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AbstractControlling thermal loads in heat transfer systems that produce high heat flux is a real mechanical challenge. Various cooling/heating techniques are available to achieve the reliability requirements of electronic devices. Among them, the use of nanofluids is one of the important techniques that provide long term stability, higher cooling rates, decreased pumping power needs, and cost-effectiveness. Instability in fluids typically occurs when a disturbance affects the equilibrium of forces of external, inertial, or viscous origin acting on a system. The disturbances may arise from the surroundings due to small changes in the boundary conditions, surface roughness, free stream turbulence, noise, etc. In several circumstances, these disturbances are very small and hence cannot be measured with the available instruments but can be observed after the instability sets in. In this study, we focus on examining the effect of time-periodic vertical gravity modulation on the initiation of natural convection in a porous medium saturated with a nanofluid. The porous medium is characterized by being heated at the bottom and possessing anisotropic properties in terms of permeability and thermal diffusivity. Specifically, we investigate the onset of convection in water-based nanofluids that contain metallic (Cu) and metal oxide (Al2O3) particles. The Khanafer-Vafai-Lightstone (KVL) nanofluid model is employed to describe the behavior of the nanofluids, and the thresholds for convective instability are determined using the Mathieu functions. In addition, we study the instabilities of synchronous and subharmonic modes and explore their transitions along with practical applications. [ABSTRACT FROM AUTHOR]

This article presents a rare case of mesothelioma in a Labrador Retriever dog. The dog exhibited symptoms such as a distended abdomen, respiratory distress, and exercise intolerance. Diagnostic tests were conducted to confirm the presence of mesothelioma in both the thoracic and peritoneal cavities. The article also discusses the characteristics and risk factors associated with mesothelioma in dogs, including exposure to asbestos and acaricides. Treatment options for mesothelioma in dogs, such as surgery, radiotherapy, and chemotherapy, are mentioned, but the prognosis is generally poor. The article emphasizes the importance of a definitive diagnosis through effusion of cell sediment and complementary tests. [Extracted from the article]

Background: Pneumococcal disease caused by Streptococcus pneumoniae is an important cause of morbidity and mortality across all ages, particularly in younger children and older adults. Here, we describe pneumococcal disease hospitalizations at Ministry of Health (MoH) facilities in Malaysia between 2013 and 2015. Methods: This was a retrospective databases analysis. Tabular data from the Malaysian Health Data Warehouse (MyHDW) were used to identify microbiologically confirmed, pneumococcal disease hospitalizations and deaths during hospitalization, using hospital-assigned ICD-10 codes (i.e., classified as meningitis, pneumonia, or non-meningitis non-pneumonia). Case counts, mortality counts, and case fatality rates were reported by patient age group and by Malaysian geographic region. Results: A total of 683 pneumococcal disease hospitalizations were identified from the analysis: 53 pneumococcal meningitis hospitalizations (5 deaths and 48 discharges), 413 pneumococcal pneumonia hospitalizations (24 deaths and 389 discharges), and 205 non-meningitis non-pneumonia pneumococcal disease hospitalizations (58 deaths and 147 discharges). Most hospitalizations occurred in children aged < 2 years. Crude mortality was highest among children aged < 2 years (for all three disease categories), among adults aged ≥ 65 years (for pneumococcal pneumonia), or among adults aged 65–85 years (for non-meningitis non-pneumonia pneumococcal disease). The case fatality rate, all ages included, was 5.8% for pneumococcal pneumonia, 9.1% for pneumococcal meningitis, and 28.3% for non-meningitis non-pneumonia pneumococcal disease. Conclusions: Our study is the first to document pneumococcal disease hospitalizations and deaths during hospitalization in Malaysia. Although this database analysis likely underestimated case counts, and the true disease burden could be even greater, the study demonstrates a substantial burden of pneumococcal disease. Public health measures, including vaccination, would significantly contribute to the prevention of hospitalizations and deaths associated with pneumococcal disease in Malaysia. [ABSTRACT FROM AUTHOR]

