Search

The significance of connectedness and compactness plays a vital role in studying the properties of topological spaces. Numerous authors explored several characterizations of topological spaces using these notions. Researchers had attempted to generalize the concepts of connectedness and compactness in various generalized topological spaces like ideal topological spaces, soft topological spaces, fuzzy topological spaces etc. In the year 2013, Babitha and John studied the concept of connectedness in soft multi topological spaces. Since then the study of these concepts has created a gap in the literature. The uniosity about the generalizations of connectedness and compactness in soft multi topological spaces explored this article.

A challenge for “Big Data” in the chemical production industry is not only to evaluate file storage but also to use online information to improve process performance. It should be spectral, vibration, thermal, and other sensors are more and more widely available. In today's harsh industrial conditions, accurate and reliable reviews or product quality assessments are critical. To predict important attribute factors utilizing quantifiable signals, information soft sensors dependent on Projection to Latent Structure (PLS) techniques are frequently used. However, due to changes in equipment, raw material, sensors, or management, most operations are carried out under real and stable conditions. The structure of the flexible sensors must be maintained at regular intervals. Reconstruction of the method using more recent sensor primary data focus of current design maintenance techniques, such as mobile window updates and recursive updates within the enterprise. In situations where data were collected with extremes, downtimes, and other transients in the non-stationary phase, this strategy was not sufficiently resilient. An alternative model update strategy was reviewed as part of this study. To assess the effectiveness of the current soft sensor approach, they modified two Key Performance Indicators (KPIs). The residue-dependent forecast KPI identifies long-term forecast damping models using a filtered estimation error. The KPI dependent on T2 would be a forecast KPI that checks the system's speculations to the expected original data. This updated strategy is effective in improving predictive accuracy without completely reconstructing the PLS model using research papers using industrial operations information. Finally, the KPI attributes and model upgrade mechanism could be used together. The researchers demonstrated that this update technique significantly improved the accuracy of the PLS soft detector predictions through the emulation of live behavior using industrial data. The configuration technique also made it possible to quickly identify underlying issues in situations where the original sample was ideal as well as informed engineers that a new method needed to be built.

The Internet of Things (IoT) was developed through information improvement and communications technologies. As IoT technologies used in a multitude of health settings make life easier for doctors and clients in the current medical system. The IoT advancements to medicine would be the Body Sensor Network (BSN) platform allows for the monitoring of patients utilizing a network of wireless sensor nodes were lightweight or small-powered. Furthermore, the lack of security considerations in creating this modern technology for health systems compromises medical confidentiality. The primary protection needs for a BSN-based modern healthcare system were initially highlighted. Therefore, proposedBSN-Care, an effective IoT-based medical system that allows BSN to efficiently address these needs.

Heat and Water Deficit Stress (WDS) tend to impede and restrict the efficiency of photosynthesis, chlorophyll fluorescence, and maximum photochemical quantum yield in plants based on their characteristic ability to interfere with the electron transport system in photosystem II. Dissection of the electron transport pathway in Photosystem II (PSII) under water deficit and Heat Stress (HS) can be insightful in gaining knowledge on the various attributes of the photosynthetic performance of a plant. We attempt a high-resolution dissection of electron transport in PSII with studies on chlorophyll a fast fluorescence kinetics and non-photochemical quenching (NPQ) as a response to and recovery from these stresses in pearl millet [Pennisetum glaucum (L.) R. Br.] in isolation and combination. In this study, we bring out the mechanisms by which both heat and water stress, in isolation and in combination, affect the photosynthetic electron transport in Photosystem II. Our results indicate that oxygen evolution complex (OEC) damage is the primary effect of heat stress and is not seen with the same intensity in the water-stressed plants. Low exciton absorption flux in heat stress and combined stress was seen due to OEC damage, and this caused an electron transport traffic jam in the donor side of PS II. Both the specific energy flux model and the phenomenological flux model developed from the derived values in our study show that water deficit stress in combination with heat stress has a much stronger effect than the stresses in isolation on the overall electron transport pathway of the PS II in pearl millet plants.

