This work aimed to develop an anionic cellulose nanofiber (CNF) bio-adsorbent from palm date tree waste and to investigate its removal efficiency against cationic methylene blue dye from contaminated water. Palm date pulp was first prepared from palm date leaves through acid hydrolysis using H2SO4, followed by hydrolysis in a basic medium using KOH, in which the process completely removed the components of hemicellulose, lignin, and silica. To obtain anionic CNF, the resulting pulp was further treated with H2SO4, followed by centrifugation. Biogel formation of the CNF suspension was promoted by sonication, where its removal efficiency of methylene blue dye was studied as a function of dye concentration, temperature, contact time, and pH value. Two equilibrium models, the Langmuir and Freundlich models were employed, and the Langmuir model was found to be consistent with the experimental data. The highest removal efficiency was obtained at 60oC and was 5mg/gm. Furthermore, several kinetic models were used to gain insight into the adsorption mechanism. The pseudo-second-order model provided an accurate description of the adsorption process, while the Elovich equation suggested a chemical reaction between methylene blue dye and CNF. The study’s findings were in agreement with the pseudo-second-order model, indicating general chemical reactions. The study indicates that CNF adsorbents derived from renewable natural waste sources such as palm date leaves can be effective in removing cationic contaminants such as methylene blue dye.

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.

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.

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

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

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.

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.

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.

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.

In a generalized topological space Tg = (Ω, Tg), ordinary interior and ordinary closure operators intg, clg : P (Ω) −→ P (Ω), respectively, are defined in terms of ordinary sets. In order to let these operators be as general and unified a manner as possible, and so to prove as many generalized forms of some of the most important theorems in generalized topological spaces as possible, thereby attaining desirable and interesting results, the present au- thors have defined the notions of generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, in terms of a new class of generalized sets which they studied earlier and studied their essen- tial properties and commutativity. The outstanding result to which the study has led to is: g-Intg : P (Ω) −→ P (Ω) is finer (or, larger, stronger) than intg : P (Ω) −→ P (Ω) and g-Clg : P (Ω) −→ P (Ω) is coarser (or, smal ler, weaker) than clg : P (Ω) −→ P (Ω). The elements supporting this fact are reported therein as a source of inspiration for more generalized operations.

Morphological and phylogenetic (45S nrDNA+RPB1 gene) analyses of three glomoid spore-producing arbuscular mycorrhizal fungi revealed the presence of two new species be-longing to the genus Glomus in the family Glomeraceae. In the field, Glomus highlandensis sp. nov. was found in a saltmarsh of the Scottish Highlands and in maritime sand dunes of the Baltic Sea in Poland, both saline environments, while G. mongioie sp. nov. originates from the Italian Alps. Phylogenetic placement analysis using environmental sequences indicated that G. highlandensis could have likely worldwide distribution while G. mongioie seems to be a rare species in the world. The molecular and phylogenetic analysis provided important insights about the presence of ribosomal variants in Glomus, with potential negative implication in phylogeny and species recognition.

In a generalized topological space T_g = (Ω, T_g) (T_g-space), the g-topology T_g : P (Ω) −→ P (Ω) can be characterized in the generalized sense by specifying the generalized open, generalized closed sets (g-T_g-open, g-T_g-closed sets), generalized interior, generalized closure operators g-Intg, g-Cl_g : P (Ω) −→ P (Ω) (g-T_g-interior, g-T_g-closure operators), or generalized derived, generalized coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω) (g-T_g-derived, g-T_g-coderived operators), respectively. For very many T_g-spaces, the δ^th-iterates g-Der_g^(δ), g-Cod_g^(δ) : P (Ω) −→ P (Ω) of g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, defined by transfinite recursion on the class of successor ordinals are also themselves g-T_g-derived, g-T_g-coderived operators for new g-topologies in the generalized sense on Ω. Thus, the use of novel definitions of g-T_g-derived, g-T_g-coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, based on a very clever construction, together with their δ^th-iterates g-T_g-operators g-Der_g^(δ), g-Cod_g^(δ) : P (Ω) −→ P (Ω), defined by transfinite recursion on the class of successor ordinals, will give rise to novel generalized g-topologies on Ω. The present authors have been actively engaged in the study of g-T_g-operators in T_g-spaces. The study of the essential properties and the commutativity of novel definitions of g-T_g-interior and g-T_g-closure operators g-Int_g, g-Cl_g : P (Ω) −→ P (Ω), respectively, in T_g has formed the first part, and the study of the essential properties and sets of consistent, independent axioms of novel definitions of g-T_g-exterior and g-T_g-frontier operators g-Ext_g, g-Fr_g : P (Ω) −→ P (Ω), respectively, has formed the second part. In this work, which forms the last part on the theory of g-T_g-operators in T_g-spaces, the present authors propose to present novel definitions and the study of the essential properties of g-T_g-derived and g-T_g-coderived operators g-Der_g, g-Cod_g : P (Ω) −→ P (Ω), respectively, and their δ^th-iterates, and the notions of g-T_g-open and g-T_g-closed sets of ranks δ in T_g-spaces.

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.

Pancreatic cancer (PC) has a poor prognosis and displays resistance to immunotherapy. A better understanding of tumor-derived extracellular vesicles (EVs) effects on immune responses might contribute to improved immunotherapy. EVs derived from Capan-2 and BxPC-3 PC cells isolated by ultracentrifugation were characterized by atomic force microscopy, western blot (WB), nanoparticle tracking analysis and label-free proteomics. Fresh PBMCs from healthy donors were treated with PC- or control-derived heterologous EVs followed by flow cytometry analysis of CD8+ and CD4+ lymphocytes. Proteomics of lymphocytes sorted from EV-treated, or -untreated PBMCs was performed and IFN-γ concentration was measured by ELISA. Notably, most of the proteins identified in Capan-2 and BxPC-3 EVs by proteomic analysis were connected in a single functional network (p=1x10-16) and were involved in “Immune System” (FDR: 1.10x10-24 and 3.69x10-19, respectively). Interestingly, treatment of healthy donor-derived PBMCs with Capan-2 EVs, but not with BxPC-3 EVs or heterologous control EVs induced early activation of CD8+ and CD4+ lymphocytes. Proteomics of lymphocytes sorted from EV-treated PBMCs was consistent with their activation by Capan-2 EVs, indicating IFN-γ among major upstream regulators, as confirmed by ELISA. Proteomic and functional analyses indicate that PC-EVs have pleiotropic effects, and some may activate early immune response, which might be relevant for the development of highly needed immunotherapeutic strategies in this immune-cold tumor.

In a generalized topological space Tg = (Ω, Tg), generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, are merely two of a number of generalized primitive operators which may be employed to topologize the underlying set Ω in the generalized sense. Generalized exterior and generalized frontier operators g-Extg, g-Frg : P (Ω) −→ P (Ω), respectively, are other generalized primitive operators by means of which characterizations of generalized operations under g-Intg, g-Clg : P (Ω) −→ P (Ω) can be given without even realizing generalized interior and generalized closure operations first in order to topologize Ω in the generalized sense. In a recent work, the present authors have defined novel types of generalized interior and generalized closure operators g-Intg, g-Clg : P (Ω) −→ P (Ω), respectively, in Tg and studied their essential properties and commutativity. In this work, they propose to present novel definitions of generalized exterior and generalized frontier operators g-Extg, g-Frg : P (Ω) −→ P (Ω), respectively, a set of consistent, independent axioms after studying their essential properties, and established further characterizations of generalized operations under g-Intg, g-Clg : P (Ω) −→ P (Ω) in Tg.

