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Rice is pivotal in global food security and Rice seeding detection in precision agriculture is essential for optimizing crop productivity and efficient resource use. Currently, the spatial distribution and detection of rice seeding are manually done, which is time-consuming. As technology advances, the rapid progress in precision agriculture calls for innovative solutions like lightweight edge-computing vision models for unmanned aerial vehicle (UAV) intelligence. However, the limited computational capabilities of UAVs make it challenging to deploy complex object detection models onboard. This article proposes Li-YOLOv9, an efficient, lightweight, and precise object detection model for detection of rice seedlings from large-scale UAV remote sensing data. The proposed Li-YOLOv9 includes a 3-D feature adaptation module, convolutional block attention modules, coordinate attention module, and deepwise point convolution modules, which offer significant advantages over the original YOLOv9. The compact Li-YOLOv9 with approximately 9 million parameters is significantly lighter than the original YOLOv9 with 60 million parameters, making it ideal for resource-efficient onboard intelligence. Li-YOLOv9 is tested and validated against a real UAV rice seedling dataset. It showcases exceptional detection capabilities, achieving impressive metrics across various performance indicators, including a mean average precision of 99.60%, an $F1$-score of 96.95%, an average recall of 96.70%, and an average precision of 97.20% in comparison to the state-of-the-art. Li-YOLOv9 is highly efficient and ideal for UAV deployment for real-time detection of rice seedlings from large-scale remote sensing data.

Abstract Smart device manufacturers rely on insights from smart home (SH) data to update their devices, and similarly, service providers use it for predictive maintenance. In terms of data security and privacy, combining distributed federated learning (FL) with blockchain technology is being considered to prevent single point failure and model poising attacks. However, adding blockchain to a FL environment can worsen blockchain's scaling issues and create regular service interruptions at SH. This article presents a scalable Blockchain‐based Privacy‐preserving Federated Learning (BPFL) architecture for an SH ecosystem that integrates blockchain and FL. BPFL can automate SHs' services and distribute machine learning (ML) operations to update IoT manufacturer models and scale service provider services. The architecture uses a local peer as a gateway to connect SHs to the blockchain network and safeguard user data, transactions, and ML operations. Blockchain facilitates ecosystem access management and learning. The Stanford Cars and an IoT dataset have been used as test bed experiments, taking into account the nature of data (i.e. images and numeric). The experiments show that ledger optimisation can boost scalability by 40–60% in BCN by reducing transaction overhead by 60%. Simultaneously, it increases learning capacity by 10% compared to baseline FL techniques.

Abstract Treating lung and prostate cancer cells is a major health problem that may be solved through the interactions of laser beams with nanoparticles. In the paper, Au-H2Ti3O7 nanotubes (NTs) are proposed as a treatment agent and the interactions of different laser beams with the nanostructure are considered to solve the mentioned health problem. Also, the NTs are employed to treat the cancers in dark conditions. The results are motivating because Au-H2Ti3O7 NPs do not affect healthy cells, while they strongly affect cancer cells, and the viability percentage of LNCap cells reaches 16% for incubation times of 48 h. Furthermore, treating LNCap cells using the irradiated Au-H2Ti3O7 NTs by NIR beam at 808 nm has no cytotoxicity, while cytotoxicity of 92% is obtained using an irradiation laser beam at 532 nm. Also, applying the laser beam at 635 nm to the NTs leads to a cytotoxicity of ∼53% in lung cancer (A549 cells). In total, the Au-H2Ti3O7 NTs have a selective effect on cancer cells and greatly reduce the viability in the given dark and irradiation conditions, leading to the introduction of them as a promising agent for the non-invasive treatment of prostate cancer and a moderate candidate for lung cancer therapy.

Regarding a simple graph $ \Gamma $ possessing $ \nu $ vertices ($ \nu $-vertex graph) and $ m $ edges, the vertex-weight and weight of an edge $ e = uv $ are defined as $ w(v_{i}) = d_{ \Gamma}(v_{i}) $ and $ w(e) = d_{ \Gamma}(u)+d_{ \Gamma}(v)-2 $, where $ d_{ \Gamma}(v) $ is the degree of $ v $. This paper puts forward a novel graphical matrix named the edge-weighted adjacency matrix (adjacency of the vertices) $ A_{w}(\Gamma) $ of a graph $ \Gamma $ and is defined in such a way that, for any $ v_{i} $ that is adjacent to $ v_{j} $, its $ (i, j) $-entry equals $ w(e) = d_{ \Gamma}(v_{i})+d_{ \Gamma}(v_{j})-2 $; otherwise, it equals 0. The eigenvalues $ \lambda_{1}^{w}\ge \lambda_{2}^{w}\ge\ldots\ge \lambda_{\nu}^{w} $ of $ A_w $ are called the edge-weighted eigenvalues of $ \Gamma $. We investigate the mathematical properties of $ A_{w}(\Gamma) $'s spectral radius $ \lambda_{1}^{w} $ and energy $ E_{w}(\Gamma) = \sum_{i = 1}^{\nu}|\lambda_{i}^{w}| $. Sharp lower and upper bounds are obtained for $ \lambda_{1}^{w} $ and $ E_{w}(\Gamma) $, and the respective extremal graphs are characterized. Further, we employ these spectral descriptors in structure-property modeling of the physicochemical properties of polycyclic aromatic hydrocarbons for a set of benzenoid hydrocarbons (BHs). Detailed regression analysis showcases that edge-weighted energy outperforms classical adjacency energy in structure-property modeling of the physicochemical properties of BHs.

IntroductionExcessive alcohol consumption negatively impacts physical and psychiatric health, lifestyle, and societal interactions. Chronic alcohol abuse alters brain structure, leading to alcohol use disorder (AUD), a condition requiring early diagnosis for effective management. Current diagnostic methods, primarily reliant on subjective questionnaires, could benefit from objective measures.MethodThe study proposes a novel EEG-based classification approach, focusing on effective connectivity (EC) derived from resting-state EEG signals in combination with support vector machine (SVM) algorithms. EC estimation is performed using the partial directed coherence (PDC) technique. The analysis is conducted on an EEG dataset comprising 35 individuals with AUD and 35 healthy controls (HCs). The methodology evaluates the efficacy of connectivity features in distinguishing between AUD and HC and subsequently develops and assesses an EEG classification technique using EC matrices and SVM.ResultThe proposed methodology demonstrated promising performance, achieving a peak accuracy of 94.5% and an area under the curve (AUC) of 0.988, specifically using frequency bands 29, 36, 45, 46, and 52. Additionally, feature reduction techniques applied to the PDC adjacency matrices in the gamma band further improved classification outcomes. The SVM-based classification achieved an accuracy of 96.37 ± 0.45%, showcasing enhanced performance through the utilization of reduced PDC adjacency matrices.DiscussionThese results highlight the potential of the developed algorithm as a robust diagnostic tool for AUD detection, enhancing precision beyond subjective methods. Incorporating EC features derived from EEG signals can inform tailored treatment strategies, contributing to improved management of AUD.

