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Abstract Blackgram, a protein-rich pulse crop (24%), is crucial for combating food insecurity, particularly in malnourished and economically weak countries. Enhancing blackgram production requires improved, input-saving management practices. Given the challenges of climate change and population growth, efficient water management is vital for increasing pulse productivity and water use efficiency with minimal investment. This study aimed to identify cost-effective irrigation methods to optimise blackgram yields. Experiments were conducted at the National Pulses Research Centre in Vamban, Pudukkottai, and the Agricultural College and Research Institute in Kumulur, Tiruchirappalli, during the kharif season of 2021 and 2022. The study compared different treatments of irrigation methods, such as check basin, raised bed, drip, sprinkler and rain hose irrigation. Results showed that the rain hose system maintained the highest soil moisture (23.93% at 10 cm depth and 19.71% at 20 cm depth). Even though drip irrigation resulted in a higher seed yield (1363 kg ha−1), the rain hose system proved to be more cost-effective, saving 27.09% in costs and achieving a 15.23% higher benefit–cost ratio. These findings suggest that the rain hose method, combined with current agronomic practices, is a viable low-cost technique for sustainable blackgram cultivation, optimising water use and maximising profits. This research provides valuable insights into water-saving irrigation methods for pulse crops.

This article addresses the crucial challenge of maintaining a reliable power supply in integrated electric systems that combine solar power and energy storage. It focuses on optimizing key parameters for remote photovoltaic, wind, and battery energy storage within the grid, with a primary goal of sustaining 24-hour load demand. The study introduces a comprehensive approach that integrates fuel price dynamics and battery depletion costs into the optimization model for hybrid grids. This approach seeks a delicate balance between sustainable energy usage and cost-effectiveness. To achieve this balance, the research employs genetic algorithms, a robust computational technique. These algorithms play a vital role in calculating discharge-charge cycles and assessing battery health, addressing concerns about battery longevity and performance. Additionally, the study explores a machine learning framework, specifically nested learning, to further enhance the optimization process. Nested learning allows for the development of a sophisticated target function that considers various grid operation parameters and constraints. This machine learning approach enhances the system's ability to dynamically monitor power consumption and generation. Within this machine learning framework, the TD Lambda learning algorithm takes a prominent role in identifying the optimal function. This algorithm is well-known for its efficiency, particularly in non-Markovian scenarios. Its quick convergence enhances the overall performance of the hybrid grid, ensuring efficiency in changing conditions. The research also evaluates the impact of weight factors on various aspects, including battery charging status, algorithmic decisions, and their consequences on optimal energy pricing within the hybrid grid. This comprehensive assessment deepens the understanding of how these weight factors influence grid performance and economic viability.

Abstract Recent years have seen an increase in research on biodiesel, an environmentally benign and renewable fuel alternative for traditional fossil fuels. Biodiesel might become more cost-effective and competitive with diesel if a solid heterogeneous catalyst is used in its production. One way to make biodiesel more affordable and competitive with diesel is to employ a solid heterogeneous catalyst in its manufacturing. Based on X-ray diffraction (XRD) and Fourier Transform infrared spectroscopy (FTIR), the researchers in this study proved their hypothesis that iron oxide core–shell nanoparticles were generated during the green synthesis of iron-based nanoparticles (FeNPs) from Camellia Sinensis leaves. The fabrication of spherical iron nanoparticles was successfully confirmed using scanning electron microscopy (SEM). As a heterogeneous catalyst, the synthesised catalyst has shown potential in facilitating the conversion of algae oil into biodiesel. With the optimal parameters (0.5 weight percent catalytic load, 1:6 oil—methanol ratio, 60 °C reaction temperature, and 1 h and 30 min reaction duration), a 93.33% yield was attained. This may be due to its acid–base property, chemical stability, stronger metal support interaction. Furthermore, the catalyst was employed for transesterification reactions five times after regeneration with n-hexane washing followed by calcination at 650 °C for 3 h.