The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of green coffee, clove, cinnamon/clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning green coffee, clove, cinnamon, cinnamon and clove, and nutmeg fine powders based on multivariate analysis of variance and supervised learning on data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography/mass spectrometry. Results showed that 7 volatile compounds namely ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of green coffee, cinnamon, clove, cinnamon and clove and nutmeg, based on selected volatile compounds, and provides further support to the literature by means of possible adulteration given the statistical models developed.

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.

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.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in Smart Cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G Smart Cities IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low Round-Trip Time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

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.

In a bid to resolve lingering problems in cosmology, more focus is being tilted towards cosmological models in which physical constants of nature are not necessarily real constants, but varying with cosmic time. In this paper we have study cosmology in nonlinear electrodynamics with the Newton's gravitational constant $G$ not a constant but vary in form of power-law of the scale factor of the universe. The evolution of the scale factor $a (t)$ is studied in this model which depends on nonlinear electrodynamics fine tuning term of $\alpha$. Then we check the stability of the model using the speed of sound.

G-quadruplexes are noncanonical nucleic acid structures formed from stacked guanine tetrads. They are frequently used as building blocks and functional elements in fields such as synthetic biology and also thought to play widespread biological roles. G-quadruplexes are often studied as monomers but can also form a variety of higher-order structures. This increases the structural and functional diversity of G-quadruplexes, and recent evidence suggests that it could also be biologically important. In this review we describe the types of multimeric topologies adopted by G-quadruplexes and highlight what is known about their sequence requirements. We also summarize the limited information available about potential biological roles of multimeric G-quadruplexes and suggest new approaches that could facilitate future studies of these structures.

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 review time expansion wave theory and refine our model showing it to accurately match observed cosmological luminosity data. The theory augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth spatial dimension that we observe as the expansion of the universe. This leads us to explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects. Our model leads to an expansion velocity of 6.87 0.36 × 106 ms-1, which results in a Hubble expansion rate constant of 71.3 3.7 km/s/Mpc. Because of the finite window of time in which we exist, an extra a degree of freedom is available leading to interesting interpretations at the subatomic level. At this size range, then a spin is allowed within the time dimension explaining why wave particle duality occurs and explains the electromagnetic force and other quantum mechanical properties. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The potential quantitative origin of the fine structure constant which governs the size of the electromagnetic force is also strongly indicated by this theory.

Heart failure (HF) is a growing issue in developed countries and most patients present with a reduced ejection fraction. This condition significantly impairs quality of life and represents a threat not only for patients, but also for the entire healthcare system due to its high management cost. In the last decade, new medical treatments and devices have been developed to reduce HF hospitalizations and improve prognosis, while reducing the overall mortality rate. Medical therapy does not achieve the same results in all patients and, whenever it fails, technology comes in handy: novel devices for the management of HF have reduced symptoms. They have also improved the treatment of fluid retention and life threatening arrhythmias. The present review article gives to the readers a comprehensive overview of the most recent and important findings that need to be considered in HF with reduced ejection fraction patients. Both novel medical treatments and devices have been presented and discussed.

Speech emotion recognition (SER) is a technology that can be applied in distance education to analyze speech patterns and evaluate speakers’ emotional states in real-time. It provides valuable insights and can be used to enhance the learning experience by enabling the assessment of instructors’ emotional stability, a factor that significantly impacts information delivery effectiveness. Students demonstrate different engagement levels during learning activities, and assessing this engagement is an important aspect of controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is the emotional states of their instructors. Accordingly, this research uses deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entails integrating Transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance SER. Feature extraction from audio data used Mel-frequency cepstral coefficients, chroma, Mel spectrogram, zero crossing rate, spectral contrast, centroid, bandwidth, roll-off, and root-mean square, with subsequent optimization processes adding noise to, conducting time stretching, and shifting the audio data. Notably, several Transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The pre-processing and data augmentation methodologies significantly enhanced the precision of the results in that the model achieved accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% on the Ryerson Audio-Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio-Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets. Furthermore, it achieved 83% accuracy on another dataset created for this research—the Saudi Higher Education Instructor Emotions dataset. The results demonstrate this model’s considerable accuracy in detecting emotions in speech data across different languages and datasets.

Several specific types of generalized compactness of generalized topological spaces have been defined, investigated and related to compactness in ordinary topological spaces from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized compactness in a generalized topological space is reported herein as a starting point for more generalized classes.

Several specific types of ordinary and generalized connectedness in a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new type of generalized connectedness in a generalized topological space is reported herein as a starting point for more generalized types.

Several specific types of generalized maps of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized maps of a generalized topological space is reported herein as a starting point for more generalized classes.

Several specific types of generalized sets of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized sets of a generalized topological space is reported herein as a starting point for more generalized classes.

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

In this study we have investigated the effect of the addition of Nb2O5 (up to 5 mol%) on the structure and luminescent properties of ZnO-B2O3 glass doped with 0.5 mol % Eu2O3 by using of infrared (IR), Raman and photoluminescence (PL) spectroscopy. Physical properties as molar volume, oxygen packing density and glass transition temperature were determined using the results of differential thermal analyisis (DTA) and Archimedes principle for density. IR and Raman spectra revealed that niobium ions incorporate into the base zinc borate glass as NbO4 trtraherda and NbO6 octahedra. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (392 nm) excitation using the sharp 7F0 - 5L6 transition of Eu3+. The integrated fluorescence intensity ratio R (5D0 → 7F2/5D0 → 7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites. The higher Еu3+ luminescence emission observed in zinc borate glasses containing 1÷5 mol% Nb2O5 compared to the Nb2O5-free zinc borate glass evidences that Nb2O5 is suitable component for modification of host glass structure and improving the emission intensity.

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.

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.

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits - grain protein content (GPC) and thousand kernel weight (TKW) - across 179 Bulgarian contemporary and historic varieties, and landraces in three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, genotypic data from the 25K Infinium iSelect array, and a Bonferroni-adjusted p-value. As a result, 776 significant quantitative trait nucleotides (QTNs) organized into quantitative trait loci were discovered, including 25 loci associated with GPC, and 35 loci linked to TKW. Additionally, 14 environmentally stable QTNs were identified for TKW. Certain loci on chromosomes 2A, 3A, and 6B favorably in-fluenced GPC, while the locus on chromosome 6D impacted TKW positively. These loci may reflect novel associations to the two traits. Annotations for proteins involved in the remobilization of carbon and nitrogen from vegetative tissues to developing grain during senescence, as well as in the following buildup of resources required for seed germination, have been found for selected pu-tative candidate genes. These include genes coding for 11S globulin seed storage protein, glutamine synthetase, metalloendopeptidase, components of the ubiquitin/proteasome system, sucrose transporter, alpha-amylase, NAC and bZIP transcription factors. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.