In hot climates, excessive heat gain through building roofs significantly increases cooling loads and energy consumption. This study aims to reduce roof heat gain by developing an innovative hybrid active slab with phase change material (PCM) panels and a geothermal well (HASP-GW). The HASP-GW system incorporates PCM panels and an active concrete slab embedded with water pipes as heat exchangers. Water at a constant temperature of 22 °C, sourced from a geothermal well, flows through these pipes to stabilize indoor temperatures. This research investigates the thermal performance of the HASP-GW with varying PCM transition temperatures and water flow rates using numerical simulations, validated against experimental results. The experimental setup involved two well-insulated test rooms (each 0.85 m × 0.85 m × 1 m); one equipped with the HASP-GW system and the other as a conventional comparison. Results showed that using the HASP-GW with a PCM transition temperature of 38–41 °C and a water flow rate of 1 L/min reduced the heat flux on inner surface of the roof, decrement factor, and inner surface temperature by 90.13 %, 0.127, and 16.24 °C, respectively, compared to a traditional roof. These findings indicate the potential of HASP-GW for energy-efficient roof cooling in hot climates.

Latent thermal energy storage units are especially preferred in renewable thermal energy systems for their significant capacity to store heat. Nevertheless, the phase change materials in these units have low thermal conductivity, prompting researchers to tackle this problem using several methods, such as incorporating fins. This numerical study contributes to improving the charging rate of a square cell (50 × 50 mm) used paraffin wax RT42 as phase change material by adding 4 copper fins inside, 1 mm thick and of different lengths. The fins were positioned on the left wall, where a constant-temperature heat flux was applied, while the other walls were thermally insulated. Four configurations of the cell were examined: without fins, with 10 mm length fins, with 20 mm length fins, and with 30 mm length fins, respectively. The results demonstrated that the presence of fins significantly improved the charging rate of the square cell. Compared to the baseline configuration without fins, the time required for the paraffin wax RT42 to completely melt was reduced by 22.22 %, 33.33 %, and 55.56 % with fins of 10 mm, 20 mm, and 30 mm lengths, respectively. Configuration four was also compared with a setup where similar fins were positioned on the bottom wall while maintaining the heat flux on the left wall. It was observed that the total melting time doubled compared to configuration four, suggesting that the optimal placement for the heat flux is on the wall where the fins are located. The study contributes to enhancing and developing the charge rates of square and rectangular PCM cells such as these used for cooling PV panels.

This study investigates the molluscicidal properties of Salvia officinalis extracts against Melanopsis nodosa snails, with a focus on environmentally friendly alternatives to traditional chemical molluscicides. Melanopsis nodosa, a common freshwater snail in Iraq, is an intermediate host for diseases affecting humans and animals. Traditional molluscicides, such as copper sulphate, pose environmental and non-target organism risks. S. officinalis, known for various medicinal uses, was explored for its potential molluscicidal activity. Snails were collected from Muhyii Canal, Baghdad, and exposed to different concentrations of S. officinalis extracts and copper sulphate in controlled laboratory conditions. The study evaluated mortality rates at 24-, 48-, 72-, and 96-hours exposure, using the WHO method for molluscicide testing and Probit analysis for mortality calculation. Results showed significant molluscicidal activity of S. officinalis extracts, with the LC50 values of 15.53 ppm (24 hrs), 6.821 ppm (48 hrs), 4.288 ppm (72 hrs), and 0.0735 ppm (96 hrs). Compared to copper sulphate, the extracts were less effective but still significant, indicating the potential of S. officinalis as an environmentally friendly molluscicide. This study contributes to the search for safer molluscicides, highlighting S. officinalis extracts' effectiveness against M. nodosa. These findings could aid in controlling snail populations, thereby reducing the spread of snail-borne diseases, with lower environmental impact compared to traditional chemical molluscicides. Further research is suggested to understand the exact mechanism of snail mortality caused by these extracts.

The goal of medical research across the world is to improve the health of patients. Nanotechnology is an emerging field that is now heavily concentrated in the realm of medicine continuous research in the sector has resulted in the emergence of a new discipline known as "nanomedicine," which attempts to provide new treatment options while also improving the therapeutic efficacy of existing medications. polymersomes have gotten a lot of attention in recent research all around the world, and it's led to the creation of novel medical therapies. Solubilization, cancer therapy targeting, and usage as diagnostic tool are some of these techniques. Polymersomes, which are artificial amphiphilic vesicles made up of a variety of chemical polymers, are presently being investigated for delivering different probes for imaging target tissues/ organs, as well as cytotoxic medicines to tumor cells for gene therapy. Thorough analysis has been confirmed that polymersomes will surely compete in the future in the rapidly developing field of nanotechnology. Polymersomes have great stability, ease of flexibility, and capacity to encapsulate a variety of different drugs will ensure that they play a significant role in the development of sophisticated drug delivery systems.

Multiple system atrophy (MSA) is characterized by glial cytoplasmic inclusions (GCIs) containing aggregated α-synuclein (α-syn) in oligodendrocytes. The origin of α-syn accumulation in GCIs is unclear, in particular whether abnormal α-syn aggregates result from the abnormal elevation of endogenous α-syn expression in MSA or ingested from the neuronal source. Tubulin polymerization promoting protein (TPPP) has been reported to play a crucial role in developing GCI pathology. Here, the total cell body, nucleus, and cytoplasmic area density of SNCA and TPPP transcripts in neurons and oligodendrocytes with and without various α-syn pathologies in the pontine base in autopsy cases of MSA (n = 4) and controls (n = 2) were evaluated using RNAscope with immunofluorescence. Single-nucleus RNA-sequencing data for TPPP was evaluated using control frontal cortex (n = 3). SNCA and TPPP transcripts were present in the nucleus and cytoplasm of oligodendrocytes in both controls and diseased, with higher area density in GCIs and glial nuclear inclusions in MSA. Area densities of SNCA and TPPP transcripts were lower in neurons showing cytoplasmic inclusions in MSA. Indeed, TPPP transcripts were unexpectedly found in neurons, while the anti-TPPP antibody failed to detect immunoreactivity. Single-nucleus RNA-sequencing revealed significant TPPP transcript expression predominantly in oligodendrocytes, but also in excitatory and inhibitory neurons. This study addressed the unclear origin of accumulated α-syn in GCIs, proposing that the elevation of SNCA transcripts may supply templates for misfolded α-syn. In addition, the parallel behavior of TPPP and SNCA transcripts in GCI development highlights their potential synergistic contribution to inclusion formation. In conclusion, this study advances our understanding of MSA pathogenesis, offers insights into the dynamics of SNCA and TPPP transcripts in inclusion formation, and proposes regulating their transcripts for future molecular therapy to MSA.

تعتبر المياه المصاحبة للنفط من أخطر أنواع التلوث على البيئة، لأنها تحتوي على العديد من الملوثات الضارة بالبيئة وصحة الإنسان مثل (النفط، المواد الصلبة العالقة، المواد الذائبة، والعديد من الملوثات الأخرى). يتناول هذا المقال عمليات الأكسدة المتقدمة (AOPs) التي تمت دراستها لتنقية المياه المنتجة من حقل الخباز النفطي الواقع في شمال العراق - محافظة كركوك من المحتوى النفطي. نظرًا لسهولة استخدام AOPs والأداء والسعر المنخفض، فهي طريقة شائعة لتنقية هذا النوع من مياه الصرف الصحي. في هذا العمل تم استخدام عمليات التحفيز الضوئي المتجانسة (Photo-Fenton (H2O2+Fe+2+UV)،) Fenton (H2O2+Fe+2، وUltra Violet (UV) فقط) في نظام الدفعات تحت أفضل الظروف (الزمن = 120 دقيقة، الرقم الهيدروجيني = 2.5، H2O2 = 20 مل في عملية فوتو فنتون، H2O2 = 80 مل في عملية فنتون، 2 مصباح UV (قدرة كل واحد = 8 وات) في عملية فوتو فنتون، 10 مصابيح UV في عملية UV مباشرة، و Fe+2=18 مجم في عمليات فوتو فنتون وفنتون). تم في هذا البحث دراسة تأثير جرعات H2O2 وFe+2 وزمن التشعيع وقيمة الرقم الهيدروجيني وشدة الأشعة فوق البنفسجية على فعالية إزالة النفط. حققت هذه الدراسة أعلى كفاءة في الفوتو-فنتون هي 85.68%، الفنتون= 75.01%، والتحليل الضوئي فوق البنفسجي المباشر= 56.64%. ونتيجة لذلك تم التوصل إلى أن عملية الفوتو فنتون هي أفضل طريقة لإزالة النفط من المياه المصاحبة للنفط.

