questionnaire-based cross-sectional study was carried out among the general public (aged 15 years or above) of Saudi Arabia during March-April 2020 using QuestionPro platform. The validated questionnaire was bilingual (English and Arabic), simple, detailed, and relevant to obtain focused responses from participants. Importantly, an item related to an agreement on a statement “Pharmacist can counsel people on psychological issues” was included on a five-point Likert scale. The survey link was shared across multiple social media platforms. Results A total of 773 participants completed the survey. The majority were female (65.2%) and youngsters (48.1%). Nearly half of the participants disagreed, while 19% agreed that pharmacists could provide support on psychological issues. Factors such as age, employment status, and the management of the psychological issues during the pandemic were significantly associated with the acceptance of community pharmacists’ role in providing mental health services (p

It is an utmost importance to characterize drug candidates as early in the development pipeline as possible. Appropriate application of the emerging high throughput analytical techniques unlocks the opportunities to obtain experimental data for in vitro absorption, distribution, metabolism and elimination (ADME) profiling of large compound libraries which is crucial for selection of lead compounds. In an usual scenario, only one drug candidate will be selected from thousands of early compounds based on several stability and screening results. A high to medium throughput screening approaches could significantly accelerates the subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high throughput LC-MS/MS techniques to meet with the lead profiling demands. In this study presented an innovative experimental approach that can offer a refreshing alternative. Laser Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS) is a quick and efficient method for characterizing complex biological samples without laborious sample preparation and chemical separation. Therefore, using an automated LA-REIMS well plate reader as fast as 8 seconds per sample, we assessed the oxidative metabolic stability of active agents using biomimetic metalloporphyrin-based oxidative model reactions at various pH for commercially available drug substances and compared stability measurements with traditional HPLC-DAD-MS results.

In this paper, inspired by recent articles of G. Anatriello and G. Vincenzi (see \cite{Ana}), and G. Cerda-Morales (see \cite{Cer1,Cer2}), we will introduce the third-order $\overline{h}$-Jacobsthal and third-order $\overline{h}$-Jacobsthal--Lucas sequences and their associated quaternions. The new results that we have obtained extend most of those obtained in \cite{Cer2}.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

Silybum marianum is a therapeutic plant belonging to the family Asteraceae. It contains silymarin, as its principal component, and has been reported to demonstrate hepatoprotective activity. The study was aimed to investigate the phytochemical constituents, synthesis of nanoparticles, antioxidant activity and antimicrobial effects of the leaf extract. Extracts were synthesized from AgNO3 and characterized via FT-IR, U.V and XRD. The antioxidant activity was determined using DPPH, H2O2 and β-carotene assays. Similarly, all extracts expressed significant DPPH inhibition (IC50) of 5.1, 5.0, 4.7, 2.3, 4.3 and 1.1 (ug/mL), H2O2 of 1.3, 2.2, 4.7, 5.6, 4.0 and 1.0 (ug/mL) from the methanol/water extract, nanoparticles, n-Hexane, ETOAC, n-Butanol and Ascorbic acid (standard) respectively. The extract exerted scavenging activity on β-carotene with a significant IC50 inhibition of 1.5, 0.8, 5.2, 0.8, 2.7, 4.8 at 0 hour and 1.5, 0.8, 5.2, 0.8, 2.7 and 4.8 (ug/mL) after 2 hours water bath incubation at 50°C in the order of the extracts above. Additionally, nanoparticles and plant extracts significantly (p<0.0001) inhibited the growth of bacteria with mean zone of inhibition ranging 7-13 mm and 4-11 mm. This study demonstrated that extracts from different solvents of S. marianum possess significant antioxidant activity, as well as antimicrobial effects which are all concentration dependent. Thus, the result suggests that methanolic/water leaf extract of S. marianum could serve as a potential source of antioxidants and can be explored as a therapeutic agent in free radical induced diseases.

In many research fields, statistical probability models are often used to analyze real-world data. However, data from many fields, such as the environment, economics, and health care, do not necessarily fit traditional models. New empirical models need to be developed to improve their fit. In this paper, we explore a further extension of the quasi-Lindley model. Maximum likelihood, least square error, Anderson-Darling algorithm, and expectation-maximization algorithm are four techniques for estimating the parameters under study. All techniques provide accurate and reliable estimates of the parameters. However, the mean square error of the expectation maximization approach was lower. The usefulness of the proposed model was demonstrated by analyzing a dynamical systems data set, and the analysis shows that it outperforms the other models in all statistical models considered.

Objective: This study aimed to explore potential interventions or preventive measures to reduce the incidence of falls among the elderly in the Madinah region, and to provide recommendations for healthcare professionals, policymakers, and community stakeholders to enhance fall prevention strategies and improve the overall well-being of the elderly population in this area. Methods: The study adopted a cross-sectional study design, and was carried out in the Madinah region using convenient physical assignment among of Saudi and non-Saudi local residents aged 65 years and over. Questionnaire surveys were circulated and demographic characteristics were collected, including participants’ fall experience and health status data over the past year, in order to assess the incidence of falls among the elderly population. This design allows for the collection of data at a single point in time, aiming to evaluate the prevalence, risk factors, and consequences of falls among the target population. Results: A total of 189 participants were recruited to the study, and the data indicated that the prevalence of falls among those aged 65 years and older in the past year was 41.5%. We found that 73% of the participants had experienced falls and post-fall injuries within the past 12 months. There were minimal differences in terms of physical handicapped cases found between those with and without a fall history. Logistic regression analysis revealed a significant link between fall experience and maximum bite force. Conclusion: There is a high prevalence of falls in the elderly population in the Madinah region. Our study reveals that 50.79% of our elderly participants had experienced more than one fall during the preceding year. Some preventable risk factors were identified in an analysis of their daily routines. The impacts of these risk factors have potential consequences for their healthy lives.

Introduction: During the COVID-19 pandemic, many countries implemented restrictions, social distancing measures, and lockdowns to limit the spread of the disease. The lockdowns have affected children’s screen time (ST), pain, and physical activity (PA) levels. The present study aimed to explore the relationships between several personal factors during the COVID-19 pandemic. Methods: The caregivers of 329 children (median age=8 years) filled out an online self-reported survey about the children’s PA, ST, and pain before, during, and after the COVID-19 curfew. Spearman’s rank correlation coefficient was used to explore the associations between these variables. Results: After the curfew, pain that existed before the pandemic had a weak negative relationship with PA intensity (-0.11, p=0.04) and a weak positive relationship with ST (r=+0.12, p=0.04). There was a strong positive relationship between ST in all time periods (p&gt;0.01). PA and ST had a weak negative relationship (p&gt;0.05) during the curfew and after the curfew but not before the COVID-19 pandemic. Age had a weak positive correlation with ST in all time periods (p&gt;0.01). In addition, ST was affected by the curfew. Conclusion: The study findings indicated that young children had longer ST during the curfew and after the curfew compared with before the curfew. Increasing PA could lessen children’s ST, which could, in turn, increase the probability that their general pain would decrease.

Ankylosing spondylitis (AS) is a chronic inflammatory arthritis that affects the axial skeleton, causing intense pain, progressive joint destruction, and a gradual reduction in physical function. It has been recognized not only as affecting the axial skeleton but as a systemic disease. Since it also causes an increase in the rates of inflammatory bowel disease, psoriasis, acute anterior uveitis, and mental disorders affecting the quality of life. Furthermore, an association with neurological and cardiovascular events is documented. With the advent of biologics, treating AS dramatically changed due to its high efficacy and tolerable safety. AS can be treated with various biological treatments. Nevertheless, there are differences in traits, including rapidity of onset, long-term efficacy, safety profile, and influence on comorbidities. A better understanding of such traits enables clinicians to make the best decision for each patient, increasing persistence, extending medication survival, enhancing patient satisfaction, and reducing the disease effect of ankylosing spondylitis. In this article, we emphasize biologics' efficacy and safety profile in patients with ankylosing spondylitis. In addition, we discuss the impact of biologics on comorbidities and health-related quality of life.

We have investigated the antiferromagnetic phase transition in the frustrated and multiferroic hexagonal manganites $h$-(Y$_{0.98}$ Eu$_{0.02}$)MnO$_3$ (YEMO) and $h$-YMnO$_3$ (YMO). Elastic neutron scattering has been used to study in detail the phase transition in YMO and YEMO in zero pressure and in YMO at a hydrostatic pressure of 1.5~GPa. In zero pressure, we find the critical temperature $T_{\rm N} = 72.11(5)$~K and 71.3(1)~K and the critical exponent $\beta = 0.206(3)$ and 0.22(2), for YEMO and YMO, respectively. This is in agreement with earlier work by Roessli {\em et al.}. In applied hydrostatic pressure of 1.5~GPa, the ordering temperature increases to $T_{\rm N} = 75.2(5)$~K, in agreement with earlier reports, while $\beta$ is unchanged. Inelastic neutron scattering was used to determine the anisotropy spin wave gap at the phase transition, expected from spin wave theory to close with a critical exponent $\beta'$ identical to the one of the order parameter, $\beta' = \beta$. Our results indicate that the gap in YEMO indeed closes at $T_{\rm N}=72.4(3)$~K with $\beta' = 0.24(2)$, while the in-pressure gap in YMO closes at 75.2(5)~K with an exponent of $\beta' =0.19(3)$. In addition, the low-temperature anisotropy gap was found to have a slightly higher absolute value under pressure. The consistent values obtained for $\beta$ in the two systems support the likelihood of a new universality class for triangular, frustrated antiferromagnets.

