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The paper presents the design of a Customised Homocentric Fresnel Collector (CHFC) based on the principle of superposition and the longest wavelength of the visible spectrum. A bottom-to-top approach is proposed that uses an individually designed homocentric prism based on visible light at a wavelength of 740 nm. The homocentric prism of the CHFC follows a uniform height method with varying pitch. An area focus is achieved on the plastic optical fibre (POF) bundle inlet without employing any secondary optical element. The CHFC achieves a uniform distribution of concentrated visible spectrum radiation from the Sun with a significant reduction in the hotspot problem. Comparison of the CHFC versus a mid-wavelength-based Fresnel lens shows that the CHFC delivers 9.24% more visible spectrum radiation on the POF bundle inlet. The simulated optical efficiency of the CHFC is 90.6%. Numerical analysis of a CHFC-based daylighting system shows that 331 lm (efficiency of 39.4%) can be delivered via a 10 m long fibre bundle made up of 32 POF each of 1 mm diameter. Experimental observations demonstrated that the maximum temperature recorded on the POF bundle entrance is 56.8°C during peak direct normal illuminance conditions. Note that the spectral distribution of the radiation emerging from the POF differs from the incident sunlight spectrum because of the transmission characteristics of the optical components used in the CHFC testbed. [ABSTRACT FROM AUTHOR]

The visible light-promoted O-alkenylation of phenols and naphthols with terminal alkynes is achieved using 2,4,6-tris(4-fluorophenyl)pyrylium tetrafluoroborate (T(p-F)PPT) as a photocatalyst at room temperature without the need of any external ligand or additive. Apart from its excellent functional group tolerance, the protocol described herein represents an appealing alternative strategy to classical transition-metal catalysed hydroarylation reactions. Mechanistic investigations revealed that the reaction involves a radical pathway. The utility of the hydroarylated products for the synthesis of fused benzofurans via a one-pot annulation was also demonstrated. Herein, we report the first intermolecular radical hydroarylation of alkynes. [ABSTRACT FROM AUTHOR]

Breast cancer is a leading cause of mortality among women globally, necessitating precise classification of breast ultrasound images for early diagnosis and treatment. Traditional methods using CNN architectures such as VGG, ResNet, and DenseNet, though somewhat effective, often struggle with class imbalances and subtle texture variations, leading to reduced accuracy for minority classes such as malignant tumors. To address these issues, we propose a methodology that leverages EfficientNet-B7, a scalable CNN architecture, combined with advanced data augmentation techniques to enhance minority class representation and improve model robustness. Our approach involves fine-tuning EfficientNet-B7 on the BUSI dataset, implementing RandomHorizontalFlip, RandomRotation, and ColorJitter to balance the dataset and improve model robustness. The training process includes early stopping to prevent overfitting and optimize performance metrics. Additionally, we integrate Explainable AI (XAI) techniques, such as Grad-CAM, to enhance the interpretability and transparency of the model's predictions, providing visual and quantitative insights into the features and regions of ultrasound images influencing classification outcomes. Our model achieves a classification accuracy of 99.14%, significantly outperforming existing CNN-based approaches in breast ultrasound image classification. The incorporation of XAI techniques enhances our understanding of the model's decision-making process, thereby increasing its reliability and facilitating clinical adoption. This comprehensive framework offers a robust and interpretable tool for the early detection and diagnosis of breast cancer, advancing the capabilities of automated diagnostic systems and supporting clinical decision-making processes. [ABSTRACT FROM AUTHOR]

In digital media copyright protection, image watermarking topologies afford a promising solution. But the robustness of watermarking methods should be considered. Therefore, a robust image watermarking technique has been proposed to show better robustness against rotation attacks and other issues in watermarking. In this work, the Deep Belief Network (DBN) is trained by the Bear Smell Search Algorithm (BSSA) during the first phase. The second phase is the embedding phase, which utilizes the hybrid transform domain of Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). After embedding, the extraction is performed with the help of a Back Propagation Neural Network (BPNN). The experiments are conducted on four kinds of host images such as Barbara, Peppers, Person and Lena. Experimental results proved that the superiority of our proposed method achieving the state-of-the-art accuracy. [ABSTRACT FROM AUTHOR]