Background Cytomegalovirus (CMV) is a major pathogen that cause remarkable rate of morbidity and mortality, especially in immunocompromised patients. It is important to find risk factors associated with CMV viremia. We studied the differences in CMV seropositivity in relation to liver function biomarkers in male and female Saudi population in an attempt to understand the variation in the CMV seroprevalence with sex and find the risk factor to develop liver dysfunction or hepatocellular carcinoma. Material and subjects: The CMV- IgG and IgM were screened in serum samples of 150 non- A-G hepatities patients with elevation of liver profiles (ALT, AST, ALP and GGT) and categorized as males and females. Samples were collected from different general hospitals and polyclinic in KSA from March 2014 to June 2015. A correlation between CMV seropositivity measured with both antibodies and liver enzymes were tested. Receiver operating characteristics (ROC) analysis and multiple regressions were done for the obtained data. Results: Our study shows that females had much higher IgG and IgM compared to age-matching males. A significant correlation between both antibodies and liver enzymes (AST, ALT) was recorded. Less significant correlation of both IgG and IgM with GGT was also observed. Receiver operating characteristics (ROC) analysis revealed that both IgG and IgM can be used as excellent predictive markers for CMV infection as both recorded 100% specificity and sensitivity together with area under the curve of 1 in males and females. Multiple regression analysis ascertain the correlation between both antibodies as dependent variables and liver enzymes as independent variables with ALT being the most affected enzyme with CMV seropositivity especially in females. Conclusion:he data discussed above This study shows that CMV is capable of initiating and accelerating liver dysfunction in both sexes. The high seroprevalence in females at reproductive age is especially important as they can transmit the virus to their developing fetus. Prevention of CMV infection in young girls 11-14 years old, through counseling on hygiene or possible future vaccination, may lead to a decrease of congenital CMV infections with the concomitant risk of developing liver dysfunction or hepatocellular carcinoma. Keywords: Cytomegalovirus, Alanine transaminase, Aspartate transaminase Alkaline phosphatase, γ-Glutamyltranspeptidase, liver function.

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.

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.

Several specific types of ordinary and generalized separation axioms of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized separation axioms of a generalized topological space is reported herein as a starting point for more generalized classes.

Peritoneal dialysis (PD) is a home-based efficacious modality for replacement of renal function in end-stage kidney failure patients but is still under-prescribed. A major limitation is the durability of the dialytic technique. Continuous exposure of the peritoneum to bioincompatible conventional glucose-based solutions is thought to be the main cause of long-term morpho-functional peritoneal changes eventually resulting in ultrafiltration failure. Poor PD solution biocompatibility is primarily related to the high glucose content, which is not only detrimental to the peritoneal membrane but has many potential metabolic side effects. To improve the clinical outcome and prolong the survival of the treatment, PD-related bioincompatibility urgently needs to be overcome. However, combining dialytic and osmotic efficacy with a satisfactory biocompatible profile proves quite difficult. New approaches targeting the composition of the PD solution include replacement of glucose with other osmotic agents and the addition of cytoprotective or osmo-metabolic compounds. Other strategies include infusion of mesenchymal cells or the administration of orally active agents. In the present article we review the current evidence on efforts to improve the biocompatible and functional performance of PD, focusing on studies performed in vivo (animal models of PD, human subjects on PD).

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.

Immunoglobulin G (IgG) adopts a modular multidomain structure that mediates antigen recognition and effector functions, such as complement-dependent cytotoxicity. IgG molecules are self-assembled into a hexameric ring on antigen-containing membranes, recruiting the complement component, C1q. To provide deeper insights into the initial step of the complement pathway, we report a high-speed atomic force microscopy study for quantitative visualization of the interaction between IgG and the C1 complex composed of C1q, C1r, and C1s. Results showed that C1q in the C1 complex is restricted regarding internal motion and has a stronger binding affinity for on-membrane IgG assemblages than C1q alone, presumably because of smaller conformational entropy loss upon binding. Furthermore, we visualized a 1:1 stoichiometric interaction between C1/C1q and an IgG variant that lacks the entire CH1 domain in the absence of antigen. In addition to the canonical C1q-binding site on Fc, their interactions are mediated through a secondary site on the CL domain that is cryptic in the presence of the CH1 domain. Our findings offer clues for novel-modality therapeutic antibodies.

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.

Mercury has a strong environmental impact since both its organic and inorganic forms are toxic and it represents a pollutant of global concern. Liquid Hg is highly volatile and it can be released during natural and anthropogenic processes in the hydrosphere, biosphere and atmosphere. In this study the distribution of Gaseous Elemental Mercury (GEM) and the total and leached mercury concentrations on paints, plasters, roof tiles, concretes, metals, dust and wood structures were determined in the main buildings and structures of the former Hg-mining area of Abbadia San Salvatore (Siena, Central Italy). The mining complex (divided into 7 units) covers a surface of about 65 ha and contains mining structures and managers and workers buildings. In this work, nine surveys of GEM measurements were carried out from July 2011 to August 2015 for the buildings and structures located in the units 2, 3 and 6. Moreover, detailed measurements were performed in February, April, July, September and December 2016 in the edifices and mining structures of Unit 6. GEM concentrations showed a strong variability in terms of space and time mostly depending on the distance from the building hosting driers, furnaces and condensers and ambient temperature, respectively. In the Unit 2 surveys carried out in the hotter period (from June to September) showed GEM concentrations up to 27,500 ng m⁻³, while in the Unit 6 they were on average much higher and occasionally they saturated the GEM measurement device (>50,000 ng m⁻³). Concentrations of total (in mg kg⁻¹) and leached (in μg L⁻¹) mercury measured in different building materials (up to 46,580 mg kg⁻¹ and 4,470 mg L⁻¹ for total and leached mercury, respectively) showed for the same type of material highly variable values in dependence on the edifice or mining structure from which they were collected. The results obtained in this study are of relevant interest for the operational cleanings to be carried out during the reclamation activities.

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 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.

By combining general relativity and CPT symmetry, the theory of CPT gravity predicts gravitational repulsion between matter and CPT-transformed matter, i.e. antimatter inhabiting an inverted space-time. Such repulsive gravity turned out to be an excellent candidate for explaining the accelerated expansion of the Universe, without the need for dark energy. The recent results of the ALPHA-g experiment, which show gravitational attraction between antihydrogen atoms and the Earth, seem to undermine this success in the cosmological field. Analyzing the above theory, we find two solutions that can be consistent with the experimental results, while preserving the large-scale gravitational repulsion. The first highlights how repulsive gravity can be the result of the interaction with an inverted space-time, but occupied by matter and not antimatter, and therefore the antimatter present in our space-time has no reason to exhibit gravitational repulsion. The second retains the original CPT transformation, resulting in repulsive gravity between matter and antimatter, but with the caveat that antimatter immersed in our space-time cannot exhibit the PT transformation which is the cause of the repulsion. Finally, it is shown that, in a Newtonian approximation of the geodesic equation, time reversal is not a necessary operation for repulsive gravity, therefore opening the possibility of an expanding cosmos with a single time direction.

