•First principles calculations are preformed on rock-salt type structures of TiC, TiN, ZrC, ZrN, VC, VN, NbC, NbN, MoC, TaC, and HfC to obtain following properties.•Mechanical properties: elastic ...constants, Young’s modulus, bulk modulus, shear modulus, Poisson’s ratio, cleavage energy of (111) plane.•Thermochemical properties: energy of formation, cohesive energy.•Thermophysical properties: pressure–volume relationship, the first derivative of bulk modulus, Debye temperature, heat capacity.•Wherever possible, calculated values have been compared with experimental (or other calculated) values.
The rock salt-type transition metal carbides and nitrides are excellent refractory materials as well as important microstructural constituents in High Strength Low Alloy (HSLA) steels. Therefore, it is important to have knowledge on their elastic, thermophysical and thermochemical properties in order to gain deeper understanding of their role in these contexts. In this paper we report their mechanical properties such as the elastic constants, various moduli, Poisson’s ratio and cleavage energies, thermochemical properties such as the energy of formation and cohesive energy and physical properties such as the p–V relation, first derivative of bulk modulus with respect to pressure, Debye temperature and the heat capacity determined using first principles calculations. Wherever possible, corresponding experimental data have been compared with and a good agreement is seen.
Interstitial lung diseases (ILD) are diverse diseases that share pathological, radiological, and clinical traits and involve interstitial fibrosis and inflammation. These have a significant impact on ...lung disease morbidity and mortality. From the lung High-Resolution Computed Tomography (HRCT) image, the region of interest (ROI) had to be manually identified for most of the early ILD classification investigations, which was time-consuming. Additionally, the clinical signs of various disorders are identical, which makes precise detection difficult. In recent studies, outstanding results were achieved in categorizing medical photos using deep learning techniques. For ILD classification, a hybrid deep learning network model has been developed in this research. The lung portion of the HRCT images was initially segmented using an improved U-Net++ model. The multi-scale improved U-Net++ module has been applied for effective lung segmentation with lung anomalies. The segmented lung image's features were extracted for categorization in the second stage using a Refined Attention Pyramid Network (RAPNet). Then, we developed a MobileUNetV3 to classify five ILD classes. The ILD database is used to test the proposed approach. Due to the stage-by-stage improvement in the DL method performance, the proposed hybrid deep learning network model's performance has significantly increased.
Valeriana jatamansi Jones is an aromatic herb well known for its essential oil contents, and its high medicinal and commercial values. The amount of essential oils present in it increases with ...maturity (age) of the plant. In this study, Hyperspectral remote sensing data recorded in the field using Analytical Spectral Devices (ASD) handheld spectroradiometer was used to discriminate the age (6, 12, 24 and 36 months) of V. jatamansi. Principal Component Analysis (PCA) was used for feature selection and 06 machine learning classifiers were used to classify the plant based on their ages, i.e., Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), Boosting Decision Tree (BDT), Decision Tree (DT) and k-Nearest Neighbourhood (kNN). For comparison, these classifiers were applied on full range of spectral reflectance data without feature selection and on feature-selected data using PCA. It was found that the accuracies of ANN, RF, BDT, SVM, DT and kNN were 91, 85, 57, 78, 35 and 42%, respectively for non-feature selected datasets. The accuracies of ANN and DT classifiers were, respectively, increased by 100% and 75% after applying PCA. The ANN classifiers resulted in 100% overall accuracy with a Kappa coefficient (K) of 1. The wavelength regions 860, 870 to 874, 876 to 885 nm in near-infrared (NIR), and 747 to 756 nm (red-edge) were identified as regions suitable for discriminate the age groups of V. jatamansi. The final trained model thus prepared was again validated on 60 plants (with different age group) grown in its natural habitat and the obtained accuracy was 88% (K = 0.84). Thus, the present study have provided a rapid technology for onsite identification of age of V. jatamansi in the field itself. The developed technology thus provides a scientific way for harvesting of this plant at its optimum age avoiding its wastage. The results of this study can also be applied to other endangered and valuable plants by way of finding its optimum growth stages for its harvesting.
