穿心莲内酯磺化物抗耐甲氧西林金黄色葡萄球菌及其生物膜的药效及机制

目的探讨穿心莲内酯磺化物(andrographolide sulfonate,AS)抗耐甲氧西林金黄色葡萄球菌(methicillin resistant staphylococcus aureus,MRSA)及其生物膜(biofilm,BF)的药效及机制。方法采用微量肉汤倍比稀释法测定AS对MRSA的最低抑菌浓度(minimum inhibition concentration,MIC);生长曲线法测定不同浓度AS作用MRSA 24小时内的细菌时间—生长曲线;微孔板法测定不同剂量AS给药对成熟MRSA生物膜(MRSA biofilm,MRSA-BF)活菌量的影响;扫描电镜(scanning electron microscope,SEM)观察不同剂量AS对成熟MRSA-BF的形态学变化;通过超高压液相色谱—飞行时间质谱仪法(UPLC-TOF-MS)分析不同剂量AS干预成熟MRSA-BF菌体的内源性代谢物谱特征。结果AS表现出显著的抗MRSA活性,MIC为50 mg/mL;12.5 mg/mL和6.25 mg/mL浓度的AS均可较好地抑制MRSA及其BF的生长,破坏已成熟的膜性结构,且抑制作用呈剂量依赖关系。代谢组学结果提示27个内源性终端代谢物是反映生物膜形成的代谢物,相关的生物通路有苯丙氨酸(phenylalanine,PA)、酪氨酸(tyrosine,Tyr)、色氨酸的生物合成以及牛磺酸和亚牛磺酸代谢;16个内源性终端代谢物是6.25 mg/mL AS干预MRSA-BF的代谢标志物,相关的生物通路为苯丙氨酸、酪氨酸和色氨酸的生物合成;18个内源性终端代谢物是12.5 mg/mL AS干预MRSA-BF的代谢标志物,通路分析未发现相关的生物通路;11个内源性终端代谢物是反映AS干预MRSA-BF的药效代谢标志物,其相关的生物通路包括苯丙氨酸、酪氨酸和色氨酸的生物合成、新生霉素的生物合成以及苯丙氨酸的代谢。结论AS对MRSA及其成熟生物膜均有抑制作用,抑制BF的机制与细菌苯丙氨酸、酪氨酸和色氨酸的生物合成、新生霉素的生物合成以及苯丙氨酸的代谢相关。AS可作为临床治疗MRSA-BF感染的潜在有效方案。

Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy breaches.This escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital world.Current methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false positives.This meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in malwaredetection.The proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data accuracy.The Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction model.This study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert opinion.The proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,respectively.The empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both datasets.This approach has substantial potential for real-world applications and can serve asa valuable tool for preventing the spread of Androidmalware and enhancing mobile device security.

Image Fusion Using Wavelet Transformation and XGboost Algorithm

Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.

Plant-derived anticancer agents: A green anticancer approach

Cancer is a frightful disease and represents one of the biggest health-care issues for the human race and demands a proactive strategy for cure. Plants are reservoirs for novel chemical entities and provide a promising line for research on cancer. Hitherto, being effective, chemotherapy is accompanied by certain unbearable side effects. Nevertheless,plants and plant derived products is a revolutionizing field as these are Simple, safer, ecofriendly, low-cost, fast, and less toxic as compared with conventional treatment methods.Phytochemicals are selective in their functions and acts specifically on tumor cells without affecting normal cells. Carcinogenesis is complex phenomena that involves many signaling cascades. Phytochemicals are considered suitable candidates for anticancer drug development due to their pleiotropic actions on target events with multiple manners. The research is in progress for developing potential candidates(those can block or slow down the growth of cancer cells without any side effects) from these phytochemicals. Many phytochemicals and their derived analogs have been identified as potential candidates for anticancer therapy. Effort has been made through this comprehensive review to highlight the recent developments and milestones achieved in cancer therapies using phytomolecules with their mechanism of action on nuclear and cellular factors. Furthermore, drugs for cancer treatment and their limitations have also been discussed.