This study explores the hydraulic and thermal characteristics of a staggered rectangular baffled channel. The first baffle is inserted in the top channel surface, with subsequent baffles placed on the bottom. Numerical simulations were conducted across a Reynolds number range of 5000 to 50,000. In this study three different baffle inclination angles are examined: Case A involves staggered obstacles perpendicular to the channel wall, while Cases B and C feature obstacles inclined at ±10 ° to the channel surface. Three different types of nanoparticles (SiO2, Al2O3, and CuO) are added to the base fluid (pure water) at a volume fraction of 4 % to formulate the nanofluids utilized in this study. Computational Fluid Dynamics (CFD) simulations were performed using ANSYS Fluent software, to solve the governing equations. The numerical results were validated against experimental data, demonstrating good agreement. The findings reveal that the maximum thermal enhancement factor is 2 at a Reynolds number of 5000 for Case A. Additionally, the heat transfer coefficient experiences a 10.3 % increase for water-CuO nanofluid compared to pure water in Case A. The highest average Nusselt number is observed with pure water, reaching 812 for Case C at a Reynolds number of 50,000.

Purpose: Human ocular tissue banking plays an important part in the advancement of translational research for identifying the molecular processes involved in disease etiology and pathogenesis. Timely obtaining a good-quality ocular tissue from a cadaveric donor is exceedingly difficult, especially in remote areas, with a variable transportation time (within 12–24 h), raising concerns about RNA quality and its subsequent applications. Therefore, we assessed the utility of retinal tissues from cadaver donor and enucleated eyes based on the RNA quality and gene expression by real-time polymerase chain reaction (PCR). Settings and Design: Prospective study. Methods: Retina tissues were separated from the donor/enucleated eyes received in the eye bank within 24 h of death (n = 15) and within an hour from OR (n = 3), respectively, and stored immediately at -80 degree. RNA was isolated using trizol, and the quantity and quality were assessed using Qubit and agarose gel electrophoresis, respectively. QPCR was performed for measuring the expression of different retinal-specific genes. The cellular viability of the retina was assessed by establishing explant primary cell cultures. Statistical Analysis: The data were calculated as an average of normalised Ct values ± standard error of the mean. Results: RNA obtained from cadaveric tissues despite being partially degraded showed a uniform strong gene expression of several retinal-specific genes such as PAX6, RHO, TUBB3, CRX, and ALDH1L1. The primary cultures established from cadaveric tissues showed viable cells. Conclusion: The cadaver donor tissues collected within 24 hours of death can be effectively utilized for gene expression profiling.

Nanomaterials with one-, two-, or three-dimensional structures have exhibited superior optical, electronic, magnetic, thermal, and mechanical properties compared to their bulk material counterparts [...]

Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

The Hamamok Dam is an earthfill dam with a height of 25 m and length of 125 m; constructed in 2011; located northwest of Koya town on a deep canyon-like valley that flows along the southeastern plunge of the Bana Bawi anticline; which forms Bawagi Mountain. The exposed rocks in the site belong to the Pila Spi and Gercus formations; however, rocks of the Khurmala and Kolosh formations are exposed upstream from the dam’s reservoir. The difference in the hardness of the carbonate rocks of the Pila Spi Formation which forms the uppermost parts of the cliffs surrounding the dam site and those of soft reddish brown clastics of the Gercus Formation caused steep slopes that suffer from slope instability problems. To assess a geotechnical study of slopes in the dam site, we have collected different field data to perform a Kinematic assessment method using Dip Analyst 2.0 software and draw the stereographic projection for the studied 10 stations using Stereonet v.11 software. Besides Bejerman’s method, which is based on field data only and indicates the Landslide Possibility Index (LPI). The results showed that the L.P.I. values range between 23 and 27, whereas the results of the Kinematic analysis showed that the right bank (Stations 1 – 5) suffers from plane sliding, whereas the left bank (Stations 6 – 10) suffers from toppling. In both cases, Joint 2 has the main role in the developed failures.

The aim of this paper is to give a comprehensive awareness of some substantial factors including the influences of the embedment level of a building and the presence of dead loading which affect the structure-soil-structure interaction (SSSI) of nearby buildings that were not investigated thoroughly in the preceding studies related to seismic analysis and design, and earthquakes hazards assessment. In order to achieve this goal, two dynamic tests will be implemented on two novel small scale multi-degree of freedom nearby steel models of six stories by a shaking table system with the consideration of soil participation in these tests; the first test includes examining the effect of several levels of embedment of one of the adjacent buildings, the second test includes examining the effect of the presence of dead loading for different situations. Test results indicated that these factors have critical impacts on the SSSI response. It is evident that the increase in embedment level led to mitigate the impact of the earthquake wave on the seismic response of the examined structure while the results of the dead loading conditions had some positive and negative aspects on the seismic responses of the tested structure. Regarding the foundation rotation and soil pressure responses, the outcomes also displayed an equivalent tendency to the previous two responses which included that as soon as the embedment level of the examined building maximized, these responses got minimized as well. The reduction was 13.1%, and 21.3% for the one-story embedment, and two-story embedment.

The lower olefins (Ethylene, propylene, and butylene) are considered the key to the polymeric and petrochemical industries. Dehydration of alcohols to produce light olefins (Methanol-to-olefins reaction) over SAPO-34 molecular sieve has attractedintoigh attention. Modified SAPO-34 zeolite catalyst with Zr metal was successfully prepared under microwave irradiation using morpholine as a structure direct agent. The microwave energy power used was 800 w and the crystallization time was 200 min. The catalyst sample was characterized by XRD, SEM, EDX, BET, FTIR, and TGA analysis. XRD analysis exhibited a typical chabazite structure with high crystallinity. The analysis showed macrocrystalline particles with moderate distribution of silica in the framework structure and a low surface area of 77 m2/g. The vibration peaks of the prepared catalyst showed agreement with the SAPO-34 CHA structure. Catalyst performance towards methanol-to-olefins conversion was performed in a trickle bed reactor with temperatures of 350, 400, 450, and 500 oC at a weight hourly space velocity of 7.7 h-1. The results also reveal at a temperature of 400 oC , that the best olefins selectivity was obtained, reaching 70%, with a longer lifetime of 500 min. methanol conversion was almost 100% at all reaction temperatures. In addition, the effect of methanol concentration was investigated and the results showed that increasing of water content plays a role in increasing catalyst lifetime and preventing coke depositions in pores.