Background: Pneumococcal disease caused by Streptococcus pneumoniae is an important cause of morbidity and mortality across all ages, particularly in younger children and older adults. Here, we describe pneumococcal disease hospitalizations at Ministry of Health (MoH) facilities in Malaysia between 2013 and 2015. Methods: This was a retrospective databases analysis. Tabular data from the Malaysian Health Data Warehouse (MyHDW) were used to identify microbiologically confirmed, pneumococcal disease hospitalizations and deaths during hospitalization, using hospital-assigned ICD-10 codes (i.e., classified as meningitis, pneumonia, or non-meningitis non-pneumonia). Case counts, mortality counts, and case fatality rates were reported by patient age group and by Malaysian geographic region. Results: A total of 683 pneumococcal disease hospitalizations were identified from the analysis: 53 pneumococcal meningitis hospitalizations (5 deaths and 48 discharges), 413 pneumococcal pneumonia hospitalizations (24 deaths and 389 discharges), and 205 non-meningitis non-pneumonia pneumococcal disease hospitalizations (58 deaths and 147 discharges). Most hospitalizations occurred in children aged < 2 years. Crude mortality was highest among children aged < 2 years (for all three disease categories), among adults aged ≥ 65 years (for pneumococcal pneumonia), or among adults aged 65–85 years (for non-meningitis non-pneumonia pneumococcal disease). The case fatality rate, all ages included, was 5.8% for pneumococcal pneumonia, 9.1% for pneumococcal meningitis, and 28.3% for non-meningitis non-pneumonia pneumococcal disease. Conclusions: Our study is the first to document pneumococcal disease hospitalizations and deaths during hospitalization in Malaysia. Although this database analysis likely underestimated case counts, and the true disease burden could be even greater, the study demonstrates a substantial burden of pneumococcal disease. Public health measures, including vaccination, would significantly contribute to the prevention of hospitalizations and deaths associated with pneumococcal disease in Malaysia. [ABSTRACT FROM AUTHOR]

In this study, machine learning algorithms viz., k-Nearest Neighbor Regression (KNN), Decision Trees Regression (DTR), Random Forest Regression (RFR), and Extra Tree Regression (ETR) are employed to predict the strength (tensile, shear and impact) of the aluminium 6061-stainless steel 304 explosive clads having different grooves on the base plate. The explosive cladding process parameters, namely the explosive mass to flyer mass ratio (0.6–1.0), distance between flyer and base plate (5–9 mm), predetermined angle (5°–15°), and groove on the base plate (V/Dovetail), were varied in 60 explosive cladding trials. Owing to the prevailing nonlinear relationship between different explosive cladding process parameters, predicting the strength characteristics by analytical techniques is intricate and hence computational machine learning approaches gain significance. The machine learning algorithms were trained in a Python environment using the tensile, shear and impact strengths collected from 80% of the experiments and preliminary experiments, and tested with the remaining results. The four models are capable of aptly predicting the strengths (tensile, shear and impact toughness), as evidenced by the less than 10% deviation from the experimental results. The ETR algorithm exceeds the other three in terms of accuracy (>5%) in predicting the strength of the explosive clads. [ABSTRACT FROM AUTHOR]

Thyroid cancer is a rare disease that often goes undetected until it reaches advanced stages. This study presents a novel approach for identifying Thyroid Imaging Reporting and Data System (TI‐RADS) stages of thyroid nodules using a deep convolutional neural network (Deep‐CNN) model. Our method incorporates pre‐processing, segmentation and feature extraction using colour based fuzzy‐c‐means and K‐means clustering, followed by deep learning classification. We demonstrate the efficacy of our proposed approach by achieving a success rate of 87% for classifying TI‐RADS1, TI‐RADS2, TI‐RADS3, TI‐RADS4 and TI‐RADS5 stages, outperforming other state‐of‐the‐art models. Our study fills an important gap in the literature, as previous studies have mainly focused on the margins of thyroid nodules rather than their calcium flecks. Our results offer promise for improving the accuracy and efficiency of thyroid cancer detection and management. [ABSTRACT FROM AUTHOR]

Titanium dioxide nanofluid is used in the thermosyphon solar flat plate collector at volume fractions of 0.1%, 0.3%, 0.5%, 0.7%, and 1% to test the collector's effectiveness. The heat transfer coefficient, Nusselt number, friction factor, and pressure drop calculations were used to analyze the impact of adding nanoparticles to the working fluid. The effectiveness of the solar flat plate collector and the heat transfer coefficient are both greatly affected by the addition of titanium dioxide to the working fluid, with a tolerable rise in pressure drop. With concomitant variances of 15% and 13%, correlations were constructed for the Nusselt number and friction factor. [ABSTRACT FROM AUTHOR]

The curent harmonics, voltage unbalance, sag and swell conditions are the serious power quality problems(PQ) arising in a power distribution system. The impact of unified power quality conditioner for mitigation of power quality problems in utility and customer side is investigated in the paper. The topology of UPQC is configured from the two voltage source inverters connected back to back with a common DC link acting as a series and shunt active power filter. The DC link voltage is greatly perturbation by voltage unbalance in utility side and sudden load change in customer side. The hysteresis voltage and current controller of UPQC strategy are implemented with the aim to have the robust control on compensation voltage and compensation current generated by the series and shunt active filter respectively. An elaborative proposed strategy applied to practical issues is investigated in Matlab/Simulink simulation tool. [ABSTRACT FROM AUTHOR]