Inhibitory activities of extracts of Rumex dentatus, Commelina benghalensis, Ajuga bracteosa, Ziziphus mauritiana as well as their compounds of gallic acid and emodin against dengue virus

Objective: To investigate the inhibitory effects against dengue virus serotype 2(DENV-2) by five different fractions(extracted by methanol, ethanol, benzene, chloroform and n-hexane) of Rumex dentatus, Commelina benghalensis, Ajuga bracteosa and Ziziphus mauritiana, as well as their constituents(gallic acid, emodin, and isovanillic acid). Methods: All the samples were tested for cytotoxicity on baby hamster kidney cells by MTT assay and for anti-DENV-2 activity by plaque reduction neutralization assay using two DENV-2 doses(45 and 90 plaqueforming units or PFU). Results: All the samples except isovanillic acid exhibited significant prophylactic effects against DENV-2 infectivity(without cytotoxicity) when administered to cells before infection, but were not effective when given 6 h post-infection. The methanol extract of Rumex dentatus demonstrated the highest antiviral efficacy by inhibiting DENV-2 replication, with IC_(50) of 0.154 μg/mL and 0.234 μg/mL, when added before infection with 45 and 90 PFU of virus, respectively. Gallic acid also exhibited significant antiviral effects by prophylactic treatment prior to virus adsorption on cells, with IC_(50) of 0.191 μg/mL and 0.522 μg/mL at 45 and 90 PFU of DENV-2 infection, respectively. Conclusions: The highly potent activities of the extracts and constituent compounds of these plants against DENV-2 infectivity highlight their potential as targets for further research to identify novel antiviral agents against dengue.

Silymarin-laden PVP-PEG polymeric composite for enhanced aqueous solubility and dissolution rate: Preparation and in vitro characterization

The aim of this work was to develop, optimize and characterize a silymarin-laden polyvinylpyrrolidone(PVP)-polyethylene glycol(PEG) polymeric composite to resolve low aqueous solubility and dissolution rate problem of the drug. A number of silymarin-laden polymeric formulations were fabricated with different quantities of PVP K-30 and PEG 6000 by the solvent-evaporation method. The effect of PVP K-30 and PEG 6000 on the aqueous solubility and dissolution rate was investigated. The optimized formulation and its constituents were characterized using powder X-ray diffraction(PXRD), differential scanning calorimetry(DSC), scanning electron microscopy(SEM) and Fourier transform infrared spectroscopy(FTIR) techniques. Both the PEG 6000 and PVP K-30 positively affected the aqueous solubility and dissolution rate of the drug. In particular, a formulation consisting of silymarin, PVP K-30 and PEG 6000(0.25/1.5/1.5, w/w/w) furnished the highest solubility(24.3972.95 mg/mL) and an excellent dissolution profile( $100% in 40 min). The solubility enhancement with this formulation was $ 1150-fold as compared to plain silymarin powder. Moreover, all the constituents existed in the amorphous state in this silymarin-laden PVP-PEG polymeric composite. Accordingly, this formulation might be a promising tool to administer silymarin with an enhanced effect via the oral route.

Role of dietary phytochemicals in modulation of miRNA expression:Natural swords combating breast cancer

The National Cancer Institute had projected breast cancer(BC) as one of the topmost prevalent malignancies around the globe.In many cases,BC becomes resistant to chemotherapy,radiation and hormonal therapies.Traditional BC therapies are associated with adverse side effects,drug resistance and recurrence.Extensive research work has shown that these dietary phytochemicals(DPs) may exert therapeutic effects by regulating the miRNA expression.A large number of DPs have been researched as miRNA regulatory agents against BC and some other DPs have not yet been tested against BC.We have discussed the effects of curcumin,diallyl disulphide,3,3′ diindolylmethane,ellagic acid,genistein,indole-3-carbinol,quercetin,resveratrol,and sulforaphane on regulation of expression of BC miRNAs in a wide range of in vitro and in vivo models.We have also shown some of the possible DPs(Oleanolic acid,capsaicin,benzyl isothiocyanate,epigallocatechin gallate,phenethyl isothiocyanate and ursolic acid) that have shown miRNA regulatory activities and have not yet been tested against BC miRNAs.Finally,current limitations,challenges,future perspectives of DPs and BC research are also critically discussed.