The spin magnetic moments and spin g factors (g_s = -2) of electron, muon and tau are explained based on the electric charges (EC) and lepton charges (LC) in terms of the three-dimensional quantized space model. The spin g factors of electron, muon and tau are g_s = -2 which is the sum of the EC g factor (g_EC = -1) and the LC g factor (g_LC = -1). The spin g factor (g_s = -2) of the electron is predicted by the Dirac’s equation. The orbit g factors of electron, muon and tau are g_L = g_EC = -1 from the EC g factor (g_EC = -1) without the contribution of the LC g factor (g_LC = -1). The spin g factors of the elementary fermions are calculated from the equation of g_s = g_EC + g_LC + g_CC where g_EC = EC/|EC|, g_LC = LC/|LC| and g_CC = CC/|CC|. For example, the spin g factors of the neutrinos and dark matters are g_s = -1. The spin g factors of the u and d quarks are g_s = 0 and g_s = -2, respectively. The g factor problem of neutrinos with the non-zero LC charges are solved by the LC Coulomb force of F_c(LC) ≈0. It is, for the first time, proposed that the binary motion (fluctuations) of the m_EC and m_LC masses for the electron, muon and tau leptons make the anomalous g factor. This binary motion could be originated from the virtual particle processes including the photons. Also, the weak force (beta) decay is closely related to the binary motion of the m_EC and m_LC for the electron, muon and tau leptons.

The G-protein-coupled estrogen receptor (GPER; G protein-coupled estrogen receptor 30, also known as GPR30) is a novel estrogen receptor and has emerged as a promising target for ovarian cancer. GPER, a seven-transmembrane receptor, suppresses cellular viability and migration in studied ovarian cancer cells. However, its impact on the fallopian tube, which is the potential origin of high-grade serous (HGSC) ovarian cancer, has not been addressed. This study was conducted to evaluate the relationship of GPER, ovarian cancer subtypes, i.e., high-grade serous cell lines (OV90 and OVCAR420), as well as potential HGSC ovarian cancer origin (i.e., the fallopian tube cell line FT190). The selective ligand assessed here is the agonist G-1, which was utilized in an in vitro study to characterize its effects on cellular viability and migration. As a result, this study has addressed the effect of a specific GPER antagonist in combination with an agonist on cell viability, providing a better understanding of the effects of these compounds on our diverse group of studied cell lines. Strikingly, attenuated cell proliferation and migration behaviors were observed in the presence of G-1. Thus, our in vitro study reveals the impact of the origin of HGSC ovarian cancers and highlights the GPER agonist G-1 as a potential therapy for ovarian cancer.

HLA-G is an immune checkpoint molecule with immunosuppressive and anti-inflammatory activities, and its expression and level of its soluble form (sHLA-G) may play an important role in tumor prognosis. The HLA-G 14 bp ins/del polymorphism and the plasma level of soluble HLA-G (sHLA-G) were investigated by a polymerase chain reaction and ELISA, respectively, in 59 glioma patients. A significantly higher proportion of glioma patients had the 14 nt insert in both homozygous and heterozygous states compared to the control group. Glioma patients had also higher plasma levels of sHLA-G. Patients with methylated MGMT promoter had lower levels of sHLA-G than those with unmethylated MGMT promoter. Level of sHLA-G negatively correlated with the overall survival of patients. Glioblastoma patients who survived more than one year after diagnosis had lower levels of sHLA-G than those surviving less than one year. Patients with sHLA-G levels below the cut off value 40 U/mL survived significantly longer than patients with sHLA-G above 40 U/mL. The levels of sHLA-G also negatively correlated with the level of IL-6 (P=0.0004) and positively with IL-10/IL-6 (P=0.046). Conclusion: The presence of 14 nt insert in both homozygous and heterozygous states of the HLA-G 14 bp ins/del polymorphism is more frequent in glioma patients and the elevated plasma levels of sHLA-G are negatively associated with their survival.

Mobile robots need an environmental perception ability in order to interact with the surrounding environment. In this paper we present the G-SLAM method, where the map is consisted of a cloud of scattered points in the continuous space and each point is accompanied by an obstacle existence probability. On the other hand the robot's pose (and trajectory) is estimated by an particle filters while the cloud of points is estimated by an adaptive recursive algorithm which is presented. Main feature of the presented method is the adaptive repositioning of the scattered points and their convergence around obstacles. In addition to our previous publications, In this paper a mathematical derivation of the method is presented and real case scenarios are discussed, presented and compared with other methods.

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.

(1) Background: In this work, a series of benzimidazole derivatives containing colchicine-like and cathechol-like moieties with methyl group substitution in the benzimidazole ring were evaluated for their in vitro antiproliferative, pro-apoptotic and antioxidative activity against highly invasive breast cancer cell line MDA-MB-231 and related impairment of tubulin dynamics; (2) Methods: MTT assay was used to evaluate the antiproliferative activity. In vitro tubulin polymerization assay as well as docking analysis was applied to prove the alterations in tubulin polymerization. Immunofluorescent and DAPI staining reveal the pro-apoptotic potential of benzimidazole derivatives and the effect on tubulin’s dynamics in living cells. The antioxidant activity was evaluated by scavenging of H2O2 and hypochlorite ion and ortho-phenanthroline tests; (3) Results: The compounds containing colchicine-like moiety displayed significant growth inhibitory effect against cancer cell line as was highlighted the role of methyl functional group on the tubulin aggregation and blockage of mitosis. All compounds showed an ability to scavenge H2O2, while the compounds with cathecol-like moiety were more effective against hypochlorite ion and chelation of iron; (4) Conclusions: The benzimidazole derivative containing colchicine-like moiety and methyl group substitution in benzimidazole ring is a potential antiproliferative and microtubule destabilizing agent.

In this study, 10%PTFE/PEEK blend were modified by potassium titanate whisker (PTW) and chopped glass fiber (GF), respectively. The blends were prepared by three-screw extruder. Through the investigation of thermal stability, tribological properties, mechanical properties and rheological behavior, the effects of reinforcing agents were determined. The results illustrated that the mechanical properties of 10%PTFE/PEEK blend can be dramatically improved by adding reinforcing agent of PTW or GF, and the reinforcing effect of GF was especially obvious. As for tribological properties, 1% addition was the best proportion. The friction coefficient and wear rate of the blend with 1% PTW were 0.283 and 4.97 × 10^-6 mm³/N · m, which decreased by 7.2% and 21% compared with those of the blend without reinforcing agent.

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.

Analyses of the three predominant types of sedimentation – clastic, carbonate and black shale – revealed their discontinuity/continuity in different facies environments of the Middle and Late Devonian of the central part of the Volga-Urals petroleum province, namely (1) in depressions, both condensed and non-condensed, (2) on the slopes of depressions and (3) in shallow water environments represented by tectonic arches or localised biohermal uplifts. The regional zonation of conodonts, correlated with the global chronostratigraphic scheme, substantiates the stratigraphic completeness of the general Devonian sequence in this area. In particular, the sedimentation of organic-rich black shales, traditionally considered as source rocks, lasted more than 29 million years, starting from the Late Eifel and ending at the Devonian-Carboniferous boundary. There was only one hiatus in the deposition of both black shales and carbonate sediments, lasting about 2.5 million years at the end of the Frasnian. That interval is dominated by clastic sediments, which are considered to be the most productive reservoirs of the Volga-Ural province. In the time interval from the beginning of the Eifel to the end of the Frasnian (about 17 Ma), (a) clastic sediments show the highest accumulation rates; (b) the most complete sequences occur in depressions; and (c) arches and uplifts show the most significant gaps in the geological record. During Famennian, (a) clastic sedimentation has completely ceased; (b) differences between the slopes of troughs and shallow-water environments have diminished, resulting in stable accumulation of carbonate sediments in both settings; (c) the decrease in sequence thickness (up to 50 m) in depressions suggests reduced accumulation rates of deep-water organic-rich black shales. The results help to understand the complex spatial relationship between different coexisting sedimentation types and focus attention to the incompleteness of the geological record in different environments.