This research aims to analyse the performance of two varieties of potato (K. Jyoti, K. Himalini) derived from four plant sources (stem cuttings, in vitro plants, apical rooted cuttings, and sprouts from minitubers) grown using aeroponics to demonstrate their potential as a seed potato source. The genotype (cultivar) and material type for planting (plant origin) had a significant impact on the total number of minitubers generated by the plant, minituber mass, and the overall production of potato growth that takes place in the aeroponic system. Depending on the plant sources, the pattern of distribution of minituber formation was different between the varieties. However, early tuberization was recorded in all plant sources except in vitro plants. Most of the productive traits, like the number of harvests and number of tubers per plant, were much greater in plants generated in vitro, allowing for the full use of plants for minituber production in aeroponic setups. This indicates that in vitro plantlets have the potential to give a viable planting material for seed potato tuber production under aeroponics. [ABSTRACT FROM AUTHOR]

Given the pandemic that hit the world, there was suddenly an increased focus on E-learning. This study aimed at determining the various factors that influence the youth of India to opt for E-learning. This study was conceptualized based on the technology acceptance model and integrating social influence (SI) and perceived enjoyment (PE) as additional constructs to determine the attitude (AT) and behavioural intention (BI) towards E-learning. The study also proposes a basic framework of knowledge for E-learning, a shift from traditional classroom learning, which is not researched adequately in previous literature. The sample for this research study were postgraduate students drawn by non-probability judgment and snowball sampling. Data analysis was performed using structural equation modelling, cross-tabulation and Pearson correlation with the help of SPSS Amos software. The results of the study concluded that AT significantly mediates between perceived usefulness, perceived ease of use, SI, PE, and BI. Additionally, the study determined the classroom and E-learning preferences of students comparatively. [ABSTRACT FROM AUTHOR]

Water is an emerging heat transfer fluid with great promise for thermal engineering because of its heat transfer coefficients. However, much more must be done with the fluid that transmits heat to make the system more effective in handling heat. Nanoparticle cooling fluid speeds up the movement of heat through the car radiator and makes it possible to make it smaller altogether. In the present study, to examine heat transfer characteristics of nanofluids of Deionized (DI) water and Ethylene glycol (60:40). Four different concentrations of nanofluids were prepared by mixing 0.05 to 0.3 Vol. % of nanofluids with a mixture of DI water and Ethylene glycol (EG). The studies were carried out by varying coolant from 3 to 15 LPM while keeping the airspeed at a mean of 5 m/s. The airflow velocity towards the radiator is continually maintained at a median of 5 m/s. The k-type thermocouple monitors the cooling outlet's temperature and a comparative study of the thermal conductivity of experimental results with machine learning. The results show that the DI water had a lower thermal conductivity of 0.891 W/m K than the EG nanofluid, which had a thermal conductivity of 0.946 W/m K. The EG nanofluid showed a more significant heat transfer coefficient of 36384.41 W/m2 K than the DI water. The viscosity of the nanofluid increases as the concentration of nanofluid in the DI water increases and decreases as the temperature rises. [ABSTRACT FROM AUTHOR]

Myofunctional appliances encompass a diverse range of intraoral devices that rely on the intrinsic forces of the orofacial musculature for their functionality. These appliances are typically designed to be removable and exhibit a passive mechanism of action. Caries and demineralisation are well known adverse side effects of myofunctional orthodontic appliances, with the most frequent reports relating to fixed appliance treatment. Hereby, the authors present a case report of a 12-year-old male patient with a slight neuromotor defect who developed significant caries and demineralisation of the permanent mandibular anteriors due to the consumption of large quantities of carbonated drinks and acidic fruits while wearing a twin block appliance for eight months and failing to return for regular orthodontic follow-ups. The patient was provided with strategies for oral health training and diet modification. Fluoride varnish was applied to treat the caries and pain caused by hypersensitivity. Additionally, at-home application of GC Tooth Mousse Plus, which is rich in Casein Phosphopeptide-Amorphous Calcium Phosphate Fluoride (CCP-ACPF), was utilised for remineralisation and dentinal tubule occlusion. The mandibular anteriors were restored with composite resin using an ultra-conservative 3D guided technique, alongside preventive care during the fluoride varnish application. The present case report emphasises the risk of decalcification of teeth during orthodontic treatment and the importance of regular dental check-ups. INSET: c. [ABSTRACT FROM AUTHOR]

