Threshold-Based Software-Defined Networking(SDN)Solution for Healthcare Systems against Intrusion Attacks

The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.

Mental health status among COVID-19 patients survivors of critical illness in Saudi Arabia:A 6-month follow-up questionnaire study

BACKGROUND Psychological assessment after intensive care unit(ICU)discharge is increasingly used to assess patients'cognitive and psychological well-being.However,few studies have examined those who recovered from coronavirus disease 2019(COVID-19).There is a paucity of data from the Middle East assessing the post-ICU discharge mental health status of patients who had COVID-19.AIM To evaluate anxiety and depression among patients who had severe COVID-19.METHODS This is a prospective single-center follow-up questionnaire-based study of adults who were admitted to the ICU or under ICU consultation for>24 h for COVID-19.Eligible patients were contacted via telephone.The patient’s anxiety and depression six months after ICU discharge were assessed using the Hospital Anxiety and Depression Scale(HADS).The primary outcome was the mean HADS score.The secondary outcomes were risk factors of anxiety and/or depression.RESULTS Patients who were admitted to the ICU because of COVID-19 were screened(n=518).Of these,48 completed the questionnaires.The mean age was 56.3±17.2 years.Thirty patients(62.5%)were male.The main comorbidities were endocrine(n=24,50%)and cardiovascular(n=21,43.8%)diseases.The mean overall HADS score for anxiety and depression at 6 months post-ICU discharge was 11.4(SD±8.5).A HADS score of>7 for anxiety and depression was detected in 15 patients(30%)and 18 patients(36%),respectively.Results from the multivariable ordered logistic regression demonstrated that vasopressor use was associated with the development of anxiety and depression[odds ratio(OR)39.06,95% confidence interval:1.309-1165.8;P<0.05].CONCLUSION Six months after ICU discharge,30% of patients who had COVID-19 demonstrated a HADS score that confirmed anxiety and depression.To compare the psychological status of patients following an ICU admission(with vs without COVID-19),further studies are warranted.

Gut microbiota predicts the diagnosis of ulcerative colitis in Saudi children

BACKGROUND Ulcerative colitis(UC)is an immune-mediated chronic inflammatory condition with a worldwide distribution.Although the etiology of this disease is still unknown,the understanding of the role of the microbiota is becoming increasingly strong.AIM To investigate the predictive power of the gut microbiota for the diagnosis of UC in a cohort of newly diagnosed treatment-naïve Saudi children with UC.METHODS The study population included 20 children with a confirmed diagnosis of UC and 20 healthy controls.Microbial DNA was extracted and sequenced,and shotgun metagenomic analysis was performed for bacteria and bacteriophages.Biostatistics and bioinformatics demonstrated significant dysbiosis in the form of reduced alpha diversity,beta diversity,and significant difference of abundance of taxa between children with UC and control groups.The receiver operating characteristic curve,a probability curve,was used to determine the difference between the UC and control groups.The area under the curve(AUC)represents the degree of separability between the UC group and the control group.The AUC was calculated for all identified bacterial species and for bacterial species identified by the random forest classification algorithm as important potential biomarkers of UC.A similar method of AUC calculation for all bacteriophages and important species was used.RESULTS The median age and range were 14(0.5-21)and 12.9(6.8-16.3)years for children with UC and controls,respectively,and 40%and 35%were male for children with UC and controls,respectively.The AUC for all identified bacterial species was 89.5%.However,when using the bacterial species identified as important by random forest classification algorithm analysis, the accuracy increased to 97.6%. Similarly, the AUC for all theidentified bacteriophages was 87.4%, but this value increased to 94.5% when the important bacteriophagebiomarkers were used.CONCLUSIONThe very high to excellent AUCs of fecal bacterial and viral species suggest the potential use of noninvasivemicrobiota-based tests for the diagnosis of unusual cases of UC in children. In addition, the identification ofimportant bacteria and bacteriophages whose abundance is reduced in children with UC suggests the potential ofpreventive and adjuvant microbial therapy for UC.