The classification of the brain tumor image is playing a vital role in the medical image domain, and it directly assists the clinicians to understand the severity and to take an appropriate solution. The magnetic resonance imaging tool is used to analyze the brain tissues and to examine the different portion of brain circumstance. We propose the convolutional neural network database learning along with neighboring network limitation (CDBLNL) technique for brain tumor image classification in medical image processing domain. The proposed system architecture is constructed with multilayer-based metadata learning, and they have integrated with CNN layer to deliver the accurate information. The metadata-based vector encoding is used, and the type of coding estimation for extra dimension is known as sparse. In order to maintain the supervised data in terms of geometric format, the atoms of neighboring limitation are built based on a well-structured k -neighbored network. The resultant of the proposed system is considerably strong and subjective for classification. The proposed system used two different datasets, such as BRATS and REMBRANDT, and the proposed brain MRI classification technique outcome is more efficient than the other existing techniques. [ABSTRACT FROM AUTHOR]

This work is concerned with finding nonlinear stability limits of a thermally stratified horizontal layer governed by the Darcy–Lapwood–Brinkman equations. Time periodic modulation is imposed on either the boundary temperatures or the gravitational field permeating the layer. Unlike the classical theory of porous media, thermodynamic non-equilibrium is assumed within the layer in the form of non-negligible temperature differences. The solid and fluid constituents may undergo their own temperature variations and the heat flow is studied using the two-temperature model. The generalized energy method is employed to determine the relevant limits that suffices the system stability. The non-equilibrium and modulational parameters are found to affect the stability limits that are based on a higher-order Galerkin solution. Moreover, it is established that the stability limits so obtained are unconditional in the Euclidean measure. [ABSTRACT FROM AUTHOR]

Due to the growth of Big Data (BD) storage and access in cloud computing infrastructure, the detection of anomalies for Cloud Servers (CSs) is essential to ensure data confidentiality. Over the past decades, different security systems have been designed based on various methods like encryption, Access Policy (AP) control schemes, signcryption and so on. Among many security systems, a new Improved NTRU (INTRU) decryption based on the AP strategy has been suggested to secure the BD processed by the CSs. Also, the shared secret data was authenticated to defend the clients from anomalies in the cloud. But, the AP upgrade must not degrade the confidentiality of storing information, reveal trust in the CS or cause any different security challenges. It is not considered that such security challenges occur when the data owner shares its data with many CSs. Hence in this article, an INTRU with Detecting Anomalous in CS (INTRU-DACS) system is proposed that employs a deep learning-based Anomaly Detection System (ADS) to handle and secure the BD stored in the CSs. The main goal of this method is to effectively identify the abnormalities in the real world by the conduct utilization, i.e., the System Call Identifier Sequences (SCISs) created from CSs in which these conducts are associated with BD. Initially, effective data summarization is constructed via different feature states to analyze the SCISs of specific durations. After that, an anomaly identification algorithm is proposed to train and test the streaming of raw SC sequences. This observable SCs execution task of CSs is gathered from log files. The variations of such SCISs having a specified duration are random for usual and unusual sequences. So, the fact of current normal and abnormal services is recognized regarding their SCISs. Such normal and abnormal behavioral states are learned from Convolutional Neural Network-Hidden Markov Model (CNNHMM) classifier to identify the anomalies in CSs. But, it is still a challenging process because of the patterns of usual and unusual events. The performance is not effective since it models only the conduct of a huge number of SCISs created from a single CS. As a result, a Secure Access Control Scheme with DACS (SACS-DACS) system is proposed in which a Multidimensional Feature Misbehavior Server Detection method (MFMSD) is introduced for detecting anomalies in multiple CSs. In this method, large-scale SCISs of multiple CSs are extracted, including different features such as network traffic sequence features, CPU energy usage and memory usage from host logs. These extracted multidimensional features are fed to the CNNHMM that identifies the anomalies and maximizes the detection accuracy. At last, the simulation results demonstrate the effectiveness of the SACS-DACS and INTRU-DACS as compared to the INTRU. [ABSTRACT FROM AUTHOR]

