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Precision agriculture (PA) technologies combined with remote sensors, GPS, and GIS are transforming the agricultural industry while promoting sustainable farming practices with the ability to optimize resource utilization and minimize environmental impact. However, their implementation faces challenges such as high computational costs, complexity, low image resolution, and limited GPS accuracy. These issues hinder timely delivery of prescription maps and impede farmers’ ability to make effective, on-the-spot decisions regarding farm management, especially in stress-sensitive crops. Therefore, this study proposes field programmable gate array (FPGA)-based hardware solutions and real-time kinematic GPS (RTK-GPS) to develop a real-time crop-monitoring system that can address the limitations of current PA technologies. Our proposed system uses high-accuracy RTK and real-time FPGA-based image-processing (RFIP) devices for data collection, geotagging real-time field data via Python and a camera. The acquired images are processed to extract metadata then visualized as a heat map on Google Maps, indicating green area intensity based on romaine lettuce leafage. The RFIP system showed a strong correlation (R2 = 0.9566) with a reference system and performed well in field tests, providing a Lin’s concordance correlation coefficient (CCC) of 0.8292. This study demonstrates the potential of the developed system to address current PA limitations by providing real-time, accurate data for immediate decision making. In the future, this proposed system will be integrated with autonomous farm equipment to further enhance sustainable farming practices, including real-time crop health monitoring, yield assessment, and crop disease detection.

The current research simulates the mass and heat energy transmission model on MHD fluid flow under concentration and temperature deviations on a two-dimensional viscous fluid along an upright facet. Following boundary layer estimations, mathematical simulations for the movement of fluids, the conveyance of heat and mass exposed to radiation, thermophoresis, and Dufour consequences are generated as a set of partial differential equations. The surface's resilient suction was assessed. The built-in solver bvp4c in MATLAB is used for numerically debugging the aforementioned models. Through the inclusion of visualizations and tables, the detrimental effects of influencing variables are examined on the velocity, temperature as well as concentration gradients in conjunction with on the skin friction, Nusselt number, and Sherwood number. Excellent coherence may be shown when comparing between the most present findings and those that have previously been made available in the literature in specific limited circumstances. The Dufour effect, radiation, thermophoresis, and the Grashof number are all factors that influence fluid motion and heat transmission at the interface layer of dirt. Moreover, developments in the Shearing stress, Nusselt number, and Sherwood number coefficient are calculated. The findings are crucial for optimizing a variety of fluid-based technologies and systems, allowing developments in a number of industries including energy-effectiveness, electronics cooling, pursued medicine administration, and many more.

Abstract Introduction Physicians need an accurate understanding of diabetic retinopathy (DR) severity to optimally manage patients. The aim of this prospective study is to correlate the severity of macular and peripheral retinal vascular abnormalities seen on widefield (WF) optical coherence tomography angiography (OCTA) with DR grading based on WF fundus photography. Methods The study included 150 eyes from 82 patients with treatment-naïve DR. All patients were imaged with WF fundus photography and swept-source WF OCTA. Quantitative and qualitative analyses of the foveal avascular zone (FAZ) size and shape, and measurement of capillary nonperfusion (CNP) areas, were performed from the OCTA images. The mixed-effects model was used to compare the DR grading from WF photography with the vascular changes seen on WF-OCTA, and Bonferroni correction was applied to the gradings. Results The mean [± standard deviation (SD)] age of patients was 55.5 (± 9.4) years. The WF-OCTA showed that an increasing size of the FAZ (from 0.442 (± 0.059) µm to 0.933 (± 0.086) µm) correlated with increasing severity of the DR (as determined with WF photography). The deep capillary plexus, FAZ size, and CNP areas in eyes with proliferative diabetic retinopathy (PDR) differed from those with mild nonproliferative diabetic retinopathy (NPDR) (p