Factors That Affect Consumption Patterns and Market Demands for Honey in the Kingdom of Saudi Arabia

Despite the significant annual consumption of honey in Saudi Arabia, information gaps remain with regard to the marketing and market structure of honey along the value chain. This study analyzed the major factors that influenced the consumption, expenditure patterns, and demand of honey in Saudi Arabia. This study forecasted the near-future expected market demands for honey in Saudi Arabia by collecting and analyzing the primary data using questionnaires. A total of 331 respondents from representative regions and large cities were randomly selected and interviewed. The data were analyzed using qualitative and quantitative methods as well as appropriate econometric models. Respondents characterized honey quality using organoleptic words, and these characterizations varied based on the relative significance of perception parameters. Taste, aroma, physical state, and color had aggregated average scores of 4.58, 4.44, 3.54, and 3.28, respectively. In addition to the above parameters, honey source, brand name, and confidence in the producers influenced its perceived quality. The major outlets for honey in Saudi Arabia included producers, specialized honey stores, and auction markets in major cities during the harvesting seasons. Medication, food, and sweetening were the major motivations for buying honey in the Saudi market, with aggregate scores of 4.52, 3.71, and 1.52, respectively. Significant honey price variations were observed within and among different honeys and packaging volumes;this finding might be due to factors such as botanical and geographical origins, package volume size economics (i.e., bulk purchases), honey variety blending, brand names, and producer policies. The average price of locally produced honey was approximately $73 per kg, which is 10 times more than the average price of honey in the US and the EU. The estimated consumption/income elasticity was 0.27. These results suggest that honey is a basic commodity in Saudi Arabia. Based on econometric model forecasts, the Saudi market demand for honey is expected to reach approximately 29,784 tons in 2025.

Structure and Performance of the Retail Outlets of Honey in the Kingdom of Saudi Arabia

The study aimed at analyzing the most important factors affecting the retail marketing of honey in Saudi Arabia. Cross sectional survey was employed using field interview (direct contact) with a random sample of 343 retail outlets represented all its forms and patterns in seven major cities in Saudi Arabia. Measurements like market share, Gini coefficient and Herfindahl Hirschman Index (HHI) were used to estimate the indicators of market structure and its performance. The result showed that the structure of honey retail market is generally closer to pure competition with a small concentration in some areas. Gini coefficients of concentration, as well as the values of the Herfindahl Hirschman Index (HHI) were relatively low for retailers. The average marketing margin was about SAR 6.4/Kg for local honey while the marketing margin of imported honey was about SAR 113/Kg. The high profit margin variation between local and imported honey is due to the high marketing costs, lower supplied quantity and higher demand for local honey. The estimated cost of marketing of onekilogram of honey was about 8 SAR at the retail level. From retailers’ point of view, low quality, lack of marketing services, improper display, high rental property, lack of knowledge and experience of the consumer about properties and quality characteristics honey, high prices and shortage of some varieties of honey in some specific season are the most important problems of honey marketing in the Saudi market. Setting priorities between different brands of honey plays a noticeable role in marketing. Some honey producers and traders were very concerned about unfair competition of honey market through high promotion as a brand based on their long history in the production and supply of high-quality varieties of honey from specific and well-known varieties. Hence, intensive awareness creation effort through training, exhibition, media and advertisement are required to improve the perception of consumers towards the local honey.

Physicians’ Instructions to Patients Regarding Medications in a Saudi University Hospital

Objectives: To estimate the proportion of patients who received instructions regarding their medications’ functions, methods of administration, dosages, adverse effects, drug-drug interactions, as well as to identify the sources of knowledge concerning medications’ instructions. Methods: A cross-sectional study was carried out in King Khalid University Hospital (KKUH) in the out-patient pharmacy in 2013. The data collection method includes personal interview with patients who are randomly selected from adults above 18 years of age. The interview was conducted among patients and any person who attends the consultation. Results: The sample was 274 patients. Patients who received instructions for drugs’ functions 208 (75.9%), method of administration 229 (83.6%), doses of drugs 220 (80.3%), drugs’ adverse effects 47 (17.1%), and drug-drug interactions 41 (15%). Sources of medications’ instructions were physicians (73.6%), pharmacists (42.3%), patient information leaflets (PILs) (40.5%) and family or friends (12.8%). Conclusion: The provided instructions about prescribed medications to patients in KKUH were incomplete that may lead to therapeutic failure.

