Potassium (K+) is the most important cationic nutrient for all living organisms. Its cellular levels are significant (typically around 100mM) and are highly regulated. In plants K+ affects multiple ...aspects such as growth, tolerance to biotic and abiotic stress and movement of plant organs. These processes occur at the cell, organ and whole plant level and not surprisingly, plants have evolved sophisticated mechanisms for the uptake, efflux and distribution of K+ both within cells and between organs.
Great progress has been made in the last decades regarding the molecular mechanisms of K+ uptake and efflux, particularly at the cellular level. For long distance K+ transport our knowledge is less complete but the principles behind the overall processes are largely understood.
In this chapter we will discuss how both long distance transport between different organs and intracellular transport between organelles works in general and in particular for K+. Where possible, we will provide examples of specific genes and proteins that are responsible for these phenomena.
Potassium (K⁺) is the most important cationic nutrient for all living organisms. Vacuolar two‐pore K⁺ (TPK) channels are important players in the regulation of cellular levels of K⁺ but have not been ...characterised in rice. In order to assess the role of OsTPKb, a K⁺ selective ion channel predominantly expressed in the tonoplast of small vacuoles, we generated overexpressing (OX) lines using a constitutive promoter and compared their phenotypes with control plants. Relative to control plants, OX lines showed better growth when exposed to low‐K⁺ or water stress conditions. K⁺ uptake was greater in OX lines which may be driven by increased AKT1 and HAK1 activity. The enhanced K⁺ uptake led to tissue K⁺ levels that were raised in roots and shoots. Furthermore, energy dispersive X‐ray (EDX) analyses showed a higher cytoplasm: vacuole K⁺ ratio which is likely to contribute to the increased stress tolerance. In all, the data suggest that TPKb can alter the K⁺ status of small vacuoles, which is important for general cellular K⁺ homeostasis which, in turn, affects stress tolerance.
Climate change is one of the most dangerous and complex issues human being has ever encountered. Pakistan is one of the highly vulnerable countries to the effects of climate change. CO2 emission from ...the combustions of fossil fuels is usually considered as the major factor of climate change. This study attempted to analyze the energy related CO2 emissions in Pakistan for a sample period of 1990–2014. The LMDI (Logarithmic Mean Divisia Index) method is applied to extended Kaya identity to decompose the change in emissions into pre-determined factors. According to our analysis, the increase in GDP per capita and populations are the major factors responsible for the increase in energy related CO2 emissions. Carbon intensity contributes to the reduction of emissions. Energy intensity and fuel substitution has mixed and unstable effect on the reduction of emission. The decomposed effects are also used in predicting future CO2 emission for the period 2015–2025. Based on the predicted results, the reduction potential of CO2 emissions in Pakistan is estimated, using special designed scenario analysis. The findings show that emissions will reach 251.5 Mt CO2 in 2025 as per BAU (Business as usual) scenario. The reduction potential for the year 2025 is estimated as 28.94 Mt CO2 and 55.02 Mt CO2 as per moderate and aggressive emission reduction scenario, respectively. The findings show that carbon tax, energy price reforms, diversification of energy supply in favor of cleaner energy and energy conservation are critical to materialize the emission reduction potential.
•We employed LMDI method on Kaya identity to decompose changes in CO2 emissions.•GDP per capita and population are the leading factors increasing CO2 emissions.•Carbon intensity is the key factor reducing CO2 emissions.•Scenario analysis shows a huge reduction potential of CO2 emissions in Pakistan.
This study presents the effect of ethylene vinyl acetate (EVA) on the setting time of cement at different temperatures as well as on the compressive, flexural and tensile strength of concrete. ...Setting time tests were conducted at various percentages of EVA at different temperatures (i-e 22, 35 and
50
∘
C
). It was found that the setting time was increasing with an increase in the EVA percentage. Moreover, for strength evaluation, samples of EVA-modified concrete were prepared with various percentages of EVA by weight of cement and then tested for compressive, flexural and tensile strength at the curing age of 3, 7 and 28 days. The results revealed that the compressive and flexural strength of EVA-modified concrete tended to increase at a rapid rate by incorporating EVA up to 16%, but beyond this percentage the rate of strength development become slow at all the ages, but in case of split tensile strength, it was maximum at 4% EVA and got decreased with further increase in EVA percentage.