Big Data Analytics in Telecommunications: Literature Review and Architecture Recommendations

This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

Big Data Analytics in Healthcare——A Systematic Literature Review and Roadmap for Practical Implementation

The advent of healthcare information management systems(HIMSs)continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale.Analysis of this big data allows for boundless potential outcomes for discovering knowledge.Big data analytics(BDA)in healthcare can,for instance,help determine causes of diseases,generate effective diagnoses,enhance Qo S guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments,generate accurate predictions of readmissions,enhance clinical care,and pinpoint opportunities for cost savings.However,BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners.In this paper,we present a comprehensive roadmap to derive insights from BDA in the healthcare(patient care)domain,based on the results of a systematic literature review.We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on No SQL databases.We also identify the limitations and challenges of these applications and justify the potential of No SQL databases to address these challenges and further enhance BDA healthcare research.We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm.We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare.Finally,we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work.The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators,practitioners and professionals to successfully implement BDA initiatives in their organizations.

Population Variation and Food Habits of Ranid Frogs in the Rice-Based Cropping System in Gujranwala Region,Pakistan

The current study aims to investigate the population variation and food habits of ranid frogs in the rice-based cropping system in District Gujranwala,Pakistan.The population in the study area was estimated using capture,mark and release method whereas food habits of the species were studied by analysis of stomach contents.The results showed the highest average population was found during August 2009(93.10±18.64/ha) while the lowest from December 2008 to February 2009.Maximum seasonal populations existed in summer 2009,whereas winter 2008 sizes were at a minimum.Stomach content analysis of the species revealed percent frequency(% F) of occurrence of insects(80.3),earthworms(28.5),whole frogs(15.8),bone pieces(22.5),rodents(1.66),vegetation(5.0),soil particles(13.3) and some unidentified material(7.5) in all the stomach samples.Most frequently consumed prey items were insects(30% by volume),although frogs also preyed upon conspecifics and rodents.Insects recovered from the stomach contents were identified as belonging to Orthoptera,Lepidoptera,Coleoptera,Diptera,Odonata and Homoptera as well as the class Archnida.Insects recovered from the stomach contents were compared to those captured from the study area.

In vitro antioxidant and anti-cancer activities and phytochemical analysis of Commelina benghalensis L. root extracts

Objective:To explore antioxidant potential,anti-cancer activity,and phytochemicals of Commelina benghalensis L.Methods:The roots of Commelina benghalensis were extracted in different solvents(methanol,ethanol,benzene,chloroform,n-hexane)with a range of polarity.Antioxidant activity was evaluated by reducing power assay,DPPH radical scavenging activity and phosphomolybdenum method,cytotoxicity by MTT assay,apoptotic and cell cycle analysis by flow cytometry,migratory and invasive potential by wound scratch assay and invasion assay,respectively,functional groups analysis by FT-IR spectroscopy and phytochemicals by aluminum chloride colorimetric and FolinCiocalteu methods.Results:The extracts showed worthy antioxidant potential.The chloroform extract demonstrated the most significant cytotoxic effect on MDA-MB-231(breast cancer)cell line,induced apoptosis and reduced migratory and invasive potential of MDA-MB-231 cells.Methanol and ethanol extracts presented good yield of total phenolic and total flavonoid contents.The FTIR spectroscopic studies revealed different characteristic peak values with various functional compounds such as alkenes,alkanes,aliphatic amines,aromatics,alkyl halides,carboxylic acid,alcohols,ester,aldehydes and ketones.Conclusions:The results demonstrate the potential use of Commelina benghalensis as a good antioxidant with significant anticancer effect.