In this paper, we investigate some kind of Dynkin game under $g$-expectation induced by backward stochastic differential equation (shortly for BSDE). We define the lower and upper value functions $\underline{V}_t=ess\sup\limits_{\tau\in{\mathcal{T}_t}} ess\inf\limits_{\sigma\in{\mathcal{T}_t}}\mathcal{E}^g_t[R(\tau,\sigma)]$ and $\overline{V}_t=ess\inf\limits_{\sigma\in{\mathcal{T}_t}}ess\sup\limits_{\tau\in{\mathcal{T}_t}}\mathcal{E}^g_t[R(\tau,\sigma)]$, respectively. Under some regular assumptions, a pair of saddle point is obtained and the value function of Dynkin game $V(t)=\underline{V}_t=\overline{V}_t$ follows. Furthermore, the constrained case of Dynkin game is also considered.

G protein-coupled receptors (GPCRs) comprise the largest family of membrane receptors that control many cellular processes and consequently often serve as drug targets. These receptors undergo a strict regulation by mechanisms such as internalization and desensitization, which are strongly influenced by posttranslational modifications. Ubiquitination is a posttranslational modification with a broad range of functions that is currently gaining increased appreciation as a regulator of GPCR activity. The role of ubiquitination in directing GPCRs for lysosomal degradation has already been well-established. Furthermore, this modification can also play a role in targeting membrane and endoplasmic reticulum-associated receptors to the proteasome. Most recently, ubiquitination was also shown to be involved in GPCR signaling. In this review, we present current knowledge on the molecular basis of GPCR regulation by ubiquitination, and highlight the importance of E3 ubiquitin ligases, deubiquitinating enzymes and β-arrestins. Finally, we discuss classical and newly-discovered functions of ubiquitination in controlling GPCR activity.

Background: The validation of laser usage during laparoscopic procedures, notably by Camran Nezhat in the late 1980s, has been significant. Lasers offer precision and depth control in tissue vaporization without bleeding. Surgical intervention remains central in managing endometrio-sis-associated pain and infertility, especially for patients unresponsive to hormonal therapy. Methods: This retrospective cohort study included 200 patients with SPE who underwent laparo-scopic laser vaporization. Surgery was performed using a CO2 laser, and histological confirma-tion of endometriosis was obtained for all cases. Pain scores and SF-36 questionnaire domains were assessed preoperatively and postoperatively. Fertility outcomes were evaluated among pa-tients desiring pregnancy. Results: Significant improvements in pain score and SF-36 questionnaire domains were ob-served postoperatively (p-value

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 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.

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.

Generally, stochastic functional differential equations (SFDEs) pose a challenge as they often lack explicit exact solutions. Consequently, it becomes necessary to seek certain favorable conditions under which numerical solutions can converge towards the exact solutions. This article aims to delve into the convergence analysis of solutions for stochastic functional differential equations by employing the framework of G-Brownian motion. To establish the goal, we find a set of useful monotone type conditions and work within the space Cr((−∞,0];Rn). The investigation conducted in this article confirms the mean square boundedness of solutions. Furthermore, this study enables us to compute both LG2 and exponential estimates.

G-protein-coupled receptors (GPCRs) are ubiquitous sensors and regulators of cellular functions. Each GPCR exists in complex aggregates with multiple resting and active conformations. Designed to detect weak stimuli, GPCRs can also activate spontaneously, resulting in basal ligand-free signaling. Agonists trigger a cascade of events leading to an activate agonist-receptor-G protein complex with high agonist affinity. However, the ensuing signaling process can further remodel the receptor complex to reduce agonist affinity, causing rapid ligand dissociation. The acutely activated ligand-free receptor can continue signaling, as proposed for rhodopsin and  opioid receptors, resulting in robust receptor activation at low agonist occupancy with enhanced agonist potency. Continued receptor stimulation can further modify the receptor complex, regulating sustained ligand-free signaling - proposed to play a role in opioid dependence. Basal, acutely agonist-triggered, and sustained elevated ligand-free signaling could each have distinct functions, reflecting multi-state conformations of GPCRs. This review addresses basal and stimulus-activated ligand-free signaling, its regulation, genetic factors, and pharmacological implications, focusing on opioid and serotonin receptors, and the growth hormone secretagogue receptor (GHSR). Ligand-free signaling of intracellular 5-HT2A receptors could mediate therapeutic effects of psychedelic drugs. Research avenues are suggested to close gaps in our knowledge of ligand-free GPCR signaling.

Industrial hemp (Cannabis sativa L.) is an attractive candidate for sustainable pest management due to its abundance of bioactive compounds with potential pesticidal properties. Solvent choice has a significant impact on the extraction efficiency of bioactive compounds. Deep Eutectic Solvents (DESs) are gaining popularity in extraction because they are safe and environmentally friendly, making them viable alternatives to organic solvents (OSs). This research first compared the extraction efficiency of OSs on the extraction of phytochemicals from the infloresences of two hemp varieties, Citrus and Cherry Dwarf. Inflorescences were extracted using three OSs, ethanol, ethyl acetate, and hexane. The highest level of cannabidiol (CBD; 0.69%) was extracted from Cherry Dwarf using ethanol while the level of delta-9 tetrahydrocannabinol THC (0.19%) was essentially the same in both. Therefore, Cherry Dwarf was selected to compare the extraction efficiency of DESs to the OSs. The DESs were choline chloride/ethylene glycol, citric acid/ethylene glycol, menthol/lauric acid, choline chloride/urea and choline chloride/glycerol. In the targeted analysis, choline chloride/ethylene glycol extracted the highest amount of CBD (0.87%) followed by choline chloride/urea (0.78%). As some DESs outperformed ethanol, the popular solvent for extracting cannabinoids, DESs are viable candidates to replace organic solvents.

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.

Methylation of cytosines at CpG sites in DNA, carried out by de novo by DNA methyltransferase Dnmt3a, is a basic epigenetic modification involved in gene regulation and genome stability. Aberrant CpG methylation in gene promoters leads to oncogenesis. In oncogene promoters, CpG sites often colocalize with guanine-rich sequences capable of folding into G-quadruplexes (G4s). Our in vitro study aimed to investigate how parallel G4s formed by a sequence derived from the c-MYC oncogene promoter region affect the activity of the Dnmt3a catalytic domain (Dnmt3a-CD). For this purpose, we designed synthetic oligonucleotide constructs: c-MYC G4-forming oligonucleotide and linear double-stranded DNA containing an embedded stable extrahelical c-MYC G4. The topology and thermal stability of G4 structures in these DNA models were analyzed by physicochemical techniques. We showed that Dnmt3a-CD specifically binds to an oligonucleotide containing c-MYC G4, resulting in inhibition of its methylation activity. c-MYC G4 formation in a double-stranded context significantly reduce Dnmt3a-CD-induced methylation of a CpG site located in close proximity to the quadruplex structure; this effect depends on the distance between the non-canonical structure and the specific CpG site. One would expect DNA hypomethylation near the G4 structure, while regions distant from this non-canonical form would maintain a regular pattern of high methylation levels. We hypothesize that the G4 structure sequesters the Dnmt3a-CD and impedes its proper binding to B-DNA, resulting in hypomethylation and activation of c-MYC transcription.