Brain cancer is the tenth leading cause of death in the U.S. Glioblastoma multiforme (GBM) is the most lethal primary malignant central nervous system tumor in adults. The present study employed samples from 1985-2014 to discover the difference in prognosis among glioblastoma subtypes after the evolution of treatment modalities over the past few years. The current study aims to find the differences between Glioblastoma multiforme (GBM) and giant cell glioblastoma (GCG) in terms of prognosis among adults and elderly patients in the U.S. This study is a historical cohort type of study and is conducted on adults and elderly individuals with GBM or GCG from the years 1985-2014 in the U.S. Data were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database. The study exposure was GBM or GCG and the outcome was mortality. The potential confounders were age, sex, race, ethnicity, year of diagnosis, primary site, and surgery. A chi-square test was used for categorical data. A univariate analysis was used for variables having a p-value < 0.05. Potential confounders were selected and evaluated using multivariate logistic regression models to calculate the odds ratio with stepwise selection. The study sample was 25,117. The incidences of GBM and GCG were not similar in relation to age group. Also, Spanish-Hispanic ethnicity was independently protective of GBM and GCG as compared to Non-Spanish-Hispanic ethnicity patients with GBM have a higher mortality rate than do GCG patients. The mortality rate was higher among patients diagnosed before 2010. In conclusion, GCG was not statistically significant in association to reduced mortality. Non-Spanish-Hispanics with GBM or GCG had a higher mortality rate than did Spanish-Hispanics. Factors such as being female, being age >59, and having a year of diagnosis before 2010 were independently associated with increased mortality.

The efficiency of a new composite material of the layered double hydroxide (LDH) of ZnMgAl and rice husk biochar (RHB) for the removal of Cu(II) and Pb(II) ions from synthetic wastewater was investigated in this study. The images of scanning electron microscope showed extremely fine crystalline LDH particles decorated on the rough surface of the RHB while the succesful formation of the composite adsorbent (LDH/RHB) was confirmed by the corresponding energy dispersive X-ray and the Fourier-transform infrared spectroscopy. An equilibrium contact time of 30 and 15 min for Cu2+ and Pb2+, respectively, was proposed for the optimum performance of the batch adsorption process. The dose of the LDH/RHB adsorbent was optimized at 0.4 g yielding maximum adsorption capacities of 117 and 124 mg g-1 for Cu2+ and Pb2+, respectively, with corresponding maximum removal efficiencies of nearly 94% and 99%. The initial meta concentrations was optimized at 50 or 60 mg L-1 corresponding to maximum removal efficiencies or adsorption capacities. For the changing initial metal’s concentration, the removal efficiencies remained unchanged for up to 50 mg L-1 and decreased by about 50% by increasing the initial concentrations from 50 to 100 mg L-1. The adsorption capacities observed a linear increasing trend by increasing the initial concentrations from 5 to 60 mg L-1 and remained unchanged afterward up to 100 mg L-1. A solution pH of 6.0 yielded optimum results with an increasing trend in adsorption capacities and percentage removal by changing the solution pH from 2.0 to 7.0. Based on the best-fit of the pseudo second-order kinetic model to the experimental data, the chemisorption was suggested to be the controlling mechanism of adsorption. The fitting of the Langmuir model suggested a monolayer sorption of Cu2+ and Pb2+ in addition to a heterogeneous adsorption as supported by the fitting of the Temkin isotherm. The application of the Dubinin–Radushkevich isotherm proposed a physical adsorption (mean free energy of adsorption less than 8 kJ mol−1) of both heavy metal ions on the surface of the LDH/RHB adsorbent.

Introduction: Laeverin is an extravillous trophoblast marker playing a significant role in the trophoblast migration. The purpose of this study was to evaluate the association between the amniotic and serum laeverin concentrations at 16-22 weeks of gestation and the fetal and placental ultrasound measurements in healthy, unaffected pregnancies. Materials and methods: This was a prospective cross-sectional study. Pregnant women with singleton pregnancies undergoing amniocentesis were recruited consecutively. Fetal structural malformations and/or aneuploidy were exclusion criteria. Fetal biometric parameters and placental growth/perfusion were measured in 44 high-risk pregnancies who had no pregnancy complication and any other chronic disease. Maternal serum and amniotic levels of laeverin were essayed with sandwich enzyme-linked immunosorbent assay. Results: Serum laeverin levels are decreasing slightly with the maternal age in mid-gestation. Serum laeverin level correlated negatively slightly with head size of the fetus with the gestational length at delivery (β=-0.38, 95% confidence interval (CI) -0.03-0.01), while the amniotic laeverin level correlated strongly with the abdominal circumference of the fetus (β=-0.64, 95% CI: -0.03-0.01). Furthermore, laeverin level in the amnion correlated moderately and positively with the placental volume (β=0.46, 95% CI: 0.01-0.08). Conclusions: Laeverin levels detected in the serum and in the amniotic fluid denotes the fetoplacental growth in uncomplicated high-risk pregnancies.

The calculation of effective doses is crucial in many medical and radiation fields, in order to ensure safety and compliance with regulatory limits. Traditionally, Monte Carlo codes using detailed human body computational phantoms have been used for such calculations. Monte Carlo dose calculations can be time-consuming and require expertise in different processes when building the computational phantom and dose calculations. This study employs various machine learning (ML) algorithms to predict the organ doses and effective dose conversion coefficients (DCCs) for different anthropomorphic phantoms. A comprehensive data set comprising neutron energy bins, organ labels, masses, and densities is compiled from Monte Carlo studies, and is used to train and evaluate the supervised ML models. This study includes a broad range of phantoms, including those from the International Commission of Radiation Protection (ICRP-110, ICRP-116 phantom), the Visible-Human Project (VIP-man phantom), and the Medical Internal Radiation Dose Committee (MIRD-Phantom), with row data prepared using numerical data and organ categorical labeled data. Extreme gradient boosting (XGB), gradient boosting (GB), and the random forest-based Extra Trees regressor are employed to assess the performance of the ML models against published ICRP neutron DCC values using the mean square error, mean absolute error, and R² metrics. The results demonstrate that the ML predictions significantly vary in lower energy ranges and vary less in higher neutron energy ranges, while showing good agreement with ICRP values at mid-range energies. Moreover, the categorical data models align closely with the reference doses, suggesting the potential of ML in predicting effective doses for custom phantoms based on regional populations, such as the Saudi voxel-based model. This study paves the way for efficient dose prediction using ML, particularly in scenarios requiring rapid results without extensive computational resources or expertise. The findings also indicate potential improvements in data representation and the inclusion of larger data sets to refine model accuracy and prevent overfitting. Thus, ML methods can serve as valuable techniques for the continued development of personalized dosimetry.

Source water quality is a key determinant of drinking water quality. The recast European Union 2020/2184 drinking water directive (DWD) introduced the obligation for comprehensive risk assessment in drinking water supplies, including the water source and incorporated new elements of natural origin in the list of parameters to be monitored. The current study is the first comprehensive assessment of 15 natural elements (B, Ba, Be, Ca, Co, K, Li, Mg, Mo, Na, Se, Sr, Ti, U and V) in 1155 (82%) Hungarian drinking water sources, including surface water, bank filtered and groundwater sources. Parameters posing a risk to health (Se, V and U) were typically below the lower limit of quantification (LOQ), but higher concentrations (max. 7.0, 17 and 41 µg/L, respectively) may occur in confined locations, the latter exceeding the DWD parametric value in one water supply. Li in a small geographical area, Mg and Ca in the majority of the water supplies reached the concentration range assumed to be protective to health. Water sources were grouped in 6 clusters based on their element distribution, some of them also showing clear geographical patterns. Water types were not differentiated, with the exception of karstic waters (dominated by Ca and Mg). None of the investigated parameters are expected to be a source of public health concern.

This article introduces a novel payload structure, which has been experimentally proven to have smaller impact force while the carried internal electronics remains intact. The study describes in details how materials and geometric structures were chosen based on information analysis. It is clarified how possible geometric structures and materials can be chosen to yield optimal efficiency. Finite element method simulations were carried out to investigate the mechanical properties of several geometric structures, which has led to the dodecahedron form. For the frame, Polylactic Acid were chosen as an optimal material. A low air pressure test for parts of the structure, and also the whole structure were carried out with successful results. Drop tests, with force measuring sensors and high speed videos, were carried out for measuring and comparing the maximal impact force of classical payloads and the novel one. Laboratory and real life tests demonstrated that the developed new structure is safer and it is applicable.