The coconut-based agricultural wastes have gained wide attention as an alternative adsorbent for the removal of diverse pollutants from the industrial effluents. This paper presents the zinc chloride activation of adsorbent carbon and the utilization as an adsorbent for the removal of malachite green dye from aqueous solution. The characterisation of activated carbon was performed to get an insight into the adsorption mechanism. The ZnCl2 activated carbon acquired a higher specific surface area (544.66 m2 g−1) and stability (−32.6 mV). The impact of process parameters including contact time (20–220 min) and initial dye concentration (20–80 mg L−1) were evaluated on the effectiveness of activated carbon for dye removal. The results concluded that zinc chloride activated carbon showed a significant dye adsorption (39.683 mg g−1) at an initial concentration of 20 mg L−1 after 3 hours. Based on the correlation coefficient (R2), the Freundlich isotherm model (0.978–0.998) was best fitted for the experimental data followed by the intraparticle diffusion model (0.88–0.929) as the most appropriate model for malachite green dye removal. Additionally, the energy and thermogravimetric analysis portrayed the suitability of the carbon material to be used as an energy alternative to coal.

Traditional recommendation approaches for the mobile Apps basically depend on the Apps related features. Now a days many users are in quench of Apps recommendation based on the version description. Earlier mobile Apps recommendation system do not handle the cold start problem and also lacks in time for recommending the related and latest version of Apps. To overcome this issues, a hybrid Apps recommendation framework which is considering the version of the mobile Apps is proposed. This novel framework named “Probabilistic Evolution based Version Recommendation Model (PEVRM)” integrates the principles of Probabilistic Matrix Factorization (PMF) with Version Evolution Progress Model (VEPM). With the help this novel recommendation algorithm, the mobile users easily identify the specific Apps for particular task based on its version progression. At same time, this framework helps in resolving cold start problems of new users. Evaluations of this framework utilize a benchmark dataset, i.e., Apple's iTunes App Store3, for revealing its promising performance.

In the early days, greenhouse energy did not pay much attention to coating inspections and new applications, spending more attention on repair solar energy projects instead. However, these attitudes have recently changed. Energy producers realize that preventing corrosion and deterioration is less expensive than solving the greenhouse problems when they occur. The proposed model also provides coating, paint control, and error analysis services within the scope of solar machinery and equipment-related services while the greenhouse equipment reached a low energy level. The greenhouse monitoring services ensure that a solar plant is economical, reliable, and of high quality, meets legal requirements, conforms to standards published by domestic and foreign organizations, and determines conditions that cause short circuits or power outages. In this context, with the help of cloud computing-based Internet of things (IOT), the industrial power stations, high-voltage substations, low-voltage networks, power stations that comply with legal regulations on safety from electricity, electrical installations for machinery, alarm systems, fire alarm systems, cathodic corrosion protection mechanisms in oil tanks and pipelines, emergency power supply installations, electrical installations in buildings, and gas alarm systems are inspected and documented.

Ozone stress identification in crops through remote sensing is a promising technology that has a major role in predicting stress-related physiological response. The spectral reflectance approach to phenotyping of rice cultivars is a non-destructive and accurate method to assess ozone stress. In this study, the leaf spectral reflectance of 15 rice cultivars was explored to evaluate the photosynthetic capacity under elevated ozone stress. Ozone injury percentage (OIP), a common indicator to identify ozone stress of rice leaves combined with leaf spectral signatures was used to identify the best fit spectral indices. The normalized difference spectral index (NDSI) was used to determine significant wavebands that showed the best correlation with leaf ozone injury. The correlation coefficient (r) between NDSI and OIP were ranged from -0.79 to 1. Normalized difference spectral index, NDSI[R564,R568], and NDSI[R558,R573] were identified as the best Pearson's correlation with leaf ozone injury percentage with correlation coefficient more than 0.96. The evaluated NDSI in visible regions were identified as a sensitive region to ozone injury. Additionally, results were compared with previously established indices and also evaluated for correlation with plant physiological traits. The correlation coefficient of determination (R2) > 0.5 was observed for newly developed spectral indices, NDSI[R564,R568] and NDSI[R558,R573] with physiological traits compared to previously established 20 indices. The highest R2 of 0.674 were observed for the spectral index, NDSI[R558,R573] with photosynthetic rate and R2 of 0.673 for NDSI[R564,R568] with relative chlorophyll content. As a result, the current research has implications for the selection of the best capable spectral regions for early detection of ozone stress in rice cultivars without destructing the crop. The outcome of the present work suggests that newly developed spectral indices could assist in remote sensing technology in monitoring large scale ozone stress and crop modeling studies to ensure food security.