The present paper reports an exact approach quantifying the electromagnetic contribution to the anomalous magnetic moment occurring in isolated system comprised of non-composite particle carrying elementary electric charge. Essential averaging procedure and regularization of the electromagnetic field potentials necessary when quantifying the electromagnetic self-interactions and when deriving equations of motion without singularities and obeying the conservation laws are thoroughly discussed. The study shows that the dynamics of the considered system is associated to unique classical transcendental equations of motion satisfied by the particle's velocity and the electromagnetic contribution to the anomalous $g$-factor known from the quantum electrodynamics. The equations of motion lead to an exact analytical expression for the anomalous $g$-factor that provides more accurate result than that calculated with the aid of quantum electrodynamics. It matches the experimentally measured value reported in the literature to a one part per trillion. We obtain a_e=0.00115965218000(65) thus reveling the potential of non-perturbative, non-probability methods in predicting the electron's anomalous g-factor.

G-quadruplex, a unique secondary structure in nucleic acids found throughout human genome elicited widespread interest in the field of therapeutic research. Being present in key regulatory regions of oncogenes, G-quadruplex structure regulates transcription, translation, splicing, telomere stability etc. Changes in its structure and stability lead to differential expression of oncogenes causing cancer. Thus, targeting G-Quadruplex structures with small molecules/ other biologics has shown elevated research interest. Covering previous reports, in this review we try to enlighten the facts on the structural diversity in G-quadruplex ligands aiming to provide newer insights to design first-in-class drugs for the next generation cancer treatment.

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.

Background and Aims: Dyslipidemia and cardiovascular diseases (CAD) are comorbidities of nonalcoholic fatty liver disease (NAFLD), which ranges from steatosis to hepatocellular carcinoma (HCC). The rs599839 A>G variant, in the CELSR2-PSRC1-SORT1 cluster, has been associated CAD, but its impact on metabolic traits and liver damage in NAFLD has not been investigated yet. Methods: We evaluated the effect of the rs599839 variant in 1426 NAFLD patients (Overall cohort) of whom 131 have HCC (NAFLD-HCC), in 500,000 individuals from the UK Biobank Cohort (UKBBC) and in 366 HCC samples from The Cancer Genome Atlas (TCGA). Hepatic PSRC1, SORT1 and CELSR2 expressions were evaluated by RNAseq (n=125). Results: The rs599839 variant was associated with reduced circulating LDL, carotid intima-media thickness, carotid plaques and hypertension (p<0.05) in NAFLD patients and with protection against dyslipidemia in UKBBC. The G allele was associated with higher risk of HCC and advanced tumor stage (p<0.05) in the Overall cohort. Hepatic PSRC1, SORT1 and CELSR2 expressions were increased in NAFLD patients carrying the rs599839 variant (p<0.0001). SORT1 mRNA levels negatively correlated with circulating lipids and with those of genes involved in lipoprotein turnover (p<0.0001). Conversely, PSRC1 expression was positively related to that of genes implicated in cell proliferation (p<0.0001). In TCGA, PSRC1 over-expression promoted more aggressive HCC development (p<0.05). Conclusions: In sum, the rs599839 A>G variant improves dyslipidemia thus protecting against CAD in NAFLD patients, but as one it might promote HCC development by modulating SORT1 and PSRC1 expressions which impact on lipid metabolism and cell proliferation, respectively

In this article/review, the selective interactions of several berberine and palmatine derivatives with various DNA G-quadruplex structures are reported. These derivatives were constructed starting from two natural compounds, berberine and palamatine, through specific synthetic passages following two different schemes for each of them and using several substituents. The details of these synthesis are also described. Indeed, the study of the interactions of these derivative compounds with various G-quadruplex forming sequences was carried out by means of various structural and biochemical techniques. The results show that the presence of suitable side chains are very useful to improve the interaction of the ligands with G-quadruplex structures. Thus, since G-quadruplex formation is promoted by these compounds, which have never been reported before, these may be tested as potential anticancer drugs.

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.

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.

This review summarizes the most recent developments of research on protozoan parasite infections ac-quired through food and drinking water and is aimed at gathering updated knowledge on the risk factors, illnesses caused, and measures for prevention. Reports included dated from 2019 to the present and regarded recent outbreaks and cases of severe infec-tions, prevalence in different population segments and food handlers, and occurrence in food and drinking water. Cryptosporidium spp., Entamoeba histolytica, Giardia intestinalis, Trypanosoma cruzi and Toxoplasma gondii were the microorganisms most frequently involved in large outbreaks and/or severe infections, while Cyclospora cayetanensis was most frequently involved in single case reports. Cystoisospora belli was implied in severe infections in immunocompromised patients, while Blastocystis homi-nis, Sarcocystis spp., Dientamoeba fragilis, Endolimax nana and Pentatrichomonas hominis appeared to be less relevant for number of symptomatic infections and pathogenic potential. A progressive improvement in surveillance of protozoan infections and infection sources was highlighted, especially in developed countries. The apparent increase in cases was concomitant with the implementa-tion of reporting systems and the application of molecular diagnostic methods that represent valuable in-struments for establishing epidemiological links and preventing or limiting outbreaks. The pathogenic role and sources of infection should be better elucidated for some species.

In the bioprinting process, controlling the motion of bioprinters involves a computer-aided design (CAD) model, converting that model into g-code, and transmitting the motion commands to the bioprinters. The g-code file contains information about the motion of the axes and can be generated using various software. However, a challenge arises when using g-code between different bioprinters. Therefore, the objective of this study was to propose a reliable method for analyzing the differences in 3D bioprinting devices by parameterizing a crucial variable for extrusion bioprinting: the E-value. Four bioprinters from three different manufacturers were used to investigate the extrusion behavior when subjected to the same E-value.

The G-NUMEN array is the future gamma spectrometer of the NUMEN experiment (Nuclear Matrix Element for the Neutrinoless double beta decay), to be installed around the object point of the MAGNEX magnetic spectrometer at the INFN-LNS laboratory.. This project aims at exploring Double Charge Exchange (DCE) reactions in order to obtain crucial information about the neutrinoless double beta decay (0νββ). The primary objective of the G-NUMEN array is to detect the gamma rays emitted from the de-excitation of the excited states populated via DCE reactions with good energy resolution and detection efficiency, amidst a background composed of transitions from competingreaction channels with far higher cross-sections. To achieve this, the G-NUMEN signalswill be processed in coincidence with those generated by the detection of the reaction ejectiles in the MAGNEX Focal Plane Detector(FPD). Under the expected experimental conditions, G-NUMEN detectors will operate at high counting rates, of the order of hundreds of kHz per detector, while maintaining excellent energy and timing resolutions. The complete array will consist of over 100 LaBr3(Ce) scintillators. Initial tests have been conducted on the first detectors of the array, allowing for the determination of their performance at high rates.