Cutaneous melanoma accounts for a yearly mortality rate of 55,500 persons. The use of oral small-molecule kinase inhibitors, specifically targeting BRAFv600, has been licensed as the principal treatment strategy for managing both locally progressed and metastatic presentations of the condition. Approximately 30% of people on vemurafenib, a BRAFv600 inhibitor, have side effects when are taken orally. Objective: This research was attempted to develop a vemurafenib microemulsion by substituting conventional oil phases with ionic liquids (ILs). The microemulsions were created by dissolving vemurafenib in a combination of ionic liquid (1-Butyl-3-methylimidazolium hexafluorophosphate and 1-Octyl-3-methylimidazolium hexafluorophosphate) and surfactant (Triton x-100). Multiple tests were conducted to measure physical stability, pH determination, content homogeneity examination, and in vitro medicine release analysis. Four formulations of Vemurafenib microemulsions successfully met all criteria in the microemulsion characterisation and assessment tests. The droplet sizes in these microemulsions fell inside the range of microemulsions, which is less than 200 nm. They were then used to create microemulsion-based hydrogels, employing Carbamer 340 as a gelling agent by conducting a simple mixing method. Hydrogels formed from microemulsions containing 1-Octyl-3-methylimidazolium hexafluorophosphate demonstrated the ability to form clear hydrogels with desirable consistency. Regarding Ex-vivo permeability study and skin deposition the permeability profiles of GOT3 formula exhibits a permeability measurement of 33569± 344 mP.s at 6 rpm, whereas GOT4 demonstrates a permeability measurement of 54723± 380 mP.s at 6 rpm. During the skin irritation test, there was no apparent erythema and edema were observed when compared to the negative group. This may indicate that the designed microemulsion-based gel formulation demonstrates good biocompatibility with skin tissue. Topical delivery of vemurafenib is a promising route of drug administration to melanoma skin. Ionic liquids (ILs) have permeation-enhancing properties with either hydrophilic or lipophilic characteristics‎‎‎‎‎.

Software-Defined Networking (SDN) offers a centralized network management approach that can effectively address the complex and varied traffic demands characteristic of Industrial Internet of Things (IIoT) environments by decoupling the control plane from the data plane. The centralized control architecture of SDN necessitates the performance optimization of controllers to manage diverse traffic efficiently within IIoT applications. This paper explores the criteria for selecting controllers in SDN-enabled IIoT (SD-IIoT) environments, utilizing the Less Complex Analytic Network Process (LC-ANP) to establish their prioritization. A ranking system for SD-IIoT controllers is formulated using LC-ANP, and experimental validation of this method underscores its effectiveness in optimizing controller performance. The proposed approach enhances the overall efficiency of SDN-enabled IIoT networks, as evidenced by experimental evaluations measuring delay, throughput, packet loss ratio (PLR), and jitter across five different topologies with varying nodes and edges. The experiments indicate an overall increase in the average throughput, and a decrease in delay, jitter, and PLR. The results also show that the suggested strategy and proposed controller surpass the benchmark controller in complex network topologies. These results confirm the method’s capacity to significantly improve network performance in SD-IIoT applications.

Background: Atrial fibrillation (AF) stands as the most prevalent cardiac arrhythmia, with associated risks of stroke and systemic thromboembolism. While vitamin K antagonists, specifically warfarin, have historically been the mainstay for stroke prevention in AF, they come with inherent limitations. Aim: This review seeks to offer a comprehensive analysis of the efficacy, safety, and clinical advantages of novel oral anticoagulants (NOACs) compared to traditional warfarin in AF management. Method: A meticulous examination of pivotal clinical trials, meta-analyses, and recent research publications was conducted. Four NOACs, namely Dabigatran, Rivaroxaban, Apixaban, and Edoxaban, were compared against warfarin, focusing on parameters like stroke prevention, risk of bleeding, patient compliance, and drug interactions. Results: NOACs, as a collective group, demonstrated a comparable or superior efficacy profile in stroke prevention compared to warfarin. They also showcased a more predictable therapeutic range, fewer drug and food interactions, and, in certain cases, a better safety profile. The challenges associated with frequent monitoring and dose adjustments inherent to warfarin therapy were notably absent with NOACs. Conclusion: NOACs present a robust alternative to warfarin for AF management, demonstrating comparable efficacy and, in certain aspects, heightened safety and practicality. However, the choice of anticoagulant should remain individualized, taking into account patient-specific factors and clinician expertise.

Interpreting machine learning models is facilitated by the widely employed locally interpretable model-agnostic explanation (LIME) technique. However, when extending LIME to signal data, its credibility falters due to perturbation techniques used to generate local datasets. These techniques disrupt temporal dependencies among features, leading to unrealistic data points and potentially misleading explanations. Additionally, LIME faces instability and local fidelity issues, limiting its suitability for real-world applications. The absence of a dedicated LIME package tailored for interpreting signal data further diminishes comprehensibility, especially when applied to models trained on such data. In this paper, we introduce Signal-based LIME (Sig-LIME) to address these limitations. Sig-LIME leverages a novel data generation technique that captures temporal dependence among features, enhancing credibility and stability. It combines a random forest model and heatmaps to provide illuminating explanations for predictions drawn from electrocardiogram (ECG) signals, improving model transparency. Empirical findings underscore the enhanced interpretability and comprehension of model predictions attained by Sig-LIME compared to baseline LIME. Our quantitative evaluation based on an analysis of variance (ANOVA) framework, reveals a notable improvement in stability with Sig-LIME, evidenced by an f-statistic of 0.0 and p-values of 1, indicating a complete absence of variation between multiple runs. Regarding local fidelity, Sig-LIME surpasses the baseline LIME, exhibiting a lower average Euclidean distance of 0.49 compared to 17.24. Sig-LIME excels in generating data more akin to the original, achieving remarkable stability and significantly enhancing credibility and local fidelity in the explanations it generates.

Predictive maintenance has gained importance across various industries, including the automotive sector. It is very challenging to detect vehicle failures in advance due to the intricate composition of various components and sensors. The vehicle’s reliability is of utmost importance for ensuring the absence of fatalities or malfunctions to foster economic development. This study introduces an innovative method for developing a predictive framework for vehicle engines with faster and higher decision accuracy. The framework is specifically designed to recognize patterns and abnormalities that may suggest prospective engine problems in real-time and allow proactive maintenance. We assessed the performance of the developed vehicular engine health monitoring systems using a deep learning model based on essential measures like root mean square error, root mean square deviation, mean absolute error, accuracy, confusion matrix, and area under the curve. In this case, the deep learning models are developed by following ensemble techniques using the most prominently used machine learning techniques. Significantly, Stacked Model 1 outperformed other stacked models (Models 2 and 3) and achieved an impressive AUC value of 0.9702 with a low root mean square error (RMSE) of 0.3355, a high accuracy rate of 0.9470, and a precision of 0.9486. It happens due to the effective incorporation of different approaches into Stacked Model 1, which signifies a significant advancement in predicting vehicular engine failures. The model can be used in real-time monitoring systems to continuously monitor the health of vehicular engines and provide early warnings of potential failures, thereby reducing maintenance costs and improving safety.

Waste management has been identified as a critical problem underpinning the vision of sustainable cities. Despite existing efforts to tackle this challenge, traditional approaches still undermine resource allocation and utilization for the task. Most methods have overlooked the fairness problem found in the garbage-collection transportation units, producing noticeable varying active time differences among the participating units. The integration of Internet of Things (IoT) to waste management has recently been an emerging trend, which offers coordinated garbage collection benefiting from IoT networks. This work investigates utilization of LoRa technology for such a purpose and argues the importance of fairness perspective in actuating the truck agents for collecting the wastes in a given region. Through enabling reliable waste data exchange by a proper design and specification of the LoRa network, we can then cast the collection issue as a capacitated vehicle routing problem with a well-formulated objective function. To improve the fairness in the waste management, we propose an objective function that incorporates both the total distance covered by all the trucks and overall distance dispersion from individual trucks. Numerical simulation demonstrates the superiority and consistency of the fairness-based optimum solution in both minimizing the total distance and achieving the fairness.