This study deals with the application of soft computing techniques viz., response surface methodology, artificial neural network, radial basis function network and support vector regression in analyzing and predicting the ram tensile and shear strengths of aluminium 5052–stainless steel 316 explosive clads, having different interlayer. 60 explosive cladding experiments were conducted, based on central composite design of experiments, by varying the process parameters viz., loading ratio (mass of the explosive/mass of the flyer plate: 0.6–1.0), distance of separation (6–10 mm), preset angle (6°–8°) and interlayer (aluminium 1100/pure copper/stainless steel 304). The responses viz., ram tensile and shear strengths obtained from 90% of the experiments and trial experiments are used for training artificial neural network, radial basis function network and support vector regression in a Matlab environment, altering training algorithms and number of neurons in the hidden layer. The remaining 10% of the experimental outcome is used for testing the developed models. Likewise in RSM, regression equations are generated for the responses, based on analysis of variance. All the four models are capable of predicting the ram tensile and shear strength effectively, as the average percentage deviation with the experimental outcome are less than 10%. Of the three models, artificial neural network model predicts the ram tensile strength and shear strength in a better manner. [ABSTRACT FROM AUTHOR]

• Developed 3D numerical model for sodium spreading using viscous-gravity current theory. • Validated the model using benchmark experiments of pool-spreading phenomena. • Simulated the spreading process of sodium under various leak scenarios in SFR cells. • Evaluated the effect of floor slope and sodium leak rate on dynamics of pool spreading. The accidental leaks of coolant from the heat transport circuit of Sodium-cooled Fast Reactor (SFR) can create fire events due to the reactivity of sodium with atmospheric oxygen, which can pose threat to safe operation of the reactor. The leaked sodium eventually reaches the cell floor, spreads gradually, and forms a burning pool. The thermal consequences of pool fire depend on its surface area, which is determined by the spreading process of sodium on the floor surface. In this context, numerical investigation has been carried out on the spreading behavior of burning sodium pool on the plane/sloped cell floor by developing a 3-D numerical model based on the viscous-gravity current equation of the shallow layer model. The governing equations of the model have been solved numerically by implementing the Finite Volume Method. The model developed has been validated using the experimental results published on liquid pool spreading under burning and non-burning conditions on plane and sloped floors for different leak rates. Using this model, numerical simulations have been carried out on sodium pool spreading under various leak scenarios envisaged in SFR cells based on the specific burning characteristics of sodium pool fire. The time-varying pool size and shape, pool height profile, and maximum pool area have been estimated for a wide range of sodium leak rates and typical floor slopes of interest to nuclear power plants. These predictions contribute towards the numerical evaluation of sodium pool fire scenarios pertaining to the safety of SFR. [ABSTRACT FROM AUTHOR]

The W-TiC composites with various concentrations of TiC were produced via powder metallurgy. The high energy ball mill was used for the manufacturing of the samples. In this paper, we have selected (Taguchi Analysis) the optimizing parameters such as sintering temperature, and compaction pressure as inputs and corresponding outputs are compressive strength and microstructure. The compressive strength was analyzed by changing the three variances which found that, the compressive strength improved with the addition of TiC. The surface morphology of the sample was verified with SEM examination which confirms the improvement in the strength of material having higher concentration of TiC with higher sintering temperature and compaction pressure. [ABSTRACT FROM AUTHOR]

Hastelloy C-276 (UNS N10276) nickel-based alloy is widely employed in the fabrication of nuclear reactor components and corrosive resistant equipment. In this work Hastelloy C-276 sheets were butt welded by a pulsed Nd:YAG laser welding machine at different thermal energy conditions. The resulting variation in macrostructure, microstructure and mechanical properties are presented. The thermal energy supplied (beam power/weld speed) was altered by varying the operational parameters viz. weld speed (350 to 450 mm/min), laser beam energy (10 to 14 J) and laser beam pulse width (6 to 8 ms). The weld macrostructures were seen to be free from cracks and defects, exhibiting complete penetration and the crest (top width) of the weld increases with the thermal energy supplied. In the microanalysis, growth of dendrite grains from periphery to mid-section of the weld was observed. In addition, Mo rich compounds and carbides are witnessed in the weld zone (WZ) for higher thermal energy conditions. The tensile and yield strengths of the weld joints are inversely proportional to the thermal energy supplied. [ABSTRACT FROM AUTHOR]