•Emphasizes 3ϕ GCPV system protection with evaluating fault ride through for LVRT/HVRT.•Introduces Machine Learning (ML) based fault classification approach for 3ϕ GCPV.•Enhancing fault detection ...through Weighted KNN & SVM based on Wavelet Transform.•Highlights the continuous need for fault detection improvement through ML techniques.•Fine Gaussian SVM's higher accuracy over Weighted KNN in GCPV condition monitoring.
Power systems protection has become more vital in recent years to ensure stability, reliability, security, and power quality due to the exponential growth of grid-connected photovoltaic (GCPV) systems. As a result, several nations have set new grid codes for the grid integration of PV plant installations to overcome these concerns. Investigating Fault Ride Through (FRT) capacity is one of the primary criteria for grid codes. For 3-phase GCPV systems, fault detection and classification approaches are proposed in this study. Firstly, different faults that occurred in the GCPV system are categorized and compared, with the critical and analytical evaluation of grid codes, particularly FRT requirements such as Low Voltage Ride Through (LVRT) and High Voltage Ride Through (HVRT) for different nations. Further, a detailed classification and a comparison of the existing FRT techniques are presented for better control methods based on system complexity, detection accuracy, and other evolutionary criteria. To ensure smooth grid operation, accurate fault detection and condition monitoring of the systems are required. This paper discusses a machine learning (ML) based technique for detecting faults in 3-phase GCPV systems. Multi-peak phenomena caused by FRT capabilities and anti-islanding detection are the main problems experienced while integrating a PV system into the local grid. The fault classification technique is developed using weighted K-nearest neighbor (WKNN) and fine Gaussian support vector machine (FGSVM) based ML approaches utilizing Wavelet Transform. The proposed ML-based findings show that the fault detection algorithm-based classification accuracy has significantly improved.
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Nitrogen (N) availability is crucial in regulating plants' abiotic stress resistance, particularly at the seedling stage. Nevertheless, plant responses to N under salinity conditions may vary ...depending on the soil's NH.sub.4.sup.+ to NO.sub.3.sup.- ratio. In this study, we investigated the effects of different NH.sub.4.sup.+:NO.sub.3.sup.- ratios (100/0, 0/100, 25/75, 50/50, and 75/25) on the growth and physio-biochemical responses of soybean seedlings grown under controlled and saline stress conditions (0-, 50-, and 100-mM L.sup.- 1 NaCl and Na.sub.2SO.sub.4, at a 1:1 molar ratio). We observed that shoot length, root length, and leaf-stem-root dry weight decreased significantly with increased saline stress levels compared to control. Moreover, there was a significant accumulation of Na.sup.+, Cl.sup.-, hydrogen peroxide (H.sub.2O.sub.2), and malondialdehyde (MDA) but impaired ascorbate-glutathione pools (AsA-GSH). They also displayed lower photosynthetic pigments (chlorophyll-a and chlorophyll-b), K.sup.+ ion, K.sup.+/Na.sup.+ ratio, and weakened O.sub.2.sup.*--H.sub.2O.sub.2-scavenging enzymes such as superoxide dismutase, catalase, peroxidase, monodehydroascorbate reductase, glutathione reductase under both saline stress levels, while reduced ascorbate peroxidase, and dehydroascorbate reductase under 100-mM stress, demonstrating their sensitivity to a saline environment. Moreover, the concentrations of proline, glycine betaine, total phenolic, flavonoids, and abscisic acid increased under both stresses compared to the control. They also exhibited lower indole acetic acid, gibberellic acid, cytokinins, and zeatine riboside, which may account for their reduced biomass. However, NH.sub.4.sup.+:NO.sub.3.sup.- ratios caused a differential response to alleviate saline stress toxicity. Soybean seedlings supplemented with optimal ratios of NH.sub.4.sup.+:NO.sub.3.sup.- (T3 = 25:75 and T = 4 50:50) displayed lower Na.sup.+ and Cl.sup.- and ABA but improved K.sup.+ and K.sup.+/Na.sup.+, pigments, growth hormones, and biomass compared to higher NH.sub.4.sup.+:NO.sub.3.sup.- ratios. They also exhibited higher O.sub.2.sup.*--H.sub.2O.sub.2-scavenging enzymes and optimized H.sub.2O.sub.2, MDA, and AsA-GSH pools status in favor of the higher biomass of seedlings. In summary, the NH.sub.4.sup.+ and NO.sub.3.sup.- ratios followed the order of 50:50 > 25:75 > 0:100 > 75:25 > 100:0 for regulating the morpho-physio-biochemical responses in seedlings under SS conditions. Accordingly, we suggest that applying optimal ratios of NH.sub.4.sup.+ and NO.sub.3.sup.- (25/75 and 50:50) can improve the resistance of soybean seedlings grown in saline conditions.