Post-translational modifications (PTMs) of histone residues shape the landscape of gene expression by modulating the dynamic process of RNAPII transcription. The contribution of particular histone modifications to the definition of distinct RNAPII transcription stages remains poorly characterized in plants. Chromatin Immuno-precipitation combined with next-generation sequencing (ChIP-seq) resolves the genomic distribution of histone modifications. Here, we review histone PTM ChIP-seq data in Arabidopsis thaliana and find support for a Genomic Positioning System (GPS) that guides RNAPII transcription. We review the roles of histone PTM “readers”, “writers” and “erasers”, with a focus on the regulation of gene expression and biological functions in plants. The distinct functions of RNAPII transcription during the plant transcription cycle may in part rely on the characteristic histone PTMs profiles that distinguish transcription stages.

Air pollution poses a significant risk to public health and ecosystems. The use of sophisticated models to simulate the transformation and dispersion of pollutants in the atmosphere is a recognized method to assess air pollution levels and its sources and inform policy decisions for effective mitigation strategies in urban and industrial environments. The reliability of models depends, in part, on the sensitivity to the variance of input parameters, which can introduce uncertainty into the model's predictions. This uncertainty is especially challenging when the input parameters exhibit inherent variability. In this study, we analyse the uncertainty of an integrated emission/dispersion model by evaluating the relationship between input parameters and model outcomes. We uncover new aspects of this relationship while clarifying some previously known dependencies. Wind speed was found to have the most significant effect on calculated concentrations, with small differences leading to substantial concentration variations. The time of day, which reflects prevailing vertical turbulence conditions, was also found to have a notable impact on concentrations, whereas ambient temperature can also significantly influence model’s results. Based on these findings, we offer specific recommendations for regulators and scientists involved in environmental impact assessment to improve the accuracy and reliability of air pollution modelling.

Background: Several kinds of research say that adjuvant blood glucose and blood pressure are usual, but an efficient solution for medical application count remains. This review analyzes the pandemic blood pressure and blood glucose to identify the publications which tell about the clinical practices and research gaps in systematic research.Methods: A study guides to identify the research of Blood Pressure (BP) and Blood Glucose. In order to analyze the recent innovations and research on BP and Blood glucose, the relevant publications and literature from journals were identified.Results: Co-morbidity of BP and Blood glucose is reported as very high. The commonness of blood pressure is thrice as high in type I diabetes patients and almost two times higher in type II diabetes patients when compared to others without Diabetes. The pervasiveness of getting depression is more in the female when compared with men. A detailed study about the linkage of BP and blood glucose tells that the relationship between them is not exactly clear.Limitations: Nearly all reviews providing the linkage of BP and blood glucose are with some limitations and they are not providing any clear conclusion.Conclusions: Present research tells that people having high blood glucose will have a greater chance of getting high blood pressure. More research is needed to state the linkage between BP, blood glucose, and the growth of diabetes mellitus issues and to provide support for managing Diabetes.

Although Eulerian approaches are standard in computational acoustics, they are less effective for certain classes of problems like bubble acoustics and combustion noise. A different approach for solving acoustic problems is to compute with individual particles following particle motion. In this paper, a Lagrangian approach to model sound propagation in moving fluid is presented and implemented numerically, using three meshfree methods to solve the Lagrangian acoustic perturbation equations (LAPE) in the time domain. The LAPE split the fluid dynamic equations into a set of hydrodynamic equations for the motion of fluid particles and perturbation equations for the acoustic quantities corresponding to each fluid particle. Then, three meshfree methods, the smoothed particle hydrodynamics (SPH) method, the corrective smoothed particle (CSP) method, and the generalized finite difference (GFD) method, are introduced to solve the LAPE and the linearized LAPE (LLAPE). The SPH and CSP methods are widely used meshfree methods, while the GFD method based on the Taylor series expansion can be easily extended to higher orders. Applications to modeling sound propagation in steady or unsteady fluids in motion are outlined, treating a number of different cases in one and two space dimensions. A comparison of the LAPE and the LLAPE using the three meshfree methods is also presented. The Lagrangian approach shows good agreement with exact solutions. The comparison indicates that the CSP and GFD method exhibit convergence in cases with different background flow. The GFD method is more accurate, while the CSP method can handle higher Courant numbers.

We used an ultrasensitive, broadband optomechanical ultrasound sensor to study the acoustic signals produced by pressurized nitrogen escaping from a variety of small syringes. Harmonically related jet tones extending into the MHz region were observed for a certain range of flow (i.e., Reynolds number), in qualitative agreement with historical studies on gas jets emitted from pipes/orifices of much larger dimensions. For higher turbulent flow rates, we observed broadband ultrasonic emission in the ~ 0 – 5 MHz range, likely limited on the upper end by attenuation in air. These observations are made possible by the broadband, ultrasensitive response (for air-coupled ultrasound) of our optomechanical devices. Aside from their theoretical interest, our results could have practical implications for the non-contact monitoring and detection of early-stage leaks in pressured fluid systems.

Mediterranean Diet (MD), rich in minimally processed plant foods and in monounsaturated fats, but low in saturated fats, meat and dairy products, represents one of the most studied diets for cardiovascular health. It has been shown, from both observational and randomized controlled trials, that MD reduces body weight, improves cardiovascular disease surrogates such as waist-to-hip ratio, lipids, and inflammation markers, and even prevents the development of fatal and non-fatal cardiovascular disease, diabetes, obesity, and other diseases. However, it is unclear whether it offers cardiovascular benefits from its individual components or as a whole. Furthermore, limitations in the methodology of studies and meta-analyses have raised some concerns on its potential cardiovascular benefits. MD is also associated with characteristic changes in the intestinal microbiota, mediated through its constituents. These include increased growth of species producing short-chain fatty acids, such as Clostridium leptum and Eubacterium rectale, increased growth of Bifidobacteria, Bacteroides and Faecalibacterium prausnitzii species, and reduced growth of Firmicutes and Blautia species. Such changes are known to be favorably associated with inflammation, oxidative status, and overall metabolic health. This review will focus on the effects of MD on cardiovascular health through its action on gut microbioma.

(1) Background: The emergence of antibiotic-resistant bacteria is a growing concern in the field of medicine. This has led to the need for alternative treatments for bacterial infections. (2) Methods: The present study aimed to investigate the synergistic effect of a water-based extract of S. fru-tescens and penicillin G on the growth of E. faecalis. (3) Results: The study found that the combina-tion of the plant extract and penicillin G had a synergistic effect on the inhibition of bacterial growth, with a significantly larger inhibition zone observed compared to penicillin G alone. The MIC and MBC tests also demonstrated that the combination of the plant extract and penicillin G was more effective against E. faecalis than penicillin G alone, with a dilution of 1 in 4 yielding 100% inhibition of growth. (4) Conclusion: Although the specific mechanism of action was not dis-cussed in the study, the results suggest that the combination of the plant extract and penicillin G may offer a promising alternative treatment for antibiotic-resistant infections. Further research is needed to determine the active compounds in the plant extract and to investigate the synergistic effect of the combination on other strains of bacteria.