The advent of 4D bioprinting, a technique that integrates time dimensions into the conventional 3D method, substantially changed tissue engineering. By providing a time dimension to conventional 3D printing, the innovative process of 4D bioprinting is revolutionising tissue engineering. This development allows the creation of dynamic tissues, allowing structures to change and adapt over time to reflect the complexity of natural tissues. Specifically, shape memory polymers enable customised scaffold fabrication with improved mechanical strength and biomimicry for use in bone tissue engineering. An essential additional use for soft tissue regeneration is the development of injectable thermosensitive hydrogels that react to body temperature. Within asymmetrical defect regions, these hydrogels gel, offering a flexible cure for healing injured soft tissues. In addition to structural considerations, the potential applications of 4D bioprinting include organisms, vascularisation and dynamic disease models. Despite the advancements, issues like suitable biocompatibility and long-term stability still need to be resolved. However, by creating complex, adaptable and patient-specific designs in the realm of tissue engineering, 4D bioprinting has enormous potential to transform personalised medicine and regenerative therapies. This review provides a comprehensive investigation into the future of regenerative medicine by exploring the various uses and potentially revolutionary effects of 4D bioprinting in tissue engineering.

Summary: A poor maternal diet during pregnancy predisposes the infant to severe lower respiratory tract infections (sLRIs), which, in turn, increases childhood asthma risk; however, the underlying mechanisms remain poorly understood. Here, we show that the offspring of high-fat diet (HFD)-fed mothers (HFD-reared pups) developed an sLRI following pneumovirus inoculation in early life and subsequent asthma in later life upon allergen exposure. Prior to infection, HFD-reared pups developed microbial dysbiosis and low-grade systemic inflammation (LGSI), characterized by hyperneutropoiesis in the liver and elevated inflammatory cytokine expression, most notably granulocyte-colony stimulating factor (G-CSF), interleukin-17A (IL-17A), IL-6 and soluble IL-6 receptor (sIL-6R) (indicative of IL-6 trans-signaling) in the circulation and multiple organs but most prominently the liver. Inhibition of IL-6 trans-signaling using sgp130Fc transgenic mice or via specific genetic deletion of IL-6Ra on neutrophils conferred protection against both diseases. Taken together, our findings suggest that a maternal HFD induces neonatal LGSI that predisposes to sLRI and subsequent asthma via neutrophil-mediated IL-6 trans-signaling.

The Load Frequency Control (LFC) scheme, with its primary aim being the maintenance of uniform frequency, has been a heavily researched topic for decades. Achieving a consistent frequency necessitates a delicate balance between load demand and power generation. Researchers strive to find an optimal solution within the LFC domain—one that can effectively withstand drastic load fluctuations. Despite a plethora of efforts, the LFC dilemma remains unresolved, complicated by factors such as dwindling demand-supply and the rapid integration of renewables. Furthermore, the lack of innovation in controller structure design exacerbates the complexity of solving modern LFC problems. Consequently, a robust control approach capable of handling uncertainties while simultaneously regulating system frequency becomes crucial. In light of this, we propose a novel hybrid control architecture called 2DOF-PID-TD. This architecture combines Two Degrees Of Freedom Proportional-Integral-Derivative (2DOF-PID) and Tilt-Derivative (TD) controllers. To optimize the proposed controller, we employ a metaheuristic called the Artificial Gorilla Troops Optimizer (AGTO), which mimics the social behavior and intelligence of gorilla troops. The proposed approach is analyzed in a realistic multi-area multi-source hydro-thermal system, accounting for nonlinearities, random load perturbations, and system parametric uncertainties. Experimental results, when compared with current state-of-the-art optimization algorithms and traditional controller structures, demonstrate the prowess of our approach in terms of precision, robustness, and resilience.

