An efficient high-gain bidirectional interleaved boost converter for PV integration to DC microgrid.

The design of a power electronic interface for high voltage difference DC buses is a key aspect in DC microgrid applications. A multi-port non isolated interleaved high-voltage gain bidirectional converter, which facilitates bidirectional power transfer and islanded operation in a DC microgrid, is presented in this paper. The forward high-voltage transfer ratio is achieved using a voltage multiplier circuit, and the high-gain step-down power conversion is performed using a resonant power module. A novel power transfer selection algorithm is proposed to control power flow among the interfaces of the RES, ESS, and DC grid converters, which utilizes the net power difference as the basis for switching the converter. The proposed converter is simulated for a 24 V PV source, 12 V battery, and 400 V DC grid interface using MATLAB/SIMULINK. A 200 W hardware prototype is implemented. The simulation results for voltages, currents, and power flow among RES, ESS, and microgrid DC bus proved an excellent voltage regulation, efficient power conversion, and a feasible duty cycle range with high voltage gain. These observations are validated through equivalent experimental results. A comparison is made regarding achieved gain, component sizing, achievable power transfer modes, efficiency, and control complexity with existing converters for DC microgrid applications. The presented topology proved to be a better interface with multiple-mode support with high efficiency.

Sustainable power management in light electric vehicles with hybrid energy storage and machine learning control.

This paper presents a cutting-edge Sustainable Power Management System for Light Electric Vehicles (LEVs) using a Hybrid Energy Storage Solution (HESS) integrated with Machine Learning (ML)-enhanced control. The system's central feature is its ability to harness renewable energy sources, such as Photovoltaic (PV) panels and supercapacitors, which overcome traditional battery-dependent constraints. The proposed control algorithm orchestrates power sharing among the battery, supercapacitor, and PV sources, optimizing the utilization of available renewable energy and ensuring stringent voltage regulation of the DC bus. Notably, the ML-based control ensures precise torque and speed regulation, resulting in significantly reduced torque ripple and transient response times. In practical terms, the system maintains the DC bus voltage within a mere 2.7% deviation from the nominal value under various operating conditions, a substantial improvement over existing systems. Furthermore, the supercapacitor excels at managing rapid variations in load power, while the battery adjusts smoothly to meet the demands. Simulation results confirm the system's robust performance. The HESS effectively maintains voltage stability, even under the most challenging conditions. Additionally, its torque response is exceptionally robust, with negligible steady-state torque ripple and fast transient response times. The system also handles speed reversal commands efficiently, a vital feature for real-world applications. By showcasing these capabilities, the paper lays the groundwork for a more sustainable and efficient future for LEVs, suggesting pathways for scalable and advanced electric mobility solutions.

Evolutionary gravitational neocognitron neural network optimized with marine predators optimization algorithm for MRI brain tumor classification.

Magnetic resonance imaging (MRI) is a powerful tool for tumor diagnosis in human brain. Here, the MRI images are considered to detect the brain tumor and classify the regions as meningioma, glioma, pituitary and normal types. Numerous existing methods regarding brain tumor detection were suggested previously, but none of the methods accurately categorizes the brain tumor and consumes more computation period. To address these problems, an Evolutionary Gravitational Neocognitron Neural Network optimized with Marine Predators Algorithm is proposed in this article for MRI Brain Tumor Classification (EGNNN-VGG16-MPA-MRI-BTC). Initially, the brain MRI pictures are collected under Brats MRI image dataset. By using Savitzky-Golay Denoising approach, these images are pre-processed. The features are extracted utilizing visual geometry group network (VGG16). By utilizing VGG16, the features, like Grey level features, Haralick Texture features are extracted. These extracted features are given to EGNNN classifier, which categorizes the brain tumor as glioma, meningioma, pituitary gland and normal. Batch Normalization (BN) layer of EGNNN is eliminated and included with VGG16 layer. Marine Predators Optimization Algorithm (MPA) optimizes the weight parameters of EGNNN. The simulation is activated in MATLAB. Finally, the EGNNN-VGG16-MPA-MRI-BTC method attains 38.98%, 46.74%, 23.27% higher accuracy, 24.24%, 37.82%, 13.92% higher precision, 26.94%, 47.04%, 38.94% higher sensitivity compared with the existing AlexNet-SVM-MRI-BTC, RESNET-SGD-MRI-BTC and MobileNet-V2-MRI-BTC models respectively.