Tuberculosis: Awareness among Students in a Saudi University

Background: Knowledge plays a vital role in influencing the behavior and practices of individuals. Tuberculosis (TB) is a major public health problem. Our objective is to identify the extent of awareness about TB among King Saud University students, and to compare knowledge about tuberculosis amongst different University tracks. Methods: This study was conducted using a cross-sectional approach including 530 students in three different academic tracks: Health, Scientific, and Humanitarian tracks. For data collection, a structured questionnaire was developed through revision of the literature which contained three different parts;demographic data of subjects, knowledge about TB and attitude toward TB. Results: The established scoring system revealed a poor grade of knowledge at 51.4%. Tuberculosis knowledge was significantly higher amongst the track of Health colleges (46.7% compared with 27.2% for the track of Science and 26% for the track of Humanitarian studies). However, some of the issues were answered fittingly in higher magnitude by the two other non-health tracks;there was no significant difference in gender-specific awareness level (48% for both). Conclusion: Although the Health track has better knowledge in general (46.7%), the level of awareness of Tuberculosis is poor among King Saud University students. Moreover, the level of awareness differs among the three tracks, which are health, humanitarian, and science. The health track showed the highest level of awareness.

Spatial and Temporal Variations of the Particulate Matter in Riyadh City, Saudi Arabia

Mass concentrations of PM10 and PM2.5 for January 2012 up to October 2013 were measured at two sites;a suburban area, Riyadh airport (AP) and an urban area, King Fahd road district (KF) (densely trafficked site). Daily concentrations of both PM10 and PM2.5 measured at these two sites were highly variable. The temporal variation observed either for PM10 or PM2.5 was associated mainly with the dust events. The annual pattern of PM10 and PM2.5 at the AP station shows a significant increase in spring and summer (dusty seasons) where monthly mean concentrations of up to 696 μg·m-3 PM10 were recorded in March. PM10 concentrations during winter months are significantly lower, with 65 μg·m-3 measured in November and 78 μg·m-3 measured in December. January exhibits PM10 concentrations little above 100 μg·m-3. Both PM10 and PM2.5 showed substantial variations at these two monitoring stations during the study period. In the ur-ban station (King Fahd), average annual PM10 varied by up to roughly a factor of two. This variation implies that local emission sources in this site often contribute much (i.e. greater than half) of the PM10 mass on annual average. The variation of monthly (temporal) mean PM10 at KF station showed more or less similar results to the AP station. Higher concentrations were observed during spring and summer (12%, 17% and 13% in Feb., March and April respectively and 17, 15% during June and July). Starting from September and October, PM10 concentrations started to drop to 7% and 8% respectively. The relationships between the mean values of suspended particle concentrations and meteorological variables (relative humidity ambient temperature and wind speed) were analyzed. The results demonstrate that the influence of weather factors upon dust particulates is largely inconclusive. However, At KF station a moderate positive correlation was observed between wind speed and PM.