More than 70 million individuals have been exposed to environmental arsenic toxicity, worldwide. United Nation Children's Fund (UNICEF) policy brief -2018 report to mitigate arsenic in drinking water, emphasizes assessing, and changing the knowledge, attitudes, and practices (KAP) as one of the long-term effective solutions to be implemented as a part of surveillance strategies. This study aims to develop a valid and reliable tool to assess knowledge, attitude, and practices of arsenic and its risk in general health. A cross-sectional survey of N=449 general population was conducted in the outpatient department of Rajendra Memorial Research Institute of Medical Sciences-Indian Council for Medical Research for data collection. The construct validation of the questionnaire was done using Exploratory Factor Analysis, Confirmatory factor analysis. The Item-Content Validity Index(I-CVI) and Scale-Content Validity Index (S-CVI) Kappa scores were used to analyze the content validity of the items. The I-CVI ranges from 0.70 to 1, the and the moderate to high cumulative content validity is S-CVI/Universal Agreement=0.84; S-CVI/Average =0.96. Following the principal component analysis, the cumulative Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) was 0.91 and the three domains in the tool (Kaiser-Meyer-Olkin measure of sampling adequacy for Knowledge (0.917), Attitude (0.825) & Practices (0.80)) were within the acceptable range. The Barret's test for sphericity was (P <0.001) and was highly acceptable. The Confirmatory Factor Analysis model of Nu-KAP has demonstrated excellent model fit where, majority of fit indices has sown good fit (X2/df=1.88, Root Mean Square Error of Approximation = 0.04, Comparative Fit Index=0.98, Goodness of Fit Index = 0.93, and Tucker Lewis Index=0.977). The Cronbach's alpha of 19 item tool was 0.72. The Nu-KAPQ questionnaire demonstrated exceptional validity and reliability while also capturing and integrating all pertinent psychometric analytic domains. Conclusively, this questionnaire can be used to assess psychometric properties associated with arsenic bridging the gap in current research to understand people's perception towards arsenic, since it is a crucial component of arsenic mitigation. [ABSTRACT FROM AUTHOR]

Elsner, Luca and Tachiya proved in [4] that the values of the Jacobi-theta constants θ 3 (m τ) and θ 3 (n τ) are algebraically independent over Q for distinct integers m , n under some conditions on τ . On the other hand, in [3] Elsner and Tachiya also proved that three values θ 3 (m τ) , θ 3 (n τ) and θ 3 (ℓ τ) are algebraically dependent over Q . In this article we prove the non-vanishing of linear forms in θ 3 (m τ) , θ 3 (n τ) and θ 3 (ℓ τ) under various conditions on m , n , ℓ , and τ . Among other things we prove that for odd and distinct positive integers m , n > 3 the three numbers θ 3 (τ) , θ 3 (m τ) and θ 3 (n τ) are linearly independent over Q ¯ when τ is an algebraic number of some degree greater or equal to 3. In some sense this fills the gap between the above-mentioned former results on theta constants. A theorem on the linear independence over C (τ) of the functions θ 3 (a 1 τ) , ⋯ , θ 3 (a m τ) for distinct positive rational numbers a 1 , ⋯ , a m is also established. [ABSTRACT FROM AUTHOR]

In the present study, Stainless steel 316L (SS316L) cylindrical specimens were fabricated at two different build orientations and two different laser powers using Laser powder bed fusion process (LPBF). Microstructural characterization such as XRD, SEM, EBSD analysis and tensile testing were carried out on fabricated specimens in stress relieved condition to understand the anisotropic behavior of LPBF printed specimens. Horizontally oriented specimens showed higher tensile strength when compared to vertically oriented specimens for both laser powers. XRD and EBSD phase maps did not reveal the presence of any secondary phases. However, build orientation and laser power affected the crystallite size of the samples. Bimodal grain structure comprising coarse columnar grains and fine equiaxed grains were observed from the micrographs. With variation in build orientation, there was a significant change in the average grain size of the specimens. High dislocation density was observed in horizontally oriented samples built at low laser power because of dislocation annihilation that can occur at high temperatures. However, EBSD analysis revealed random weak crystallographic texture which does not vary significantly with laser power or build orientation. Variation in grain size, grain morphology, sub-grain features and dislocation density are the reasons for the anisotropic tensile behavior observed in LPBF printed SS316L coupons in stress relieved condition. [ABSTRACT FROM AUTHOR]