Evolutionary Gravitational Neocognitron Neural Network optimized with Marine Predators Algorithm is proposed in this article for MRI Brain Tumor Classification (EGNNN-VGG16-MPA-MRI-BTC). Initially, the brain MRI pictures are collected under Brats MRI image dataset. By using Savitzky-Golay Denoising approach, these images are pre-processed. The features are extracted utilizing visual geometry group network (VGG16). By utilizing VGG16, the features, like Grey level features, Haralick Texture features are extracted. These extracted features are given to EGNNN classifier, which categorizes the brain tumor as glioma, meningioma, pituitary gland and normal. Batch Normalization (BN) layer of EGNNN is eliminated and included with VGG16 layer. Marine Predators Optimization Algorithm (MPA) optimizes the weight parameters of EGNNN.

Impact of Bonding Temperature on Microstructure, Mechanical, and Fracture Behaviors of TLP Bonded Joints of Al2219 with a Cu Interlayer.

The present study aims at producing transient liquid phase (TLP) bonded Al2219 joints with pure Cu (copper) as an interlayer. The TLP bonding is carried out at the bonding temperatures in the range of 480 to 520 °C while keeping the bonding pressure (2 MPa) and time (30 min.) constant. Reaction layers are formed at the Al-Cu interface with a significant increase in diffusion depth with the increase in the bonding temperature. The microstructural investigations are carried out using scanning electron microscopy and energy-dispersive spectroscopy. X-ray diffraction study confirms the formation of CuAl2, CuAl, and Cu9Al4 intermetallic compounds across the interface of the bonded specimens. An increase in microhardness is observed across the bonding zone with the increase in the bonding temperature, and a maximum hardness value of 723 Hv is obtained on the diffusion zone of the specimen bonded at 520 °C. Furthermore, the fractography study of the bonded specimens is carried out, and a maximum shear strength of 18.75 MPa is observed on the joints produced at 520 °C.

Deep Transfer Learning Technique for Multimodal Disease Classification in Plant Images.

Rice (Oryza sativa) is India's major crop. India has the most land dedicated to rice agriculture, which includes both brown and white rice. Rice cultivation creates jobs and contributes significantly to the stability of the gross domestic product (GDP). Recognizing infection or disease using plant images is a hot study topic in agriculture and the modern computer era. This study paper provides an overview of numerous methodologies and analyses key characteristics of various classifiers and strategies used to detect rice illnesses. Papers from the last decade are thoroughly examined, covering studies on several rice plant diseases, and a survey based on essential aspects is presented. The survey aims to differentiate between approaches based on the classifier utilized. The survey provides information on the many strategies used to identify rice plant disease. Furthermore, model for detecting rice disease using enhanced convolutional neural network (CNN) is proposed. Deep neural networks have had a lot of success with picture categorization challenges. We show how deep neural networks may be utilized for plant disease recognition in the context of image classification in this research. Finally, this paper compares the existing approaches based on their accuracy.

Porous nanocomposites for sorptive elimination of ibuprofen from synthetic wastewater and its molecular docking studies.

Pharmaceuticals are a new developing pollutant that is threatening aquatic ecosystems and impacting numerous species in the ecosystem. The aim of this study is the green synthesis of TiO2-Fe2O3-Chitosan nanocomposites in conjunction with Moringa olifera leaves extract and its applicability for ibuprofen removal. Various characterization studies were performed for the synthesized nanocomposites. Box-Behnken design (BBD) is employed to optimize pH, agitation speed, and composite dosage. Equilibrium results show that adsorption process matches with Langmuir isotherm, demonstrating adsorption on the nanocomposite's homogenous surface and follows pseudo-first-order kinetics. Using the BBD, pH, adsorbent dose, and agitation speed were examined as adsorption parameters. Ibuprofen elimination was demonstrated to be most successful at a pH of 7.3, using 0.05 g of nanocomposites at a rotational speed of 200 rpm. Thermodynamic parameters for ibuprofen sorption were carried out and the ΔH and ΔS was found to be 76.23 & 0.233. Molecular Docking was performed to find the interaction between the pollutant and the nanocomposite. UV-vis spectra confirm the 243 nm absorption band corresponding to the nanocomposite's surface plasmon resonances. Fourier transform infrared spectroscopy spectra relate this band to a group of nanocomposites. The findings of this work emphasize the importance of TiO2-Fe2O3-Chitosan nanocomposites for removing ibuprofen from wastewater.