Synthesis,Crystal Structure and Spectroscopic Properties of 1,2-Benzothiazine Derivatives:An Experimental and DFT Study

1,2-Benzothiazine derivatives methyl 3-methoxy-4-oxo-3,4-dihydro-2H-benzo[e] [1,2]thiazine-3-carboxylate 1,1-dioxide（1） and methyl 2-ethyl-3-hydroxy-4-oxo-3,4-dihydro-2Hbenzo[e][1,2]thiazine-3-carboxylate 1,1-dioxide（2） were synthesized, and characterized by spectroscopic techniques; 1H-NMR and infrared（IR） spectroscopy. Crystals of 1 and 2 were grown by slow evaporation of methanol and ethyl acetate, respectively and their crystal structures were investigated by single-crystal X-ray diffraction analysis. Geometric properties were calculated by the B3 LYP method of density functional theory（DFT） at the 6-31G＋（d） basis set to compare with the experimental data. Simulated properties were found in strong agreement with the experimental ones. Intermolecular forces have also been modeled in order to investigate the strength of packing and strong hydrogen bonding was observed in both compounds 1 and 2. Electronic properties such as Ionization Potential（IP）, Electron Affinities（EA） and coefficients of the highest occupied molecular orbital（HOMO） and the lowest unoccupied molecular orbital（LUMO） of com- pounds 1 and 2 were simulated for the first time.

Sedimentology of Marl and Marly Limestone Sequence of Upper Cretaceous Kawagarh Formation from Northern Kalachitta Range, Attock Hazara Fold and Thrust Belt, Pakistan

Upper Cretaceous Kawagarh Formation is well exposed in the Attock Hazara Fold and Thrust Belt (AHFTB) and shows significant lateral and vertical variations in lithology. The present work deals with the sedimentological studies of marl and marly limestone sequence of Kawagarh Formation exposed at the Bagh Neelab, Ghariala north and Sojhanda villages in Northern Kalachitta Range. Detailed petrographic studies of marly limestone and hard marl substrate show that planktons and oysters are the main skeletal constituents of studied samples and clay and detrital quartz mainly composed the non skeletal fraction. X-Ray diffraction analyses of selected marl samples confirm the petrographic data. On the basis of skeletal and non skeletal content, two microfacies—marl microfacies and Planktonic microfacies are constructed. The faunal content, their paleoecology and detrital content of microfacies suggest that marl and marly limestone sequence of Kawagarh Formation was deposited over the mid and outer ramp settings.

Impact of population dynamics on Margalla Hills Ecosystem:a community-level case study

Margalla Hills National Park(MHNP) is a declared natural reserve of Pakistan,and Saidpur village is located at its foothills.To sustain livelihood,Saidpur community relies on natural resources and has established an intriguing relationship with the surrounding ecosystem.Human intrusion and related impacts were investigated through self-structured questionnaire from village community to gather information about demography,life practices,natural resource use,and their perception about the environment.Quadrat analysis revealed that the overall plant density was<4 plants/m^2,whereas ordination biplot has indicated significant reduction in plant cover and sparse distribution of species in areas close to human settlement.Survey results show that more than 50%families rely on forest wood as fuel source.Logistic regression has identified education paucity(odds ratio,OR=2.6,95%confidence interval,CI=1.0-6.7),large family size(OR= 5.0,95%CI=1.5-16.6),and fuel type(OR=3.5,95%CI=1.2-9.9)as significant predictors of accelerated forest cutting in MHNP.Male members were mostly illiterate and in favor to promote construction activities which reflects their low concern and casual attitude toward resource conservation.In this study,lack of awareness and peoples' dependency on natural resources emerged as priority challenges,and hence,we suggest provision of alternate fuel sources,better education and sustained income resources as incentives to bring behavioral change.It is pivotal to involve local community before the adoption of any conservation plan as intervention strategy to protect MHNP ecosystem.