Four groundnut (Arachis hypogaea L.) genotypes- Narayani, Dharani, K-6 and K-9 were assessed for growth and yield responses at elevated temperature of 3.0 ± 0.5°C above ambient canopy temperature (eT) and its interaction with elevated CO of 550 ± 50ppm (eT+eCO ) under Free Air 2 2 Temperature Elevation (FATE) facility. The study revealed that eT significantly decreased photosynthetic rate (A ) of all groundnut genotypes whereas eT+eCO condition ameliorated the ill effects of eT. The net 2 impact of eT on A was higher than transpiration rate (Tr) and this reflected in decreased WUE with all net genotypes. WUE improved significantly at eT+eCO with increased A and decreased Tr. Increase in 2 net canopy temperature (eT) resulted decreased relative water content (RWC), cell membrane stability and increased osmotic potential, Malondialdehyde (MDA) content and accumulation of proline. Elevated CO 2 along with eT (eT+eCO ) facilitated these parameters to recover to that of ambient controls, revealing the 2 ameliorative effect of eCO . Similar responses were recorded for biomass and yield parameters. Among 2 the selected groundnut genotypes, superior performance for seed yield at high temperature of >40°C by K-9 was due to ability to maintain better reproductive capacity and Dharani was responsive to elevated CO even at high temperature, indicating the genotypic variability.

A field experiment was conducted with maize (Zea mays L.) hybrid DHM-117 under elevated temperature and moisture deficit stress to assess the phenology, physiology, biomass and yield responses. The elevated canopy temperature (ET) was maintained as 3°C above ambient canopy temperature (AT) in Free Air Temperature Elevation (FATE) facility and water deficit stress (WD) was imposed at initiation of tasseling stage in an open plot experiment to assess the impact of these two abiotic stresses. As compared with ambient control, the phenology of flowering with the ET was early as 3 days for anthesis, 1 day for silking and this increased 4 days for anthesis silking interval (ASI), while with WD, anthesis was delayed by 2 days, silking by 3 days and ASI increased by 3 days. It was observed that both ET and WD significantly decreased photosynthetic rate (32%, 24%), stomatal conductance (45%, 28%), transpiration rate (36%, 44%) while increased WUE (6%, 38%). It is interesting to record that there was reduction in total biomass (11%, 13%) especially reproductive biomass (44%, 31%) with both ET and WD while vegetative biomass was improved (27%, 8%) revealing that reproductive components are effected with these abiotic stresses thereby decreased HI (42%, 36%). The impact of ET was more on seed set than seed filling as the reduction in test weight (8%) was higher than at WD (4%).