This study uses adoption and usage data on the client and firm–client interactions across four technology generations of new-age products/services from 13 developed and emerging markets over an eight-year period to describe how multigenerational service (MGS) adoption behavior influences direct (purchases) and indirect (references and feedback) global client engagement and whether this relationship is moderated by product/service failures and cultural factors. The authors propose metrics to measure the number of generations adopted (MGD), the number of products and features within a generation (MGFs), and the adoption time between generations (MGT). They find that client usage revenue (CUR) is enhanced by greater MGD and higher MGFs combined with lower MGT. However, CUR varies by differences in the needs of clients' own customers, failures, and culture. Greater direct engagement affects reference and feedback behavior, moderated by cultural differences in individualism, power distance, and masculinity. For a typical client in the United States and Canada, a one-unit improvement in MGD and MGFs and a one-year improvement in MGT enhance CUR by $8,150, $5,200, and $2,310 per client, respectively, versus a corresponding enhancement of $4,820, $3,640, and $1,620, respectively, per client in Colombia and Mexico. These findings provide several implications for executives who manage multigenerational innovations across countries regarding client engagement, launching MGS, market entry, and failure recovery. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Engineering Transactions C: Aspects is the property of International Journal of Engineering (IJE) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In IoT-based social networking, devices such as smartphones, wearable devices, and smart home appliances can be used to collect data about users' activities, preferences, and social connections. Analyzing such information may lead to more tailored suggestions, improved social interactions, and an overall better user experience. To realize and predict IoTbased dynamic social interactions for future recommendations, machine-learning algorithms are used to evaluate data gathered from IoT devices and social networking apps to provide user-specific suggestions. To do this, the system would have to collect and analyze information from a wide variety of sources, such as social media activity via IoT gadgets, location data, device usage statistics, and usage patterns. The most significant difficulty is maintaining compatibility with ever-evolving user preferences and routines. Recommendations tailored to the user's preferences and actions can be generated using machine learning techniques. So, in this research, we combine modular neural networks with the reinforcement learning approach to create robust and versatile learning systems that can easily adjust to new contexts and challenges. The use of modular neural networks allows for the decomposition of large tasks into smaller, more feasible sub-tasks, all of which is assigned to a different module. The modules are trained to carry out their functions and coordinate their activities using reinforcement-learning techniques. When applied to IoT-based social networking applications, the combination of modular neural networks and reinforcement learning algorithms can produce more efficient and flexible learning systems that can continuously learn from user reviews/feedback and accommodate those recommendations appropriately. Finally, the suggested model is experimentally evaluated using an appropriate testbed, and the findings are compared and assessed in light of some recently existing models. The results show that the suggested paradigm effectively addresses IoT-based social networking activities, which bodes well for future suggestions. Moreover, it is observed that the predicted accuracy is higher than 93% in all the relevant contexts. [ABSTRACT FROM AUTHOR]

In the quaternary system PbTiO3-PbZrO3-SrTiO3-SrZrO3, compositions that lie close to the antiferroelectric tetragonal and ferroelectric rhombohedral (AFET-FER) phase boundary have potential applications in micro-actuators. However, in thin films, this phase boundary is reported to shift significantly to the zirconium-rich region. Hence, it is necessary to seek alternative approaches to stabilize the tetragonal AFE phase in such compositions. Therefore, this study explores the effect of B-site Mn3+-doping on their structure. Dielectric, ferroelectric, and piezoelectric characteristics of such thin films have been compared with those with increasing Zr/Ti ratios to understand the efficacy of this approach. Transverse piezoelectric coefficient, e31,f, and bipolar strain are found to be higher in Mn3+-doped thin films. Furthermore, large strains and e31,f in thin films have been correlated with structural modifications revealed by systematic Raman spectroscopic investigations. [ABSTRACT FROM AUTHOR]

Supercontinuum (SC) generation from alkali antimony zinc borate glasses was investigated using a femtosecond laser. The optical bandgap values were determined for all the glass samples. An enhancement in the generated SC is seen from sodium-doped glass although it possesses the least bandgap among the glass samples. The physical parameters of the glasses such as density, molar volume, refractive index, oxide ion polarizability, and optical basicity have been analyzed and discussed. The smaller values of the metallization criterion indicate the tendency of the glass samples to exhibit metallic behavior, which, in turn, affects the non-linear optical properties of the glasses. The shift in the binding energies of metal cations and oxygen anions was observed using XPS analysis, which gives an understanding about the extent of overlapping of valence orbitals in the glass system. The observations from the physical and structural investigations provide an insight into the anomaly in the enhanced SC generation from the low bandgap sodium-doped glass. [ABSTRACT FROM AUTHOR]