Jemmal Mohammed,1 Sahilu Assegid,2 Lata Fekadu,2 Teshome Kabeta2 1Department of Ophthalmology, Faculty of Medical Science, Institute of Health, Jimma University, Jimma, Ethiopia; 2Department of Epidemiology, Faculty of Public Health, Institute of Health, Jimma University, Jimma, EthiopiaCorrespondence: Lata Fekadu, Jimma University, Institute of Health, Faculty of Public Health, Department of Epidemiology, PO Box 378, Jimma, Ethiopia, Tel +251911924107, Email latafekadu@gmail.comBackground: Cataract is the leading cause of blindness and the second leading cause of visual impairment worldwide, accounting for 51% and 33% of all cases, respectively, in low- and medium-income countries bearing a disproportionately high burden. Hence, this study aimed to assess the visual outcome of age-related cataract surgery and identify factors associated with patients’ postoperative visual outcomes in Jimma University Medical Center, Southwest Ethiopia.Methods: An institution-based cross-sectional study design was conducted among 386 cataract surgery patients from January 1, 2016, to December 30, 2017. The study participants were selected using a systematic random sampling technique. Data were collected by reviewing the selected patients’ medical records using a pre-tested checklist, entered into EpiData version 3.1, and exported to SPSS 20 for analysis. Proportions, summary statistics, and tables were used for presentations of the findings. Binary logistic regression was carried out to identify independent predictors of visual outcome. Findings were presented with adjusted odds ratios and their 95% confidence interval. A p-value < 0.05 was used to declare a statistically significant association.Results: About 231 individuals (59.8%) had poor visual results following cataract surgery. Furthermore, age > 70 (AOR = 3.64; 95% CI [1.35– 9.82]), preoperative ocular co-morbidities (AOR = 2.34; [1.32– 4.15]), incision-based cataract surgery (AOR = 7.11; [3.16– 16.02]), compared phacoemulsification operated by resident surgeons (AOR = 2.19; [1.23– 3.89]), presence of intraoperative complication (AOR = 3.41; [1.47– 7.92]), lens remnant (AOR = 2.91; [1.11– 4.92]), ocular inflammation (OR = 2.56; [1.34– 4.92]), and striate keratopathy/corneal edema (AOR = 1.91; [1.07– 3.44]) were significantly associated with poor visual outcome.Conclusion: The visual outcome following cataract surgery fall below WHO recommendation. In this study, age, ocular co-morbidities, surgical method, surgeon status, intraoperative complication, SK, and ocular inflammation associated with post-operative Uveitis and anterior chamber reaction were associated with a poor visual outcome.Keywords: cataract surgery, visual outcome, Jimma University Medical Center

Abstract Misfolded α-synuclein (α-syn) is believed to contribute to neurodegeneration in Lewy body disease (LBD) based on considerable evidence including a gene-dosage effect observed in relation to point mutations and multiplication of SNCA in familial Parkinson’s disease. A contradictory concept proposes early loss of the physiological α-syn as the major driver of neurodegeneration. There is a paucity of data on SNCA transcripts in various α-syn immunoreactive cytopathologies. Here, the total cell body, nuclear, and cytoplasmic area density of SNCA transcripts in neurons without and with various α-syn immunoreactive cytopathologies in the substantia nigra and amygdala in autopsy cases of LBD (n = 5) were evaluated using RNAscope combined with immunofluorescence for disease-associated α-syn. Single-nucleus RNA sequencing was performed to elucidate cell-type specific SNCA expression in non-diseased frontal cortex (n = 3). SNCA transcripts were observed in the neuronal nucleus and cytoplasm in neurons without α-syn, those containing punctate α-syn immunoreactivity, irregular-shaped compact inclusion, and brainstem-type and cortical-type LBs. However, SNCA transcripts were only rarely found in the α-syn immunoreactive LB areas. The total cell body SNCA transcript area densities in neurons with punctate α-syn immunoreactivity were preserved but were significantly reduced in neurons with compact α-syn inclusions both in the substantia nigra and amygdala. This reduction was also observed in the cytoplasm but not in the nucleus. Only single SNCA transcripts were detected in astrocytes with or without disease-associated α-syn immunoreactivity in the amygdala. Single-nucleus RNA sequencing revealed that excitatory and inhibitory neurons, oligodendrocyte progenitor cells, oligodendrocytes, and homeostatic microglia expressed SNCA transcripts, while expression was largely absent in astrocytes and microglia. The preserved cellular SNCA expression in the more abundant non-Lewy body type α-syn cytopathologies might provide a pool for local protein production that can aggregate and serve as a seed for misfolded α-syn. Successful segregation of disease-associated α-syn is associated with the exhaustion of SNCA production in the terminal cytopathology, the Lewy body. Our observations inform therapy development focusing on targeting SNCA transcription in LBD.

The solar air heater has a low heat transfer coefficient due to the development of a laminar sublayer inside the channel of the solar collector. Adding artificial roughness or ribs to the surface of the wall of the absorber plate is an effective and promising method to increase heat transfer by interrupting the laminar sublayer. In this study, a trapezoidal rib was used to enhance the thermal performance of the solar air heater. The characteristics of flow and heat transfer were numerically analyzed using a RNG k-ɛ turbulent model based on the Reynolds number range of 5000, 10000, 15000, 20000, 25000, and 30000. Eight different types of trapezoidal ribs, arranged in shapes that increase in height towards or against the direction of flow, were studied. Four case studies included a solar collector with attached trapezoidal ribs, while another four case studies included a solar collector with detached trapezoidal ribs. The current research involved validation of the results compared to the previously obtained results and showed good acceptable agreement. The results demonstrated that the best thermal performance ratio of the solar collector was achieved when the ribs were attached and detached to the inner surface of a wall, with an increase in the height of the trapezoidal ribs in the opposite direction of the airflow for all ribs. However, these cases resulted in the highest coefficient of friction ratio. On the other hand, the thermal performance was at its lowest level in the cases where the increase in the height of the attached or detached trapezoidal ribs is in the direction of the airflow.

Ventilation Air Methane (VAM) significantly contributes to global warming. Capturing and mitigating these emissions can help combat climate change. One effective method is the thermal decomposition of methane, but it requires careful control to prevent explosions from the high temperatures involved. This research investigates the influence of methane concentration and coal dust particle properties on the minimum ignition energy (MIE) required for fugitive methane thermal decomposition and flame propagation properties. This knowledge is crucial for the mining industry to effectively prevent and mitigate accidental fires and explosions in VAM abatement plants. Coal dust samples from three different sources were selected for this study. Experiments were conducted using a modified Hartmann glass tube and a Thermal Gravimetric Analyser (TGA). The chemical properties of coal dust were determined through ultimate and proximate analysis. The particle size distribution was determined using a Mastersizer 3000 apparatus (manufactured by Malvern Panalytical, Malvern, UK). The results showed that the MIE is significantly affected by coal dust particle size, with smaller particles (3. In contrast, small amounts of coal dust had little impact on MIE variation. Moreover, the presence of methane during combustion increased the upward flame travel distance and propagation velocity. The flame’s vertical travel distance increased from 124 mm to 300 mm for a coal dust concentration of 300 g·m−3 blended with 1% and 2.5% methane, respectively.