Abstract A Wireless Sensor Network (WSN) aided by the Internet of Things (IoT) is a collaborative system of WSN systems and IoT networks are work to exchange, gather, and handle data. The primary objective of this collaboration is to enhance data analysis and automation to facilitate improved decision-making. Securing IoT with the assistance of WSN necessitates the implementation of protective measures to confirm the safety and reliability of the interconnected WSN and IoT components. This research significantly advances the current state of the art in IoT and WSN security by synergistically harnessing the potential of machine learning and the Firefly Algorithm. The contributions of this work are twofold: firstly, the proposed FA-ML technique exhibits an exceptional capability to enhance intrusion detection accuracy within the WSN-IoT landscape. Secondly, the amalgamation of the Firefly Algorithm and machine learning introduces a novel dimension to the domain of security-oriented optimization techniques. The implications of this research resonate across various sectors, ranging from critical infrastructure protection to industrial automation and beyond, where safeguarding the integrity of interconnected systems are of paramount importance. The amalgamation of cutting-edge machine learning and bio-inspired algorithms marks a pivotal step forward in crafting robust and intelligent security measures for the evolving landscape of IoT-driven technologies. For intrusion detection in the WSN-IoT, the FA-ML method employs a support vector machine (SVM) machine model for classification with parameter tuning accomplished using a Grey Wolf Optimizer (GWO) algorithm. The experimental evaluation is simulated using NSL-KDD Dataset, revealing the remarkable enhancement of the FA-ML technique, achieving a maximum accuracy of 99.34%. In comparison, the KNN-PSO and XGBoost models achieved lower accuracies of 96.42% and 95.36%, respectively. The findings validate the potential of the FA-ML technique as an active security solution for WSN-IoT systems, harnessing the power of machine learning and the Firefly Algorithm to bolster intrusion detection capabilities.

In recent years, there has been an increase in the interest in adopting Explainable Artificial Intelligence (XAI) for healthcare. The proposed system includes • An XAI model for cancer drug value prediction. The model provides data that is easy to understand and explain, which is critical for medical decision-making. It also produces accurate projections. • A model outperformed existing models due to extensive training and evaluation on a large cancer medication chemical compounds dataset. • Insights into the causation and correlation between the dependent and independent actors in the chemical composition of the cancer cell.While the model is evaluated on Lung Cancer data, the architecture offered in the proposed solution is cancer agnostic. It may be scaled out to other cancer cell data if the properties are similar. The work presents a viable route for customizing treatments and improving patient outcomes in oncology by combining XAI with a large dataset. This research attempts to create a framework where a user can upload a test case and receive forecasts with explanations, all in a portable PDF report.

The Gas Tungsten Arc Welding process weld for the 4 mm thickness of the ASTM A36 steel plate with varied heat input parameters of 0.608 kJ/mm, 0.900 kJ/mm and 1.466 kJ/mm, respectively. The effect of different heat inputs on microstructure, corrosion, and mechanical characteristics of developed weld joints are examined by three zones: heat-affected zone, welded zone, and base metal zone. The optical microscopic results of weld joints illustrate that fine grain structure leads to enhance welding strength. It is revealed that the increased heat input parameter on the weld joint shows a decreased tensile strength and hardness of the weld joint. The corrosion resistance of the weld joint is evaluated by Potentio-dynamic polarization. It facilitates that the corrosion rate of the weld joint is decreased with increasing heat input, which results indicate the best and worst corrosion micrograph of the polygonal ferrite and ferrite plus polygonal ferrite. However, the weld joint prepared with 0.900 kJ/mm heat input found maximum corrosion resistance.

Abstract Background Sclerotinia sclerotiorum is the causal agent of white mould, stem and head rot diseases on a wide variety, including cabbage in the field and storage. Control of this pathogen by using commercial disease management methods is extremely difficult. Therefore, this study was performed to identify the potential biological control agent. Results The antagonist fungal isolates, a mycoparasite of S. sclerotiorum, were isolated and described as KET Cm1, PAL Cm 2 and TDK Cm 3. They were subjected to morphological and microscopic observation. The growth of antagonist fungal isolates on different media revealed that PDA and half-strength Czapek dox agar medium showed the maximum mycelial growth (28.67 and 28.33 mm) and pycnidial production in the PDA medium. The studies on pH and temperature found that growth and sporulation of the antagonist fungal isolates were optimum at pH 5.5 (34 mm) and 20 °C. The molecular confirmation of antagonist fungal isolates was carried out using ITS 1 and ITS 4 primers, which target 18S-28S rRNA gene fragment. The isolates were partially sequenced and showed that more than 99% identity with Coniothyrium minitans already exist in the NCBI database. The accession numbers (MW093134, MW111282 and MW136938) were obtained for all the three isolates and also confirmed using specific primers Cm sp 1F and Cm sp 1R. Among the tested isolates, the antagonistic activity of C. minitans TDK Cm 3 showed the maximum mycelial growth inhibition of 48.8% S. sclerotiorum and was used for further studies. Penetration and formation of appressoria on the hyphae of S. sclerotiorum by C. minitans isolate TDK Cm 3 were observed through the scanning electron microscope. The ethyl acetate fractions of TDK CM 3 isolate were evaluated against S. sclerotiorum by agar well diffusion assay, paper disc assay and poison food technique in vitro. Through GC–MS analysis, the effective antifungal compounds were identified. Conclusion The present study focused on the identification and characterization of effective Coniothyrium isolates as eco-friendly, integrated disease management strategies against cabbage head rot disease.