A hybrid technique is proposed for electric vehicles (EVs) or hybrid electric vehicles (HEVs) with a battery thermal management system (BTMS). The proposed hybrid method is the combined execution of the Pelican Optimization Algorithm (POA) and Firebug Swarm Optimization (FSO). The hunting behavior of pelicans is improved with the help of the FSO technique; hence, it is named the POA-FSO strategy. Here, a battery of 36 lithium-ion (Li-ion) cells is considered. The proposed method of analyzing battery thermal performance analyzed factors like heat flux from the battery cell to the passage spacing size, cooling air and the cooling air's mass flow rate (MFR). The BTMS performance is studied under maximum battery unit temperature, pressure drop and temperature uniformity. The proposed method enhances the coolant passage spacing and decreases the temperature difference in the battery cells. The proposed approach is executed on the MATLAB platform, and its performance is compared with existing approaches. From the results, it is concluded that the MFR maximizes, and a nonuniform distribution of the MFR of the passage occurs. By using the proposed approach, the maximal temperature change of cooling air among the passages is 2.0 K, the maximal temperature change between the battery cells is 7.5 K and a pressure drop of 228.03 Pa is obtained. [ABSTRACT FROM AUTHOR]

In the colloquy concerning human rights, equality, and human health, mental illness and therapy regarding mental health have been condoned. Mental disorder is a behavioral motif that catalyzes the significant anguish or affliction of personal functioning. The symptoms of a mental disorder may be tenacious, degenerative, or transpire as a single episode. Brain sickness is often interpreted as a combination of how a person thinks, perceives, contemplates and reacts. This may be analogous to a specific region or workings of the brain frequently in a social context. Anxiety disorders, psychotic disorders, personality disorders, mood disorders, eating disorders, and many more are examples of mental disorders, while complications include social problems, suicides, and cognitive impairment. These days, mental disorders are quotidian worldwide, and clinically consequential levels of derangement rise adversely. The purpose of this paper is to aid in prognosis of the type of mental disorder by analyzing the brainwaves such as Alpha (α), Beta (β), Gamma (γ), Theta (), Delta (δ) with the help of big data analysis and the Internet of Medical Things (IoMT). IoMT helps in gathering the required data and data transmission, while big data analysis helps in predicting the type of disorder. [ABSTRACT FROM AUTHOR]

Development and characterization of guinea pig anti-insulin polyclonal antibody against a target-specific insulin antigen. In India, an insulin immunogenicity kit for detecting insulin antibodies (neutralizing Nab) is an unmet medical need for diabetic patient's routine diagnosis. Type 1 diabetics rely on insulin injections daily basis for survival; if the body develops anti-insulin antibodies and neutralizes the exogenous recombinant insulin, glucose control is lost, and the patient eventually dies. Antibodies are excellent diagnostic reagents due to the specificity and sensitivity they provide in recognizing specific and unique target antigens. The paper describes the use of insulin as a target antigen and the development of target (insulin) specific antibodies in guinea pigs for use as a positive control for immunogenicity kit validation. Anti-insulin polyclonal antibody was raised against insulin in the Dunkin Hartley guinea pigs host. Anti-insulin antibody titer of all bleeds from four animals was tested using an indirect ELISA assay format. All four animals responded to the target-specific antigen but only one animal (#4) responded with a high-affinity antibody titer. The hyperimmune sera were purified using a protein A column. The purified anti-insulin antibody was characterized through SDS Page and western blot. The specificity, reactivity, and antibody binding efficiency were confirmed through immunoassays. Guinea pig anti-insulin polyclonal antibody developed in this study showed good specificity, reactivity, and efficiency in the immunoassays. This paper describes the development and characterization of anti-insulin antibodies for use as a control in developing a user-friendly insulin immunogenicity kit. [ABSTRACT FROM AUTHOR]