Managing Health Treatment by Optimizing Complex Lab-Developed Test Configurations: A Health Informatics Perspective

A complex Laboratory Developed Test(LDT)is a clinical test developed within a single laboratory.It is typically configured from many fea-ture constraints from clinical repositories,which are part of the existing Lab-oratory Information Management System(LIMS).Although these clinical repositories are automated,support for managing patient information with test results of an LDT is also integrated within the existing LIMS.Still,the support to configure LDTs design needs to be made available even in standard LIMS packages.The manual configuration of LDTs is a complex process and can generate configuration inconsistencies because many constraints between features can remain unsatisfied.It is a risky process and can lead patients to undergo unnecessary treatments.We proposed an optimized solution(opt-LDT)based on Genetic Algorithms to automate the configuration and resolve the inconsistencies in LDTs.Opt-LDT encodes LDT configuration as an optimization problem and generates a consistent configuration that satisfies the constraints of the features.We tested and validated opt-LDT for a local secondary care hospital in a real healthcare environment.Our results,averaged over ten runs,show that opt-LDT resolves 90%of inconsistencies while taking between 6 and 6.5 s for each configuration.Moreover,positive feedback based on a subjective questionnaire from clinicians regarding the performance,acceptability,and efficiency of opt-LDT motivates us to present our results for regulatory approval.

Dietary isoflavones,the modulator of breast carcinogenesis:Current landscape and future perspectives

Breast cancer is a frightful disease and serious concern in women around the world causing significant health care burden in both developed and developing countries. Extensive research work has shown that breast cancer provides strong resistance to chemical agents, U V radiation,and hormonal treatments. It is generally accepted that cell genetics is not the only main reason for breast cancer and genetic risk factors, for example, mutations in RRCAI and BRCA2 genes constitute 5%-10% of all breast cancer rates. Other related factors include age, gender,race, ethnicity, weight, reproductive factors, exo-and endogenous hormonal exposures, oral contraceptives use, ultraviolet radiation, diet, and night work(circadian disruption). Many studies have revealed that dietary isoflavones regulate breast cancer occurrence, recurrence and prognosis. Dietary isoflavones have long been part of Asian population diet and there is a significant increase as compared to dietary isoflavones intake among other populations. Dietary isoflavones are natural phytoestrogens having both estrogenic and anti-estrogenic potentials on breast cancer cells in culture, animal models and in experimental trials. This literature survey provides a comprehensive overview on the tumor preventive and tumor promoting potentials of dietary isoflavones on breast cancer. In addition, this paper provides a literature review of dietary isoflavones and their effects on up-regulation and down-regulation of different signaling pathways, genes and proteins. Finally, future perspectives of dietary isoflavones and breast cancer researchers are also critically discussed, which will provide a deeper insight regarding the inner molecular mechanisms of action.

Synthesis and Structural Investigations of New 4-Hexyl-1-(4-nitrophenyl)-1-H-1,2,3-triazole:An Experimental and Theoretical Insight

The title compound, 4-hexyl-1-（4-nitrophenyl）-1-H-1,2,3-triazole （CI4HIsN402）, was synthesized using one-pot strategy via click reaction and the structure was characterized mainly by single-crystal X-ray diffraction, NMR, FT-IR and MS. C14H18N4O2 was crystallized from an EtOH/EtOAc solution in triclinic system, space group PI, with a = 5.3679（3）, b = 7.5499（5）, c = 17.5534（11） A, a = 92.360（4）, β = 90.359（4）, γ = 98.864（4）°, V （A3） = 702.24（8）, Z = 2, crystal size （mm） = 0.42 × 0.26 × 0.18, Rint = 0.096. Packing diagram indicates that there is dimeric interaction between two units via N（3）...H（6）. The crystal structure of the title compound （1） is stabifized by intermolecular interactions. In addition, X-ray analys!s also reveals C-H…π and π-π interactions in the molecule. Theoretical investigations were performed by using Gaussian 09 software at the B3LYP/6, 31G （d,p）level of density,finctional theory （DFT）.to compare the theoretical results with the experimental and to probe structural properties. The molecular electrostatic potential （MEP） mapped over the entire stabilized geometry of the molecule indicated their chemical reactivities. Furthermore, frontier molecular orbital （electronic properties） was computed at the same level of DFT as used. forenergy minima structure.