Thermovibrational convection in a water based metallic (Cu-water and Ag-water) or metallic oxide (Al 2 O 3 -water and TiO 2 -water) nanofluid saturated porous medium is addressed incorporating the Brinkman boundary correction. The nanofluid behaves more like a fluid rather than a conventional solid–fluid mixture and is studied through Khanafer–Vafai–Lightstone (KVL) model. A linear stability analysis is carried out through the Floquet theory to find the instability thresholds for convection onset in terms of critical Rayleigh number and critical wavenumber. The results corresponding to synchronous as well as subharmonic modes are obtained for the Darcy and Brinkman regimes. A rise in particle concentration is found to cause stabilizing response in general. However, it leaves an opposite effect in the Brinkman regime when the medium is filled with metallic nanofluid and is heated from above. Under this situation, the use of oblate-spheroidal particles in achieving optimal convective heat transfer enhancement is highlighted. • Floquet theory is used to investigate convective instability under periodic gravity. • Khanafer–Vafai–Lightstone (KVL) homogeneous model is used for the nanofluid. • Influence of boundary friction is included in the equations for porous media flows. • Synchronous and subharmonic instability modes are considered. • Use of non-spherical particles for heat transfer enhancement is explained. [ABSTRACT FROM AUTHOR]

Foot-and-mouth disease virus (FMDV) causes a severe infection in ruminant animals. Here we present an in-depth transcriptional analysis of soft-palate tissue from cattle experimentally infected with FMDV. The differentially expressed genes from two Indian cattle (Bos indicus) breeds (Malnad Gidda and Hallikar) and Holstein Friesian (HF) crossbred calves, highlighted the activation of metabolic processes, mitochondrial functions and significant enrichment of innate antiviral immune response pathways in the indigenous calves. The results of RT-qPCR based validation of 12 genes was in alignment with the transcriptome data. The indigenous calves showing lesser virus load, elicited early neutralizing antibodies and IFN-γ immune responses. This study revealed that induction of potent innate antiviral response and cell mediated immunity in indigenous cattle, especially Malnad Gidda, significantly restricted FMDV replication during acute infection. These data highlighting the molecular processes associated with host-pathogen interactions, could aid in the conception of novel strategies to prevent and control FMDV infection in cattle. • RNA-Seq transcriptome was compared in three breeds of cattle infected with FMDV. • The DEGs highlighted strong innate immunity in the indigenous Bos indicus calves. • Initiation of innate and cell mediated immunity contribute to a reduced viral load. [ABSTRACT FROM AUTHOR]

Using density functional theory (DFT) technique, we explored the interaction behaviour of target chloroform (CHCl3) molecules on armchair blue phosphorene nanoribbon (ABPNR). Besides, van-der-Waals dispersion correction (vdW-DF) density functional is included in the adsorption studies for accurate calculation. The most preferential adsorption sites (ring, bridge, and top site) of CHCl3 on ABPNR were considered in the study. Initially, the structural stability of ABPNR system is confirmed with the negative magnitude of formation energy – 4.82 eV. The energy gap of pristine ABPNR is calculated to be 1.78 eV. The semiconductor nature of ABPNR facilitates it to be used as chemical sensor. The transfer of charge takes place between ABPNR and CHCl3 that leads to variation in energy gap and electron density upon adsorption of CHCl3 molecules. Thus, the report suggests the use of ABPNR as an efficient sensing substrate for CHCl3 vapours. [ABSTRACT FROM AUTHOR]

A nonlinear study is made to find the influence of transverse anisotropy on the onset of thermomagnetic convection in a homogeneous and rotating porous medium. The medium is filled with a magnetic fluid and is subjected to centrifugal force with alternating directions. Unconditional nonlinear stability bounds are found by exploiting the variational principles. Effects of various parameters on the stability threshold are discussed. The overpredicting nature of the linear theory is demonstrated by isolating the subcritical region which cannot be obtained a priori. [ABSTRACT FROM AUTHOR]

This study attempts to develop statistical model for predicting the tensile strength of Nd:YAG laser butt welded UNS S32750 super duplex stainless steel (SDSS) joints. Experimental design based on the central composite face centred design is attempted by varying the process parameters viz. laser power, welding speed and pulse frequency. Weld microstructure exhibit a smooth interface free from defects. Tensile strengths of the resulting welds are determined, as per relevant standard, for each experimental condition. The determined strengths are utilized to develop predictive models by employing response surface methodology (RSM). Analysis of variance determines the factors viz. welding speed and laser power are more influential in dictating the tensile strengths of the weld joints. In addition, the percentage error between the experimental and the predicted models is less than 2%. [ABSTRACT FROM AUTHOR]