As the demand of heating and air conditioning is increasing day by day due to getting a comfortable life, for that reason, the market for heat pump and air conditioning systems or both, is seeing a steady increase in low global warming potential. All researchers on heat pump and air conditioning systems are searching for environmentally friendly refrigerants. However, a significant number of contemporary refrigerants (HCFCs) have the potential to cause global warming and ozone depletion, such as those found in heat pump air conditioning systems. Using more environmentally friendly refrigerants, including hydrocarbon and blend refrigerant mixtures, is one way to lower GWP and Ozone depletion potential. This study examines the performance of several alternative refrigerants, including R32, R134A, R410A, R22, and R290. In order to examine the performance of R290, theoretical and simulation results are compared on various refrigerants while taking into account a number of performance parameters, including the refrigerant energy efficiency ratio, mass flow rate, coefficient of performance, cooling capacity, and compressor work for one ton of refrigeration (1TR) air conditioners. One player with a very low GWP is R290. However, the only drawback is that it can catch fire and is hazardous to use in split-type commercial heat pump air conditioning applications. The environmental and thermo physical properties of HC-290 are significantly better than those of other materials, according to theoretical and simulation studies utilizing Cool Pack software, hence it is a viable replacement.

Multiwalled Carbon Nanotubes (MWCNTs) is more efficient for fabrication modern design of silicone rubber (SR) that used in industrial engineering applications; it has been embedded in room temperature vulcanization silicone rubber (RTV-SR) matrix for controlling in dielectric characterization. Frequency dielectric measurements were performed for multiwalled carbon nanotubes SR/MWCNT nanocomposites. Hence, the dielectric properties of modern design SR/MWCNT nanocomposites has been deduced as experimental work done to clarify the benefit of filling MWCNT with different patterns inside dielectrics. In variant thermal conditions (up to 40oC), it has been investigated that the new behaviors of SR/MWCNT nanocomposites dealing with nanotechnology techniques for designing new dielectric behaviors of insulation materials. Finally, this research succeeded to characterize dielectric constant, electric modulus and dielectric loss of SR/MWCNT nanocomposites with respect to traditional silicon rubber under variant thermal conditions and frequency response analysis (FRA) according to using certain types and concentrations of MWCNTs.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

Polysulfides are endogenously produced in mammals and generally associated with protective functions. Our aim was to investigate the effect of dimethyl trisulfide (DMTS) in a mouse model of acute stress. DMTS activates transient receptor potential ankyrin 1 (TRPA1) channels and leads to neuropeptide release, potentially that of substance P (SP). We hypothesize that DMTS might inhibit the degrading enzymes of endocannabinoids, so this system was also investigated as another possible pathway for mediating the effects of DMTS. Trpa1 gene wild type (WT) and knock out (KO) mice were used to confirm the role of the TRPA1 ion channel in mediating the effects of DMTS. C57BL/6J, NK1 gene KO, and Tac1 gene KO mice were used to evaluate the effect of DMTS on the release and expression of SP. Some C57BL/6J animals were treated with AM251, an inhibitor of the cannabinoid CB1 receptor, to elucidate the role of the endocannabinoid system in these processes. Open field test (OFT) and forced swim test (FST) were performed in each mouse strain. Tail suspension test (TST) was performed in TRPA1 WT and KO animals. C-FOS immunohistochemistry was carried out on TRPA1 WT animals. DMTS treatment increased the number of highly active periods and decreased immobility time in the FST in WT animals, but had no effect on Trpa1 KO mice. DMTS administration induced neuronal activation in stress-related brain areas such as the locus coeruleus, dorsal raphe nucleus, lateral septum, paraventricular nucleus of the thalamus, and paraventricular nucleus of the hypothalamus. DMTS may have a potential role in the regulation of stress-related processes, and the TRPA1 ion channel may also be involved in mediating the effects of DMTS. DMTS can be an ideal candidate for further study as a potential remedy in stress-related disorders.

This paper presents a particular tunneling method or new Austrian tunneling method (NATM) which plays an important role in reducing the subsidence of the Earth surface and the damage to the structures in urban areas. It has a wide range of applications in shallow tunneling projects all over the world. In this study, numerical modeling of third-line Metro tunnel in Tehran is under discussion which is designed and stabilized by NATM. The foregoing tunnel is excavated manually with a one-meter advancing step. In this project, the constructors used a lattice girder and sprayed concrete with 31 cm thickness as the initial lining. A suitable numerical software for this modeling is Plaxis 3D tunnel, which allows performing high-resolution finite element modeling (FEM) of the studied object. The performance of this method is investigated and compared with other NATM methods. As a result of numerical modeling, we give a value of 30.01 mm earth subsidence in the most damaged area of the settlement, in comparing with that of earth surface monitoring, which confirmed it with a dramatically low difference. Moreover, this tunnel was drilled and excavated with various methods, among which the less settlement has obtained by the proposed method. The results are promising to continue the tunneling with this method to expand the subway line in the city.

Informal settlements pose multifaceted challenges to urban development, necessitating a reconsideration of traditional upgrading approaches. This study examines the integration of the Street-Led Approach within the Ezbit Hegazi informal settlement, leveraging the Alexandria University Centre of Excellence for Smart Urban Governance's (ALEXU-CoE-SUG) innovative framework. It highlights the centrality of 'Demand for Good Governance' (DFGG) practices in bridging the gap between governmental (supply-side) and community (demand-side) objectives, fostering a collaborative urban upgrading process. Through an in-depth case study analysis, this paper reveals the potential of aligning governmental agendas with local aspirations, emphasizing the importance of local dynamics in sustainable urban development. The findings contribute to the urban studies literature by providing insights into the synergies between supply and demand perspectives in the context of informal settlement upgrading, offering implications for policy and practice in similar urban settings globally.

As a result of increased energy consumption, global trade has surged, and serious environmental problems have arisen. The problem is made more complicated by the fact that either environmental damage or economic advancement cannot be compromised. The elements contributing to environmental contamination must be identified and dealt with accordingly if we are to have a healthier future. In this study, what causes CO₂ emissions in Malaysia are examined using the Autoregressive distributed lag (ARDL) model using time series data from 1995 to 2020. The paper also examines the impact of energy use and economic complexity on CO2 emissions. Firstly, it is noted that the Environmental Kuznets Curve (EKC) theory holds in Malaysia. Furthermore, energy consumption has a detrimental impact on reducing CO2 emissions. Furthermore, it has been noted that a greater degree of economic complexity leads to an elevated amount of CO2 emissions over an extended period. The findings suggest significant environmental policy implications for reducing CO2 emissions in Malaysia.

Recently, the use of drones/unmanned aerial vehicles (UAVs) has notably increased due to their broad commercial spread and low cost. The wide diffusion of drones increases the hazards of their misuse in illegitimate actions such as drug smuggling and terrorism. Thus, the surveillance and automated detection of drones are crucial for safeguarding restricted regions or special zones from illegal drone interventions. One of the most challenging issues in drone detection in surveillance videos is the apparent similarity of drones and birds against complex backgrounds. In this work, an automated image-based drone-detection system utilizing an advanced deep-learning-based object-detection method known as you only look once (YOLOv5) is introduced for protecting restricted regions or special zones from unlawful drone interventions. Due to the lack of sufficient data, transfer learning was utilized to pretrain the object-detection method to increase the performance. The experiments showed outstanding results, and an average precision of 94.7% was accomplished.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

In this paper, we investigate a new $q$-analogue of the higher order degenerate Changhee polynomials and numbers, which are called the Witt-type formula for the $q$-analogue of degenerate Changhee polynomials of order $r$. We can derive some new interesting identities related to the degenerate $(h,q)$-Changhee polynomials and numbers.

The evidential value of an mtDNA match between biological remains and its potential donor is determined by the random match probability of the haplotype. This probability is based on the haplotype’s population frequency estimate. Consequently, implementing a population study representative of the population relevant to the forensic case is vital to correctly evaluating the evidence. The emerging number of poaching cases and the limited availability of such data emphasizes the need for improved fallow deer mtDNA population databank for forensic purposes, including targeting the entire mitochondrial control region. By sequencing the whole mitochondrial control region in 138 animals from five populations in Hungary we found four different haplotypes, including one which has not yet been described. Our results, supplemented with data already available from previous research do not support the possibility of determining the population of origin, although some patterns of geographical separation can be distinguished. Estimates of molecular diversity indicate approximately similarly low mtDNA diversity (Hd=0.565 and π = 0.002), compared with data from other countries. The calculated random match probability of 0.547 shows a high probability of coincidence and, therefore, a limited capacity for exclusion. Consequently, it may be necessary to search for polymorphic sites on other mitochondrial gene sections or to sequence the entire mitogenome of fallow deer.

In this paper, we address the problem of car detection from aerial images using Convolutional Neural Networks (CNN). This problem presents additional challenges as compared to car (or any object) detection from ground images because features of vehicles from aerial images are more difficult to discern. To investigate this issue, we assess the performance of two state-of-the-art CNN algorithms, namely Faster R-CNN, which is the most popular region-based algorithm, and YOLOv3, which is known to be the fastest detection algorithm. We analyze two datasets with different characteristics to check the impact of various factors, such as UAV’s altitude, camera resolution, and object size. The objective of this work is to conduct a robust comparison between these two cutting-edge algorithms. By using a variety of metrics, we show that none of the two algorithms outperforms the other in all cases.

The human landscape transforming activity contributes to the global change of vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We are investigating the vegetation dynamics over several years in in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). One important background factor is changes in precipitation and temperature. The novelty of our present study lies in the fact that the observation takes place with continuous disturbance, where the human influence is very large. Our results confirm that the weed infestation be detectable at bait sites over a long period, and the interannual changes were typical in every year, according to the fact that in August, more weed species are usually present with a greater cover at the bait sites. The main meteorological factors played a role in the degree of weed infestation in each year. There was a higher proportion of vegetation regeneration in wetter years, while dry periods do not favor successional processes. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. A more precise understanding of vulnerable systems and careful planning of treatment interventions is necessary.