Explainable Artificial Intelligence Solution for Online Retail

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for them.In the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business.In this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one year.The main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the future.The permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the future.The performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC curve.RF model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree classifier.Hence,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying behaviour.Our research also reveals the importance of page value as a key feature for capturing online purchasing trends.This may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

Morpho-Physiological Traits Linked to High Temperature Stress Tolerance in Tomato <i>(S. lycopersicum L.)</i>

The identification of heat tolerance traits that express across environments is key to the successful development of high temperature tolerant tomatoes. A replicated experiment of 145 tomato genotypes was established at two temperature regimes in two planting seasons using hydroponics in a poly greenhouse to assess high temperature tolerance. Electrolyte leakage, number of inflorescences, number of flowers and fruits, fresh fruit weight and fresh and dry plant weight were measured and genotype and temperature treatment differences were observed for all traits. Planting season impacted all traits except electrolyte leakage and number of flowers. High temperature reduced number of fruits by 88.8%, flower fruit set ratio by 77.2% and fresh fruit weight by 79.3%. In contrast, traits little impacted by temperature included number of flowers per inflorescence (1.3%) and plant dry weight (11.1%). The correlation between plant dry weight under both high and optimal temperature was significant (R2 = 0.82). To assess the effectiveness of plant dry weight and flower-fruit set ratio for selection under heat stress two subsets of genotypes (A and B) comprising ten and six genotypes respectively, were subsequently selected on the basis of their dry weight loss and flower-fruit set ratio under high temperature. Organic metabolite analyses of set A and B respectively, showed a significant change (%) in citric acid (77.4 and 15.4), L-proline (117.8 and 40.2), aminobutyric acid (68.6 and 11.8), fructose (24.9 and 21.3), malic acid (50.3 and 42.7), myo-inositol (55.1 and 6.1), pentaerythitol (54.1 and 39.0) and sucrose (34.7 and 25.8). The change (%) in all metabolites was greater in heat tolerant genotypes with the exception of fructose and sucrose where sensitive genotypes produced a higher variation. The change in sucrose in tolerant genotypes was variable in subset A and more uniform in subset B. Flower-fruit set ratio was found as a reliable trait for discriminating between heat tolerant and sensitive genotypes and the sucrose levels in plant tissues provided confirmation of the heat stress response.

Assessment of phytochemicals, antioxidant, anti-hemolytic, anti-inflammatory and anti-cancer potential of flowers, leaves and stem extracts of Rosa arvensis

OBJECTIVE:To evaluate phytochemicals and in vitro biological potential of flowers,leaves and stem extracts of Rosa arvensis.METHODS:Presence of twenty secondary metabolites was confirmed and then phenolic and flavonoid contents were quantified spectrophotometrically.Fourier Transform Infrared spectroscopy was conducted to ascertain functional groups and antioxidant potential was examined using 2,2-diphenyl-1-picrylhydrazyl scavenging activity,total antioxidant capacity and total reducing power assays.Human erythrocytes were used to assess anti-hemolytic activity and five bacterial strains were examined to determine antibacterial potential of plant extracts.Radish seeds were used to perform phytotoxic activity and cytotoxic potential was evaluated via brine shrimps and PC3 cell lines.RESULTS:Highest phenolic contents were detected in the methanolic extract of Rosa arvensis flower(RAFM)[(151.635±0.005)gallic acid equivalent mg/g]and highest flavonoid contents in the chloroform leaf extract(RALC)[(108.228±0.004)quercetin equivalent mg/g].Fourier-transform infrared spectroscopy analysis showed the presence of wide range of functional groups.The antioxidant assays indicated highest DPPH scavenging activity[IC50(23.5±0.6)μg/mL]in the methanolic stem extract(RASM),highest total antioxidant capacity[(265.1±0.9)μg/mL]in RAFM and highest reducing potential[(209.9±0.6)μg/mL]in leaf extract(RALM).Highest antihemolytic activity[(90.0±0.5)μg/mL]was recorded in RAFM and brine shrimp cytotoxicity potential[(52.3±0.3)μg/mL]in RASM.The antimicrobial activity was detected highest[(21.1±0.5)mm inhibition zones]in RALM against Streptococcus aureus.In the end,antiinflammatory and anti-cancer activity results depicted less than 50%inhibition in the methanolic extracts.CONCLUSIONS:Our findings will be helpful in designing pharmaceutical regimens and therefore,more studies can be recommended to isolate and characterize compounds associated with the biological activities of Rosa arvensis.