This study was conducted to characterize canine bone marrow‐derived mesenchymal stem cells (BMSCs); in vivo tracking in mice, and therapeutic evaluation in canine clinical paraplegia cases. Canine ...BMSCs were isolated, cultured, and characterized in vitro as per International Society for Cellular Therapy criteria, and successfully differentiated to chondrogenic, osteogenic, and adipogenic lineages. To demonstrate the homing property, the pGL4.51 vector that contained luciferase reporter gene was used to transfect BMSCs. Successfully transfected cells were injected around the skin wound in mice and in vivo imaging was done at 6, 12 and 24 hr post MSCs delivery. In vivo imaging revealed that transfected BMSCs migrated and concentrated predominantly toward the center of the wound. BMSCs were further evaluated for allogenic therapeutic potential in 44 clinical cases of spinal cord injuries (SCI) and compared with conventional therapy (control). Therapeutic potential as evaluated by different body reflexes and recovery score depicted significantly better results in stem cell‐treated group compared to control group. In conclusion, allogenic canine BMSCs can serve as potent therapeutic candidate in cell‐based therapies, especially for diseases like SCI, where the conventional medication is not so promising.
Canine bone marrow‐derived mesenchymal stem cells (BMSCs) successfully tracked in excision wounds.
MSCs can be used allogenically for regenerative medicine.
MSCs found very effective for nerve injury cases which are otherwise difficult to treat.
The present study focuses on the pathological and molecular characterization of African swine fever virus (ASFV) associated with an outbreak in wild boars in two national parks in southern India in ...2022–2023. Significant mortality was observed among free-ranging wild boars at Bandipur National Park, Karnataka, and Mudumalai National Park, Tamil Nadu. Extensive combing operations were undertaken in both national parks, spanning an area of around 100 km
2
, originating from the reported epicenter, to estimate the mortality rate. Recovered carcasses were pathologically examined, and ASFV isolates was genetically characterized. Our findings suggested spillover infection of ASFV from nearby domestic pigs, and the virus was equally pathogenic in wild boars and domestic pigs. ASFV intrusion was reported in the Northeastern region of the country, which borders China and Myanmar, whereas the current outbreak is very distantly located, in southern India. Molecular data will help in tracing the spread of the virus in the country.
Physiological signals such as electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) provide valuable clinical information but pose challenges for analysis due to their ...high-dimensional nature. Traditional machine learning techniques, relying on hand-crafted features from fixed analysis windows, can lead to the loss of discriminative information. Recent studies have demonstrated the effectiveness of deep convolutional neural networks (CNNs) for robust automated feature learning from raw physiological signals. However, standard CNN architectures require two-dimensional image data as input. This has motivated research into innovative signal-to-image (STI) transformation techniques to convert one-dimensional time series into images preserving spectral, spatial, and temporal characteristics. This paper reviews recent advances in strategies for physiological signal-to-image conversion and their applications using CNNs for automated processing tasks. A systematic analysis of EEG, EMG, and ECG signal transformation and CNN-based analysis techniques spanning diverse applications, including brain-computer interfaces, seizure detection, motor control, sleep stage classification, arrhythmia detection, and more, are presented. Key insights are synthesised regarding the relative merits of different transformation approaches, CNN model architectures, training procedures, and benchmark performance. Current challenges and promising research directions at the intersection of deep learning and physiological signal processing are discussed. This review aims to catalyse continued innovations in effective end-to-end systems for clinically relevant information extraction from multidimensional physiological data using deep neural networks by providing a comprehensive overview of state-of-the-art techniques.
This paper deals with the study of dimple type RF MEMS capacitive shunt switch using different meandering techniques for high isolation and low actuation voltage. The novelty of the proposed RF MEMS ...switch is it incorporates the meanders and dimples, which help to reduce the actuation voltage. The proposed switch structure is optimized, designed, and simulated with FEM analysis such as electromechanical and electromagnetic by using COMSOL and HFSS tools respectively. The best performance of the switch is observed by varying different parameters such as beam material, beam thickness, dielectric thickness, and airgap. The proposed switch with different meandering techniques attains the pull-in voltage in the range of 10.3-46 V, particularly the three uniform meander technique has low actuation voltage of 10.3 V. The RF performance of the device is particularly tuned in the range of 26.5-40 GHz frequency range and it is analyzed for all types of meanders. Among them, the non-uniform single meander has attained the best isolation of -54.13 dB at 40 GHz in the off state. The insertion and return losses of the device are -0.514 dB and -17.35 dB over 1-40 GHz frequency in on state.