Low temperature oxidation of silicon in plasma ambient is a potential candidate for replacing thermally grown SiO2 films for surface passivation of crystalline silicon solar cells. In this work, we report the growth of silicon oxy-nitride (SiOxNy) film in N2O plasma ambient at 380 °C. However, this process results in trapping of interstitial oxygen within silicon. The impact of this trapped interstitial oxygen on the surface passivation quality is investigated. The interstitial oxygen trapped in silicon was seen to decrease for larger SiOxNy film thickness. Effective minority carrier lifetime (τeff) measurements on n-type float zone silicon wafers passivated by SiOxNy/silicon nitride (SiNv:H) stack showed a decrease in τeff from 347 µs to 68µs, for larger SiOxNy film thickness due to degradation in interface properties. From high frequency capacitance-voltage measurements, it was concluded that the surface passivation quality was governed by the interface parameters (fixed charge density and interface state density). High temperature firing of the SiOxNy/SiNv:H stack resulted in a severe degradation in τeff due to migration of oxygen across the interface into silicon. However, on using the SiOxNy/SiNv:H stack for emitter surface passivation in screen printed p-type Si solar cells, an improvement in short wavelength response was observed in comparison to the passivation by SiNv:H alone, indicating an improvement in emitter surface passivation quality. [ABSTRACT FROM AUTHOR]

Organometallic Ru–arene complexes are promising as anticancer agents, but the lack of tumor uptake and poor solubility in the physiological medium impede their development. In order to deal with these challenges, we developed gold nanoparticles coated with Ru(arene)-functionalized PNVP-Py, where PNVP-Py is pyridine end-functionalized poly(N-vinylpyrrolidone). It is demonstrated that these particles exhibit higher anti-proliferative activity than the individual organometallic ruthenium(II) complex of the type [Ru(η6-p-cymene)(NN)Cl]PF6, where NN is bis(4-methoxyphenylimino)acenaphthene, against colorectal adenocarcinoma cell lines. More specifically, a RuII(η6-p-cymene) complex containing a NN bidentate ligand has been prepared and characterized by spectral studies and X-ray crystallography. To tether the isolated complex onto the surface of the AuNPs, PNVP-Py, which contains a pyridine group at one end to coordinate to the Ru-complex and a suitable functional group at the other end to bind on the surface of the AuNPs, has been prepared and utilized to obtain the macromolecular complex [Ru(η6-p-cymene)(NN)(PNVP-Py)]Cl2. Next, stable Ru(p-cym)(NN)(PNVP-Py)@AuNPs were obtained via a ligand exchange reaction of citrate-stabilized AuNPs with a macromolecular complex by a direct 'grafting to' approach and characterized well. Despite the lower DNA cleavage activity, the nanoconjugate exhibits better cytotoxicity than the individual complex against HT-29 colorectal adenocarcinoma cells on account of its enhanced permeability across the cell membrane. The AO/EB staining assay revealed that the nanoconjugate is able to induce an apoptotic mode of cell death, which was further quantitatively evaluated by Annexin V-FITC/PI double assay. An immunofluorescence assay indicated the higher potency of the nanoconjugate to inhibit cyclin D1 gene expression that is required for cancer cell growth. To the best of our knowledge, this is the first report of the modification of an organometallic Ru(arene) complex into a Ru(arene)metallopolymer–gold nanoconjugate for the development of ruthenium-based nanomedicine for cancer treatment. [ABSTRACT FROM AUTHOR]

In general, medical images acquired at insufficient lighting conditions are suffering from low contrast issues which are inadequate for image analysis steps. One standard solution to improve the image contrast is to change its intensity distribution with the help of an image histogram. The histogram‐based contrast enhancement methods treat the images as regions rather than objects which would be more useful for applications like brain image enhancement. In this paper, a Fuzzy and Spline based Histogram Equalization (FSDHE) is proposed to perform contrast enhancement with medical images. The proposed FSDHE method partitions the image into connected components, and the type of components are identified with a fuzzy membership function. The dynamic histogram equalization is applied to each component individually. The equalized sub‐histograms are combined to drive the global histogram, which is inconsistent as dynamic histogram equalization treated the intensity range for each connected component differently. Hence, a spline‐based histogram smoothing is proposed here in this research work. The equalized intensity mapping is received as control points for the polynomial curve, and a smooth intensity transformation is interpolated as a spline curve. The proposed FSDHE model is analyzed with MRI‐brain image dataset of 3064 images, which consists of both benign and malignant cases. The contrast enhancement performance of the proposed FSDHE method is quantified by various measures like Absolute Mean Brightness Error (AMBE), Peak Signal to Noise Ratio (PSNR), Contrast (C), Weber Contrast (WC), Entropy, Hausdorff Distance (HD) and Texture Preservation (TP) measures. The performance of the FSDHE method is compared against with other histogram equalization methods, and the results indicate that the FSDHE method achieves better quality measures of 3.1401, 30.5499, 21.5486, 0.7779, 4.0252, 0.2777, and 0.7836 for the seven‐performance metrics. [ABSTRACT FROM AUTHOR]