Introduction: Age estimation plays a vital role in various medico legal cases including both civil and criminal litigations. Assessment of age of an individual by examination of teeth is one of the universally accepted methods of age estimation. In the present study we observed the patterns of dental eruption in Coimbatore. In this study we considered the eruption pattern of all permanent teeth (Molar 1 teeth, Central Incisor teeth, Lateral Incisor teeth, Pre Molar 1, Pre Molar 2, Canine and Molar 2). Material and Methods: The present study was a community based cross sectional study conducted in C.R.R. Matric Higher Secondary School, Ondipudur. C.R.R. Mat.Hr.Sec. School (CMHSS) located at Coimbatore S.S. Kulam, Ondipudur, The study was conducted among 1000 study participants. Results: The mean age for complete eruption of the first molar teeth and central incisor was observed to be between 75.9 to 77.9 months and 80.8 to 84 months respectively. Lateral Incisor teeth was completely erupted among all the study participants aged between 105.2 and 107.4 months of age. The mean age for complete eruption of the first premolar was observed to be between 109.58 to 112.6 months. The mean age for complete eruption of the second pre molar was observed to be between 131.0 to 133.8 months. Complete eruption of Canine and second molar was observed to be between 142.6 to 144.8 months and 174.5 - 178.6 months of age respectively. Conclusion: First Pre Molar, Second Pre Molar, Canine and the second molar appears to be earlier on left side as compared to the left side. The eruption of the second molar tooth was significantly earlier in the female study participants as compared to the male study participants. The dental eruption patterns should be studied in detail to assess the role off various associated factors like nutrition, oral hygiene. [ABSTRACT FROM AUTHOR]

Ridesharing platforms compensate drivers using a fixed commission system that does not systematically reward effective drivers, which reduces platform engagement. Unsurprisingly, driver transaction activity is intermittent and service unpredictable. Influenced by agency theory, we propose a variable commission that jointly accounts for drivers' transactions and service performance. To alleviate disengagement, we propose a customer-oriented engagement framework that challenges the notion of the sole monetary focus of drivers. We compare the effects of variable and fixed commission schemes on consequences such as driver net revenue and referral value, mediated by attitudinal outcomes. In a 3-month cluster-randomized field experiment with 3,367 ridesharing drivers across 16 cities and two population tiers, we show improvements in driver satisfaction and emotional connectedness accentuated by goal-oriented feedback. Variable commission with goal-oriented feedback translates to a 24.5% rise in revenue, a 19.5% increase in referral value, and a 43.21% lower churn. A cost–benefit analysis reinforces these results. [ABSTRACT FROM AUTHOR]

In real life applications, using electronics switch in high voltage and high current applications is very challenging due to limitation of hardware and safety. In this manuscript, a hybrid system is proposed for battery management system (BMS) used in electric vehicle (EV) is a critical part for effective utilization of the energy storage. The proposed hybrid technique is joint performance of fuzzy logic controller (FLC) and Artificial eco-system algorithm (AEO), hence it is called FLTAEO technique. The existing battery management control system is not effective for the Induction motor drive based solar PV powered electric vehicle system. In this manuscript, the control strategies of charging with discharging of Li-ion batteries coupled Induction motor with solar PV power are used with proposed technique. Here, the introduced FLC and AEO are discussed with detailed control abilities for charging/discharging. The simulations are done in MATLAB platform to analyze the superiority of the proposed method. Here, BESS life comparison, fitness function for charging, fitness function for discharging, error Distribution, RMSE calculation for 1 hour and 5 minutes ahead prediction interval (PI) are analyzed and compared with various existing techniques, like Emperor Penguin Algorithm (EPA) and Seagull Optimization Algorithm (SOA). [ABSTRACT FROM AUTHOR]

To understand the castor wax layer's multifaceted contribution to Amphobotrys ricini pathogenesis, the hydrophobic components of cuticular wax were analysed from waxy and non‐waxy castor genotypes. Gas chromatography–mass spectrometry (GC–MS) technology enabled the stable detection and quantitative determination of various fatty acids and terpenoids. The investigation revealed a significant presence of triterpenoid compound 'lupeol', accounting for approximately 53.6% of the wax composition in the waxy genotype (DCH‐519), which was absent in non‐waxy genotype (ICS‐324). On exposure to lupeol, about 93.3% of conidia germinated leading to rapid mycelium growth and sporulation of A. ricini. SEM analysis of waxy and non‐waxy genotypes infected with A. ricini confirmed faster germination and production of longer germ tubes on waxy genotype compared with non‐waxy genotype, which may likely due to early recognition of the suitable host in the presence of lupeol, ultimately aiding in speedy germination and growth of the pathogen setting pace for pathogenesis. [ABSTRACT FROM AUTHOR]

