Smart Energy Management System for Minimizing Electricity Cost and Peak to Average Ratio in Residential Areas with Hybrid Genetic Flower Pollination Algorithm

Demand Side Management (DSM) plays a significant role in the smart grid to minimize Electricity Cost (EC). Home Energy Management Systems (HEMSs) have recently been studied and proposed explicitly for HEM. In this paper, we propose a novel nature-inspired hybrid Genetic Flower Pollination Algorithm (GFPA) to minimize cost with an affordable delay in appliance scheduling. Our proposed GFPA algorithm combines elements of the Genetic Algorithm (GA) and Flower Pollination Algorithm (FPA) to create a hybrid approach. To assess the effectiveness of the proposed algorithm, we consider a scalable town consisting of 1, 10, 30, and 50 homes, respectively. The proposed solution finds an optimal scheduling pattern that simultaneously minimizes EC and Peak to Average Ratio (PAR) while maximizing User Comfort (UC). We assume that all homes are homogeneous regarding appliances and power consumption patterns. Simulation results show that our proposed scheme GFPA performs better when applying Critical Peak Pricing (CPP) signal using different Operational Time Intervals (OTIs) and compared with unscheduled, GA, and FPA-based solutions in terms of reducing cost since they achieve on average 98%, 36%, 23%, and 22%, respectively. Similarly, PAR averages 98%, 36%, 59%, and 55%, respectively. While, UC comparing to GA and FPA, are around 88%, 48%, and 63%, respectively. Our proposed scheme achieves better results by applying Real Time Pricing (RTP) signals and different OTIs. As these schemes, i.e., unscheduled, GA, FPA, and GFPA, achieve cost on average 92%, 50%, 29%, and 28%, respectively. While PAR on average 94%, 39%, 62%, and 56%, and UC for GA, FPA, and GFPA on average 98%, 52%, and 49%, respectively. Overall, ourproposed GFPA algorithm offers a more effective solution for minimizing EC with an affordable delay in appliance scheduling while considering PAR and UC

Efficacy assessment of diatomaceous earth against Callosobruchus maculatus (F.) (Coleoptera: Bruchidae) on gram at different temperature and relative humidity regimes

The efficacy of diatomaceous earth against Callosobruchus maculatus (Coleoptera: Bruchidae) was evaluated on stored gram under laboratory conditions. The bioassay was conducted at 25 and 30°C in combination with 50 and 60% r.h. Diatomaceous earth (DE) formulation (Diafil 610), at the dose rates of 200, 400, 600 and 800 ppm was admixed with gram grains. Fifty unsexed adults of C. maculatus were released in each jar and treatments replicated thrice. Mortality data was recorded after 2, 3 and 5 days of exposure intervals and after every count the dead individuals were removed, and the commodity was maintained for an additional period of 25 d, in order to record the emergence of F1 adults. The results showed that all treatments were highly effective against the bruchids; however, the highest mortality (100%) was observed at 30°C and 50% relative humidity at 800 ppm of DE with minimal progeny production.Keywords: Diatomaceous earth, Callosobruchus maculatus, Temperature, relative humidity, Gra

Changes in chlorophyll, phenols, sugars and mineral contents of cucumber plants infected with cucumber mosaic virus

Biochemical studies were made to monitor the relationship of chemical components and development of resistance in cucumber plants against Cucumber mosaic virus (CMV). Total soluble phenols, soluble sugars, chlorophyll and mineral nutrients; Potassium, Magnesium, Sodium and Lead were compared among resistant and susceptible varieties. Different metabolites showed different trends among diseased and healthy plants from resistant and susceptible groups of varieties. The phenolic and Magnesium contents increased in the inoculated plants of both susceptible and resistant genotypes. In resistant variety, rise in magnesium concentration in inoculated plants was less as compared to that of inoculated plants of the susceptible varieties. However, the chlorophyll, sugars, potassium were reduced in the inoculated plants of both reaction resistant and susceptible reaction groups. Plants from susceptible group presented a lower of level of nutrients as compared to un-inoculated ones whereas; the changes in sodium contents were not showing any relation to resistance mechanism