A theoretical study of the effect of gravity modulation on a nanofluid filled porous medium subjected to a constant temperature gradient across is made. In particular the onset of convection in water based nanofluids containing conventional metallic and metal oxide particles (Cu‐water, Al2O3‐water, TiO2‐water, and Ag‐water) is investigated. The nanofluid behaves more like a single‐phase fluid rather than a conventional solid–liquid mixture. Darcy's law of flow through porous media and Boussinesq approximation are employed. Stability analysis based on the method of small perturbations is performed using the normal mode assumption. The resulting synchronous and asynchronous, restricted to subharmonic, instability modes are predicted directly through the Mathieu functions for different nanoparticle concentrations. It is found that Al2O3‐water nanofluid can be effectively used in applications involving gravity modulation. [ABSTRACT FROM AUTHOR]

Background: Brinjal or eggplant (Solanum Melongena L.), a member of solanacea family, is one of the most common vegetable crops grown in India. Brinjal is staple vegetable in almost all tropical countries in the world and liked by both poor and rich. Its nutritive value varies among varieties. It contains vitamin A and B. Since there is a common belief that it is not good vegetable more while brinjal may have the medicinal property like white brinjal which is used for Diabetics patients. The basic concept underlying the principles is the maintenance and improvement of soil fertility for sustaining crop productivity on a long-term basis, which can be achieved through the combined use of various sources of nutrients and by managing them scientifically along with optimum growth, yield and quality of crop. Considering the above facts, the present study was therefore under taken to investigate the intergraded management on yield and yield contributing characters of brinjal and on soil properties. Methods: An experiment was conducted at Horticulture Experimental field Department of Horticulture, Naini Agriculture Institute, SHUATS, Allahabad during Rabi season of 2016-17. The experiment was laid out in randomized block design with 8 treatments and each replicated thrice. Thirty days old healthy and uniform seedlings were transplanted on 24thSep. 2016. Result: Overall vegetative parameters were influenced due to application of Nutrient through combination of organic manure and inorganic fertilizers were proved beneficially for increasing growth of brinjal crop. The fruit and yield parameters like Average fruit weight, Length of fruit, Diameter of Fruit, Fruit per plot, Fruit per plant and Fruit per hectare was influenced significantly by the combination of organic and inorganic fertilizers in different treatments which were recorded after harvesting of fruits. [ABSTRACT FROM AUTHOR]

Medical images play a significant role in diagnosis and experimentation. For years, many experimentation and analysis have been made on medical images with a broad scope of achieving the desired results. Medical modalities like MRI, CT, PET, X-Ray, Ultrasound, etc. are popular in representing internal organ pictures of human bodies. Such volumetric images are stored and accessed with a huge demand in storage space. Compressing the images solves the problem of storage and transmission and also become beneficial for the telemedicine application. Since Medical images depict the human body's detailed and vital information, it needs to be compressed without distorting the details present over it. The lossless image compression approach works efficiently in representing the information present on the medical images without distorting the details. Deep learning neural networks proved to be efficient in analyzing the medical images in recent years. Deep Autoencoder attains to be achieving a higher level in dimensionality reduction with retaining the original quality of the input data. Pretraining of the architecture with the Deep Boltzmann Machines makes the algorithm more efficient to achieve a higher compression ratio with a high PSNR value. Analyzing the Deep autoencoder's performance with the other state of the art architecture proves to be efficient with low computational time. [ABSTRACT FROM AUTHOR]

Medical images play a significant role in diagnosis and experimentation. For years, many experimentation and analysis have been made on medical images with a broad scope of achieving the desired results. Medical modalities like MRI, CT, PET, X-Ray, Ultrasound, etc. are popular in representing internal organ pictures of human bodies. Such volumetric images are stored and accessed with a huge demand in storage space. Compressing the images solves the problem of storage and transmission and also become beneficial for the telemedicine application. Since Medical images depict the human body's detailed and vital information, it needs to be compressed without distorting the details present over it. The lossless image compression approach works efficiently in representing the information present on the medical images without distorting the details. Deep learning neural networks proved to be efficient in analyzing the medical images in recent years. Deep Autoencoder attains to be achieving a higher level in dimensionality reduction with retaining the original quality of the input data. Pretraining of the architecture with the Deep Boltzmann Machines makes the algorithm more efficient to achieve a higher compression ratio with a high PSNR value. Analyzing the Deep autoencoder's performance with the other state of the art architecture proves to be efficient with low computational time. [ABSTRACT FROM AUTHOR]