The Impacts of Building Regulations on the Thermal Performance and Energy Consumption of Residential Buildings in Riyadh City-Saudi Arabia

Riyadh city is the fastest growing city in Saudi Arabia. The rapid urban growth that happened recently in Riyadh was not based on the traditional urban planning principles, which have been established and applied for the city development process. The imported building regulations have created a new urban structures and street patterns. The contemporary urban form in Riyadh city is based mainly on traffic and economic consideration with the neglect of environmental dimensions. This research aims to examine the impacts of building regulations on the thermal performance of residential buildings in Riyadh city, with the ultimate goal of establishing planning guidelines that consider the environmental conditions of the city. The methodology adopted for achieving the aim of this study consists of two phases. First, the literature related to building regulations development in Riyadh, as of 2018, was reviewed. Second, buildings energy simulation was conducted to examine the thermal performance of the typical current status of residential building blocks in Riyadh city, and then several changes to building regulations were made to investigate their impacts on the thermal performance of buildings. The results showed that the impacts of Riyadh building regulations on the thermal performance of residential buildings differ across the evaluated cases. The ratio of building height to street width, urban block street orientation, and building orientation are the main factors affecting thermal performance of buildings within urban block. The study also concludes that adjusting the ratio of building height to the distance between buildings could have a significant impact in reducing cooling loads. This study will help policy makers, planners and designers to investigate the shortcoming in the current building regulations.

Adherence of Community Pharmacies in Riyadh, Saudi Arabia, to Optimal Conditions for Keeping and Selling Good-Quality Medicines

Exposure to excessive temperature during distribution or storage has unfavorable consequences on the quality of medicines, particularly in hot climates. This could be one of the possible reasons behind the existence of substandard amoxicillin in community pharmacies in Riyadh, Saudi Arabia. This study explored the conditions under which medicines were kept in a random sample of 181 community pharmacies in Riyadh. The pharmacist in charge in each pharmacy was interviewed and our observations about the quality of storage were recorded. The inspection revealed that in 9% of the sample the readings of the existing room thermometers were >25℃, and that 13% of the sample lacked thermometers. Also in 33% of the sample the readings of the refrigerator thermometers were outside the accepted range, and 7% of the sample lacked refrigerator thermometers. About 15% of pharmacists were not informed about the local regulations of community pharmacy practice, neither before nor after taking up their current positions. Surprisingly, incorrect answers to simple questions about the system were frequently given by the informed pharmacists. Certain aspects of substandard storage conditions existed, in varying degrees, in significant percentages of pharmacies regardless of the pharmacists’ qualifications, experience, or awareness about the local regulations of community pharmacy practice. Stricter monitoring by the authorities regarding the adherence of community pharmacies to optimal conditions of storing medicines is recommended. Continuing education of community pharmacists must also be improved.

Gut microbiota predicts the diagnosis of celiac disease in Saudi children

BACKGROUND Celiac disease(CeD)is a multisystem immune-mediated multifactorial condition strongly associated with the intestinal microbiota.AIM To evaluate the predictive power of the gut microbiota in the diagnosis of CeD and to search for important taxa that may help to distinguish CeD patients from controls.METHODS Microbial DNA from bacteria,viruses,and fungi,was isolated from mucosal and fecal samples of 40 children with CeD and 39 controls.All samples were sequenced using the HiSeq platform,the data were analyzed,and abundance and diversities were assessed.For this analysis,the predictive power of the microbiota was evaluated by calculating the area under the curve(AUC)using data for the entire microbiome.The Kruskal-Wallis test was used to evaluate the significance of the difference between AUCs.The Boruta logarithm,a wrapper built around the random forest classification algorithm,was used to identify important bacterial biomarkers for CeD.RESULTS In fecal samples,AUCs for bacterial,viral,and fungal microbiota were 52%,58%,and 67.7%respectively,suggesting weak performance in predicting CeD.However,the combination of fecal bacteria and viruses showed a higher AUC of 81.8%,indicating stronger predictive power in the diagnosis of CeD.In mucosal samples,AUCs for bacterial,viral,and fungal microbiota were 81.2%,58.6%,and 35%,respectively,indicating that mucosal bacteria alone had the highest predictive power.Two bacteria,Bacteroides intestinalis and Burkholderiales bacterium 1-1-47,in fecal samples and one virus,Human_endogenous_retrovirus_K,in mucosal samples are predicted to be“important”biomarkers,differentiating celiac from nonceliac disease groups.Bacteroides intestinalis is known to degrade complex arabinoxylans and xylan which have a protective role in the intestinal mucosa.Similarly,several Burkholderiales species have been reported to produce peptidases that hydrolyze gluten peptides,with the potential to reduce the gluten content of food.Finally,a role for Human_endogenous_retrovirus_K in immune-mediated disease such as CeD has been reported.CONCLUSION The excellent predictive power of the combination of the fecal bacterial and viral microbiota with mucosal bacteria alone indicates a potential role in the diagnosis of difficult cases of CeD.Bacteroides intestinalis and Burkholderiales bacterium 1-1-47,which were found to be deficient in CeD,have a potential protective role in the development of prophylactic modalities.Further studies on the role of the microbiota in general and Human_endogenous_retrovirus_K in particular are needed.