The Dictionary of Countries is considered one of the most important ‌works and sources that many researchers relied on with everything that ‌includes the science of geography to know the names of countries and ‌places and see them more accurately, especially this dictionary has become ‌an important source for other types of science, the political situation in the ‌Islamic Maghreb emerged for the leaders of the conquest as the state faced ‌Arab and Islamic obstacles to the conquest of the countries of the Islamic ‌Maghreb, which clarified several things for this stage, including the radical ‌change of Morocco from transforming the people of that country into an ‌Islamic society liberated from slavery that was controlled by the Romans ‌and the Franks, and the establishment of a military force that would be a ‌defensive and fortified center for them from the enemies. The first steps of ‌Muslims to conquer the Maghreb.

BackgroundThis study aims to evaluate real-world (rw) outcomes of immunotherapy (IO) for advanced stage NSCLC at King Hussein Cancer Center (KHCC) in Jordan.MethodsAdvanced stage NSCLC patients who received IO at KHCC between 2017 and 2022 were included. The data were retrospectively collected. PFS and OS were estimated for patients with ECOG performance status (ECOG PS) 0-1. Cox regression analyzed predictors of OS in first-line (1L) IO, regardless of performance status.ResultsThe total number of patients included was 244. Out of those, 160 (65%), 67 (28%), and 17 (7%) patients received IO as 1L, second-line (2L), or third-line or beyond (3L or beyond), respectively. The median age for all patients was 59 years. Male were 88%, and 77% were smokers. The median follow-up time was 12.5 months. The median PFS and OS for 1L IO were 7 [95% CI 5.8 – 10.3] and 11.8 [95% CI 8.8 – 14.4], months, respectively. In the first 3 months after starting 1L IO, 34/160 (21%) patients had died. For those who survived beyond 3 months after starting 1L IO, the median PFS and OS were 11.3 [95% CI 8.3 – 16.5] and 15.4 [95% CI 13.2 – 21] months, respectively. In the Cox regression model of 1L IO patients with any performance status, ECOG PS 2 was predictive of worse OS compared to ECOG PS 0-1 (p= 0.005).ConclusionThis real-world study of advanced-stage NSCLC patients treated with immunotherapy at KHCC reveals outcomes that fall short of those anticipated from clinical trials. The inclusion of Middle Eastern patients in lung cancer trials is essential to ensure adequate representation of various ethnicities in clinical research.

The study aimed to find out the effect of molecular substitution of some vegetable sources, namely oatmeal and chia, instead of animal fat, on the manufacture and preservation of low-fat burger patties stored by freezing at a temperature of (-18 ± 2 C) during the storage period for a period of (60) days and follow-up of their characteristics during the storage period by (1, 30, 60) days during which the chemical characteristics were monitored, which included (pH, peroxide number, and percentage of free fatty acids), as well as follow-up on the qualitative characteristics, and compared the factory burger with the commercial one Available in the markets. The burger was made from 80% lean veal and 20% beef fat, which is the standard treatment. The fat was replaced with 50% oatmeal and 50% chia powder for the manufacture of the beef burger. It was also observed a significant decrease in the peroxide values and the percentage of free fatty acids for the replacement treatments compared to the control treatment and the commercial Berger treatment. The results indicated that the percentage of water retention ability, cooking yield, and the percentage of weight loss during cooking increased in the replacement treatments compared to the control treatment. The results also showed a clear and remarkable improvement for all the technological characteristics under study. Therefore, the study recommends the use of oatmeal and chia powder as a substitute for animal fats in the manufacture of burgers.

This paper presents a numerical investigation of the performance of a rectangular storage solar collector with three different absorber plate shapes: smooth, parabolic, and triangular. The research employs three-dimensional, unsteady modeling using COMSOL software version 5.5 to simulate a solar storage collector system in Kufa-Najaf's climatic conditions. Two days in November and July were selected to evaluate the system's performance under various atmospheric conditions. The results showed that the highest water temperature for a no-load condition was 36.2 °C in November and 51.7 °C in July. For a triangular corrugation absorber storage collector under load, the largest temperature difference between the outflow and inflow temperatures was 14.9 °C at 1 p.m. and 11.9 °C at sunset in November, while the maximum temperature difference was 13.4 °C at 4 p.m. in July. The study also found that the total efficiency of the triangular corrugation absorber storage collector was higher than that of the other designs, and generally, the total efficiency under no-load conditions was lower than the load. The present work offers a novel solar storage collector configuration with a parabolic or triangular roughened integrated plate absorber, which enhances heat transfer, promoting energy efficiency and improving outlet water temperature.

Abstract This study focused on developing a new cocktail extraction agent (CEA) composed of solvent and a new surfactant material (SM) for enhancing the efficiency of fuel recovery from real waste oil sludge (WSO). The effects of different solvents (e.g. methyl ethyl ketone (MEK), naphtha, petrol and kerosene), SMs (Dowfax and sodium thiosulfate), extraction time (10–20 min), extraction temperatures (20–60 °C) and CEA/sludge ratios (1–4) on the extraction performance were investigated. SMs and DBBE design enhanced the extraction efficiency by increasing the dispersion of solvent in WSO and enhancing the mixing and mass transfer rates. Results proved that Dowfax was the best SM for oil recovery under various conditions. The best CEA (e.g. MEK and Dowfax) provides the maximum fuel recovery rate of 97% at a period of 20 min, temperature of 60 °C and 4:1 CEA/sludge ratio. The produced fuel was analysed and fed to the distillation process to produce diesel oil. The characteristics of diesel oil were measured, and findings showed that it needs treatment processes prior its use as a finished fuel.

As cancer-related deaths continue to rise, developments in nanotechnology have emerged as a feasible option for finding successful treatments targeting cancerous cells while avoiding all of the drawbacks of traditional drugs. Selenium nanoparticles (SeNPs) have been reported to exhibit an inhibitory effect on cancerous cells. The aim of the present study was to use the drug delivery systems poly(lactic-co-glycolic acid) (PLGA) and poly(lactic-co-glycolic acid-poly(ethylene glycol)-folic acid (PLGA-PEG-FA) to encapsulate SeNPs and investigate their antineoplastic effects against two cell line types (MCF-7 as a positive folate receptor and HBL as a negative folate receptor) by exploiting overexpression features in some types of cancer cells to ensure delivery of drug molecules at high dosages toward targeted cells and circumvent normal cells/tissues. SeNPs were chemically synthesized and characterized with dynamic light scattering (DLS) and transmission electronic microscopy (TEM). The cytotoxicity of both nanomaterials was evaluated against MCF-7 and HBL cells by using the methyl thiazolyl tetrazolium (MTT) assay which showed a high cytotoxic effect against MCF-7 cells with a lesser effect against HBL cells. Additionally, an apoptosis assay was also performed by using acridine orange/ethidium bromide dual staining, and the antioxidant effect was also investigated by using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) colorimetric method with high antioxidant potential for both formulations. They showed nonhemolytic activity on human red blood cells. This work could be considered promising for pharmaceutical formulation.