Synthesis of metal-based functional nanocomposite material and its application for the elimination of paracetamol from synthetic wastewater.

Non-steroidal anti-inflammatory medicines (NSAIDs) like paracetamol and other substances released into the water system pose serious environmental issues. The current work examines the synthesis of a nanocomposite combined with Moringa olifera aqueous leaf extract as a reducing and stabilizing agent for the green synthesis of nanocomposites. Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Thermogravimetric analysis (TGA), Scanning Electron Microscope (SEM), Transmission Electron Microscope (TEM) were used to investigate metal based functional nanocomposites. The absorption band centered at a wavelength of 243 nm, which corresponds to the surface plasmon resonances of the produced nanocomposite, is confirmed in UV-vis spectra. The distinctive band at this particular wavelength is attributed to a particular group of nanocomposites based on the result from the Fourier transform infrared spectroscopy spectra. The spherical with irregularly shaped aggregates was confirmed by transmission electron microscopy, and the average size of nanoparticles was found to be 1 nm. For the elimination of pharmaceutical contaminants such as paracetamol from aqueous solutions, the adsorptive characteristics of nanocomposites were examined. Temperature, pH, adsorbent dosage, and agitation speed were investigated as adsorption parameters using Box-Behnken Design (BBD). The best removal outcomes were found under the following circumstances: temperature at 303.15 K, pH = 7.5, 0.05 g of nanocomposites at 200 rpm. Based on the adsorption study, the kinetics was found to be pseudo first order (R2 > 0.9481) which was validated and fitted by Langmuir isotherm (R2 > 0.9973). The adsorption study confirms that it was adsorbed onto the synthesized nanocomposite and found to be present on the homogeneous surface.

Potential risks and approaches to reduce the toxicity of disinfection by-product - A review.

Water contamination through anthropogenic and industrial activities has led to the emergence and necessity of disinfection methods. Chlorine and bromine gases, often used to disinfect water, resulted in the by-product formation by reacting with organic matter. The Disinfectant by-products (DBP) led to the formation of Trihaloaceticacid (TAA), Trihalomethane (THM), and other minor components. The release of chemicals has also led to the outbreak of diseases like infertility, asthma, stillbirth, and types of cancer. There are new approaches that are found to be useful to compensate for the generation of toxic by-products and involve membrane technologies, namely reverse osmosis, ultrafiltration, and nanofiltration. This review mainly focuses on the toxicology effects of DBPs and various approaches to mitigate the same. The health hazards caused by different DBPs and the various treatment techniques available for the removal are discussed. In addition, a critical comparison of the different removal techniques was discussed.

Green synthesis of bio-functionalized nano-particles for the application of copper removal - characterization and modeling studies.

Green technology for the synthesis of nanoparticles has gained momentum due to its cost-effectiveness and eco-friendly nature. In this research study, silver nanoparticles (AgNps) were synthesized using an eco-friendly biological method involving the use of marine algae, Halimeda gracilis. The surface properties of the synthesized silver nanoparticles were studied using UV-visible spectroscopy, Fourier transform infrared spectroscopy and scanning electron microscopy methods. During the synthesis of nano particles, the parameters namely temperature (30 °C to 90 °C), pH (6-10), silver nitrate (AgNO3) concentration (1-3 mg/ml) and quantity of algal extract (1-3 ml) were optimized to improve the production of AgNPs. The application of the synthesized silver nanoparticles for the adsorptive removal of copper from aqueous and industrial wastewater was investigated. Intra-particle diffusion mechanism was identified to be controlling step in metal removal. Regeneration of sorbent was carried out using 2.0 M HCl and the reusability was verified for 6 cycles. A removal efficiency of copper (64.8%) from electroplating wastewater demonstrated the industrial application potential of the synthesized silver nanoparticles.

Anaerobic mixed consortium (AMC) mediated enhanced biosynthesis of silver nano particles (AgNPs) and its application for the removal of phenol.