Nature has the potential to reduce metal salts to their relative nanoparticles. Traditionally, physical and chemical methods were used for the synthesis of nanoparticles but due to the use of toxic ...chemicals, non-ecofriendly methods and other harmful effects, green chemistry approaches are now employed for synthesizing nanoparticles which are basically the most cost effective, ecofriendly and non-hazardous methods. In this review, we aimed to evaluate and study the details of various mechanisms used for green synthesis of silver nanoparticles from plants, their size, shape and potential applications. A total of 150 articles comprising both research and review articles from 2009 to 2019 were selected and studied in detail to get in-depth knowledge about the synthesis of silver nanoparticles specifically through green chemistry approaches. Silver ions and their salts are well known for their antimicrobial properties and have been used in various medical and non-medical applications since the emergence of human civilization. Miscellaneous attempts have been made to synthesize nanoparticles using plants and such nanoparticles are more efficient and beneficial in terms of their antibacterial, antifungal, antioxidant, anti-biofilm and cytotoxic activities than nanoparticles synthesized through physical and chemical processes. Silver nanoparticles have been studied as an important research area due to their specific and tunable properties and their application in the field of biomedicine such as tissue and tumor imaging and drug delivery. These nanoparticles can be further investigated to find out their antimicrobial potential in cell lines and animal models.
The rapid urbanization and changing climate patterns in Swat, Pakistan have increased the vulnerability of urban areas to flood events. Accurate assessment of flood risk is crucial for effective ...urban planning and disaster management. In current research study flood hazard index was developed using analytic hierarchy process (AHP) technique in combination with the geographical information system (GIS) environment in Swat, Pakistan. The study integrates various data sources, including topographic maps, land use/land cover information, rainfall data, and infrastructure data, to develop a comprehensive flood risk assessment model. The weights obtained from the AHP analysis are combined with geospatial data using a geographic information system (GIS) to generate flood risk maps. The flood hazard levels were categorized into five distinct classes: very low, low, moderate, high, and very high. Using the GIS-AHP approach, higher weights were assigned to rainfall, distance to river, elevation, and slope in comparison to NDVI, TWI, LULC, curvature, and soil type. The flood hazard map was then reclassified for each parameter. By overlaying these maps, it was determined that 5.6% of the total area is classified as very high flood risk, 52% as high risk, 39.3% as moderate risk, and 3.1% as low risk. The developed comprehensive flood risk assessment model in current study can identify high-risk areas, prioritize mitigation measures, and aid in effective urban planning and disaster management.
The article provides an α-cut-based method that solves linear fractional programming problems with fuzzy variables and unrestricted parameters. The parameters and variables are considered as ...asymmetric triangular fuzzy numbers, which is a generalization of the symmetric case. The problem is solved by using α-cut of fuzzy numbers wherein the α- and r-cut are applied to the objective function and constraints, respectively. This reduces the problem into an equivalent biobjective model which leads to the upper and lower bounds of the given problem. Afterwards, the membership functions corresponding to various values of r∈(0,1 are obtained using the optimal values of the biobjective model. The proposed method is illustrated by taking an example from the literature to highlight the fallacy of an existing approach. Finally, a fuzzy linear fractional transportation problem is modelled and solved using the aforementioned technique.
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