Choroidal thickness measurements in young Saudi adult population: a cross-sectional study

AIM:To determine the choroidal thickness(CT)in young healthy Saudi adults using spectral-domain optical coherence tomography(SD-OCT)with an automated CT segmentation software.METHODS:Fifty-eight young adults(total of 116 eyes),39 males and 19 females participated in this study between the ages of 18 and 38y(mean 22.65±3.9y).All participants underwent ophthalmic screening examination,including the SD-OCT for measurements of CT in each quadrant egmented into five eccentric regions starting from the foveal region up to 4.5 mm towards the periphery.RESULTS:The choroid was thickest in the foveal region(central 1 mm,300±60μm)and began to progressively thinner beyond the parafovea(1.5–2.5 mm,284±67μm)towards the peripheral region(3.5–4.5 mm from the fovea,254±83μm).The superior choroid showed the thickest profile(309±57μm),while the nasal choroid exhibited the thinnest(229±76μm).The rate of the thinning with increasing eccentricity was more predominant in the nasal choroid,which thinned from the foveal region(294±58μm)to the peripheral region(158±55μm).The superior and inferior choroid did not show a statistically significant thinning with eccentricity(all P>0.05).There was no statistically significant difference in the CT between gender,age,and laterality of the eyes(all P>0.05).A significant association of myopia with thinner subfoveal choroid was observed(Pearson’s,r=0.37),and regression analysis showed that a 10.3μm choroidal thinning for each diopter increase of myopia.CONCLUSION:CT profile depends on eccentric and the quadrant.The CT profile across the measured area in the young Saudi adult population is comparable to other previous reports.Refractive error is critical for CT evaluation.

Perspectives and clinical practices of optometrists in Saudi Arabia concerning myopia in children

AIM:To investigate the practice patterns of optometrists in Saudi Arabia regarding myopia management.METHODS:An internet-based survey was distributed to all practicing optometrists in Saudi Arabia(n=1886).The survey contained questions related to 1)demographics,2)knowledge about myopia and its associated complications,3)current clinical care,4)type and frequency of myopia treatment prescribed,and 5)potential barriers limiting treatment adoption.RESULTS:The completed surveys were collected from 171 optometrists(9.06%response rate,60%male).Knowledge regarding myopia-associated complications was prevalent but somewhat inaccurate among the respondents.Cycloplegic refraction at initial visit was used by 59%of the respondents.The cover test was the most reported binocular vision test(83%),and 38%of optometrists did not perform any ocular biometrics.Twothirds prescribed single-vision spectacles for children with myopia.Increased time spent outdoors was selected by 80%of the practitioners who prescribed myopia control treatment as the primary approach.Insufficient support and lack of clinical experience in providing myopia treatment were reported as the most important factors limiting the adoption of myopia management strategies.CONCLUSION:The current optometric practices in Saudi Arabia require further investigation.Optometrists appear to be somewhat aware of myopia and the associated risks.However,most evidence-based myopia treatments are not being locally adopted,primarily because of lack of support,lack of experience,and limited availability.