Organic Coatings have potential applications in the prevention of metal corrosion in an aqueous solution. The protective effect of SEBS coated copper corrosion in NaCl 3% solution was investigated by using electrochemical methods. The main objective of this work is to find the optimal conditions of the protocol immersion to evaluate the effects of SEBS ratio and two-immersion time on the anticorrosive behaviour of copper in 3 wt % NaCl solution in order to determine the best conditions to produce a protective SEBS film on the copper surface. Response Surface Methodology (RSM) is used as an optimization method. The study’s findings show the combination of three environmental factors that minimize corrosion rate. The Box-Behnken Design (BBD) is working perfectly for the statistical significance of the model (ANOVA test). This analysis calculates the contribution value of each parameter in changing the value of the corrosion rate (CR) in not only individual but also synergistic cases. The optimized parameters were found to be a 2.17% of SEBS ratio, 20 min of immersion 1, and 21 min of immersion 2. The electrochemical impedance spectroscopy tests confirmed the results.

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.

The treatment of the bulky Rind-based dibromosilanes, (Rind)2SiBr2 (2) [Rind = 1,1,7,7-tetra-R1-3,3,5,5-tetra-R2-s-hydrindacen-4-yl: EMind (a: R1 = Et, R2 = Me) and Eind (b: R1 = R2 = Et)], with two equivalents of tBuLi in Et2O at low temperatures resulted in the formation of blue solutions derived from the diarylsilylenes, (Rind)2Si: (3). Upon warming the solutions above −20 °C, the blue color gradually faded, accompanying the decomposition of 3 and yielding the cyclic hydrosilanes (4) via intramolecular C−H bond insertion at the Si(II) center. The molecular structures of the bulky Eind-based 3b and 4b were confirmed by X-ray crystallography. Thus, at −20 °C, blue crystals were formed (Crystal-A), which were identified as mixed crystals of 3b and 4b. Additionally, colorless crystals of 4b as a singular component were isolated (Crystal-B), whose structure was also determined by an X-ray diffraction analysis. Although the isolation of 3 was difficult due to their thermally-labile nature, their structural characteristics and electronic properties were discussed based on the experimental findings complemented by computational results. We also examined the hydrolysis of 3b to afford the silanol, (Eind)2SiH(OH) (5b).

A modular approach to the construction of electric machines, drive systems, power supply systems is a new direction of modern technology development. Especially, the modular approach is promising for electric vehicles due to such positive aspects as increased efficiency, fault tolerance, overall reliability, safety, enhanced control capabilities, etc. In this work, the modular approach is comprehensively applied to an EV powertrain system, which includes a dual three-phase (DTP) BLDC motor with two machine modules of an asymmetric configuration, two battery modules and a supercapacitor module (SCM). The proposed H–H configuration of modular EV powertrain system includes four voltage source inverters that combine the power modules with the open ends of the windings (OEW) of the module machine armature, and provide control of their operation. Based on the developed mode system of the OEW machine module operation for EV traction and braking, a general control algorithm for the proposed configuration of the modular EV powertrain system has been developed. It combines the control of the operating modes with the functions of maintaining the required SOC level of the SCM and equalizing the SOCs of the two battery modules. The conducted simulation and experimental studies confirmed the workability and effectiveness of the proposed solutions.

Introduction: Galectin-13 (Gal-13) is predominantly produced by the syncytiotrophoblast, while laeverin is expressed on the outgrowing extravillous trophoblast, and both are thought to be biomarkers of preeclampsia. The aim of this study was to assess the correlation between concentrations of Gal-13 and laeverin measured in maternal serum and amniotic fluid at 16-22 weeks of gestation and the sonographic assessment of the fetoplacental measurements. Materials and methods: Fetal biometric data, and placental volume and perfusion indices were measured in 62 singleton pregnancies. Serum and amniotic levels of Gal-13 and laeverin levels were measured using a sandwich ELISA. Results: Both amniotic fluid and serum Gal-13 levels expressed a negative correlation to the plasma laeverin level in mid-pregnancy. Serum laeverin level correlated positively with the gestational length at delivery (β=0.39, p

In this paper, we address the problem of car detection from aerial images using Convolutional Neural Networks (CNN). This problem presents additional challenges as compared to car (or any object) detection from ground images because features of vehicles from aerial images are more difficult to discern. To investigate this issue, we assess the performance of two state-of-the-art CNN algorithms, namely Faster R-CNN, which is the most popular region-based algorithm, and YOLOv3, which is known to be the fastest detection algorithm. We analyze two datasets with different characteristics to check the impact of various factors, such as UAV's altitude, camera resolution, and object size. The objective of this work is to conduct a robust comparison between these two cutting-edge algorithms. By using a variety of metrics, we show that YOLOv3 yields better performance in most configurations, except that it exhibits a lower recall and less confident detections when object sizes and scales in the testing dataset differ largely from those in the training dataset.

Background: The study describes the comparison of different microbial load results of natural falling and dipping of the house fly (Musca domestica) in water and milk to investigate the possibilities of preventing the effect of the transferred pathogens from the house fly to our sources by pointing out the existence of antimicrobial factors within the house fly. Methods: Samples of house fly were collected from Jeddah and Makkah (Makkah region) and were directly transferred to the laboratory. Each house fly was packed in sterile test tubes. Each tube was opened oppositely to a larger test tube containing 10 ml of sterile tap water, and sterile water at pH 4.0 in other similar series of treatments to represent the reactions of stomach fluids. Later, the house flies were left for 20 seconds after reaching the water surface, and then cultured on different microbial media to evaluate the microbial load of the natural falling of the house fly. To evaluate the complete dipping of house flies in the water, two methods were tested by one complete dip for the flies for 20 seconds, and three times complete dipping for 20 seconds in water before evaluating the microbial load. The same methods were achieved on milk in a series of experiments and the microbial load was evaluated after the incubation at room temperature for three hours. Results: It was found that dipping treatments of house flies gave lower microbial contamination in water at pH 4.0 than neutral pH. The lower microbial load was also observed when dipping the house flies three times in water as compared to once dipping and natural falling treatments. It was also found that the complete dipping of house flies’ treatments in milk will reduce the microbial contamination as compared to natural falling treatments. Conclusion: The observed results support the presence of antimicrobial factors on the house fly.

The worldwide competition to vaccinate against COVID-19 has highlighted the importance of immunization measures in containing the virus. Saudi Arabia, like the rest of the globe, must assess socio-demographic subtleties, chronic illnesses, vaccination effects, and public health policy implications as it navigates this complicated environment. This cross-sectional study examined Saudi COVID-19 vaccine in many ways. It examined the socio-demographic makeup of vaccine recipients, the prevalence of chronic conditions in this population, vaccine administration patterns, post-vaccination side effects, and vaccine-infection rates. A questionnaire-based online survey of 401 participants ensured gender, nationality, age, weight, and educational diversity. We analyzed vaccine manufacturer choice for each dosage, side effects after the first and second doses, and chronic diseases in the sample. Pfizer/BioNTech vaccines are preferred for all three doses, reflecting worldwide vaccination acceptance patterns. Side effects were not significantly different between vaccination kinds. Interestingly, immunization reduced infection rates, demonstrating the efficacy of COVID-19 vaccines. The data fills important information gaps and illuminates Saudi COVID-19 vaccination kinetics. These data support the global preference for mRNA vaccines, demonstrating the faith in this breakthrough technology. They also sponsor COVID-19 vaccine safety and effectiveness studies. The dramatic drop in infection rates among vaccinated people shows how vaccinations suppress the pandemic. These findings inform Saudi Arabia's immunization efforts. As booster doses become more common, long-term vaccination research is crucial. Vaccine reluctance, especially in certain demographics, must be addressed. Due to vaccines' protective potential, equitable vaccine distribution and large immunization programs are essential for herd immunity and pandemic management. This thorough cross-sectional study helps policymakers and healthcare practitioners build successful and inclusive COVID-19 immunization regimens in Saudi Arabia.

In this paper, the design and analysis of coupled tank water level control system is done using robust control theory. The main aim of this work is to improve level controlling mechanisms in industries and household areas. In this paper, H ∞ and μ –synthesis controllers are designed to improve the level control system. The coupled tank water level control system is designed using the proposed controller’s comparison and tested for tracking a reference level signals (step, sine wave and random) and simulation results have been analyzed successfully. Finally the comparative simulation results prove the effectiveness of the proposed coupled tank water level control system with H ∞ controller for improving the tracking mechanism performance of the system.