Sunflower Hybrid (KBSH-1) was cultivated in Open Top Chambers (OTCs) at ambient (380 ppm) and elevated CO2 (550 and 700ppm) conditions. Biomass accumulation in root, stem, head and seed was significantly greater at elevated CO2 (550 ppm and 700ppm) compared with ambient (380 ppm).The improvement in total biomass with 550 and 700 ppm CO2was 18.7 per cent and 40.5 percent and seed yield was 21.0 per cent and 45.9 per cent respectively compared to ambient. The positive growth response to increased atmospheric CO2 resulted in N and C concentrations. Although elevated CO2 levels tended to lower N concentration in some plant parts compared to ambient, elevated CO2 enhanced total N accumulation in each plant component via an increase in biomass.Elevated CO2 decreased the N per cent compared to ambient in seed meal, leaf and stem. At the recommended dose of nutrients, the total N uptake was high in plants grown at 700 ppm (1.25 g per plant), followed by 550 ppm (1.11g per plant) and ambient (0.96 11 g per plant). At the recommended dose of nutrients, physiological N use efficiency (PE) and grain N use efficiency (NUEg) was also high in plants grown at elevated CO2 in OTCs and nitrogen harvest index (NHI) was similar for ambient (70.3%) and elevated CO2 conditions (70.4 and 70.2 per cent at 550 ppm and 700 ppm).The total carbon accumulation was high in plants grown at 700 ppm, followed by 550 ppm and ambient.The C/N ratio of plants was high at elevated CO2 conditions being 21.2, 20.0 and 19.0 at 700, 550ppm and ambient control respectively.

Sunflower (Helianthus annuus L.) and maize (Zea mays L.) were chosen as C3 and C4 crop plants and assessed for the impact of enhanced CO2 (700 ppm) and its interaction with drought stress in open top chambers (OTCs). The ameliorative effect of higher CO2 concentration (eCO2) under drought stress was quantified. It is interesting to note that the C3 crop responded significantly and positively with eCO2 under both well-watered and drought stress treatments for root: shoot ratio while C4 crop showed a better response only with the drought stress environment. Root volume showed a positive significant response with CO2 concentration enhanced over ambient level and the increment in root volume was 146% and 340% in sunflower and maize crops, respectively. The leaf water potential, stomatal conductance and transpiration showed a decreasing trend in both the crops with drought stress and eCO2 showed an ameliorative effect leading to higher Pn rates in sunflower crop under drought stress treatment. The findings reveal that improvement of root traits is worth attempting for the future crop behavioral responses under eCO2 and drought stress environments. The study confirmed the beneficial effect of eCO2 in maize and sunflower by ameliorating the adverse affects of drought stress.

Sorghum bicolor L. Moench cv. SPV462 was transformed with the mtlD gene encoding for mannitol-1-phosphate dehydrogenase from E. coli with an aim to enhance tolerance to water deficit and NaCl stress. Transgene (pCAM mtlD) integration and expression were successfully confirmed by PCR, Southern, RT-PCR and Western analysis. Segregation analysis based on germination of T0 seed on hygromycin-supplemented medium revealed an expected Mendelian ratio 3:1 in lines 5, 72 and 75. Retention of leaf water content was remarkably higher in transgenic leaf segments when exposed to polyethylene glycol 8000 (-2.0 MPa), as compared to the untransformed controls. Another significant finding is that the transgenics maintained a 1.7 to 2.8 fold higher shoot and root growth, respectively, under NaCl stress (200 mM) when compared to untransformed controls. These results demonstrate that engineering mannitol biosynthetic pathway into sorghum can impart enhanced tolerance to water deficit and salinity.

Pigeon pea (Cajanus cajan L. Millsp.) is an important grain legume crop of the semi arid tropics and is a major dietary protein source. The extra short duration cultivar of pigeon pea ICPL 88039 was evaluated at ambient(370 μmol/mol) and twice the ambient (700 μmol/mol) concentrations of CO2 in open top chambers (OTCs). The results showed that the crop recorded a significant positive enhanced response for total biomass, fodder yield, grain yield, number of pods and seeds per plant, test weight and HI at elevated CO2. The ANOVA revealed significant differences in response of the characteristics to CO2 concentrations. Under elevated CO2 the total biomass recorded an improvement of 91.3%, grain yield 150.1%, fodder yield 67.1%. The major contributing components for improved grain yield under elevated CO2 were number of pods, number of seeds and test weight which recorded an increase of 97.9%, 119.5% and 7.2%, respectively. The crop maintained a significant positive increase of harvest index (HI) at elevated CO2 with an increment of 30.7% over ambient values. This increase in HI was due to its improved pod set and seed yield under enhanced CO2 concentration thereby emphasizes this crop for sustained food with nutritional security under climate change scenario.