The occurrence of partial shading in solar power systems presents a substantial challenge with widespread implications, sparking extensive research, notably in the field of maximum power point tracking (MPPT). This study emphasizes the critical process of accurately tracking the maximum power points with the characteristic curves of photovoltaic (PV) modules under real-time, diverse partial shading patterns. It explores the various stages of the tracking process and the methodologies employed for optimization. While conventional methods show effectiveness, they often fall short in swiftly and accurately tracking maximum power points with minimal errors. To address this limitation, this research introduces a novel machine learning approach known as adaptive reinforcement learning with neural network architecture (ARL-NNA) for MPPT. The results obtained from ARL-NNA are compared with existing algorithms using the same experimental data. Furthermore, the outcomes are validated through different factors and processing time measurements. The findings conclusively demonstrate the efficacy and superiority of the proposed algorithm in effectively tracking maximum power points in PV characteristic curves, providing a promising solution for optimizing solar energy generation in partial shading patterns. This study significantly impacts various realms of electrical engineering including power engineering, power electronics, industrial electronics, solid-state electronics, energy technology, and other related field of engineering and technology. [ABSTRACT FROM AUTHOR]

Classification of different brain tumors is challenging due to unpredictable variations in intra-inter-classes. Unlike existing methods which are not effective for images of complex backgrounds, the proposed work aims at accurate classification of diverse types of brain tumors such that an appropriate model can be used for disease identification. This study considers glioma, meningioma, no tumor, and pituitary tumors for classification. To achieve an accurate classification, we explore the Xception architecture layer, which involves flattening, dropout, and dense layer operations. The model extracts features based on shapes, spatial relationships, and structure of the image, discriminating between the different brain tumor images. The model is evaluated on a dataset of 7023 MRI images for classification. The results of a large dataset and comparative study with the existing methods show that the proposed method is better than state of the art in terms of classification rate. Specifically, our method achieves more than a 90% average classification rate, which is better than state of the art. The results on noisy and blurred datasets show that the proposed model is robust to noise and blur. [ABSTRACT FROM AUTHOR]

The application of nanofluids in the presence of a magnetic field holds promise for advanced drug delivery systems, where controlled manipulation of magnetic nanoparticles within nanofluids can enhance targeted and localized drug delivery. This study explores the instability of a viscous fluid-nanofluid interface arranged in a planar configuration influenced by a tangential magnetic field using the irrotational flow theory. When the nanofluid is positioned above a viscous fluid, the interface is susceptible to the Rayleigh-Taylor instability. Employing linear stability theory, an explicit relationship connecting the perturbation growth parameter with the wavenumber is derived. Different dimensionless quantities such as the Atwood number, Weber number, Froude number, and Reynolds number are analyzed using stability plots. These plots provide valuable information about the behavior of interfaces. Increased magnetic field strength is observed to delay instability onset. Surface tension is found to stabilize the interface, whereas inertial forces destabilize it. This investigation contributes to understanding and controlling the interface dynamics in nanofluid systems. © 2024 University of West Bohemia. [ABSTRACT FROM AUTHOR]

Microalgae-based biodiesel production has gained momentum over petroleum-based fuels due to its carbon neutrality and environment friendly properties. However, issues like high cost of cultivation and usage of inorganic fertilizers possess hindrance towards its commercial production and warrant new approaches of its eco-friendly cultivation techniques. In the present study, effect of hydrochar derived from hydrothermal carbonization (HTCb) of banana pseudostem as a supplement was investigated on the growth performance of microalgae, Graesiella emersonii MN877773, for biodiesel production. The study revealed that hydrochar supplementation (250 ppm) to the 10 days old microalgae culture improved (p < 0.05) biomass productivity (2 times higher; 0.018 g/L/day). There was also 27% increase (p < 0.05) in lipid content (16%) and improved lipid productivity (i.e. 0.003 g/L/day) noticed due to the reduction of culture solution pH from highly alkaline to slightly alkaline through hydrochar addition. Fatty acid profiling revealed presence of more amount of methyl palmitate (56% higher) with the high saturated/unsaturated fatty acid ratio (1.3). The vehicular properties of the biodiesel produced from the hydrochar treated microalgae were also found in compliance with the national and international standards with the high heating value of 40.2 MJ/kg. Microalgae grown in hydrochar-supplemented treatment also settled at the bottom within 1 h of resting period with the flocculation efficiency of 50%. This leads to the reduction (62%) in energy expenditure (5.5 kWh/g) and cost (0.4 US$/g) required for harvesting the microalgae. The present study accentuates that hydrochar supplementation at certain dosage to the pre-grown microalgae stimulates more production of quality lipids in the test microalgae with possibility to thrust sustainable biodiesel production. [ABSTRACT FROM AUTHOR]