Business Blockchain Suitability Determinants: Decision-Making through an Intuitionistic Fuzzy Method

Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency.The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems,as well as the possibility to create new business models which can increase a firm’s competitiveness.Due to the novelty of the technology,whereby many companies are still exploring potential use cases,and considering the complexity of blockchain technology,which may require huge changes to a company’s existing systems and processes,it is important for companies to carefully evaluate suitable use cases and determine if blockchain technology is the best solution for their specific needs.This research aims to provide an evaluation framework that determines the important dimensions of blockchain suitability assessment by identifying the key determinants of suitable use cases in a business context.In this paper,a novel approach that utilizes both qualitative(Delphi method)and quantitative(fuzzy set theory)methods has been proposed to objectively account for the uncertainty associated with data collection and the vagueness of subjective judgments.This work started by scanning available literature to identify major suitability dimensions and collected a range of criteria,indicators,and factors that had been previously identified for related purposes.Expert opinions were then gathered using a questionnaire to rank the importance and relevance of these elements to suitability decisions.Subsequently,the data were analyzed and we proceeded to integrate multi-criteria group decision-making(MCGDM)and intuitionistic fuzzy set(IFS)theory.The findings demonstrated a high level of agreement among experts,with the model being extremely sensitive to variances in expert assessments.Furthermore,the results helped to refine and select the most relevant suitability determinants under three important dimensions:functional suitability of the use case,organizational applicability,and ecosystem readiness.

GA-Stacking:A New Stacking-Based Ensemble Learning Method to Forecast the COVID-19 Outbreak

As a result of the increased number of COVID-19 cases,Ensemble Machine Learning(EML)would be an effective tool for combatting this pandemic outbreak.An ensemble of classifiers can improve the performance of single machine learning(ML)classifiers,especially stacking-based ensemble learning.Stacking utilizes heterogeneous-base learners trained in parallel and combines their predictions using a meta-model to determine the final prediction results.However,building an ensemble often causes the model performance to decrease due to the increasing number of learners that are not being properly selected.Therefore,the goal of this paper is to develop and evaluate a generic,data-independent predictive method using stacked-based ensemble learning(GA-Stacking)optimized by aGenetic Algorithm(GA)for outbreak prediction and health decision aided processes.GA-Stacking utilizes five well-known classifiers,including Decision Tree(DT),Random Forest(RF),RIGID regression,Least Absolute Shrinkage and Selection Operator(LASSO),and eXtreme Gradient Boosting(XGBoost),at its first level.It also introduces GA to identify comparisons to forecast the number,combination,and trust of these base classifiers based on theMean Squared Error(MSE)as a fitness function.At the second level of the stacked ensemblemodel,a Linear Regression(LR)classifier is used to produce the final prediction.The performance of the model was evaluated using a publicly available dataset from the Center for Systems Science and Engineering,Johns Hopkins University,which consisted of 10,722 data samples.The experimental results indicated that the GA-Stacking model achieved outstanding performance with an overall accuracy of 99.99%for the three selected countries.Furthermore,the proposed model achieved good performance when compared with existing baggingbased approaches.The proposed model can be used to predict the pandemic outbreak correctly and may be applied as a generic data-independent model 3946 CMC,2023,vol.74,no.2 to predict the epidemic trend for other countries when comparing preventive and control measures.

Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking

Recent advancements in the Vehicular Ad-hoc Network(VANET)have tremendously addressed road-related challenges.Specifically,Named Data Networking(NDN)in VANET has emerged as a vital technology due to its outstanding features.However,the NDN communication framework fails to address two important issues.The current NDN employs a pull-based content retrieval network,which is inefficient in disseminating crucial content in Vehicular Named Data Networking(VNDN).Additionally,VNDN is vulnerable to illusion attackers due to the administrative-less network of autonomous vehicles.Although various solutions have been proposed for detecting vehicles’behavior,they inadequately addressed the challenges specific to VNDN.To deal with these two issues,we propose a novel push-based crucial content dissemination scheme that extends the scope of VNDN from pullbased content retrieval to a push-based content forwarding mechanism.In addition,we exploitMachine Learning(ML)techniques within VNDN to detect the behavior of vehicles and classify them as attackers or legitimate.We trained and tested our system on the publicly accessible dataset Vehicular Reference Misbehavior(VeReMi).We employed fiveML classification algorithms and constructed the bestmodel for illusion attack detection.Our results indicate that RandomForest(RF)achieved excellent accuracy in detecting all illusion attack types in VeReMi,with an accuracy rate of 100%for type 1 and type 2,96%for type 4 and type 16,and 95%for type 8.Thus,RF can effectively evaluate the behavior of vehicles and identify attacker vehicles with high accuracy.The ultimate goal of our research is to improve content exchange and secureVNDNfromattackers.Thus,ourML-based attack detection and preventionmechanismensures trustworthy content dissemination and prevents attacker vehicles from sharing misleading information in VNDN.