In this work, we introduce the class of h-MN-convex functions by generalizing the concept of MN-convexity and combining it with h-convexity. Namely, let M : [0, 1] → [a, b] be a Mean function given by M (t) = M (t; a, b); where by M (t; a, b) we mean one of the following functions: A_t (a, b) := (1 − t) a + tb, G_t (a, b) = a^1−tb^t and H_t (a, b) := $\frac{ab}{ta+\left(1-t\right)b}=\frac{1}{A_t\left(\frac{1}{a},\frac{1}{b}\right)}$ with the property that M (0; a, b) = a and M (1; a, b) = b. Let I, J be two intervals subset of (0, ∞) such that (0, 1) ⊆ J and [a, b] ⊆ I. Consider a non-negative function h : J → (0, ∞), a function f : I → (0, ∞) is said to be h-MN-convex (concave) if the inequality f (M (t; x, y)) ≤ (≥) N (h(t); f (x), f (y)), holds for all x, y ∈ I and t ∈ [0, 1]. In this way, nine classes of h-MN-convex functions are established, and therefore some analytic properties for each class of functions are explored and investigated. Characterizations of each type are given. Various Jensen’s type inequalities and their converses are proved.

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid bat-tery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is of particular importance because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system perfor-mance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, and cost-effective energy storage op-tion. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. In this work, battery-supercapacitor storage system (HBSS) is established by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that ef-fectively controls the different power sources. The algorithm's purpose is to regulate the charge and discharge cycles of the HBSS, ensuring that the state of charge (SOC) of both batteries and supercapacitors remains within the desired range. The proposed management algorithm is de-signed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. By maintaining the SOC of these energy storage components within the specified limits, the proposed method ensures their longevity and max-imizes their performance. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.

The ribonuclease H (RNase H) active site of HIV-1 reverse transcriptase (RT) is the only viral enzyme not targeted by approved antiretroviral drugs. Using a fluorescence-based in vitro assay, we screened 65,239 compounds at a final concentration of 10 µM to identify inhibitors of RT RNase H activity. We identified 41 compounds that exhibited 50% inhibitory concentration (i.e., IC50) values &lt; 1.0 µM. Two of these compounds, 2-(4-methyl-3-(piperidin-1-ylsulfonyl)phenyl)benzo[d]isothiazol-3(2H)-one (1) and ethyl 2-(2-(3-oxobenzo[d]isothiazol-2(3H)-yl)thiazol-4-yl)acetate (2), which both share the same benzisothiazolone pharmacophore, demonstrate robust antiviral activity (50% effective concentrations of 1.68 ± 0.94 µM and 2.68 ± 0.54, respectively) in the absence of cellular toxicity. A limited structure-activity relationship analysis identified two additional benzisothiazolone analogs, 2-methylbenzo[d]isothiazol-3(2H)-one (3) and N,N-diethyl-3-(3-oxobenzo[d]isothiazol-2(3H)-yl)benzenesulfonamide (4), which also resulted in inhibition of RT RNase H activity and virus replication. Compounds 1, 2 and 4, but not 3, inhibited the DNA polymerase activity of RT (IC50 values ~ 1 to 6 µM). In conclusion, benzisothiazolone derivatives represent a new class of multifunctional RT inhibitors that warrants further assessment for the treatment of HIV-1 infection.

The use of mobile phones has increased dramatically among drivers in multiple countries in the past few years. The primary objective of this study was to measure the prevalence of cell phone use while driving in Saudi Arabia and to find whether there is a relationship between car accidents and the use of mobile phones while driving. The secondary objective was to explore general knowledge and attitudes toward traffic regulations related to cell phone usage while driving. This is a cross-sectional study conducted among 585 drivers in Saudi Arabia using a self-reported online survey distributed through social media channels. Our results showed that 78.6% of the participants acknowledged that they use the phone while driving. The percentage who reported car accidents involving them or their friends or relatives while using the phone while driving was 43.8%, along with 71.8% mentioning near misses. The percentage of respondents who thought that using a mobile phone while driving had a strong impact on the driver’s ability to drive was 31.5%. This study highlights the importance of raising awareness about risks of using Mobile phones during driving in Saudi Arabia and it recommends harsher penalties to reduce the use of mobile phones while driving.

Migraine is a primary headache disorder with a prevalence of 11.6% globally and 27% in Saudi Arabia. Irritable bowel syndrome has a prevalence of 9.2% worldwide. The prevalence of IBS has not been established nationally. However, provincial studies for both migraine and IBS have been conducted across the nation. There is a significant link between migraines and IBS globally. This identifies an association that needs to be investigated in a nationwide manner. This study aims to observe the association and the relationship between migraine and irritable bowel syndrome in Saudi Arabia. A cross-sectional study was conducted between March 2021 to June 2021 among the general population of Saudi Arabia, whose ages are 15 years old or greater. The data collection tools included MS-Q for migraine symptoms, MIGSEV scale for severity of migraine, and The IBS module of the Rome IV Diagnostic Questionnaire (R4DQ) for IBS symptoms and its subtype. With a total of 2802 participants, the majority of the study sample were males, who constituted 52.5%. Among the study's sample, the prevalence of migraine consisted of 27.4%, and the prevalence of IBS was 16.4%. The odds of having IBS in migraineurs were much higher than in those without migraines (OR 4.127; 95% CI 3.325-5.121), and the association was statistically significant (P&lt;0.001). In conclusion, there is a strong association between migraine and irritable bowel syndrome in Saudi Arabia.

This paper aims to unify q-derivative/q-integral and h-derivative/h-integral in a single definition, this will be called q−h-derivative/q−h-integral. These notions are further extended on finite interval [a,b] in the form of left and right q−h-derivatives and q−h-integrals. Some inequalities are studied for q−h-integrals which are directly connected with well known results. In diverse fields of science and engineering the theory based on q-derivatives/q-integrals and h-derivatives/h-integrals can be unified by using the concept of q−h-derivative/q−h-integral.

Renewable resources gain increasing interest as source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014–2018). Special focus is drawn on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.

An H-bond involves the sharing of a hydrogen atom between an electronegative atom to which it is covalently bound (the donor) and another electronegative atom serving as an electron acceptor. Such bonds represent a critically important geometrical force in biological macromolecules and, as such, have been characterized extensively. H-bond formation invariably leads to a weakening within the acceptor moiety due to the pulling exerted by the donor hydrogen. This phenomenon can be compared to a spring connecting two masses; pulling one mass stretches the spring, similarly affecting the bond between the two masses. Herein, we describe the opposite phenomenon when investigating the energetics of the C-H...O=C bond. This bond underpins the most prevalent protein transmembrane dimerization motif (GxxxG) in which a glycine C-H on one helix forms a hydrogen bond with a carbonyl in a nearby helix. We use isotope-edited FT-IR spectroscopy and corroborating computational approaches to demonstrate a surprising strengthening of the acceptor C=O bond upon binding with the glycine C-H. We show that electronic factors associated with the C-H bond strengthen the C=O oscillator by increasing the s-character of the -bond, lowering the hyperconjugative disruption of the -bond. In addition, a reduction of the acceptor C=O bond’s polarity is observed upon the formation of the C-H...O=C bond. Our findings challenge the conventional understanding of H-bond dynamics and provide new insights into the structural stability of inter-helical protein interactions.

In this data deposit, I describe a dataset that is the result of content mining 167,318 published articles for statistical test results. As a result of this content mining, 688,112 results from 50,845 articles were extracted. In order to provide a comprehensive set of data, the statistical results are supplemented with metadata from the article they originate from. The dataset is provided in a comma separated file (CSV) in long-format. For each of the 688,112 results, 20 variables are included, of which seven are article metadata and 13 pertain to the individual statistical results (e.g., reported and recalculated p-value). A five-pronged approach was taken to generate the dataset: (i) collect journal lists, (ii) spider journal pages for articles, (iii) download articles, (iv) add article metadata, and (v) mine articles for statistical results.

In this study, we define new classes of convexity called of h-Godunova-Levin and h-Godunova-Levin preinvexity, through which some new inequalities of Hermite-Hadamard type were established. These new classes are the generalisation of several known convexity including the s-convex, P-function, Godunova-Levin. Further, the properties of h-Godunova-Levin function were also discussed. Meanwhile, the applications of h-Godunova-Levin Preinvex function are given

In this work, several inequalities of Popoviciu type for h-MN-convex functions are proved, where M and N are denote to Arithmetic, Geometric and Harmonic means and h is a non-negative superadditive or subadditive function.

The fitting and modeling of skewed, complex, symmetric, and asymmetric datasets is an exciting research topic in many fields of applied sciences, notably lifetime, medical, and financial sciences. The Heavy tailed Nadarajah Haghighi model is introduced by compounding the heavy tailed family and Nadarajah Haghighi distribution in this paper. The so obtained model has three parameters accounting for the scale and shape of the distribution. The proposed distribution's fundamental characteristics such as probability density, cumulative distribution, hazard rate, and survival functions are provided, and several key statistical properties are established, and several entropy information measures are proposed. The estimation of model parameter is performed via the ML procedure. Further, different simulation experiments are conducted to demonstrate the performance of proposed estimator’s using some measure, like the average estimate, the average bias, and associated mean square error. Finally, we are applied our proposed model to analyze three different real datasets. In our illustration, we are compared the practicality of the recommended model with several well-known competing models.

Modern automotive systems should must satisfy strict reliability requirements. Most of the real vehicle systems and safety-critical networks have complex interconnections. Sensitivities and probabilistic uncertainties of reliability of System with Complex Interconnections (SwCI) can be investigated by the Monte-Carlo Simulation (MCS). The paper focuses on sensitivities and parametrical uncertainties of SwCIs reliability. The proposed method can be used forimplemented in the investigation of uncertainties of SwCIs reliability – in other wordsi.e., for in the determination of critical system elements and to estimateion of the Required Number of Spare Parts (RNSP) of the system, which depends on the probability of allowable spare equipment shortage.