In this research, silver nano particle (AgNP), was synthesized through a novel anaerobic mixed consortium mediation method and applied for the removal of phenol. The best operating conditions for the fabrication of silver nanoparticles were identified through response surface methodology (RSM) and the maximum yield was found to be 2.65 g/100 ml of anaerobic mixed consortium at optimal conditions of pH-8.6, temperature-90 °C, silver nitrate concentration-3 mg/ml and inoculum volume-3 ml. The synthesized nano particle exhibited a maximum phenol removal of 87.65% was achieved at pH:5.8. The synthesized silver nanoparticles were characterized by superior surface area (19.26 m2/g) and the stability was confirmed by thermo gravimetric analysis (upto 500 °C). The surface morphology was well explained using High Resolution Transmission Emission Microscopy (HR-TEM) and Scanning Electron Microscope with EDS (SEM-EDS) techniques. X-ray Diffraction (XRD) analysis confirmed the changes in crystalline structure due to the adsorption of phenol. Kinetic experiments fitted well with the intra-particle diffusion model. The nature of adsorption of phenol was confirmed as monolayer by the goodness of fit with Langmuir isotherm (R2 > 0.9969).

Strategies for Gene Mapping in Inherited Ophthalmic Diseases.

Gene mapping of inherited ophthalmic diseases such as congenital cataracts, retinal degeneration, glaucoma, age-related macular degeneration, myopia, optic atrophy, and eye malformations has shed more light on the disease pathology, identified targets for research on therapeutics, earlier detection, and treatment options for disease management and patient care. This article details the different approaches to gene identification for both Mendelian and complex eye disorders.

Prenatal genetic diagnosis of retinoblastoma and report of RB1 gene mutation from India.

BACKGROUND: Retinoblastoma is the most common intraocular malignancy of childhood. There is a paucity of genetic testing and prenatal genetic diagnosis from India, which has the highest incidence worldwide. MATERIALS AND METHODS: RB1 gene screening of an 8-month-old female child with bilateral retinoblastoma was accomplished using next generation sequencing. The results were used for prenatal testing in this family. RESULTS: A heterozygous germline mutation (chr13: 48951119delA; c.1281delA) was detected, which resulted in premature termination of a protein product (p.Glu428Argfs*29). Prenatal testing in maternal DNA revealed carrier status of the mother. Further clinical examination in the family members revealed retinocytomas in both eyes of the mother and maternal grandmother. Prenatal genetic testing of the developing fetus showed positivity for the mutation. As the family preferred to continue the pregnancy, serial 3-D ultrasounds were carried out every 2 weeks in the third trimester. Ten days after delivery, small extrafoveal tumors developed in both eyes, which were then treated successfully with transpupillary thermotherapy. CONCLUSION: We report the significance of genetic testing in the early detection and management of retinoblastoma from India.

Synthesis of silver nanoparticle and its application.

In this work, silver nanoparticles have been synthesized by wet chemical technique, green synthesis and microbial methods. Silver nitrate (10(-3)M) was used with aqueous extract to produce silver nanoparticles. From the results it was observed that the yield of nanoparticles was high in green synthesis. The size of the silver nanoparticles was determined from Scanning Electron Microscope analysis (SEM). Fourier Transform Infrared spectroscopy (FTIR) was carried out to determine the presence of biomolecules in them. Its cytotoxic effect was studied in cancerous cell line and normal cell line. MTT assay was done to test its optimal concentration and efficacy which gives valuable information for the use of silver nanoparticles for future cancer therapy.

The use of breast ultrasound color Doppler vascular pattern morphology improves diagnostic sensitivity with minimal change in specificity.