Exploring the nano-fungicidal efficacy of green synthesized magnesium oxide nanoparticles(MgO NPs)on the development,physiology,and infection of carrot(Daucus carota L.)with Alternaria leaf blight(ALB):Molecular docking

In this research,green synthesized magnesium oxide nanoparticles(MgO NPs)from lemon fruit extracts and their fungicidal potential was evaluated against Alternaria dauci infection on carrot(Daucus carota L.)under greenhouse conditions.The scanning and transmission electron microscopy(SEM and TEM)and ultra-violet(UV)visible spectroscopy were used to validate and characterize MgO NPs.The crystalline nature of MgONPs was determined using selected area electron diffraction(SAED).MgO NPs triggered substantial antifungal activity against A.dauci when exposed to 50 and 100 mg L^(–1)concentrations but the higher antifungal potential was noticed in 100 mg L^(–1)under invitro conditions.In fungal inoculated plants,a marked decrease in growth,photosynthetic pigments,and an increase in phenol,proline contents,and defense-related enzymes of carrot were seen over control(distilled water).However,foliar application of MgO NPs at 50 and 100 mg L^(–1)resulted in significant improvement of plant growth,photosynthetic pigments,phenol and proline contents,and defense enzymes activity of carrots with and without A.dauci infection.Spraying of MgO NPs at 100 mg L^(–1)had more plant length(17.11%),shoot dry weight(34.38%),plant fresh weight(20.46%),and root dry weight(49.09%)in carrots when challenged with A.dauci over inoculated control.The leaf blight indices and percent disease severity were also reduced in A.dauci inoculated plants when sprayed with MgO NPs.The non-bonding interactions of Alternaria genus protein with nanoparticles were studied using molecular docking.

SCS-CN and GIS-Based Approach for Estimating Runoff in Western Region of Saudi Arabia

Designing reservoir operations, hydraulic structure, and soil erosion management techniques all require an estimation of a potential runoff. Accurate runoff in-formation is typically scarce in Saudi Arabia—a significant challenge for hydrologists. Wadi-Rahjan catchment in Western Saudi Arabia has been taken as a case study to determine the potential runoff estimates. The study integrates the soil conservation service curve number (SCN-CN) technique, remote sensing (RS), and geographical information system (GIS). Critical parameters including the digital elevation model (DEM), land use/land cover (LULC), hydrologic soil groups (HSGs), and rainfall data were also employed. The curve number (CN), which shows the catchment’s reaction to a storm was estimated based on LULC and HSG layers. The CN map obtained and rainfall data were employed in the GIS-based SCS-CN model to develop the potential runoff map. Based on the results of calculations, the study area is classified into three HSGs, namely, B, C, D. Averagely, CN for a normal condition is 90 while wet and dry conditions are 97 and 80, respectively. Results obtained from the SCS-CN method’s calculations reveal a yearly runoff result that varies from 194 mm to 295 mm. A higher percentage of runoff water (35%) in a runoff range from 289 to 295 mm, followed by 24%, ranged 269 to 288 mm. An interesting rainfall-runoff regression evaluation reveals a good 0.90 correlation. Other watersheds in Saudi Arabia may use this method for planning and development.