•We report the first complete genome characterization of LSDV from India, LSDV-WB/IND/19 from a calf in 2019 outbreak isolated in vero cells determined by Illumina next-generation sequencing ...(NGS).•LSDV-WB/IND/19 has a genome size of 150,969 bp encoding 156 putative ORFs.•Phylogenetic analysis based on complete genome sequence suggested that LSDV-WB/IND/19 is closely related to Kenyan LSDV strains with 10–12 variants.•In contrast to complete kelch-like proteins in Kenyan LSDV strains, LSDV-WB/IND/19 LSD_019 and LSD_144 genes were found to encode truncated versions (019a, 019b, and 144a, 144b).•This study demonstrates the circulation of unique Kenyan-like LSDV strains in India and highlights the importance of constant monitoring of the molecular evolution of LSDV.
Lumpy skin disease (LSD) is an economically important poxviral disease endemic to Asia, Europe, and Africa. Recently, LSD has spread to naïve countries, including India, China, Bangladesh, Pakistan, Myanmar, Vietnam, and Thailand. Here, we describe the complete genomic characterization of LSDV from India, LSDV-WB/IND/19 isolated from an LSD affected calf in 2019 determined by Illumina next-generation sequencing (NGS). The LSDV-WB/IND/19 has a genome size of 150,969 bp encoding 156 putative ORFs. Phylogenetic analysis based on complete genome sequence suggested that LSDV-WB/IND/19 is closely related to Kenyan LSDV strains with 10–12 variants with non-synonymous changes confined to LSD_019, LSD_049, LSD_089, LSD_094, LSD_096, LSD_140, and LSD_144 genes. In contrast to complete kelch-like proteins in Kenyan LSDV strains, LSDV-WB/IND/19 LSD_019 and LSD_144 genes were found to encode truncated versions (019a, 019b, and 144a, 144b). LSD_019a and LSD_019b proteins of LSDV-WB/IND/19 resemble that of wild-type LSDV strains based on SNPs and the C-terminal part of LSD_019b except for deletion at K229, whereas the LSD_144a and LSD_144b proteins resemble that of Kenyan LSDV strains based on SNPs, however, C-terminal part of LSD_144a resembles that of vaccine-associated LSDV strains due to premature truncation. The NGS findings were confirmed by Sanger sequencing of these genes in Vero cell isolate as well as in the original skin scab along with similar findings in another Indian LSDV from scab specimen. LSD_019 and LSD_144 genes are thought to modulate virulence and host range in capripoxviruses. This study demonstrates the circulation of unique LSDV strains in India and highlights the importance of constant monitoring of the molecular evolution of LSDV and associated factors in the region in light of the emergence of recombinant LSDV strains.
Machining of polymeric composite is inevitable during assembly of components. In view of making holes on structural composites, drilling is essential and a study to optimize the machining parameters ...is very important. The present study has been made to investigate the defaces and cutting forces associated during drilling of natural fiber reinforced plastics. Plastic composite has been manufactured using chemically treated
vetiveria zizanioides
as the reinforcement and polyester as the matrix. The composite has been drilled several times on the basis of central composite design. Speed and feed rate of the spindle, point angle and diameter of the tool are considered as the input parameters. Deface of each hole during entry and exit, thrust force and torque have been measured as the output parameters. A fuzzy model has been created and a comparative study between the central composite design and fuzzy model is made. The design has been optimized with the objective of minimizing the output parameters and a set of confirmatory experiments have been conducted. The central composite model has been validated by comparing it with the fuzzy model and confirmatory runs. The comparison presented only a minimal error and hence the modeling by central composite design and fuzzy are consummate.
The need of the natural fibers as an alternative for existing synthetic fibers is in great demand for automotive applications. The primary objective of this work is to examine the effect of palm ...kernel fibers as the replacement of existing synthetic fibers. In this work the palm kernel shell fiber is added in three different weight percentages such as 0%, 5% and 10% and developed in the form of the standard brake pad as per industrial standards by keeping the Barites were used as an space filling ingredient. The various Physical, Chemical and mechanical properties were examined as per industrial standards. Chase Test Rig was used to examine the Tribological properties. Based on the evaluated Results it can be concluded that the coefficient of friction shows a decreasing value on increasing the fiber content. The Brake pad Composites containing 5 wt% of palm kernel fibers possessed high frictional value 0.454 and fade percentage was low with minimal undulations. Palm kernel fibers with 10 weight percentages showed some undulations. It can be concluded Palm Kernel Fiber with 5 weight percentage can be used as a replacement of the synthetic fibers. Scanning Electron Microscopy was used to determine the wear mechanism of the developed brake pad composites.
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