Alzheimer’s disease (AD) is a neurological disorder characterized by mental and behavioral changes that develop progressively with a decline in brain function. Dysfunctions in glutamatergic and cholinergic pathways, along with an increased concentration of beta-amyloid protein (Aβ), lead to synapses that are full of phosphorylated protein. These changes result in several pathological, biochemical, cellular, and molecular alterations that increase neural excitation directly or indirectly at the neural level, affecting the synapse, axons, signal transmission, and all parts of neurons. All these alterations, with continuous excitatory effects, eventually lead to neural loss and degradation due to stimulation of the immune response. However, memantine is a non-competitive antagonist of N-methyl-D-aspartic acid (NMDA) glutamatergic receptors of moderate affinity and voltage-dependent that blocks the effects of pathologically elevated glutamate tonic levels, which can lead to neuronal dysfunction. Memantine has shown improvement in cognition, global clinical status, activities of daily living, and behavioral disturbances in moderate and severe AD. In this review, we will discuss the effects of memantine use and side effects, as well as its application in treating other diseases or pathological conditions with the prospective use of memantine or an alternative. Memantine is generally well-tolerated, and the most common adverse reactions are vertigo, headache, and hallucinations, which are usually mild.

Polymeric composites with boron nitride nanosheets (BNNs), which are thermally conductive yet electrically insulating, have been pursued for a variety of technological applications, especially those for thermal management in electronic devices and systems. Highlighted in this review are recent advances in the effort to improve in-plane thermal transport performance in polymer/BNNs composites and also the growing research activities aimed at composites of enhanced cross-plane or isotropic thermal conductivity, for which various filler alignment strategies during composite fabrication have been explored. Also highlighted and discussed are some significant challenges and major opportunities for further advances in the development of thermally conductive composite materials and their mechanistic understandings.

Graham and Pollack in 1971 presented applications of eigenvalues of the distance matrix in addressing problems in data communication systems. Spectral graph theory employs tools from linear algebra to retrieve the properties of a graph from the spectrum of graph-theoretic matrices. The study of graphs with “few eigenvalues” is a contemporary problem in spectral graph theory. This paper studies graphs with few distinct distance eigenvalues. After mentioning the classification of graphs with one and two distinct distance eigenvalues, we mainly focus on graphs with three distinct distance eigenvalues. Characterizing graphs with three distinct distance eigenvalues is “highly” non-trivial. In this paper, we classify all trees whose distance matrix has precisely three distinct eigenvalues. Our proof is different from earlier existing proof of the result as our proof is extendable to other similar families such as unicyclic and bicyclic graphs. The main tools which we employ include interlacing and equitable partitions. We also list all the connected graphs on ν ≤ 6 vertices and compute their distance spectra. Importantly, all these graphs on ν ≤ 6 vertices are determined from their distance spectra. We deliver a distance cospectral pair of order 7, thus making it a distance cospectral pair of the smallest order. This paper is concluded with some future directions.

In this work, the performance of coded continuous phase modulation (CPM) transceivers for orthogonal frequency-division multiplexing (OFDM) in underwater acoustic channels is evaluated. The proposed technique employs the Bose–Chaudhuri–Hocquenghem (BCH) class of cyclic codes, and a CPM-based mapper is being used in place of a traditional OFDM mapper. Bit-error-rates (BERs) for various distances are evaluated. We use the Bellhop acoustic channel simulator that is considered to be very close to a real underwater channel. The performance of the proposed system is evaluated for 23 values of the CPM modulation index h as a function of the distance between the transmitter (Tx) and receiver (Rx). Based upon the error performance, we identified several best-performing CPM indices. We also observed that for Tx–Rx distances of 100 and 250 m, the proposed system gives acceptable performance without the need for equalization. We also compared the out-of-band radiation of the proposed system with PSK-OFDM and observed that the uncoded CPM-OFDM has a better out-of-band (OOB) performance than the traditional OFDM. Moreover, a comparison of BERs with the traditional PSK-OFDM system shows that the proposed system outperforms the traditional OFDM system by a wide margin.

The measurement of glucose concentration is a fundamental daily care for diabetes patients, and therefore, its detection with accuracy is of prime importance in the field of health care. In this study, the fabrication of an electrochemical sensor for glucose sensing was successfully designed. The electrode material was fabricated using polyaniline and systematically characterized using scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and UV-visible spectroscopy. The polyaniline nanofiber-modified electrode showed excellent detection ability for glucose with a linear range of 10 μM to 1 mM and a detection limit of 10.6 μM. The stability of the same electrode was tested for 7 days. The electrode shows high sensitivity for glucose detection in the presence of interferences. The polyaniline-modified electrode does not affect the presence of interferences and has a low detection limit. It is also cost-effective and does not require complex sample preparation steps. This makes it a potential tool for glucose detection in pharmacy and medical diagnostics.

For a graph G=(VG,EG), a degree-based graphical index GId takes the general form GId=∑xy∈EGϕ(dx,dy), where ϕ is a symmetric map and di is the degree of i∈VG. For α∈R, if ϕ=(dxdy)α (resp. ϕ=(dx+dy)α), the index is called the general product-connectivity Rα (resp. general sum-connectivity SCIα) index. In this paper, by formulating an optimization problem, we determine the value(s) of α, for which the linear/multiple correlation coefficient of Rα and SCIα with physicochemical properties of benzenoid hydrocarbons is the strongest. This, in turn, fills some research gaps left by similar studies in this area.

Claude Berge (1987) introduced the concept of k-extendable graphs, wherein any independent set of size k is inherently a constituent of a maximum independent set within a graph H=(V,E). Graphs possessing the property of being 1-extendable are termedas Berge graphs. This introduction gave rise to the notion of well-covered graphs and well-dominated graphs. A graph is categorized as well-covered if each of its maximal independent sets is, in fact, a maximum independent set. Similarly, a graph attains the classification of well-dominated if every minimal dominating set (DS) within it is a minimum dominating set. In alignment with the concept of k-extendable graphs, the framework of (k,γ)-endowed graphs and symmetric (k,γ)-endowed graphs are established. In these graphs, each DS of size k encompasses a minimum DS of the graph. In this article, a study of γ-endowed dominating sets is initiated. Various results providing a deep insight into γ-endowed dominating sets in graphs such as those characterizing the ones possessing a unique minimum DS are proven. We also introduce and study the symmetric γ-endowed graphs and minimality of dominating sets in them. In addition, we give a solution to an open problem in the literature. which seeks to find a domination-based parameter that has a correlation coefficient of ρ>0.9967 with the total π-electronic energy of lower benzenoid hydrocarbons. We show that the upper dominating number Γ(H) studied in this paper delivers a strong prediction potential.

Malaria is a serious, acute disease spread by female Anopheles mosquito bites. Malaria is an epidemic in the Wolaita Zone, affecting 85% of the population despite the implementation of effective prevention and control measures in the area’s public health services. The main objective of this study is to apply geospatial techniques to environmental, socioeconomic, and epidemiological parameters that increase certain conditions for malaria incidence to identify malaria vulnerability hotspots using a multi-criteria evaluation method. The malaria vulnerability hotspot map is identified by using AHP and the malaria hotspot identification algorithm. The findings show that the research area is 51% very high and highly vulnerable (224.14 km2), 26% moderate (116.560 km2) and 23% low vulnerable (103.600 km2). The western part of the area, which is near the Omo River and has low elevation, is highly vulnerable to malaria incidence. Reliable malaria vulnerability hotspot maps are critical for estimating the scope of the problem and, consequently, the resources required to combat malaria.

