Melatonin is considered a potential plant growth regulator to enhance the growth of plants and increase tolerance to various abiotic stresses. Nevertheless, melatonin's role in mediating stress ...response in different plant species and growth cycles still needs to be explored. This study was conducted to understand the impact of different melatonin concentrations (0, 50, 100, and 150 muM) applied as a soil drench to maize seedling under drought stress conditions. A decreased irrigation approach based on watering was exposed to maize seedling after drought stress was applied at 40-45% of field capacity. The results showed that drought stress negatively affected the growth behavior of maize seedlings, such as reduced biomass accumulation, decreased photosynthetic pigments, and enhanced the malondialdehyde and reactive oxygen species (ROS). However, melatonin application enhanced plant growth; alleviated ROS-induced oxidative damages by increasing the photosynthetic pigments, antioxidant enzyme activities, relative water content, and osmo-protectants of maize seedlings. Melatonin treatment also enhanced the stomatal traits, such as stomatal length, width, area, and the number of pores under drought stress conditions. Our data suggested that 100 muM melatonin application as soil drenching could provide a valuable foundation for improving plant tolerance to drought stress conditions.
The aim of research work is to characterize hyperelastic material and to determine a suitable strain energy function (SEF) for an indigenously developed rubber to be used in flexible joint use for ...thrust vectoring of solid rocket motor. In order to evaluate appropriate SEF uniaxial and volumetric tests along with equi-biaxial and planar shear tests were conducted. Digital image correlation (DIC) technique was utilized to have strain measurements for biaxial and planar specimens to input stress-strain data in Abaqus(R). Yeoh model seems to be right choice, among the available material models, because of its ability to match experimental stress-strain data at small and large strain values. Quadlap specimen test was performed to validate material model fitted from test data. FE simulations were carried out to verify the behavior as predicted by Yeoh model and results are found to be in good agreement with the experimental data.
Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multi-hop communication and a shorter ...transmission range. Clustering and routing are treated separately in different solutions and, therefore, efficient solutions in terms of energy consumption and network lifetime could not be provided. This work focuses data collection from IoT-nodes distributed in an area and connected through WSN. We address two interlinked issues, clustering and routing, for large-scale IoT-based WSN and propose an improved clustering and routing protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. During process of clustering, cluster-heads are selected in such a way that provide fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop-count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity.
Abstract
The data quality of low-cost sensors has received considerable attention and has also led to PM
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warnings. However, the calibration of low-cost sensor measurements in an environment with ...high relative humidity is critical. This study proposes an efficient calibration and mapping approach based on real-time spatial model. The study carried out spatial calibration, which automatically collected measurements of low-cost sensors and the regulatory stations, and investigated the spatial varying pattern of the calibrated low-cost sensor data. The low-cost PM
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sensors are spatially calibrated based on reference-grade measurements at regulatory stations. Results showed that the proposed spatial regression approach can explain the variability of the biases from the low-cost sensors with an R-square value of 0.94. The spatial calibration and mapping algorithm can improve the bias and decrease to 39% of the RMSE when compared to the nonspatial calibration model. This spatial calibration and real-time mapping approach provide a useful way for local communities and governmental agencies to adjust the consistency of the sensor network for improved air quality monitoring and assessment.
Internet of Things (IoT) devices are well-connected; they generate and consume data which involves transmission of data back and forth among various devices. Ensuring security of the data is a ...critical challenge as far as IoT is concerned. Since IoT devices are inherently low-power and do not require a lot of compute power, a Network Intrusion Detection System is typically employed to detect and remove malicious packets from entering the network. In the same context, we propose feature clusters in terms of Flow, Message Queuing Telemetry Transport (MQTT) and Transmission Control Protocol (TCP) by using features in UNSW-NB15 data-set. We eliminate problems like over-fitting, curse of dimensionality and imbalance in the data-set. We apply supervised Machine Learning (ML) algorithms, i.e., Random Forest (RF), Support Vector Machine and Artificial Neural Networks on the clusters. Using RF, we, respectively, achieve 98.67% and 97.37% of accuracy in binary and multi-class classification. In clusters based techniques, we achieved 96.96%, 91.4% and 97.54% of classification accuracy by using RF on Flow & MQTT features, TCP features and top features from both clusters. Moreover, we show that the proposed feature clusters provide higher accuracy and requires lesser training time as compared to other state-of-the-art supervised ML-based approaches.