The response of blackgram (Vigna mungo L. Hepper) to two levels of elevated carbon dioxide (550 and 700 ppm) in terms of growth and yield was investigated and compared with ambient CO2 level (365 ppm) using open-top chambers. The growth parameters viz., length and weight of root and shoot, root:shoot ratio, leaf area and weight significantly increased at 700 ppm CO2 when compared with 550 ppm. The percentage increase in total biomass at 700 and 550 ppm CO2 was 65.4% and 39%, respectively compared to the ambient (chamber) control. The increase in total seed yield at 700 ppm (129%) was due to an increase in number of pods per plant and 100 seed weight, whereas at 550 ppm (88.7%) it was due to an increased number of pods/plant and seeds/pod. The results indicate variable responsive effects at different levels of CO2 emphasizing the pertinence of research on elevated CO2 in various agroecological inhabitations all over the world. The indication of higher responses for root and leaf at initial growth stages at the higher elevated level of CO2 (700 ppm), which leads to better root establishment, achieving early photosynthetic efficiency and also better biomass production, and its improved partitioning can be reckoned as a positive aspect of increasing concentrations of CO2 in atmosphere. The harvest index increased significantly to 35.7 and 38.4% at 550 and 700 ppm, respectively; it is a very important phenomenon in pulses for breaking the yield barrier.

A study was conducted with two important rainfed food crops viz., sorghum (Sorghum bicolor L. Moench.) and blackgram (Vigna mungo L. Happer) and two oil seed crops viz., sunflower (Helianthus annuus L.) and groundnut (Arachis hypogaea L.) under two conditions viz., elevated CO2 (600 ppm) and ambient CO2 (365 ppm) in open top chambers (OTCs). The observations were recorded at the vegetative stage at 7, 14, 21 and 30 days after sowing (DAS). The results showed significant differences between crops, conditions and time intervals, as well as the single and double order interactions for all the characters studied viz., total dry weight, stem dry weight, root dry weight, leaf dry weight, shoot length, root length and leaf area. Total dry weight and its components viz., stem dry weight, root dry weight and leaf dry weight along with leaf area showed a significant increase under enhanced CO2 conditions. Among the four crops studied the overall results showed the highest response to elevated CO2 by blackgram while the lowest response by sorghum.

The compounds in pharmaceutical and personal care products (PPCPs) that may be potential environmental pollutants include metformin and triclosan. The suitable method to estimate the presence of metformin (MET) and triclosan (TRI) in wastewater treatment facilities is developed and validated in this research study. This study aimed to quantify the MET and TRI in sewage through a liquid chromatograph – mass spectrometer (LC-MS 8040) by a Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) technique of sample preparation. In LC-MS 8040, the Milli-Q water and sewage were examined at three different concentrations (0.01, 0.02 and 0.03 mg L−1) of MET and TRI. The recoveries of MET in both the matrixes ranged between 88.10 to 116.10% whereas the recoveries were ranged from 86.70 to 116.30% for TRI (n = 7, RSD <10%). The respective limit of detection (LOD) and the limit of quantification (LOQ) for MET and TRI were 0.005 and 0.01 mg L−1. With the matrix effect of < 10% in sewage, the approach was shown to be very linear (R2 = 0.9969 for MET and R2 = 0.9939 for TRI) and reliable. The precision was also exemplary with the RSD value of < 10% (n = 6). This method accurately assessed MET (BDL to 0.0657 mg L−1) and TRI (BDL to 0.1833 mg L−1) concentrations in sewage samples of Ukkadam sewage treatment plant (USTP) and Tamil Nadu Agricultural University treatment plant (TSTP). This is a unique use of the QuEChERS method for calculating these two compounds from aqueous matrixes with substantially greater outputs (20–25 samples per day) than typical Solid Phase Extraction (SPE) procedures. [ABSTRACT FROM AUTHOR]