Despite abundant research on the application of artificial intelligence (AI) in reverse logistics, no comprehensive study with bibliometric and network analysis has been conducted. This study uses bibliometric analysis to derive the prominent research statistics in AI-centric reverse logistics, considering 2929 articles from the last three decades. The most impactful contributors and countries that employ AI in reverse logistics are identified using various bibliometric tools. Also, network analysis is performed to reveal the most influential articles and emerging trends and map the relationships via clustering. The results of keyword co-occurrence and co-citation analyses reveal that machine learning and deep learning techniques have been commonly used for addressing reverse logistics challenges with higher frequency in recent years. Furthermore, a systematic review is carried out, considering the influential articles from recent years. The review is conducted following the systematic literature review framework, and 79 articles are chosen to be studied thoroughly. Subsequently, the articles are divided based on various reverse logistics processes, and the most frequently used AI techniques are identified and categorized into five distinct groups. The comprehensive investigation of AI techniques reveals the use-case scenario of AI algorithms in the reverse logistics domain. This study concludes with implications and recommendations for prospects by addressing the shortcomings of the current studies and providing future researchers and practitioners with a robust roadmap to investigate reverse logistics in their research further.

Introduction: Systemic lupus erythematosus (SLE), the commonest type of lupus, is an autoimmune multisystemic disorder that can affect any organ system of the body, especially blood vessels and connective tissues, causing widespread inflammation. Pediatric onset of SLE is a rare condition with more hematological involvement. Aim: This study was undertaken to observe various hematological abnormalities and their association with various autoantibodies present in pediatric SLE in Eastern India. Methodology: It was a single-centered, cross-sectional, observational, hospital-based study conducted in the Department of Pediatric Medicine in collaboration with the Department of Rheumatology in IPGME and R and SSKM Hospital, Kolkata. The duration of the study was 1.5 years, and a total of 30 children up to 12 years of age of either gender were enrolled. Study participants were evaluated for various parameters like demographic, hematological (anemia, neutropenia, leucopenia, lymphopenia, and thrombocytopenia), biochemical (CRP, Lactate dehydrogenase (LDH), and bilirubin), autoantibodies (anti-dsDNA, anti-Ro 52, and anti-Ribonucleoprotein [RNP]), and SLE related pathologies (Cutaneous, nephritis, serositis). Results: In the present study, most of the participants had arthritis, muscle pain (86.66%), and hematological involvement (80%). Among cytopenias, anemia was the commonest. dsDNA autoantibody was positive in most of the patients (83%), and about one-third suffered from autoimmune hemolytic anemia (AIHA). No association was observed between autoantibodies and various hematological manifestations. Conclusion: It can be concluded from the present study that anemia is the most common cytopenia in pediatric SLE, but there is no association between autoantibodies and these cytopenias. However, study on larger population may give better results.

Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, manual detection of such faults periodically can be both time-consuming and costly. In this paper, we have proposed a Deep Learning (DL)-based algorithm for automatic fault detection in railway tracks, which we termed an Ensembled Convolutional Autoencoder ResNet-based Recurrent Neural Network (ECARRNet). We compared its output with existing DL techniques in the form of several pre-trained DL models to investigate railway tracks and determine whether they are defective or not while considering commonly prevalent faults such as—defects in rails and fasteners. Moreover, we manually collected the images from different railway tracks situated in Bangladesh and made our dataset. After comparing our proposed model with the existing models, we found that our proposed architecture has produced the highest accuracy among all the previously existing state-of-the-art (SOTA) architecture, with an accuracy of 93.28% on the full dataset. Additionally, we split our dataset into two parts having two different types of faults, which are fasteners and rails. We ran the models on those two separate datasets, obtaining accuracies of 98.59% and 92.06% on rail and fastener, respectively. Model explainability techniques like Grad-CAM and LIME were used to validate the result of the models, where our proposed model ECARRNet was seen to correctly classify and detect the regions of faulty railways effectively compared to the previously existing transfer learning models.