Polymer-based matrix hybrid composites meet their demand in various engineering applications and food industries due to their excellent mechanical, thermal, corrosion, and biodegradable performance. The polymer-based hybrid composites have been a better choice for high thermal insulation at low cost. This experiment attempted to find the thermal adsorption characteristics, heat deflection temperature, linear thermal expansion, and thermal conductivity of epoxy hybrid composites, which contained four different layers of Kevlar and basalt fiber fabricated via a low-cost conventional hand mold layup technique. This experiment revealed that the effect of basalt/Kevlar fiber on epoxy increased thermal performance. The results noted that the hybrid composite consists of less Kevlar fiber with the maximum basalt fiber of sample 4, showed excellent thermal adsorption effect on weight loss limited at 70.98%, and a better heat deflection temperature and11.78×10−6per °C linear thermal expansion were obtained. Sample 3 exhibited a maximum thermal conductivity of 0.251 W/mK. However, the thermal adsorption of hybrid composite has been limited by more basalt fiber, leading to a 1 wt%/°C decomposition rate.

Abstract Introduction Duplication cyst of the alimentary tract is a rare congenital anomaly. Duodenal duplication cyst accounts for less than 5% overall. These entities rarely present in adults. They are often mistaken as choledochoceles. Management is most often complete excision, but it is individualized to the particular case. Case presentation A 22-year-old woman was admitted to our hospital with a history of intermittent colicky right hypochondrial pain not relieved by any medications for the past 3 months. Initially, she was given proton pump inhibitors, but her pain was not relieved. Further evaluation was done, and preoperative imaging showed a cyst in the second part of the duodenum. Magnetic resonance imaging revealed it as a choledochocele, but duodenal duplication cyst was kept in the differential diagnosis. Further ultrasound identified it to be a duplication cyst. After failed endotreatment, the patient was successfully managed with partial excision and marsupialization. Conclusion Duodenal duplication cyst is uncommon and rarely diagnosed in adults. Duplications in the duodenum should always be a part of the differential diagnosis, especially in cystic lesions. Ultrasonogram of the cyst might lead to the proper diagnosis. Surgery is the treatment of choice if endotherapy is not successful.

Friction and wear studies enable the investigation of material interaction between two sliding surfaces in contact. In the present investigation, the coefficient of friction and the wear resistance of AISI 316 L parts were studied under self-mating, dry sliding conditions using a pin-on-disc type configuration. The experiments were conducted at vacuum based high temperature pin-on-disc tribometer. The 4 mm diameter pin and 180 mm diameter disc were subjected to varying sliding velocities (0.5, 0.75 and 1.5 m/s) and were operated in 200, 400, 500 and 580 °C temperature at 600 Torr vacuum. The variation of specific wear rates with sliding velocities and different environmental conditions was studied. The morphology of sliding/rubbed surfaces was observed using Scanning Electron Microscope. In summary, it was found that a severe to mild wear transition occurred in sliding under operating conditions. Increased wear rates have been observed for 500 and 580 °C with increasing sliding velocity. Adhesive wear has been found to be predominant at 500 and 580 °C where as de-lamination has been observed at ambient temperature, 200 and 400 °C in vacuum. The present paper also carried out the numerical analysis of the vibration behavior of AISI 316 L under thermal environment. Results revealed that at high temperature vibrational amplitude and natural frequency is significantly reduced. This can be attributed to the reduction in stiffness of the material at elevated temperatures. This high amplitude vibration during service can lead to high wear rate. Keywords: Pin-on-disc, Sliding wear, Vacuum, De-lamination, Scanning electron microscope, Vibration