Soaring capacity and coverage demands dictate that future cellular networks need to migrate soon toward ultra-dense networks. However, network densification comes with a host of challenges that ...include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads, and higher backhaul costs. Interestingly, most of the problems that beleaguer network densification stem from legacy networks' one common feature, i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of the aforementioned challenges. In this survey, we review various proposals that have been presented in the literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification, namely: energy efficiency, system level capacity maximization, interference management, and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP) and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up-to-date survey on SARC, CoMP, and D2D. Most importantly, this survey provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.
Natural fiber composites have great potential for reducing the product cost, lowering weight and enhancing renewability. Functionality and performance of natural fibers can be enhanced many folds ...using them together with synthetic fibers. Hybridization of carbon and low-cost natural jute fiber offers a sustainable hybrid composite having high modulus and mechanical strength. This study investigates flexural behavior of carbon/jute epoxy composites experimentally and numerically. Also, impact response is characterized through drop weight method. Study concludes that flexural strength decreases with increase in jute percentage. Simulation of flexural behavior diverges more than 10 % from experimental results. This anomaly is due to waviness of fiber resulting in heterogeneous property distribution in composites. Further, the fracto-graphic study revealed modes of failure. The drop weight impact tests reveal increased damage area with increase in jute percentage.
Since its inception, the Internet of Things (IoT) has witnessed mushroom growth as a breakthrough technology. In a nutshell, IoT is the integration of devices and data such that processes are ...automated and centralized to a certain extent. IoT is revolutionizing the way business is done and is transforming society as a whole. As this technology advances further, the need to exploit detection and weakness awareness increases to prevent unauthorized access to critical resources and business functions, thereby rendering the system unavailable. Denial of Service (DoS) and Distributed DoS attacks are all too common. In this paper, we propose a Protocol Based Deep Intrusion Detection (PB-DID) architecture, in which we created a data-set of packets from IoT traffic by comparing features from the UNSWNB15 and Bot-IoT data-sets based on flow and Transmission Control Protocol (TCP). We classify non-anomalous, DoS, and DDoS traffic uniquely by taking care of the problems like imbalanced and over-fitting. We have achieved a classification accuracy of 96.3% by using deep learning (DL) technique.
This numerical investigation effectively establishes a unique computing exploration for steady magnetohydrodynamic convective streams of tangent hyperbolic nanofluid traveling across a nonlinearly ...elongating elastic surface with a variable thickness. In addition, the importance of an externally imposed magnetic field of tangent hyperbolic nanofluid is comprehensively analyzed by considering the substantial impact of thermal conductivity and thermal radiation consequences. The governing PDEs (partial differential equations) are transmuted into a nonlinear differential structure of coupled ODEs (ordinary differential equations) using a series of variable similarity transformations. Furthermore, these generated ODEs (ordinary differential equations) are numerically set using a novel revolutionary Runge-Kutta algorithm with a shooting approach constructed in a MATLAB script. In this regard, extensive comparison studies are carried out to validate the acquired numerical results. The interactions between the associated profiles and the relevant parameters are rationally explored and shown using graphs and tabular forms. The velocity distribution declined with improving Weissengberg number We and power-law index m, while the reverse performance can be observed for temperature. As enhancement in Brownian motion, Thermophoretic and radiation parameters significantly rise in temperature distribution. The use of many different technological and industrial systems, including nano-bioconvective systems, nano-droplet evaporation, nano-ink jet printing, and microbial fuel cells, would benefit this research study.
China Pakistan Economic Corridor has been touted by many as a gateway to economic prosperity and stability in Pakistan. It accompanies great potential in terms of solving the ongoing energy crisis ...and eventually leading Pakistan towards energy security. In this respect, a meta-analytic review has been conducted to identify the underlying concerns that can hinder the successful achievement of energy security though China Pakistan Economic Corridor energy projects. This meta-analysis has revealed strong evidence supporting achievement of Pakistan's energy security dream (89%) along with five main distressing factors which are economic burden (22.22%), security threat (38.89%), project completion delays (22.22%), lack of project feasibility studies (22.22%) and provincial conflict (50%). Additionally, statistically significant strong negative correlation between energy security and economic burden is unearthed with Spearman's rho-value of − 0.759. Moreover, strong negative correlation exists between energy security and project completion delays with rho-value of − 0.500 and P-value of 0.035. Also, project feasibility and project completion delays is found to have a very strong positive correlation as well with rho-value of 0.709 and P-value of 0.001. These findings will assist policy makers and strategists in formulating limitation frameworks for the restriction of undesirable influences on energy security from these identified factors.
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•It is found that CPEC energy projects can enhance Pakistan’s energy security.•Energy security and economic burden is found to be negatively associated.•Energy security and project completion delay is found to be negatively associated.•Project feasibility concern and project completion delay has positive correlation.•Security threat and provincial conflicts are also found as main concerns.
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