Heterojunctions based on metal halide perovskites (MHPs) are promising systems for photocatalytic hydrogen evolution reaction (HER). In this work, we coupled Cs3Bi2Br9 nanocrystals (NCs), obtained by wet ball milling synthesis, with g-C3N4 nanosheets (NSs) produced by thermal oxidation of bulk g-C3N4 in air. These methods are reproducible, inexpensive, and easy to scale up. Heterojunctions with different loadings of Cs3Bi2Br9 NCs were fully characterized and tested for HER. A relevant improvement of H2 production with respect to pristine carbon nitride was achieved at low NCs levels reaching values up to about 4600 µmol g-1 h-1. This work aims to provide insights on the synthesis of inexpensive and high performing heterojunctions using MHP for photocatalytic applications.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

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.

Convolutional neural network architectures have become increasingly complex, which has improved the performance slowly on well-known benchmark datasets in the recent years. In this research, we have analyzed the true need for such complexity. We have introduced G-Net light, a lightweight modified GoogleNet with improved filter count per layer to reduce feature overlaps and complexity. Additionally, by limiting the amount of pooling layers in the proposed architecture, we have exploited the skip connections to minimize the spatial information loss. The investigations on the proposed architecture are evaluated on three retinal vessel segmentation publicly available datasets. The proposed G-Net light outperforms other vessel segmentation architectures by reducing the number of trainable parameters..

Background: Night-migratory birds sense the Earth´s magnetic field by an unknown molecular mechanism. Theoretical and experimental evidence support the hypothesis that light-induced formation of a radical-pair in European robin cryptochrome 4a, ErCry4a, is the primary signalling step in the retina of the bird. In the present work, we investigated a possible route of cryptochrome signalling involving the α-subunit of the cone specific heterotrimeric G protein from European robin. Methods: Protein-protein interaction studies include surface plasmon resonance, pulldown affinity binding and Förster resonance energy transfer. Results: Surface plasmon resonance studies showed direct interaction revealing high to moderate affinity for binding of non-myristoylated and myristoylated G protein to ErCry4a, respectively. Pulldown affinity experiments confirmed this complex formation in solution. We validated these in vitro data by monitoring the interaction between ErCry4a and G protein in a transiently transfected neuroretinal cell line using Förster resonance energy transfer. Conclusions: Our results suggest that ErCry4a and the G protein also interact in vivo and might constitute the first biochemical signalling step in radical-pair-based magnetoreception.

G-protein coupled receptors (GPCRs) are large protein families known to be important in many cellular processes. They are well known for their allosteric activation mechanisms. They are drug targets for several FDA-approved drugs. We have investigated the diversity of the ligand binding site for these class of proteins against their cognate ligands using computational docking, even if their structures are known in the ligand-complexed form. The cognate ligand of some of these receptors dock at allosteric binding site, with better score than the binding at the conservative site. Further, ligands obtained from GLASS database, which consists of experimentally verified GPCR ligands, also show allosteric binding to GPCRs. The allosteric binders show strong affinity to the binding site, though the residues at the binding site are not conserved across GPCR subfamilies.

Accumulating evidence suggests that histamine synthesis induced in several types of tumor tissues should modulate tumor immunity. We found that a transient histamine synthesis was induced in CD11b⁺Gr-1⁺splenocytes derived from BALB/c mice transplanted with a syngeneic colon carcinoma, CT-26, when they were co-cultured with CT-26 cells. Significant levels of IFN-γ were produced under this co-culture condition. We explored the modulatory roles of histamine on IFN-γ production and found that several histamine receptor antagonists, such as pyrilamine, diphenhydramine, JNJ7777120, and thioperamide, could significantly suppress IFN-γ production. However, suppression of IFN-γ production by these antagonists was also found when splenocytes were derived from the Hdc^-/- BALB/c mice. Suppressive effects of these antagonists were found on IFN-γ production induced by concanavalin A or the combination of an anti-CD3 antibody and an anti-CD28 antibody in a histamine-independent manner. Murine splenocytes were found to express H₁ and H₂ receptors, but not H₃ and H₄ receptors. IFN-γ production in the Hh1r^-/- splenocytes induced by the combination of an anti-CD3 antibody and an anti-CD28 antibody was significantly suppressed by these antagonists. These findings suggest that pyrilamine, diphenhydramine, JNJ7777120, and thioperamide could suppress IFN-γ production in activated splenocytes in histamine-independent manner.

The purpose of the study is to establish compliance of the design of the modernized car with the requirements for safe operation. An option has been proposed for upgrading a passenger wagon to a Mobile Diagnostic Complex for transporting a combined vehicle equipped with appropriate flaw detection equipment intended for rail diagnostics. The authors have established the most optimal option for locating the diagnostic vehicle on board the Mobile Diagnostic Complex (MDC) wagon, taking into account the additional load from the vehicle. To achieve this goal, the article developed a three-dimensional model of the supporting structure of the wagon body, proposed a methodology and presented the results of a study of the stress-strain state of the wagon body, taking into account the additional weight of the wagon. The article develops a methodology for studying the natural frequencies of vibrations of the wagon body and develops a three-dimensional model of the wagon for calculating dynamic indicators in the Universal Mechanism software package. Taking into account the previously carried out strength calculations, as well as in order to maintain the factory life cycle indicators of the supporting structure of the wagon body, it is recommended to use the model in the first version.

An orthogonal pore ('orthopore') is conceptually based on an electrolytic cell with a standard pore (the main or 'longitudinal' pore) between cis and trans compartments filled with electrolyte and augmented by a secondary or 'transverse' pore in the form of a channel that is perpendicular to and intersects the main pore. Orthopores can be designed at different scales: macro through micro to nano. With nano-sized pores an analyte (polymer) can be threaded through the main pore and exposed at the junction to electrolyte flow through the secondary pore. Polymer translocation speeds are then independent of the current measured, which can be of an arbitrary magnitude even with the polymer stationary. Orthopores have a wide range of potential applications, including polymer (DNA and protein) sequencing, DNA unzipping, logic circuitry, and protein identification. The present report shows how orthopores can be used to implement boolean logic.

Predicting Length of Stay (LoS) and understanding its underlying factors is essential to minimize the risk of hospital-acquired conditions, improve financial, operational, and clinical outcomes, and to better manage future pandemics. The purpose of this study is to forecast patients’ LoS using a deep learning model and analyze cohorts of risk factors minimizing or maximizing LoS. We employed various pre-processing techniques, SMOTE-N to balance data, and Tab-Transformer model to forecast LoS. Finally, Apriori algorithm was applied to analyze cohorts of risk factors influencing LoS at hospital. The Tab-Transformer outperformed the base Machine Learning models with an F1-score (.92), precision (.83), recall (.93), and accuracy (.73) for discharge dataset, and F1-score (.84), precision (.75), recall (.98), and accuracy (.77) for deceased dataset. The association mining algorithm was able to identify significant risk factors/indicators belonging to lab, X-Ray, and clinical data such as elevated LDH, and D-Dimer, lymphocytes count, and comorbidities such as hypertension and diabetes responsible for extending patients LoS. It also reveals what treatments has reduced the symptoms of COVID-19 patients leading to reduction in LoS particularly when no vaccines or medication such as Paxlovid were available.