In the current era, the desire for high boost DC-to-DC converter development has increased. Notably, there has been voltage gain improvement without adding extra power switches, and a large number of passive components have advanced. Magnetically coupled isolated converters are suggested for the higher voltage gain. These converters use large size inductors, and thus the non-isolated traditional boost, Cuk and Sepic converters are modified to increase their gain by adding an extra switch, inductors and capacitors. These converters increase circuit complexity and become bulky. In this paper, we present a hybrid high voltage gain non-isolated single switch converter for photovoltaic applications. The proposed converter connects the standard conventional Cuk and boost converter in parallel for providing continuous current mode operation with the help of a single power switch, which gives less voltage stress on controlled switch and diodes. The proposed hybrid topology uses a single switch with a lower component-count and provides a higher voltage gain than non-isolated traditional converters. The converter circuit mode of operation, operating performance, mathematical derivations and steady-state exploration and circuit parameters design procedures are deliberated in detail. The proposed hybrid converter circuit components, voltage gain and performance, were compared with other topologies in the literature. The MATLAB/Simulink simulation study and microcontroller-based experimental laboratory prototype of 150 W were implemented. The simulation study and experimentation results were confirmed to be a satisfactory agreement with the theoretical analysis. This topology produced non-inverting output in continuous input current mode using a single switch with high voltage gain (≈5.116 gain) with a maximum efficiency of 92.2% under full load.

A series of 20 novel chromone embedded [1,2,3]-triazoles derivatives were synthesized via an easy and convenient synthetic procedure starting from 2-hydroxy acetophenone. The in vitro anti-mycobacterial evaluation studies carried out in this work reveal that seven compounds exhibit significant inhibition against Mycobacterium tuberculosis H37Rv strain with MIC in the range of 1.56–12.5 µg ml−1. Noticeably, compound 6s was the most potent compound in vitro with a MIC value of 1.56 µg ml−1. Molecular docking and chemoinformatics studies revealed that compound 6s displayed drug-like properties against the enoyl-acyl carrier protein reductase of M. tuberculosis further establishing its potential as a potent inhibitor.

Stereospermum suaveolens is a folk remedy for the treatment of diabetes and liver disorders in southern parts of India. In the present study, the protective effect of the ethyl acetate fraction of ethanol extract from S. suaveolens against hepatic oxidative stress was evaluated in streptozotocin (STZ)-induced diabetic rats for 14 days. The ethyl acetate fraction was administered orally to the STZ diabetic rats at the doses of 200 and 400 mg/kg. Blood glucose level was measured according to glucose oxidase method. In order to determine hepatoprotective activity, changes in the levels of serum biomarker enzymes such as aspartate transaminase (AST), alanine transaminase (ALT), and serum alkaline phosphatase (SALP) were assessed in the ethyl acetate fraction treated diabetic rats and were compared with the levels in diabetic control rats. In addition, the antioxidant activity of ethyl acetate fraction was evaluated using various hepatic parameters such as thiobarbituric acid reactive substances (TBARS), reduced glutathione (GSH), superoxide dismutase (SOD), and catalase (CAT). It was found that administration of ethyl acetate fraction (200 and 400 mg/kg) produced a significant (P

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.

A Tall x Tall coconut genotype resistant to basal stem rot (Ganoderma) disease has been developed for the first time in India. The resistant coconut genotype registered higher survival rate, growth characters and nut yield in disease endemic area. It contains more amount of phenolics, lignin, amino nitrogen and lesser amount of sugars which may be the factors responsible for the disease resistance.

The molecular title compound, [MnCl2(C5H5N)2(H2O)2], lies about an inversion centre. The MnII atom is in an all-trans octahedral environment defined by two water molecules, two chloride anions and two pyridine ligands. An intermolecular hydrogen-bonding interaction between a water molecule and a chloride anion bonded to an adjacent MnII atom generates an eight-membered ring. The crystal packing exhibits two intermolecular π–π stacking interactions between the aromatic rings, with centroid–centroid distances of 3.485 (12) and 3.532 (12) Å.

This article discusses the potential use of the neutrophil-lymphocyte ratio (NLR) as a diagnostic marker for predicting early-stage diabetic nephropathy in patients with diabetes mellitus (DM). The study found a correlation between NLR and microalbuminuria, suggesting that NLR could be used to assess the onset and progression of diabetic nephropathy. The article also mentions other studies that have explored the use of NLR as a diagnostic marker for various complications of DM. However, further research with larger sample sizes is needed to evaluate the accuracy and implications of using NLR in clinical practice. [Extracted from the article]