SCREENING FOR RESISTANCE TO CUCUMBER MOSAIC CUCUMOVIRUS IN CHILLI PEPPER

ABSTRACT Cucumber mosaic cucumovirus (CMV) is destructive pathogen with widest host range, infecting more than 100 botanical families comprising more than 500 genera and 1300 plant species. Chilli pepper is a significant cash crop of Pakistan among vegetable grown. The identification of genetic resistance to CMV in Pakistan (CMV chilli isolate) in chilli pepper is of economic importance. Thus, 40 Chilli pepper genotypes, both local and imported, were evaluated by mechanical/ manual virus inoculation and resistance to CMV chilli isolate was examined by visual observations and enzyme-linked immunosorbent assay (DAS-ELISA). On the basis of 0-5 disease rating scale and ELISA, nine genotypes viz., C-2, CV-2, CV-5, BSS-269, PGRI, M-2001, CM-2001, M-97 and CP-328 were remained free of infection and catalogued as highly resistant. Rest of the genotypes exhibited characteristic symptoms like mosaic, mottling, leaf curling and reduced leaf size depending upon tested genotypes. Among these genotypes, five were categorized as resistant, seven as moderately resistant, eight as moderately susceptible and 11 as susceptible. These resistant and moderate resistant genotypes could be used by farmers in cultivation under integrated production systems and by breeders in developing new chilli pepper hybrid resistant genotypes to CMV

AI-driven optimization of ethanol-powered internal combustion engines in alignment with multiple SDGs: A sustainable energy transition

With the escalating requirement for global sustainable energy solutions and the complexities linked with the complete transition to new technologies, internal combustion engines (ICEs) powered with biofuels like ethanol are gaining significance over time. However, problems linked to the performance and emissions of such ICEs necessitate accurate prediction and optimization. The study employed the integration of artificial neural networks (ANN) and multi-level historical design of response surface methodology (RSM) to address these challenges in alignment with the Sustainable Development Goals (SDGs). A single-cylinder spark ignition (SI) engine powered with ethanol-gasoline blends at different loads and speeds was used to gather data. Among six initially trained ANN models, the most efficient model with a regression coefficient (R2) of 0.9952 (training), 0.98579 (validation), 0.98847 (testing), and 0.99307 (overall) was employed to predict outputs such as brake power, brake specific fuel consumption (BSFC), brake thermal energy (BTE), concentration of carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen NOx. Predicted outputs were optimized by incorporating RSM. On implementing optimized conditions, it was observed that BP and BTE increased by 19.9%, and 29.8%, respectively. Additionally, CO, and HC emissions experienced substantial reductions of 28.1%, and 40.6%, respectively. This research can help engine producers and researchers make refined decisions and achieve improved performance and emissions. The study directly supports SDG 7, SDG 9, SDG 12, SDG 13, and SGD 17, which call for achieving affordable, clean energy, sustainable industrialization, responsible consumption, and production, taking action on climate change, and partnership to advance the SDGs as a whole respectively

NS4A protein as a marker of HCV history suggests that different HCV genotypes originally evolved from genotype 1b

<p>Abstract</p> <p>Background</p> <p>The 9.6 kb long RNA genome of Hepatitis C virus (HCV) is under the control of RNA dependent RNA polymerase, an error-prone enzyme, for its transcription and replication. A high rate of mutation has been found to be associated with RNA viruses like HCV. Based on genetic variability, HCV has been classified into 6 different major genotypes and 11 different subtypes. However this classification system does not provide significant information about the origin of the virus, primarily due to high mutation rate at nucleotide level. HCV genome codes for a single polyprotein of about 3011 amino acids which is processed into structural and non-structural proteins inside host cell by viral and cellular proteases.</p> <p>Results</p> <p>We have identified a conserved NS4A protein sequence for HCV genotype 3a reported from four different continents of the world i.e. Europe, America, Australia and Asia. We investigated 346 sequences and compared amino acid composition of NS4A protein of different HCV genotypes through Multiple Sequence Alignment and observed amino acid substitutions C₂₂, V₂₉, V₃₀, V₃₈, Q₄₆and Q₄₇in NS4A protein of genotype 1b. Furthermore, we observed C₂₂and V₃₀as more consistent members of NS4A protein of genotype 1a. Similarly Q₄₆and Q₄₇in genotype 5, V₂₉, V₃₀, Q₄₆and Q₄₇in genotype 4, C₂₂, Q₄₆and Q₄₇in genotype 6, C₂₂, V₃₈, Q₄₆and Q₄₇in genotype 3 and C₂₂in genotype 2 as more consistent members of NS4A protein of these genotypes. So the different amino acids that were introduced as substitutions in NS4A protein of genotype 1 subtype 1b have been retained as consistent members of the NS4A protein of other known genotypes.</p> <p>Conclusion</p> <p>These observations indicate that NS4A protein of different HCV genotypes originally evolved from NS4A protein of genotype 1 subtype 1b, which in turn indicate that HCV genotype 1 subtype 1b established itself earlier in human population and all other known genotypes evolved later as a result of mutations in HCV genotype 1b. These results were further confirmed through phylogenetic analysis by constructing phylogenetic tree using NS4A protein as a phylogenetic marker.</p