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel Electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer number of sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: Up, Down, Left, and Right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration has been implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based Brain-Computer Interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50% and 92.62% for precision, recall, and F1-score, respectively.

One of the main challenges of cultured meat is reducing the costs of production, often described as scaling. The main components of the cultivation process include: cells, media, scaffolds and bioreactors. This work presents an alternative to current stainless steel or glass bioreactors and uses food-grade plant-based scaffolds. Bioreactors must be sterile and leak-free to maintain a proper environment for cell growth. Thermoplastic films are a popular material for constructing these fluidic systems, but traditional methods of welding these film are expensive and do not allow rapid prototyping resulting in high research and development costs for companies. In this study, a laser welding method was developed to join thermoplastic films in a way that prevents contamination and leaks, affording effective macro-fluidics fabrication. This technique was tested using polyethylene (PET) films and a laser cutter operating with settings calibrated for the material to be welded or cut. The laser welding method was found to produce strong, leak-free seals in PET films with minimal heat-induced damage to the films. The ability to design fluidics, chambers and ports of various size. Using this method afforded the incorporation of plant-based scaffolds from food-grade plants (Rice). The laser welding method developed in this study provides a reliable, contamination-free method for the rapid fabrication of fluidic systems for cell cultivation. This technique has the potential to be compatible with a vast range of cell types and scaffolds and to be widely adopted in tissue engineering for regenerative medicine and food applications such as cultured meat.

In the frame of our diversity-oriented research on multitarget small molecule anticancer agents, utilizing convergent synthetic sequences terminated by Sonogashira coupling reactions, a preliminary selection of representative alkyne-tethered vindoline hybrids was synthesized. The novel hybrids with additional pharmacophoric fragments of well-documented anticancer agents, including FDA-approved tyrosine-kinase inhibitors (imatinib and erlotinib) or ferrocene or chalcone units, were evaluated for their antiproliferative activity on malignant cell lines MDA-MB-231 (triple negative breast cancer), A2780 (ovarian cancer), HeLa (human cervical cancer) and SH-SY5Y (neuroblastoma) as well as human embryonal lung fibroblast MRC-5 served as reference non-malignant cell line for the assessment of the therapeutic window of the tested hybrids. The biological assays identified a trimethoxyphenyl-containing chalcone-vindoline hybrid (36) as a promising lead compound exhibiting submicromolar activity on A2780 cells with a marked therapeutic window. These results suggest that ovarian cancer might be considered as a prioritized target of treatment with 36.

This work aims to follow the corrosion behavior of copper in 3 wt% NaCl solution in the presence of a bio-oily extract. Spent coffee grounds (SCG), a highly recyclable and usable biomass - often thrown away and becoming a serious threat to the environment - , has a fraction of oils (12%) that we have opted to use as a corrosion inhibitor for copper. The extraction was carried out using n-hexane as the solvent for the decoction. The oily fraction was analyzed by Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). Potentiodynamic polarization measurements have revealed SCG extract acts as a cathode-type inhibitor for copper in saline media, mainly preventing the diffusion of oxygen molecules toward the substrate. As the extract concentration increased, the inhibition efficiency has improved as well, reaching 95.78 % with 0.6 g/L of SCG extract. The obtained results by electrochemical impedance spectroscopy (EIS) are in accordance with the order of inhibitory efficiency obtained by potentiodynamic polarization. We have found that the SCG extract adsorption process on copper surface is spontaneous and complies with Langmuir isotherm.

The growing importance of edge and fog computing in the modern IT infrastructure is driven by the rise of decentralized applications. However, resource allocation within these frameworks is challenging due to varying device capabilities and dynamic network conditions. Conventional approaches often result in poor resource use and slowed advancements. This study presents a novel strategy for enhancing resource allocation in edge and fog computing by integrating machine learning with blockchain for reliable trust management. Our proposed framework, called CyberGuard, leverages blockchain’s inherent immutability and decentralization to establish a trustworthy and transparent network for monitoring and verifying edge and fog computing transactions. CyberGuard combines the Trust2Vec model with conventional machine learning models like SVM, KNN, and Random Forests, creating a robust mechanism for assessing trust and security risks. Through detailed optimization and case studies, CyberGuard demonstrates significant improvements in resource allocation efficiency and overall system performance in real-world scenarios. Our results highlight CyberGuard’s effectiveness, evidenced by a remarkable accuracy, precision, recall, and F1-Score of 98.18%, showcasing the transformative potential of our comprehensive approach in edge and fog computing environments.

Autonomous vehicles (AV)s will transform transport, but public opinion will play a key role in the decision how widely and quickly, they will be adopted. The purpose of the study presented here, was to investigate community’s views on the transition. As a method for primary data collection on public awareness, attitudes, and readiness to use autonomous cars, survey was conducted in Saudi Arabia. Following that, we have used statistical tools to analyse responses. Our findings indicate that the participants are mainly open to use new technology and had favourable attitude towards transition. Ordinal logistic regression model showed a wide variation in public opinion regarding the expected benefits that may accompany the transition, despite an average high score on this factor. Our findings reveal that awareness of AVs' benefits is more positively correlated to the age of participants. Perceived cost, on one side, and convenience, and safety, on the other side, have substantial impact on opinions. Investigation, presented here, shows how AVs are seen in Saudi Arabia. This can guide the development of AVs and deployment in that region.

The quantile estimation of extreme wind speed is needed in various environmental fields such as climatology, design of structures, renewable energy sources and agricultural operations. These calculations are crucial for the coding of wind speed. In this study, the required wind speed series of 16 stations in Khyber Pakhtunkhwa, Pakistan, was obtained from the NASA official website and measured in meters per second (m/s) at a 10-meter distance. A Regional Frequency Analysis of 16 AMWS stations was performed using L-moments. The quantile estimates of extreme wind speed are needed for various areas of interest using Regional Frequency Analysis (RFA) and extreme value theory. These calculations are crucial for the coding of wind speed. The data was taken from the NASA official website at a 10-meter distance and measured in meter per second (m/s). A Regional Frequency Analysis of AMWS using L-moments is performed utilizing wind speed data from sixteen sites (16) in Pakistan's Khyber Pakhtunkhwa province. There are no sites that are found to be discordant. The wards method is used to construct a homogenous region and make two homogenous regions from 16 sites. The heterogeneity test justifies that both clusters are homogeneous. The most appropriate probability distribution from the Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type-3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV) distributions are chosen to calculate regional quantiles. According to the L-moments diagram and Z statistics, GEV for Cluster- Ι and GLO for Cluster- ΙΙ are the best suggestions from the others. Both clusters’ robustness is measured utilizing Relative Bias (RB) and Relative Root Mean Square Error (RRMSE). Overall, GEV distribution is fit for cluster-Ι, and the GLO distribution is fit for cluster-ΙΙ. Utilizing the site mean and median as index parameters, we can also find at-site quantiles from regional quantiles. The study’s quantile estimates can be employed in codified structural designs with policy consequences.

On the H-type group G⊂Rm×Rn, we study the existence of solutions for the Brezis-Nirenberg problem

Most Acinetobacter baumannii strains are naturally competent. Although some information is available about factors that enhance or reduce the frequency of transformation of this bacterium, the regulatory elements and mechanisms are barely understood. In this article, we describe studies on the role of H-NS in the regulation of expression of genes related to natural competency and the ability to uptake foreign DNA. The expression levels of the natural transformation-related genes pilA, pilT, pilQ, comEA, comEC, comF, and drpA were significantly increased in a Δhns derivative of Acinetobacter baumannii A118. Complementation of the mutant with a recombinant plasmid harboring hns restored expression levels of six of these genes (pilT remained expressed at high levels) to those of the wild-type strain. The transformation frequency of the A. baumannii A118 Δhns strain was significantly higher than that of the wild-type. Similar, albeit not identical, effects occurred when hns was deleted from the hypervirulent A. baumannii AB5075 strain. Reduction of gene expression in a few cases was not as pronounced as to reach wild-type levels, and expression of comEA was enhanced further. In conclusion, the expression of all seven transformation-related genes was enhanced after deleting hns in A. baumannii A118 and AB5075, and these modifications are accompanied by an increase in the cells’ transformability. The results demonstrate a role of H-NS in A. baumannii’s natural competence.

The growing shift toward Internet of Things (IoT)-based solutions expands the attack surface of systems by connecting an extensive network of heterogeneous devices and technologies. The heterogeneity of IoT devices and the scale of the network often make conventional security measures impractical. Therefore, recent research efforts have focused on machine learning (ML)-based device-agnostic IoT security solutions. However, most proposed solutions have focused solely on detecting malicious traffic in IoT networks. While this is important, further information about the attack is needed to provide a comprehensive defense before, during, and after the incident. To address this gap, we proposed an anomaly-based intrusion detection model that detects malicious traffic and identifies the attack category and subcategory with high accuracy, recall, precision, and F1-score. The proposed intrusion detection model is an ensemble model that integrates multiple ML models to produce more robust and reliable detections. For evaluation, we performed three sets of experiments: (1) a binary classification to detect malicious traffic; (2) a multi-class classification to detect the attack category; and (3) a multi-class classification to detect the attack subcategory. In the experiments, our model achieved an accuracy, recall, precision, and F1-score of 100% for the binary detection; a precision, recall, and F1-score of 99% and an accuracy of 100% for the multi-class category classification; and an accuracy, recall, precision, and F1-score of 88% for the multi-class subcategory classification. These results suggest that the proposed model can reliably detect anomalies in IoT devices.