PURPOSE: The aim of this study was to evaluate the use of vascular morphology, around and within the B-mode region of abnormality, for improving the diagnostic accuracy of two of the most common solid breast pathologies. MATERIALS AND METHODS: The B-mode and Doppler images of 117 breast cancers and 366 fibroadenomas and lesions with a fibroadenoma-like appearance were reviewed retrospectively and the morphology of the vascular pattern was evaluated. The ratio of external to internal color Doppler, the external vascular pattern and the connecting vessels to internal vessels were assessed and differentiated into benign and malignant vascular patterns. These patterns were correlated with the histological diagnosis. RESULTS: Vascularity was demonstrated in 95 % of cancers and in 46 % of benign lesions with a trend to increasing vascularity in cancers. This provided poor specificity for excluding cancer in fibroadenomas. Variations in vascular pattern were recorded. The observed benign vascular patterns were avascularity, vascularity in the periphery and peripheral marginal vessels connecting with internal vascularity. The observed malignant vascular patterns were radially aligned external vessels with internal vessels being more numerous than external vessels which connected to radial vessels. (Fisher exact test p < 0.0001). Analysis of the vascular morphology improved the sensitivity for identifying cancers from 97 % (B-mode) to 99 % (B-mode and color Doppler) with a minimal reduction in specificity (93.7 to 92.6 %) or accuracy (94.6 to 94.2 %). CONCLUSION: The presence of vascularity within a lesion, by itself, is no longer a good predictor of malignancy because of the increase in Doppler sensitivity associated with improvements in ultrasound technology. The color Doppler ultrasound vascular pattern morphology improves the accuracy and sensitivity of B-mode image diagnosis, breast cancers and fibroadenomas with a minimal loss of specificity. Any breast lesion with radial rather than marginal connecting vessels should be regarded with suspicion.

Modulation of the immunosuppressive activities by blastocoelic fluid during rabbit pregnancy.

Temporal variation in immunosuppressive activity was determined in biological samples such as embryo-foetal fluids (blastocoelic- or amino-allantoic fluid) and blood collected from pregnant and pseudopregnant rabbits. Each of the fluids to be analyzed was pre-incubated with mitogen stimulated human lymphocytes for 48 h and then inhibition of [3H]thymidine incorporation or IL-2 receptor expression was estimated. Both means of assessing immunosuppression indicated variations in the suppressive activity throughout pregnancy. This was observed in embryo-foetal fluids but not in autologous peripheral blood nor in homologous pseudopregnant blood. At days 9-13 of pregnancy, the immunosuppressive effects of blastocoelic fluids were higher than that of the autologous sera, reached a peak at days 12 and 13 and declined thereafter, to reach the lowest levels. In order to further characterize the biological activity of day-12 blastocoelic fluid and autologous serum, they were submitted to ultracentrifugation. No suppressive activity could be demonstrated in the lipoprotein fractions. But all the activity was found in the protein fraction. Precipitation with cold ethanol confirmed that the biologically active compound was a protein. Furthermore, results obtained after ultrafiltration suggest biologically active compounds of high mol. wt (greater than 300 kDa). From the above findings, we can suggest that in the rabbit, there is no pregnancy specific systemic immunosuppression. We can also infer that (1) the immuno-tolerance of the mother towards the embryo is more due to a localized effect; (2) this effect decreases with the progression of gestation and (3) a high mol. wt factor is responsible for the immunosuppression.

Immunosuppressive effects of rabbit blastocoelic fluid and embryo culture medium.

In order to understand the mechanism of the feto-maternal immune relationship, we assayed the immunosuppression activities of fresh blastocoelic fluid and decomplemented peripheral serum collected from day-9 pregnant white New Zealand rabbits and of rabbit embryo culture medium (ECM). Because the viability of the human lymphocytes was not affected by either of these biological fluids and since they were easy to obtain in sufficient quantities, they were used uniformly in all the experiments. Immunosuppressive effect was calculated by the relative inhibition of proliferation of Con A-stimulated lymphocytes. The immunosuppressive effect of blastocoelic fluid of the 9-day pregnant rabbits was significantly higher than that of autologous decomplemented serum (P less than 0.001). The inhibition by the serum was non-specific because sera from non-pregnant animals as well as sera from different stages of pregnancy and pseudo-pregnancy showed the same level of inhibition. The ECM of 6.5-7-day-old embryo showed a pronounced immunosuppressive effect. When embryos of 1,3 and 5 days were cultured and their culture media were assayed only with 5-day-old embryo the effect had begun to appear, but it was far less than that of 7-day-old embryo (P less than 0.02). The suppressive activity of both the blastocoelic fluid and ECM was not due to cytotoxic effect, since this fluid supported the in vitro growth of single-cell rabbit embryos up to the stage of blastocyst. These results suggest that the immunologic tolerance of the embryo might be due to the immunosuppressors secreted by the embryo and that there might be a localized effect at the implantation site rather than a maternal systemic immunosuppressive effect.