India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional ...disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Internet of Things (IoT) has now become an embryonic technology to elevate the whole sphere into canny cities. Hasty enlargement of smart cities and industries leads to the proliferation of waste ...generation. Waste can be pigeon-holed as materials-based waste, hazard potential based waste, and origin-based waste. These waste categories must be coped thoroughly to make certain of the ecological finest run-throughs irrespective of the origin or hazard potential or content. Waste management should be incorporated into ecological preparation since it is a grave piece of natural cleanliness. The most important goalmouth of waste management is to maintain the pecuniary growth and snootier excellence of life by plummeting and exterminating adversative repercussions of waste materials on environment and human health. Disposing of unused things is a significant issue, and this ought to be done in the best manner by deflecting waste development and keeping hold of cost, and it involves countless human resources to deal with the waste. These current techniques predominantly focus on cost-effective monitoring of waste management, and results are not imprecise, so that it could not be developed in real time or practically applications such as in educational organizations, hospitals, and smart cities. Internet of things-based waste management system provides a real-time monitoring system for collecting the garbage waste, and it does not control the dispersion of overspill and blowout gases with poor odor. Consequently, it leads to the emission of radiation and toxic gases and affects the environment and social well-being and induces global warming. Motivated by these points, in this research work, we proposed an automatic method to achieve an effective and intelligent waste management system using Internet of things by predicting the possibility of waste things. The wastage capacity, gas level, and metal level can be monitored continuously using IoT based dustbins, which can be placed everywhere in city. Then, our proposed method can be tested by machine learning classification techniques such as linear regression, logistic regression, support vector machine, decision tree, and random forest algorithm. The proposed method is investigated with machine learning classification techniques in terms of accuracy and time analysis. Random forest algorithm gives the accuracy of 92.15% and time consumption of 0.2 milli seconds. From this analysis, our proposed method with random forest algorithm is significantly better compared to other classification techniques.
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Two different skeletally modified cardanol based asymmetric benzoxazines monomers, cardanol-aminophenol/
p
-toludine and cardanol-aminophenol/4-fluoroaniline, were synthesized using cardanol, ...4‑aminophenol,
p
-toludine/4-fluoroaniline and paraformaldehyde through Mannich condensation reaction. The molecular structure of the benzoxazine monomers was confirmed by FTIR and
1
H-NMR spectral analyses. Cure behavior and thermal stability were studied using differential scanning calorimetry and thermogravimetric analysis respectively. It was found that these benzoxazines exhibit marginally lower polymerization temperature than that of conventional benzoxazines. The formation of polybenzoxazine was confirmed by FTIR analysis after the thermal curing through the cleavage of benzoxazine ring and subsequently led to the formation of three-dimensional cross-linked network structure. Among the polybenzoxazines studied, poly(cardanol-aminophenol/4-fluoroaniline) possess better thermal stability than that of poly(cardanol-aminophenol/
p
-toludine) due to fluoro substitution in the molecular structure of benzoxazine. Both polybenzoxazines exhibit an excellent thermal and hydrophobic behavior.
The security in a mobile ad hoc networks is more vulnerable and susceptible to the environment, because in this network no centralized environment for monitoring individual nodes activity during ...communication. The intruders are hacked the networks either locally and globally. Now a day’s mobile ad hoc network is an emerging area of research due to its unique characteristics. It’s more vulnerable to detect malicious activities, and error prone in nature due to their dynamic topology configuration. Based on their difficulties of intrusion detection system, in this paper proposed a novel approach for mobile ad hoc network is Fuzzy Based Intrusion Detection (FBID) protocol, to identify, analyze and detect a malicious node in different circumstances. This protocol it improves the efficiency of the system and does not degrade the system performance in real time.This FBID system is more efficient and the performance is compared with AODV, Fuzzy Cognitive Mapping with the following performance metrics: Throughput, Packet Delivery Ratio, Packets Dropped, Routing overhead, Propagation delay and shortest path for delivering packets from one node to another node. The System is robust. It produces the crisp output to the benefit of end users. It provides an integrated solution capable of detecting the majority of security attacks occurring in MANETs.
Time series data mining becomes an active research area due to the rapid proliferation of temporal-dependent applications. Dimensionality reduction and uncertainty handling play a pivotal role in ...extracting the time series pattern. Most of the dimensionality reduction schemes are designed based on the assumption that every class of samples follows the Gaussian distribution. Lack of this property in real time data distribution does not allow dimensionality reduction techniques to characterize the different classes well and measure the data uncertainty accurately. In addition to, applying an uncertainty measurement evenly on inconsistent time series data samples may underestimate the source of uncertainty among various sub-samples. This paper presents the Handling UNcertainty and missing value prediction in Time series (HUNT). The proposed approach employs Adaptive Reservoir Filling for sampling the time series and Discrepant Sample dependent Chebyshev inequality for handling the uncertainty. The HUNT implements the adaptive reservoir filling using discrepancy estimation over a statistical population and decides the reservoir size according to the variations in the data stream. The state of the statistical population ensures the uncertainty handling over discrepant samples. The proposed approach precisely replaces the missing values with the support of the Mean-Mode imputation method. To effectively select the key features, it applies both the indirect and direct performance measures on the statistical samples. Finally, the proposed model generates the fine-tuned statistical samples through segmentation to facilitate the time series pattern matching. The experimental results demonstrate that the HUNT approach significantly outperforms the existing time series pattern matching approaches such as KSample approach by 18% higher recall and UG-Miner approach by 20% minimum Mean Absolute Error (MAE) while testing on the Weather forecasting dataset.