Nanomaterials have shown significant promise for enhancing the performance of composite materials and increasing their functionality for various industrial applications. This review explores the unique properties of nanomaterials, particularly carbon-based nanomaterials, and provides key findings in utilizing them to enhance composite performance. It highlights specific nano-based composite materials and their significant potential in advancing the field of nanocomposites. Challenges associated with nanocomposite production and utilization are also discussed, along with possible solutions to address them. Finally, the study provides recommendations for continued research and innovation in nanocomposites to fully unlock the benefits of these advanced materials for broader future applications.

Background/Objectives: This study looks at how a kinematic chain exercise regimen that targets the lower, core, and upper body affects university shot put participants' shoulder muscle strength and throwing efficiency. This study fills an apparent research void on shot put training approaches by presenting a comprehensive kinematic chain workout program. It was anticipated that this method would improve performance the most, considering the complex biomechanical require-ments of the sport. Methodology: Athletes, seventy in age (19.87 ± 1.31 years), were assigned into two groups at random: experimental (n = 35) and control (n = 35). While the control group carried on with their usual training, the experimental group participated in an 8-week kinematic chain training program, pre- and post-training evaluations were carried out to evaluate shot put throwing ability, shoulder muscle strength, and participant satisfaction with the exercise regimen. Results: demonstrated that, when compared to the control group, the athletes in the kinematic chain program had a significantly improved throwing distance (p = 0.01) and shoulder muscle strength (p = 0.01). Furthermore, there was a significant difference (p = 0.005) in the athletes' satisfaction levels with the workout program among those in the experimental group. This implies that a kinematic chain-focused strategy improves performance and emphasizes the significance this type of training is for shot put athlete performance. Conclusion: As an improvement forward in sports science, the study's finding promotes the inclusion of kinematic chain workouts in shot put training programs and calls for more research on kinematic chain-based approaches in a variety of sports.

Today, more than 70 million tons of lignin are produced by the pulp and paper industry every year. However, the utilization of lignin as a source for chemical synthesis is still limited due to the complex and heterogeneous lignin structure. The purpose of this study was a selective photodegradation of industrially available kraft lignin in order to obtain appropriate fragments and building block chemicals for further utilization, e.g. polymerization. Thus, kraft lignin obtained from soft wood black liquor by acidification was dissolved in sodium hydroxide and irradiated at a wavelength of 254 nm with and without the presence of titanium dioxide in various concentrations. Analyses of the irradiated products via SEC showed decreasing molar masses and decreasing polydispersity indices over time. At the end of the irradiation period the lignin was depolymerised to form fragments as small as the lignin monomers. TOC analyses showed minimal mineralisation due to the depolymerisation process.

The adoption of recycling and proper disposal techniques for electronic waste is crucial in advancing sustainable development. The traditional approaches of motivating people for collection of electronic waste are often insufficient due to inadequate methods reaching out, given incentives, calculating appropriate incentives associate to the task of gathering the electronic waste and a lack of transparency in the entire process. Insufficient collection of electronic waste could result in the release of numerous harmful substances into the environment. Prior research studies have been carried out to tackle the issue of electronic waste management in a broad sense. The findings of those studies indicated diverse strategies, each of which is relevant solely to a restricted range of electronic waste reprocessing circumstances. The current study has presented a proposed technique for incentivizing tasks and activities associated to collection of electronic waste through the adoption of vector space technique. Blockchain smart contact technology, has been used to implemented the strategy. The method used involves various well defined mapping of tasks, nature of activities, and their magnitude in order to derived an incentive. Some scenarios for the calculations of incentives are presented, and the findings reveals the based case is by utilizing weighting scale scheme where each tasks and activities are mapped to its associated inventive rather than providing fixed incentive values. Ethereum was used as digital token for each unit of incentive. This concept has contributed in encouraging personal accountability in the management of e-waste collection in order to cultivate sustainable behaviors for a long term solution.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

Reactions in water between the Cu2(µ-EGTA) chelate (EGTA = ethylene-bis(oxyethyleneimino)tetraacetate(4-) ion) and 2,6-diaminopurine (Hdap) in molar ratios 1:1 and 1:2 yield only blue crystals of the ternary compound [Cu4(μ-EGTA)2(μ-H(N3)dap)2(H2O)2]·7H2O (1) that has been studied by single crystal X-ray diffractometry, various physical methods (thermal stability, spectral and magnetic properties), as well as DFT theoretical calculations. In the crystal, uncoordinated water is disordered. The tetranuclear complex molecule also has some irrelevant disorder in an EGTA-ethylene moiety. In the complex molecule, both bridging organic molecules act as binucleating ligands. There are two distorted five- (type 4+1) and two six- (type 4+1+1) Cu(II) centres. Each half EGTA acts as a tripodal tetradentate Cu(II) chelator, with mer-NO2+O(ether, distal) conformation. Hdap exhibits the tautomer H(N3)dap, with the dissociable H-atom on its less basic N-heterocyclic atom. These features favour the efficient cooperation between Cu-N7 or Cu-N9 bonds with appropriate O-EGTA atoms, as N6-H···O or N3-H···O interligand interactions respectively. Bridging role of both organics determines the tetranuclear dimensionality of the complex in 1. In this crystal, such molecules associate in zig-zag chains, built by alternating ,-interactions between the five- or six-atom rings of Hdap ligands of adjacent molecules. DFT theoretical calculations (using two different theoretical models and characterized by the quantum theory of “atoms in molecules”) reveal the importance of these ,-interactions between Hdap ligands, as well as that corresponding to the referred hydrogen bonds in the contributed tetranuclear molecule.

Infections contribute to carcinogenesis through inflammation-related mechanisms. It is well established that H. pylori infection is an etiological factor in gastric carcinogenesis. However, the mechanism through which H. pylori infection contributes to the development of gastric cancer has not been fully elucidated. H. pylori-associated chronic inflammation is linked to genomic instability via reactive oxygen and nitrogen species (RONS). In this article, we summarize the current knowledge of H. pylori-induced double strand breaks (DSBs). Further, we will provide mechanistic insight into how processing of oxidative DNA damage via base excision repair (BER) leads to double strand breaks (DSBs). We review the recent progress how H. pylori infection triggers NF-kB /iNOS versus NF-kB/nucleotide excision repair (NER) axis mediated DSBs to drive genomic instability. Taken together, this review discusses current findings related to DSBs and their implications for the mechanisms of DSB repair.

In this paper we obtain some inequalities of Hermite-Hadamard type for composite convex functions. Applications for AG, AH-h-convex functions, GA, GG, GH-h-convex functions and HA, HG, HH-h-convex function are given.

The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenol structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both, scavenging activity and antimicrobial activity are depending on the biomass source showing the following trend: organosolv of softwood > Kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against gram-positive and gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both gram-positive and gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.

The extrinsic and intrinsic factors are essential in glioma initiation. Many extrinsic factors (UV, radiation, food, etc.) and intrinsic factors (proteins, hormones, ageing, DNA and RNA damages, etc.) was reported to being responsible for glioma initiation and progression. However, the cell responsible for glioma origin is still unknown. Many research papers have reported that glioma stem cells, senescent cells, injured cells, and death neurons are the cells of glioma origin. However, gene mutation and oncogene protein overexpression doesn’t occur only in cancer but during life evolution. The source of genetic mutations has become a fundamental issue in understanding its role in the initiation of glioma. The glioma is the precise coordination of several distant factors that work together in the initiation and development of glioma. However, the role and effects of the genes (GDNF and SOX1) on cancer cells are well known, but their gene mutation origin is controversial. Several models and theories have been proposed to explain the origins of GDNF and SOX1 genetic mutations and epigenetic modification related to cancer. Our aim in this review is to clear that incertitude about glioma origin (gene mutation and epigenetic modifications) and those factors involved in glioma initiation and recurrence.

Sharing confidential information is a critical concern in today’s world. Secret sharing schemes facilitate the sharing of secrets in a way that ensures only authorized participants (shareholders) can access the secret using their allocated shares. Hierarchical secret sharing schemes (HSSSs) build upon Shamir’s scheme by organizing participants into different levels based on priority. Within HSSS, participants at each level can reconstruct the secret if a specified number, denoted as the threshold value (t), or more of them are present. Each level has a predetermined threshold value. If the number of participants falls below the threshold at any level, higher-level participants must be involved in reconstructing the secret at lower levels. Our paper proposes schemes that implement hierarchical access structures and enable the sharing of multiple secrets. Additionally, our proposed scheme includes share verification. We have analyzed potential attacks and demonstrated the scheme’s resistance against them. Through security analysis and comparison with existing schemes, we highlight the novelty and superiority of our proposed approach, contributing to advancements in secure information sharing practices.