The requirement for clinically effective treatments to remineralize early enamel caries lesions is dictated by the principles of minimally invasive dentistry. Numerous studies outlined the significance of treating early carious lesions with different remineralizing agents. This study aimed to evaluate and compare the remineralization potential of topical cream containing casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) and CPP-ACP with fluoride in remineralizing artificial carious lesions on enamel. Forty-five freshly extracted human premolar teeth were selected as samples. These samples were divided into three groups: Group I-regular toothpaste without specific remineralizing agent; Group II-topical cream containing CPP-ACP and Group III topical cream containing CPP-ACP with fluoride. All the samples were viewed under scanning electron microscope (SEM) to assess the topographical pictures of the enamel surface and also subjected to energy dispersing X-ray analysis (EDX) for quantitative estimation of minerals, calcium (Ca), and phosphorous (P). In the result of the study, Group I does not show any increase in the Ca and P after applying toothpaste without any remineralizing agent but Group II and Group III showed a net increase in Ca and P- values after applying concerned remineralizing agents. Intergroup comparison showed Group III yielded higher net Ca and P- values than Group II. Two remineralizing agents showed remineralization potential on samples. Descriptive statistics were used to calculate the mean and standard deviation. Mann–Whitney test was used. The level of significance was set at 0.05. CPP-ACP containing fluoride showed better remineralizing potential than CPP-ACP. Hence, CPP-ACP containing fluoride can be considered the material of choice in remineralizing early enamel carious lesions.

Objective: The effect of feeding yeast-fermented feed in various forms on broiler growth performance and bone mineralization was studied. Materials and Methods: Initially, a corn-soy-based diet was formulated and fermented in anaerobic conditions at 28°C in laboratory space for 48 h with yeast (2.0%) and moisture (50%). Afterward, the 150 newly hatched Arbeor Acres commercial broiler chicks were divided into 5 dietary groups (30 chicks, 6 cages, and 5 birds per cage). Each group received one of the following formulated and fermented diets: dry feed (DF), moist feed (MF), yeast-added dry feed (Y-DF), yeast-added moist feed (Y-MF), or yeast-fermented moist feed (YF-MF). Water and feed were supplied ad libitum. Six birds per group were slaughtered at age 37 for the determination of carcass traits and tibia ash. Results: Fermentation improved crude protein from 20.7% to 22.8% but declined crude fiber from 7.9% to 6.3% in the YF-MF group compared to the DF group. High body weight gain was recorded in 771, 830, and 992 gm in the MF, Y-MF, and YF-MF groups, respectively, compared to the DF (762 gm) group (p < 0.01). The feed conversion ratio was better in the Y-MF (1.57) and YF-MF (1.57) groups than in the DF (1.75) group. Feeding a fermented, moist diet resulted in improved carcass yield (69%) in the YF-MF group. Bone mineralization expressed a better tibia ash percentage (35% from 30%) in the YF-MF group compared to the DF group. Conclusion: Therefore, YF-MF enhanced the quality of feed and improved growth, carcass weight, and bone mineralization in broiler. [J Adv Vet Anim Res 2024; 11(1.000): 78-84]

We look at the viscous free-convective transitional magnetohydrodynamic thermal and mass flow over a plate that is always perforated and standing upright through permeable media while thermal radiation, a thermal source, and a chemical reaction are all going on. There is additional consideration for the Soret effect. The plate receives a normal application of a transversely consistent magnetic field. The magnetic Reynolds number is considerably lower considering the axial applied magnetic field instead of the induced magnetic field. The models that control mass, heat, and fluid flow are turned into two-dimensional shapes, and the answers are found by running numerical simulations using the MATLAB algorithm bvp4c. In realistic circumstances, the outcomes have been illustrated graphically. Several fluid properties have been found to have an impact on velocity, temperature, and concentration profiles. There is noticeable increase in velocity along with the growth of the permeability parameter and Soret number. Other dimensionless parameters have a significant impact on the fluid velocity. Likewise, the temperature profile diminishes as the radiation parameter has increased. The concentration distribution falls as the heat source parameter expands. Also, the analysis is encompassed in tabular form for the shearing stress, Nusselt number, and Sherwood number. The combined knowledge of heat and mass moving through viscous flows can be used to make a wide range of mechanisms and processes. These include biological reactors, therapeutic delivery systems, methods of splitting, aerodynamic aircraft design, and modeling for sustainability. It also optimizes automotive radiators and engine efficiency, and it improves cooling systems.