The success of aquaculture production greatly depends on the health status of aquatic species and the proper management of the water quality. The significance of microbes in their contribution to the healthy aquatic environment, disease control and proper waste management is incredible. Among these, the role of bacteria in developing probiotics, vaccines, immunostimulants, bioremediators, quorum quenchers, etc. has been well established. Nevertheless, the importance of archaea, the third domain of life, in aquaculture applications is least explored. However, the advances in culture-independent methods revealed the archaeal diversity and their ubiquitous occurrence in various aquaculture systems such as recirculating aquaculture systems (RAS), aquaculture ponds, aquaponics systems and biofloc systems. Most of the studies on archaea in aquaculture systems were concentrated on nitrification and the associated ammonia oxidizing archaea (AOA). Most archaea detected from the aquaculture systems belong to the phylum Thaumarchaeota and Euryarchaeota, and they play a vital in the nitrogen and sulphur cycles. Thus, the archaea are proposed as potent bioaugmentors for mitigating the nitrogen and sulphur toxicity in cultured system. Besides nutrient cycling, recent studies highlight the role of archaea in aquaculture nutrition and pave the way for aquafeed development as probiotics. Several factors such as temperature, pH, salinity and dissolved oxygen affect the archaeal diversity and abundance in aquaculture. Challenges in the isolation and maintenance of pure archaeal cultures limit our understanding and applications of archaea in aquaculture. Considering all the limitations and lack of collective information on archaeal aquaculture, this review summarizes the significance and diversity of archaea in various aquaculture systems, factors affecting their diversity, detection methods, applications and advantage over bacteria, challenges and future prospects. [ABSTRACT FROM AUTHOR]

Land price plays a crucial role in the development of a region, which serves as an indicator of the features of a property. The primary goal of this paper is to explore the relationship between land price and various geographical and accessibility parameters and thereby arrive at a model to predict the land price. Based on literature surveys, the parameters that influence land price are identified further through which data collection from primary surveys, the creation of a road network map, a geographic information system (GIS) analysis to determine the distance to the central business district (CBD), measurement of road density and access road width, assessment of employment opportunities through establishment surveys, and identification of various land use parcels in the study region are accomplished. The land prices are collected from recently sold parcels in each of the zones in the study region. A negative and significant correlation is observed between land price and distance to the CBD. Positive correlations are observed between land price and other factors considered, such as road density, availability of educational facilities, employment opportunities, and the extent of commercial and residential land use areas. A non-linear regression model is developed that can predict land price depending on the significant parameters. [ABSTRACT FROM AUTHOR]

Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is a serious invasive insect pest affecting global maize production. Effective integrated management of FAW is essential to minimize the yield losses. The objective of this study is to determine a suitable package for the sustainable management of FAW by validating the potentiality of various integrated approaches through field trials. In the present study, five different integrated pest management treatments consisted of different components were synthesized and evaluated against fall armyworm in maize-based systems during winter (December 2022–April 2023) and rainy (July–November 2023) seasons. The data on the number of plants damaged, leaf damage rating (1–9 scale), and natural enemies such as spiders, coccinellids, and earwigs were recorded from 20 randomly selected plants at 7 and 14 days after the first and second sprays. Yield data (q ha−1) were recorded at the time of harvest. Treatment 1 consisting of pheromone traps at a rate of 4 per acre with ICAR-NBAIR lures, erection of bird perches at a rate of 10 per acre, seed treatment with Chlorantraniliprole 50 FS at a rate of 5.6 ml per kilogram of seed, and spray application of azadirachtin 1500 ppm at the rate of 5 ml per litre, and Metarrhizium anisopliae with spore count of 1 × 108 cfu/g (1 kg per acre) at a rate of 5 g per litre significantly reduced the per cent plant infestation (12.7) and leaf damage rating (2.1) by FAW larvae compared to untreated control (39.7, 4.1), respectively. The higher natural enemy population (spiders, coccinellids, and earwigs) was also observed in Treatment 1 (8.8) compared to Treatment 5 (4.1) (chemical control). Furthermore, higher grain yield of 51.5 q ha−1 was obtained in Treatment 1 with a cost–benefit ratio of 1:2.1, whereas in untreated control, the yield obtained was 29.0 q ha−1 with a cost–benefit ratio of 1:1.3. The highest per cent of avoidable yield losses of 43.6 was observed in Treatment 1 in comparison with other treatments. Integration of sustainable management approaches reduces the application of chemical insecticides and enhances the population of natural enemies which would be beneficial to maize farmers. [ABSTRACT FROM AUTHOR]