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Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the position of the bird at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field.

The importance of plant genetic diversity (PGD) is now being recognized as a specific area since exploding population with urbanization and decreasing cultivable lands are the critical factors contributing to food insecurity in developing world.Agricultural scientists realized thatPGDcan be captured and stored in the formof plant genetic resources (PGR) such as gene bank,DNAlibrary, and so forth, in the biorepository which preserve genetic material for long period. However, conserved PGR must be utilized for crop improvement in order to meet future global challenges in relation to food and nutritional security.This paper comprehensively reviews four important areas; (i) the significance of plant genetic diversity (PGD) and PGR especially on agriculturally important crops (mostly field crops); (ii) risk associated with narrowing the genetic base of current commercial cultivars and climate change; (iii) analysis of existing PGD analytical methods in pregenomic and genomic era; and (iv) modern tools available for PGD analysis in postgenomic era. This discussion benefits the plant scientist community in order to use the new methods and technology for better and rapid assessment, for utilization of germplasm from gene banks to their applied breeding programs. With the advent of new biotechnological techniques, this process of genetic manipulation is now being accelerated and carried out with more precision (neglecting environmental effects) and fast-track manner than the classical breeding techniques. It is also to note that gene banks look in to several issues in order to improve levels of germplasm distribution and its utilization, duplication of plant identity, and access to database, for prebreeding activities. Since plant breeding research and cultivar development are integral components of improving food production, therefore, availability of and access to diverse genetic sources will ensure that the global food production network becomes more sustainable. The pros and cons of the basic and advanced statistical tools available for measuring genetic diversity are briefly discussed and their source links (mostly) were provided to get easy access; thus, it improves the understanding of tools and its practical applicability to the researchers

In this manuscript, a dramatic increase in the energy density of ~ 69 Wh kg −1 and an extraordinary cycleability ~ 2000 cycles of the Li-ion hybrid electrochemical capacitors (Li-HEC) is achieved by employing tailored activated carbon (AC) of ~ 60% mesoporosity derived from coconut shells (CS). The AC is obtained by both physical and chemical hydrothermal carbonization activation process and compared to the commercial AC powders (CAC) in terms of the supercapacitance performance in single electrode configuration vs. Li. The Li-HEC is fabricated with commercially available Li 4 Ti 5 O 12 anode and the coconut shell derived AC as cathode in non-aqueous medium. The present research provides a new routine for the development of high energy density Li-HEC that employs a mesoporous carbonaceous electrode derived from bio-mass precursors.

In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets’ inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes. Our model’s superior performance, demonstrated through rigorous evaluation, exhibits significant improvements in accuracy, precision, recall, and F1 score, even with limited data. The results highlight the potential of ESACN as a reliable tool for enhancing diagnostic accuracy in medical settings. In our case study, the ESACN model was applied to a dataset comprising 659 images across four classes: 178 images of Monkeypox, 171 of Chickenpox, 80 of Measles, and 230 of Normal skin conditions. This case study underscores the model’s effectiveness in real-world applications, providing robust and accurate classification that could greatly aid in early diagnosis and treatment planning in clinical environments.

Background: In this article, we attempt to demonstrate the superiority of the Bayesian approach over the frequentist approaches of the multiple linear regression model in identifying the influencing factors for the response variable. Methods and Material: A survey was conducted among the 310 respondents from the Kathirkamam area in Puducherry. We have considered the response variable, body mass index (BMI), and the predictors such as age, weight, gender, nature of the job, and marital status of individuals were collected with the personal interview method. Jeffreys's Amazing Statistics Program (JASP) software was used to analyze the dataset. In the conventional multiple linear regression model, the single value of regression coefficients is determined, while in the Bayesian linear regression model, the regression coefficient of each predictor follows a specific posterior distribution. Furthermore, it would be most useful to identify the best models from the list of possible models with posterior probability values. An inclusion probability for all the predictors will give a superior idea of whether the predictors are included in the model with probability. Results and Conclusions: The Bayesian framework offers a wide range of results for the regression coefficients instead of the single value of regression coefficients in the frequentist test. Such advantages of the Bayesian approach will catapult the quality of investigation outputs by giving more reliability to solutions of scientific problems.