Incorporating pumpkin pulp into tomato sauces could serve as a viable solution to meet the growing consumer demand for healthy foods that offer functional benefits. In this study, various pumpkin: tomato pulp ratios of 100:0; 0:100; 75:25; 50:50; and 25:75 were employed in the production of sauces and named S1, S2, S3, S4, and S5, respectively. The sauces were subsequently subjected to assess their physicochemical properties (color, pH, TSS, total sugar, reducing and non-reducing sugar), content of bioactive compounds (phenolics, flavonoids, vitamin C, and β-carotene content), antioxidant and anti-diabetic activities, and consumer approval. The changes in physicochemical properties among all samples were negligible. However, the amount of non-reducing sugar and total sugar were statistically distinct (p ≤ 0.05) among the formations and the order of rank was S5>S4>S3≈S2≈S1. The sauces enriched with tomato pulp exhibited elevated levels of phenolics, flavonoids, vitamin C, and β-carotene content. The formulations of sauces were ranked: S2>S5>S4>S3>S1 concerning phenolics, flavonoids, vitamin C, and β-carotene content. The antioxidant and antidiabetic activities were significantly higher in S2 followed by the rank: S2>S4≈S5>S1≈S3. Based on the results obtained from this research, it was observed that the product formulated up to a composition of 50 to 75 % tomato pulp and 50 to 25 % pumpkin pulp (S4 and S5) exhibited a greater degree of sensory appeal compared to S2 which is commercial tomato sauce (100 % tomato). Therefore, the use of pumpkin pulp has demonstrated its usefulness as a viable substitute for augmenting the levels of bioactive components, while concurrently mitigating the quantity of color, sugar, and other nutrition employed in conventional sauce formulations.

Understanding how today’s children will act in the future is essential to education supporting sustainable development. This study investigated how students in three contexts in Nepal, Peru and Uganda understand environmental, epistemic and transitional justice. It used a tablet-based app to present students with scenarios that illustrates different attitudes, experiences and intended actions with respect to these three forms of justice and analysed responses to focus on factors related to intended actions. The analysis suggests that both attitudes and experiences are important in shaping intended actions in the future. Thus, education systems should not only develop attitudes to support sustainable development, but also exemplify and embody socially justice practices, providing students with experience of social contexts that support sustainable development.

The quality of datasets is crucial in computer graphics and machine learning research and development. This paper presents the Render Lighting Dataset, featuring 63,648 rendered images of Blender's primitive shapes with various lighting conditions and engines. The images were created using Blender 4.0′s Cycles and Eevee Render Engines, with careful attention to detail in texture mapping and UV unwrapping. The dataset covers six different lighting conditions, including Area Light, Spotlight, Point Light, Tri-Light, HDRI (Sunlight), and HDRI (Overcast), each adjusted using Blender's different options in the Color Management panel. With thirteen unique materials, ranging from Coastal Sand to Glossy Plastic, the dataset provides visual diversity for researchers to explore material properties under different lighting conditions using different render engines. This dataset serves as a valuable resource for researchers looking to enhance 3D rendering engines. Its diverse set of rendered images under varied lighting conditions and material properties allows researchers to benchmark and evaluate the performance of different rendering engines, develop new rendering algorithms and techniques, optimize rendering parameters, and understand rendering challenges. By enabling more realistic and efficient rendering, advancing research in lighting simulation, and facilitating the development of AI-driven rendering techniques, this dataset has the potential to shape the future of computer graphics and rendering technology.

Background: The traditional treatment of choice for subungual melanoma has been that of amputation. However, more recently a conservative approach with wide resection especially for paediatric subungual melanoma in-situ has been adopted. Case report: This is a case of a paediatric left little finger subungual melanoma in-situ. The child underwent wide resection and reconstruction with a full-thickness skin graft. 3 years post operation, the child has no clinical recurrence and has good cosmesis and function. We discuss the controversies and rationale for our treatment. Conclusion: We recommend considering wide resection and reconstruction with full-thickness skin graft as a viable treatment for pediatric subungual melanoma in-situ.