The Correlation between Nutrition and Transport Mechanism under Abiotic Stress in Plants: A Comprehensive Review

Variations in the nutrients and water that plants require for metabolism,development,and the maintenance of cellular homeostasis are the main causes of abiotic stress in plants.It has,however,hardly ever been studied how these transporter proteins,such as aquaporin which is responsible for food and water intake in cell plasma mem-branes,interact with one another.This review aims to explore the interactions between nutrient transporters and aquaporins during water and nutrient uptake.It also investigates how symbiotic relationships influence the plant genome’s responses to regulatory processes such as photoperiodism,senescence,and nitrogenfixation.These responses are observed in reaction to various abiotic stresses.For instance,plasma membrane transporters are upregulated during macronutrient insufficiency,tonoplast transporters are overexpressed,and aquaporins are downregulated in micronutrient deficiency.Additionally,tolerant plants often exhibit increased expression of nutrient transporters and aquaporins in response to drought,salt,and cold temperatures.To better comprehend plant stress tolerance to abiotic challenges including starvation,K famine,salt,and freezing temperatures,both classes of nutrient and water transporters should be considered at the same time.

UV固化的环氧丙烯酸树脂耐磨加硬涂层的制备及性能（英文）

本文通过环氧树脂和丙烯酸为原料反应合成了环氧丙烯酸树脂(EA),然后用硅烷偶联剂3-甲基丙烯酰氧丙基三甲氧基硅烷(MPS)对其进行改性,得到可紫外光固化的有机硅耐磨透明涂层,并对涂层的各种性能进行了测试,如硬度测试、附着力测试和耐磨性能测试等。结果表明,相比未涂覆的有机玻璃基材,涂覆后的有机玻璃基材的表面硬度和透光率均有所增加,且随硅烷偶联剂含量的增加而有所提高。对耐磨涂层的热稳定性也进行了研究,结果发现,改性后的环氧丙烯酸树脂的热稳定性要明显好于未改性的。

Antimicrobial chemical constituents from endophytic fungus Phoma sp.

Objective:To evaluate the antiniicrobial polenlial of different extracts of the endophytic fungus Phoma sp.and the tentative identification of their active constituents.Methods:The extract and compounds were screened for antimicrobial activity using the Agar Well Diffusion Method.Four compounds were purified using column chromatography and tlieir structures were assigned using～1H and～(13)C NMR spectra,DEPT,2D COSY,HMQC and HMBC experiments.Results:The ethyl acetate fraction of Phoma sp.showed good antifungal,antibacterial,and algicidal properties.One new dihydrofuran derivative,named phomafuranol(1),together with tliree known compounds,phomalacton(2),(3R)-5-hydroxymellein(3)and emodin(4)were isolated from the ethyl acetate fraction of Phoma sp.Preliminary studies indicated that phomalacton(2)displayed strong antibacterial,good antifungal and antialgal activities.Similarly(3R)-5-hydroxymellein(3)and emodin(4)showed good antifungal,antibacterial and algicidal properties.Conclusions:Antimicrobial activities of the ethyl acetate fraction of the endophytic fungus Phoma sp.and isolated compounds clearly demonstrate that Phoma sp.and its active compounds represent a great potential for the food,cosmetic and pharmaceutical industries.

Load Balancing Framework for Cross-Region Tasks in Cloud Computing

Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them.To maximize various performance parameters in cloud computing,researchers suggested various load balancing approaches.To store and access data and services provided by the different service providers through the network over different regions,cloud computing is one of the latest technology systems for both end-users and service providers.The volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been experienced.Users of the cloud are looking for services that are intelligent,and,can balance the traffic load by service providers,resulting in seamless and uninterrupted services.Different types of algorithms and techniques are available that can manage the load balancing in the cloud services.In this paper,a newly proposed method for load balancing in cloud computing at the database level is introduced.The database cloud services are frequently employed by companies of all sizes,for application development and business process.Load balancing for distributed applications can be used to maintain an efficient task scheduling process that also meets the user requirements and improves resource utilization.Load balancing is the process of distributing the load on various nodes to ensure that no single node is overloaded.To avoid the nodes from being overloaded,the load balancer divides an equal amount of computing time to all nodes.The results of two different scenarios showed the cross-region traffic management and significant growth in revenue of restaurants by using load balancer decisions on application traffic gateways.