In recent times, video inpainting techniques have intended to fill the missing areas or gaps in a video by utilizing known pixels. The variety in brightness or difference of the patches causes the state-of-the-art video inpainting techniques to exhibit high computation complexity and create seams in the target areas. To resolve these issues, this paper introduces a novel video inpainting technique that employs the Morphological Haar Wavelet Transform combined with the Krill Herd based Criminisi algorithm (MHWT-KHCA) to address the challenges of high computational demand and visible seam artifacts in current inpainting practices. The proposed MHWT-KHCA algorithm strategically reduces computation times and enhances the seamlessness of the inpainting process in videos. Through a series of experiments, the technique is validated against standard metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), where it demonstrates superior performance compared to existing methods. Additionally, the paper outlines potential real-world applications ranging from video restoration to real-time surveillance enhancement, highlighting the technique’s versatility and effectiveness. Future research directions include optimizing the algorithm for diverse video formats and integrating machine learning models to advance its capabilities further.

Biomass utilization has received much attention for production of high density solid fuels. Utilization of cheap and naturally available precursors through environmentally friendly and effective processes is an attractive and emerging research area. Pyrolysis and hydrothermal carbonization (HTC) are well-known technologies available for production of solid biofuel using conventional or microwave heating. Microwave heating is a simpler and more efficient heating method than conventional heating. This study presents a critical review on microwave pyrolysis and microwave HTC for solid fuel production in terms of yield and quality of products. Moreover, a brief summary of parameters of microwave pyrolysis and microwave HTC are discussed. The fuel, chemical, structural and thermal weight loss characteristics of solid fuels produced from different biomass are discussed and compared.

Hydrological processes, including runoff generation, depend on the distribution of water in a catchment, which varies in space and time. This paper presents experimental results from a headwater research catchment in New Zealand, where we made distributed measurements of streamflow, soil moisture and groundwater levels, sampling across a range of aspects, hillslope positions, distances from stream and depths. Our aim was to assess the controls, types and implications of spatial and temporal variability in soil moisture and groundwater tables. We found that temporal variability in soil moisture and water table is strongly controlled by the seasonal cycle in potential evapotranspiration, for both the mean and extremes of their distributions. Groundwater is a larger water storage component than soil moisture, and this general difference increases even more with increasing catchment wetness. The spatial standard deviation of both soil moisture and groundwater is larger in winter than in summer. It peaks during rainfall events due to partial saturation of the catchment, and also rises in spring as different locations dry out at different rates. The most important controls on spatial variability in storage are aspect and distance from the stream. South-facing and near-stream locations have higher water tables and showed soil moisture responses for more events. Typical hydrological models do not explicitly account for aspect, but our results suggest that it is an important factor in hillslope runoff generation. Co-measurement of soil moisture and water table level allowed us to identify relationships between the two. Locations where water tables peaked closer to the surface had consistently wetter soils and higher water tables. These wetter sites were the same across seasons. However, patterns of strong soil moisture responses to summer storms did not correspond to the wetter sites. Total catchment spatial variability is composed of multiple variability sources, and the dominant type is sensitive to those stores that are close to a threshold such as field capacity or saturation. Therefore, we classified spatial variability as \"summer mode\" or \"winter mode\". In \"summer mode\", variability is controlled by shallow processes, e.g. interaction of water with soils and vegetation. In \"winter mode\", variability is controlled by deeper processes, e.g. groundwater movement and bypass flow. Double streamflow peaks observed during some events show the direct impact of groundwater variability on runoff generation. Our results suggest that emergent catchment behaviour depends on the combination of these multiple, time varying components of storage variability.

The potassium L-ascorbate monohydrate (KLAM) crystal was grown by slow evaporation technique. The EDX analysis shows the presence of chemical elements in the KLAM crystal. In d norm surface, the red (− 0.721), blue (0.804), and white (zero) are used to denote the positive, negative, and neutral values of KLAM intermolecular interactions. The C–O–C stretching mode of the KLAM molecule is noted at 1123 cm −1 in the FTIR spectrum. The KLAM crystal has no absorption in the Vis–NIR regions. The isoascorbate fragment is located on the LUMO orbital. The fragmentation orbitals (H, K, C and O) are caused by the partial density of states. The calculated dipole moment ( μ ) of KLAM is 15.7385 Debye. The chemical hardness is found to be 0.47 eV. The contact of H atoms with ring atoms causes the positive attraction in the KLAM molecule. All the oxygen atoms of KLAM possess electronegative charges. The electronic transition π (C3—C4) → π* (C1–O7) has stabilization energy value of 206.05 kJ/mol. The KDP and KLAM both have SHG output voltage of 30 mV and 33 mV, respectively. The emission spectrum was measured from 350 to 525 nm. TG/DTA analysis shows that the KLAM has two endothermic points at 134 and 600 ℃.