Background: Prostate cancer is a disease that occurs in men aged more than 50 years. In Iraq, 8.89 men per 100,000 population suffer from prostate cancer, with the incidence being 14,016 cases and mortality being 6,367 cases. Despite advances in treatment against prostate cancer, it can become resistant to drugs. Therefore, the aim of current study was to search and identify binding sites for the repositioning of drugs by computational methods (docking). Methods: Based on the protein structure of the wild androgen receptor, the analysis parameters (22x22x22 on the X, Y, and Z axes) were established. Results: The interactions of the natural ligands with androgen receptor were 10.0 (testosterone) and 10.8 (dihydrotestosterone) while mutated androgen receptor (T877A) had a low affinity with testosterone and dihydrotestosterone (-5.3 and -6.7, respectively). In the interactions of both receptors with the reported inhibitors (antagonists), a decrease with Bicalutamide (-8.3 and -4.3, respectively) and an increase in affinity with Flutamide and Nilutamide (-7.7 and 8.6, wild AR; -8.7 and -9.3 AR T877A) were observed. As for Enzalutamide and Apalutamide (second-generation antagonists), the change was minimal between wild androgen receptor and T877A (-7.6 and -7.7; -7.3 and -7.3, respectively). The change in the affinity of the ligands with androgen receptor and androgen receptor T877A shows how a mutation alters the bonds between these molecules. Conclusion: The identification of key sites and potent inhibitors against abnormal androgen receptor functions will enrich prostate cancer treatments.

In the face of rapid urbanization in Saudi Arabia, understanding the impact of landscape changes on land surface temperature (LST) is crucial for sustainable urban planning. This study assesses the influence of landscape morphology on LST and predicts future LST changes. A multi-temporal land use and land cover (LULC) analysis using random forest (RF) quantified urban expansion and its ecological impacts. Accuracy assessment using the kappa coefficient illustrated the precision of the classification techniques. Morphological Spatial Pattern Analysis (MSPA), developed in Python, analyzed the structural evolution of urban areas, vegetation and exposed rocks. Polynomial regression models established the relationship between landscape morphology and LST and predicted future temperature trends. Results for Asir show a significant improvement in accuracy of the LULC models over three decades, with overall accuracy increasing from 89.99% in 1990 to 91.72% in 2020. The bootstrapping trend analysis showed an urban expansion with a positive slope of 9.27 and a decline in water bodies with a negative slope of −0.03. The MSPA analysis reflected a significant urban expansion, with the core area growing from 45.19 km2 in 2001 to 230.33 km2 in 2021. The vegetated areas showed resilience and dynamic connectivity despite slight reduction and fragmentation. The polynomial regression predicted an increase in future average LST by 2030, with urban core areas reaching 58.47 °C, vegetated cores 42.19 °C and exposed rock cores 55.79 °C. These results highlight the link between urban expansion and LST rise and make the case for integrating green infrastructure and cooling strategies into urban development.

Background. People who are addicted to amphetamines have a much greater chance of developing psychosis compared to those who are not. It is essential to study the behavioral and psychological effects of amphetamines. Therefore, this research aimed to examine conditions such as depression, anxiety, mood, cognitive abilities at the workplace, and social responsibilities by using sociodemographic factors as useful tools in determining effective strategies for preventing, managing, and treating amphetamine addiction. Methods. A cross-sectional study among addicts hospitalized at two rehabilitation centers across Saudi Arabia between May and October 2023. A validated questionnaire consisting of psychiatric disorders assessment tools was distributed to healthcare professionals to start an interview with addicts to assess the abnormalities. The results were compared with healthy people (control). The assessment tools used are Hamilton Anxiety and Depression Rating Scale, Young Mania Rating Scale, and Work and Social Adjustment Scale. The data were analyzed using SPSS version 22.0. Pearson correlation coefficients (r) were employed. Results. A total of 60 subjects participated in this study. The participants were divided into two groups (n = 60): group I was control (n = 25) healthy volunteers and group II was amphetamine abusers (n = 35), who were hospitalized for detoxification. The ages ranged from 18 to 60 years old with mean ages of 38.68 (±8.14) and 37.77 (±10.95) years in the control and amphetamine groups, respectively. Among the addicts, the mean severity dependence scale value was 10.46 (±1.82), which denotes high dependency on the illicit drug. The prevalence of high levels of anxiety, depression, and bipolar disorder was significantly higher among addicts when they were compared to healthy people (control). The assessment of the Work and Social Adjustment Scale (WSAS) reflected a higher impairment that minimized their ability to perform the work requirements, home management, social leisure, and relationships. Conclusions. The addiction to amphetamines was associated with high impairment of work performance and social obligations and a negative impact on the addict’s mental health. The risk of suffering anxiety, depression, and bipolar is higher than in nonaddict people. These effects are attributed to brain damage, neurotoxicity, and neuronal inflammation, particularly when these substances are abused over extended periods and at higher doses.

Language inequities in global health stem from colonial legacies, and global health security is no exception. The International Health Regulations (IHRs), a legally binding framework published by the WHO, lay the foundation for global health security and state the roles and responsibilities States Parties are compelled to follow to improve their capabilities to prevent, detect and respond to potential public health emergencies of international concern. It includes the submission of a mandatory status report that assesses a nation’s implementation of IHRs. Known as the States Party Self-Assessment Annual Report (SPAR) tool, WHO has made its guidance document available in all six WHO official languages (Arabic, Chinese, English, French, Russian and Spanish). The Republic of Iraq (Iraq) experienced significant challenges during the completion and submission of the 2022 SPAR. This experience demonstrated that translation of English materials to other languages, such as Arabic, is not prioritised and further underscored how scoring of a country’s global health security capacities can be significantly impacted by users’ ability to read and comprehend the materials in English. Not only can this lead to inaccurate SPAR scoring, but it can also lead to the improper allocation of resources and prioritisation of policy developments and/or amendments. By drawing attention to this issue, we aim to inform and advocate for global health security decision-makers to consider opportunities for increasing inclusion and accessibility, especially for requirements under legally binding international instruments.

This study was conducted on the creation of the nanopolitan manganese particles and the study of the physiological effect of the nanopolitan magnes.The results or indicators of blood sugar showed the confirmation of low levels of sugar in the group of diabetes treatment by giving oral throughout the experiment period (28 days. In addition to the high percentage of insulin in the affected group and the treatment of Mn-NPs compared to the affected (positive) control group during the study period. The current study aimed to achieve preventive effects against diabetes. It turned out that eating the nanoparticles and within the permissible concentration 2 mg /kg per day reduces blood sugar and contributes to losing weight, as its consumption is related to a decrease in the risk of type 2 diabetes and reduces the level Blood Glucose in Adult Male Rats.

Many organizations around the world have recognized lightweight, long-lasting, cost and environmentally-friendly construction materials as a future necessity. The lightweight concrete is manufactured mainly either by replacing the original aggregate with lightweight aggregate or addition foam production materials to concrete mixtures. These additions lead to a decrease in the lightweight concrete density and change mechanical properties such as compressive strength. Therefore, there is much experimental research has been conducted to add different material types that can improve lightweight concrete compressive strength while maintaining low density. In this review, the effect of various additions such as steel fiber, product waste materials, and nano-materials on the lightweight concrete compressive strength and density have been explained. The various effects of these additive materials on lightweight concrete properties, some additives lead to improving the properties of lightweight concrete, while other materials lead to a decrease in those properties, and this depends on the type and amount of material additive, the method lightweight concrete manufacturing, and their mixture composition.