Yield and Quality of Forage Oat (<i>Avena sativa</i>L.) Cultivars as Affected by Seed Inoculation with Nitrogenous Strains

Nitrogen availability can be enhanced with the application of nitrogen fixing bacteria and it may be helpful in increasing forage yield and improving quality of oat. Therefore, a field trial to evaluate the effect of seed inoculation with nitrogen fixing bacteria on forage yield and quality of oat was carried out at Agronomic Research Area, University of Agriculture, Faisalabad during Rabi season 2013-14. The experiment was laid out in Randomized Complete Block Design (RCBD) with factorial arrangements using three replications. The experiment was comprised of two integrated approaches. The first approach was oat cultivars consisting of four treatments, V1 (AVON), V2 (S-2000), V3 (S-2011) and V4 (PD2LV65) and the second approach was seed inoculation consisting of three treatments, S0 (control), S1 (Azotobacter spp.), S2 (Azospirillum spp.). Fisher’s analysis of variance technique was used for statistically interpretation of data by using least significant difference (LSD) test at 5% level of probability. Nitrogen fixing bacteria significantly affect the germination count (m2), plant height (cm), number of tillers (m2), number of leaves per tiller, leaf area per tiller (cm2), green forage yield (t·ha-1) and dry matter yield (t ha-1). The maximum green forage yield (85.2 t·ha-1), dry matter yield (14.1 t ·ha-1) and crude protein (11.5%) were recorded where Azotobacter inoculation was applied. The interaction between cultivars and nitrogenous strains was significant for green forage yield (t·ha-1), dry matter yield (t·ha-1) and crude protein (%). Conclusion showed that cultivar Sargodha-2011 which was inoculated with Azotobacter spp. gave higher forage yield of good quality.

Simple Preparation and Characterization of Nano-Crystalline Zinc Oxide Thin Films by Sol-Gel Method on Glass Substrate

Nanocrystalline ZnO thin films have been fabricated by a multi-step solgel method using spin coating technique. Zinc acetate dihydrate, 2-methoxyethanol and monoethanolamine were used as a starting material, solvent and stabilizer, respectively. X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) were employed to characterize structure and morphologies of the as-deposited samples. The results of XRD and SEM showed that the heat treatment conditions, final rotational (spinning) speed, fume exhaust and precise control of concentration of reactants (precursor and solvent used) strongly affect the crystallographic orientation and morphology of the resultant ZnO films. The XRD pattern showed that the ZnO films formed the preferred orientation along c-axis and the grain size is 16nm for the samples. Only one peak corresponding to the (002) plane at 2θ = 34.34 appears on the diffractograms. The as-deposited films had a transparency of greater than 80% in the visible-near IR region from 400 nm - 800 nm. The optical band gap energy and thickness were calculated to be 3.296 eV and 266 nm respectively.

The New Neutrosophic Double and Triple Exponentially Weighted Moving Average Control Charts

The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.

Hyper-Convergence Storage Framework for EcoCloud Correlates

Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and facilities to this audience and the number of providers is increasing very swiftly.This enormous pace is generating the requirement of a comprehensive ecosystem that shall provide a seamless and customized user environment not only to enhance the user experience but also to improve security,availability,accessibility,and latency.Emerging technology is providing robust solutions to many of our problems,the cloud platform is one of them.It is worth mentioning that these solutions are also amplifying the complexity and need of sustenance of these rapid solutions.As with cloud computing,new entrants as cloud service providers,resellers,tech-support,hardware manufacturers,and software developers appear on a daily basis.These actors playing their role in the growth and sustenance of the cloud ecosystem.Our objective is to use convergence for cloud services,software-defined networks,network function virtualization for infrastructure,cognition for pattern development,and knowledge repository.In order to gear up these processes,machine learning to induce intelligence to maintain ecosystem growth,to monitor performance,and to become able to make decisions for the sustenance of the ecosystem.Workloads may be programmed to“superficially”imitate most business applications and create large numbers using lightweight workload generators that merely stress the storage.In today’s current IT environment,when many enterprises use the cloud to service some of their application demands,a different performance testing technique that assesses more than the storage is necessary.Compute and storage are merged into a single building block with HCI(Hyper-converged infrastructure),resulting in a huge pool of compute and storage resources when clustered with other building blocks.The novelty of thiswork to design and test cloud storage using themeasurement of availability,downtime,and outage parameters.Results showed that the storage reliability in a hyper-converged system is above 92%.

QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any time.After assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation model.Cloud is the emerging environment for distributed services at various layers.Due to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing models.Allocation of resources in the Cloud is difficult because resources provide numerous measures of quality of service.In this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource loading.This article is focused on the cloud service’s security,cloud reliability,and could performance.In this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust issues.The findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.

Bit Rate Reduction in Cloud Gaming Using Object Detection Technique

The past two decades witnessed a broad-increase in web technology and on-line gaming.Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology.The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers.As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience.In cloud-based video gaming,game engines are hosted in cloud gaming data centers,and compressed gaming scenes are rendered to the players over the internet with updated controls.In such systems,the task of transferring games and video compression imposes huge computational complexity is required on cloud servers.The basic problems in cloud gaming in particular are high encoding time,latency,and low frame rates which require a new methodology for a better solution.To improve the bandwidth issue in cloud games,the compression of video sequences requires an alternative mechanism to improve gaming adaption without input delay.In this paper,the proposed improved methodology is used for automatic unnecessary scene detection,scene removing and bit rate reduction using an adaptive algorithm for object detection in a game scene.As a result,simulations showed without much impact on the players’quality experience,the selective object encoding method and object adaption technique decrease the network latency issue,reduce the game streaming bitrate at a remarkable scale on different games.The proposed algorithm was evaluated for three video game scenes.In this paper,achieved 14.6%decrease in encoding and 45.6%decrease in bit rate for the first video game scene.

Identification of Potential F₁Hybrids in Maize Responsive to Water Deficient Condition

The assessment of heterotic F1 combinations is a basic requisite for hybrid seed development. A set of 30 F1 hybrids along with their parental inbred lines were evaluated under both normal and water deficit conditions for various physiological and agronomic traits. Highly significant mean squares due to general combining ability, specific combining ability and reciprocal effect were observed for all traits under both water regimes. Components of variation exhibited greater estimates for GCA variance (б2g) than SCA variance (б2s) for majority of the traits under both normal and stress conditions depicting the predominant role of additive genetic component. Inbred lines NCIL-20-20, D-157 and OH-8 were found to be the best general combiner on the basis of performance regarding grain yield per plant under water deficit condition. The F1 combinations namely, NCIL-20-20 × D-109, NCIL-20-20 × OH-8 and D-157 × NCIL-20-20 were out-performers based on yield and yield attributes under water deficit conditions. On the basis of our results, we recommend these hybrids for further exploitation to assess their potential for commercial cultivation under water deficit condition.

Wound dehiscence with continuous versus interrupted mass closure of transverse incisions in children with absorbable suture:a randomized controlled trial

Introduction Numerous meta-analyses done on adults suggest superiority of continuous mass closure technique,but any such study does not exist for the pediatric age group.The results in adults cannot be applied to pediatrics because of numerous physiologic and anatomic differences.Methods This is a single-blinded,randomized controlled trial,1:1 parallel groups,that compares the frequency of dehiscence between the interrupted and continuous mass closure techniques for transverse incisions in pediatric patients.The age range was from birth to 12 years.We sampled 350 patients undergoing emergency or elective exploratory laparotomies in our pediatric surgery unit.Blocked randomization was used and only the patients remained blinded during the intervention.One group was closed with interrupted mass closure(group A)and the other group with continuous mass closure technique(group B).We had to drop 50 patients for not meeting the inclusion criteria.results The wound dehiscence rate for group A was 1.34%(4 patients)and for group B was 3.0%(9 patients).Significance was calculated usingχ^(2)(p<0.156).The global wound dehiscence rate was 4.34%(13 patients).The maximum number of patients dehisced on the fifth postoperative day,while the range was 4-11 days.The only statistically significant confounding factor was wound classification(p<0.002).Discussion Statistically there is no significant difference between interrupted and continuous mass closures techniques in terms of wound dehiscence.The dirty wounds are at a maximum risk of developing wound dehiscence irrespective of the technique used.We need to strictly adhere to the basic principles of closure especially when dealing with dirty wounds.trial registration number TCTR20150318001.