The use of bio-based materials has become a focus of research nowadays. For the development of new generations of advanced resources, renewable and available resources must be combined with advanced ...technologies. Researchers have looked into biomass and waste cellulosic materials as sustainable sources for nano-crystalline cellulose extraction. Besides the different treatment methods suitable for various applications, this review aims to provide integrated details on the extraction methods and applications of cellulosic fibers and cellulose nanocrystals derived from wastes of different sources. There are numerous applications including building materials, electronics, furniture, automobiles, medical applications, sports goods, filtrations, water purification, and delivery systems of drugs which have been discussed.
Fibres derived from waste can be used in textile industries, cosmetics, wastewater treatment, etc. In the present study, the potential use of biosorbent material obtained from
Cucumis melo
for the ...removal of antibiotic, cationic and anionic dyes from aqueous solutions have been investigated. Seed coat from
C. melo
have been used to extract cellulose fibres which were characterised using ultraviolet–visible spectroscopy (UV–Vis), Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction spectroscopy (XRD). The rheological properties such as moisture and ash content, amount of cellulose, lignin, hemicellulose of fibre and its thermal stability using thermogravimetric analysis (TGA) and differential thermal analyser (DTA) and bioactivity like antibacterial and antioxidant activities for the seed coat and the extracted fibre were examined. Furthermore, superparamagnetic iron oxide nanoparticles (SPIONs) were synthesised using co-precipitation method and was coated onto the extracted fibre and used for the removal of different dyes and antibiotic. It was observed that SPION-coated muskmelon fibre showed highest removal of dyes—crystal violet, methylene blue, Congo red and antibiotic rifampicin—with the percentage 79.67%, 60.55%, 91.98% and 72.79%, respectively, compared with seed coat and extracted fibre. Results suggest that the biosorbents from
C. melo
could be an effective and eco-friendly alternative for the removal of pollutants from aqueous contaminations.
INTRODUCTION: Pharmaceuticals evolve alongside advancing technology driven by ongoing research and pharmaceutical companies’ production of new medications. Ongoing research and adjustment are ...necessary for various aspects of the pharmaceutical sector, such as patient understanding, drug testing, manufacturing, and communication of complex concepts through technology. OBJECTIVES: This paper discusses the intersection of cloud computing, technological advancements, and healthcare applications. METHODS: The Azure Cloud facilitates data processing, customer and patient engagement, employee and care team empowerment, clinical and operational optimisation, and healthcare digital transformation in the pharmaceutical industry. The integration of Microsoft Azure cloud technologies inside the pharmaceutical industry is examined in this research. RESULTS: Analysing how Internet of Things (IoT) sensors and the Industrial Internet of Things (IIoT) are used in pharmaceutical manufacturing and logistics, benefits in drug research, production monitoring and supply chain optimisation are highlighted. CONCLUSION: Cloud computing's potential to facilitate General Data Protection Regulation compliance, improve security, and promote innovation is explored.
Gamma radiation inactivation of phytohemagglutinin (PHA) of red kidney bean in purified form as well as in seeds in different moisture conditions was demonstrated at different doses viz. 1, 10, 30, ...50, 100 and 200 kGy. Irradiation of PHA in dry state (99.5% dry) or in 50% moisture condition showed structural intactness as studied by SDS–PAGE, size exclusion chromatography (SEC), fluorescence measurement, CD spectroscopy below 30 kGy, while a 50% reduction in hemagglutinin and mitogenic activity was observed in the dose range of 30–50 kGy. Radiation inactivation of purified PHA was more pronounced when irradiated in aqueous solution form resulting in complete destruction of secondary and tertiary structure as well as function at a dose of 10 kGy. Radiation processing of dry and soaked seeds of kidney bean exhibited 50% loss in functional activity of PHA at the doses of 50 and 30 kGy, respectively. Practicality of implication of the radiation processing for inactivation of this antinutrient in legume seeds is discussed.
•Structural stability of pure PHA towards gamma radiation is moisture dependent.•Gamma radiation inactivates purified PHA in dry and 50% moisture condition at 30 kGy.•Irradiation of PHA solution destroyed the structure completely at dose ≥10 kGy.•50% loss in hemagglutination activity was observed at dose of 50 kGy in kidney bean seeds.
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