Opioids have served as a cornerstone in pain management for decades. However, the emergence of increasingly potent synthetic analogs brings forth a range of side effects, including respiratory depression, tolerance, dependence, constipation, and, more importantly, the development of severe and debilitating opioid use disorder (OUD). Search for therapeutics to mitigate OUD has been challenging and this has called for novel approaches that include design of small molecules targeting neuronal circuits involved in addiction (opioid, dopamine, serotonin, norepinephrine, and glutamate receptors, etc.) and development of biologics that target circulating opioids/opiates. In this review, we retrieved and discussed over two dozen of relevant patents filed in the past twelve (12) years that focus on novel approaches to produce therapeutics for OUD. The current review excluded patents on biologics and concentrated on small molecules, which will be discussed separately in a subsequent sequel. The chemical entities disclosed were highlighted and specific examples were provided where necessary. Although the number of patents in the realm of drug discovery for OUD is currently limited, we foresee a continued expansion in the quest for therapeutics for OUD in the years to come.

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

In this study, the degradable superhydrophobic Mg/P/Z/F/H (magnesi-um/poly(-caprolactone)/zinc oxide/1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES)/ heating process) composite materials were prepared through one-step method for enhancing the corrosion resistance of AZ91D magnesium alloys. Electrochemical measurements showed that Mg/P/Z/F/H materials significantly improved the corrosion resistance of magnesium alloys in 3.5 wt.% NaCl. The self-cleaning, adhesion and stability tests suggested that Mg/P/Z/F/H composite materials had well self-cleaning properties, good adhesion strength and stability in wet atmosphere.

Introduction: The trophoblast derived angiogenic factors are considered to play an important role in the pathophysiology of various complications of pregnancy. The aim of this study was to establish relationship between concentrations of soluble Human Leukocyte Antigen-G (sHLA-G) in maternal serum and amniotic fluid at 16-22 weeks of gestation and the sonographic measurements of the fetal and placental growth. Materials and methods: sHLA-G in serum and amniotic fluid, as well as fetal biometric data and placental volume and perfusion indices were determined in 41 uncomplicated singleton pregnancies. Results: The sHLA-G levels were unchanged both in amniotic fluid and in serum during mid-pregnancy. The sHLA-G level in serum correlated positively with amniotic sHLA-G level (β=0.63, p<0.01). Significant correlation was found between serum sHLA-G level and abdominal measurement (β=0.41, p<0.05) and estimated fetal weight (β=0.41, p<0.05). The amniotic sHLA-G level and placental perfusion (VI: β = -0.34, p<0.01 and VFI: β = -0.44, p<0.01, respectively) were negatively interrelated. A low amniotic sHLA-G level was significantly associated with nuchal translucency (r = -0.102, p<0.05). Conclusions: sHLA-G assayed in amniotic fluid might be a potential indicator for placental function, whereas the sHLA-G level in serum can be a prognostic modality for feto-placental insufficiency.

Let $n \geq 2$ be a fixed integer and $\mathcal{A}$ be a $C^*$-algebra. A permuting $ n $-linear map $ \mathcal{G} : \mathcal{A} ^{n} \rightarrow \mathcal{A} $ is known to be symmetric generalized $n$-derivation if there exists a symmetric $n$-derivation $ \mathfrak{D} : \mathcal{A} ^{n} \rightarrow \mathcal{A} $ such that $ \mathcal{G} \left(x_{1}, x_{2}, \ldots, x_{i} x_{i}^{\prime}, \ldots, x_{n}\right)= \mathcal{G} \left(x_{1}, x_{2}, \ldots, x_{i}, \ldots, x_{n}\right) x_{i}^{\prime}+x_{i} \mathfrak{D} (x_{1}, x_{2},\ldots, x_{i}^{\prime}, \ldots, x_{n})$ holds for all $x_{i}, x_{i}^{\prime} \in \mathcal{A} $. In this paper, we investigate the structure of $C^*$-algebras involving generalized linear $n$-derivations. Moreover, we describe the forms of traces of linear $n$-derivations satisfying certain functional identity.

Background: This study was conducted to investigate medical students' lifestyle habits, including sleep quality, eating and drinking pattern, physical activity, and social status. Method: This research project is part two of a multi-institutional cross-sectional observational study conducted among medical students from six medical colleges in Saudi Arabia between September and December 2019. Results: 675 medical students were enrolled electively into the lifestyle study. About half of this number were male students, and the majority aged 18-24 years. Most students (87.6%) slept between 4-8 hours a day, and over 44% were dissatisfied with their sleep. Only 28.1% had three meals a day; about 40% of them usually or always skipped breakfast. While 44% usually or always eat fast food, 44.7% drink 2 liters of water per day. Moreover, male students were significantly consuming fast foods than females, p<0.001. The majority (63.3%) revealed they usually or always drink black coffee daily. Females were significantly more inclined to regular coffee consumption than males, p<0.001. Only 4.3% exercising for 30 minutes or more daily. The majority (65%) of the students were introverted; they had few close friends. Yet, 81% were somewhat satisfied or satisfied with their social life. Male students were predicted to be significantly more satisfied with their social life than females, p=0.001. Only 4.6% smoked cigarettes daily. Whereas 7.1% smoke e-cigarette daily. In contrast, only 0.3% use shisha (hookah) daily. Male medical students were substantially more predicted to be inclined to e-cigarette use than females (p <0.001. The top five leisure activities of a medical student are surfing social media (75.9%), watching movies (61.3%), hanging out with friends (58.1%), spent time with their family (55.4%), and browsing the internet (53.6%). Female medical students were significantly more inclined to surfing social media than male medical students, p=0.022; also, watching movies was preferred for females compared to males, p=0.006. Conclusion: This study revealed that the majority of medical students in Saudi Arabia exhibited healthy lifestyles to some extent, and these health-promoting behaviors differed based on gender, especially concerning physical activity and eating patterns. The findings of this study provide relevant information for future actions that will be geared towards effectively decreasing the occurrence of chronic illnesses and improving future doctor’s well-being.

Introduction: The escalating morbidity, mortality, and healthcare costs associated with invasive candidiasis pose significant challenges in pediatric intensive care units (PICUs). Conventional diagnostic methods fall short in effectiveness, while various risk factors exacerbate the prevalence of these infections. This study introduces a novel model that amalgamates the Candida Score with key predictors to enhance the specificity and applicability of mortality risk assessments for pediatric patients with fungemia. Methods: This retrospective cohort study aimed to develop an integrated model for estimating mortality risk in children with fungemia in PICUs. We constructed and evaluated multiple predictive models using the Candida Score and other relevant clinical and laboratory variables. The discriminative abilities of the models were assessed using the area under the receiver operating characteristic curve (AUC). Results: The study cohort comprised 85 pediatric patients admitted between 2016 and 2020, with a median age of 6 months and a male predominance of 62.4%. The mortality rate was 45.9%. Candida albicans was the most prevalent causative agent, accounting for 37.55% of fungemia cases. Multivariable Logistic regression revealed the duration of mechanical ventilation, and the Candida Score were significant predictors of mortality. Each additional day of ventilation increased mortality odds by 11.5% (OR = 1.115, 95% CI: 1.025-1.212, p = 0.011), while a higher Candida Score more than doubled the odds (OR = 2.205, 95% CI: 1.359-3.578, p = 0.001).The Random Forest predictive model demonstrated superior discriminative performance, with an AUC of 0.838 (95% CI: 0.738-0.917), outperforming Gradient Boosting and Logistic Regression models, which had AUCs of 0.7759 (95% CI: 0.667-0.877) and 0.7085 (95% CI: 0.589-0.813), respectively. Although the internal validation yielded satisfactory results, external validation is warranted. Conclusion: This study presents an innovative approach for accurately assessing the risk of mortality due to fungemia in PICU patients by integrating the Candida Score with critical predictors. The Random Forest model emerged as the most effective predictive tool due to its exceptional discriminative ability.

This study introduces an innovative seeding method for cells on large scaffolds (1-100 sqcm) with an accuracy of 0.1mm, comparing the conventional drop-wise seeding technique with an automated seeding approach using an open sourced robotic liquid handling system (OpenLH). This automated system employs an algorithm in which the user inputs the desired droplet volume and seeding pattern dimensions such in number of rows, columns and distance between droplets, thus optimizing the distribution of cells on the scaffold. By adjusting these parameters, the method achieves greater accuracy and consistency over manual seeding and requires less operation space volume than dynamic seeding. Additionally, the system’s tip replacement feature can support the precise seeding of multiple cell types on a single scaffold and the dispensing of growth factors to foster patterns of cell differentiation and proliferation on the large 3D scaffold. This seeding method not only enhances the precision and efficiency of cell distribution on scaffolds but also shows significant potential for scalability in the cultured meat industry, where large scaffolds are essential. The adoption of such automated systems could promote efficient scaffold-based tissue engineering by promoting uniform cell distribution and enabling the creation of complex tissue constructs, thereby advancing both biomedical research and cultured meat production.

This paper addresses a mode-dependent state-feedback H∞ control for descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H∞ performance ? of the closed-loop system is proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator saturated control input is expressed as a linear combination of given state-feedback control input and a virtual control input that remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the LMI conditions for the existence of the mode-dependent state-feedback H∞ control and the ellipsoidal shape of invariant set are successfully derived. Two numerical examples demonstrate the effectiveness of the proposed approach in optimizing H∞ performance $\gamma$ and identifying the largest invariant set.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.