The security of the data becomes the main concern due to the quick rise in the exchange of data over the open networks and the Internet. The cryptographic techniques based on chaos theory reveal some novel and effectual orders to develop secure image encryption approaches. Images are the most attractive kinds of data in the encryption domain. In current years, the chaos-based cryptographic techniques have provided an efficient way to expand secure image encryption frameworks. This proposal temps to develop an optimized HCM for promoting novel image encryption. The proposed image encryption model involves 4 steps, such as image pre-processing, key generation, image encryption using optimized HCM, and image decryption. In the pre-processing, the RGB image is converted into a grayscale image, and the key is generated by the SHA-256 cryptographic hash algorithm. Further, the encryption of the image is performed by HCM with the integration of 2DLCM, and PWLCM. While hybridizing the two chaotic maps for image encryption, parameter tuning or optimization is performed for improving its performance. Moreover, Information entropy is considered as the objective model that has to be maximized while tuning the parameters, and the maximum value of information entropy will mean the best performance. An improvement in the well-known optimization algorithms termed as CI-WOA is adopted for performing the parameter optimization of HCM. Hence, the optimized HCM-based image encryption can be confirmed as an efficient and secure way for all types of image transmissions. [ABSTRACT FROM AUTHOR]

In this study, aluminium (Al 5052)/magnesium (AZ31B) composites were fabricated with and without wire mesh (SS 304) and different amounts of silicon carbide particles (1% and 2% SiCp of weight of the flyer plate) as reinforcements through explosive welding at varying loading ratios (R = 0.7–0.9). The melted layer, pore, and crack formed near the interface of the Al 5052/AZ31B weld and wire mesh reinforced weld, whereas no such defects were found in the silicon carbide reinforced weld. AlFe3, FeSi, and Al12Mg17 intermetallics were detected near the interface in wire mesh-reinforced welds. On the contrary, in SiCp-reinforced welds, intermetallic development was suppressed because the addition of reinforcement enhanced the utilization of kinetic energy and inhibited intermetallic development. The maximum microhardness was found close to the interface for attempted conditions. Higher tensile (234 MPa) and shear (135 MPa) strengths were obtained in wire mesh with a 1% SiCp reinforced explosive weld. The corrosion rate of fabricated composites is not significant, so they can be utilized in corrosive environments. [ABSTRACT FROM AUTHOR]

Agroforestry systems establish a symbiosis among agriculture crops, tree species and raising livestock on the same unit of land. In other words, these are complementary and beneficial to each other. Agroforestry is the system of developing agricultural land in combination with forestry technologies. Agroforestry practices in Tamil Nadu (TN), India, have existed since time immemorial and are evidenced in all parts of the state with less or no scientific management. Agroforestry research is a new field that is getting momentum in recent times due to popularization of industrial agroforestry. In the present context, to meet the national target of forest cover (33%) and to reduce pressure on natural forests, agroforestry plays a vital role and provides additional income to the farming community. This article aims to provide an insight into agroforestry practices in TN, including reasons for opting them, problems faced, etc. It also provides information on agroclimatic zone-wise tree species and agroforestry systems being practised by farmers, central and state government initiatives towards promotion of agroforestry, new technological interventions, etc. for the welfare of the farming community. [ABSTRACT FROM AUTHOR]

In this proposed work, we examined the interaction properties of alcohol viz. methanol and ethanol molecules on stair phosphorene nanosheet (stair-PNS) based on the first-principles study. Moreover, the adsorption property of chief molecules on the stair-PNS base substrate is explored based on the binding energy, average energy gap variation, and Bader charge transfer. The methanol and ethanol molecules are physisorbed on stair-PNS, which is validated with regard to the lower scale of binding energy. Besides, the band gap of stair-PNS gets changed upon the adsorption of alcohol vapors. Thus, we suggest from the results that stair-PNS can be facilitated as the chemi-resistive sensor to probe alcohol vapors. [ABSTRACT FROM AUTHOR]

The objective of this examination is to characterize the fibers from the bark of Ficus racemosa fibers (FRF). FRF is composed of cellulose (72.36 wt. %), hemicellulose (11.21wt. %), lignin (10.45 wt. %), and has a density of 895 Kg/m3. The Differential thermogravimetry (DTG) shows that the maximum degradation peak temperature was attained at 310.56°C. The presence of a chemical group in the fibers was revealed through Fourier transform (FT-IR) analysis. The crystalline structure was characterized by X-ray diffraction (XRD). For surface morphology, Scanning electron microscopy (SEM) and Atomic force microscopy (AFM) were used. The obtained results indicated that FRFs are suitable fibers for polymer composite as reinforcement. [ABSTRACT FROM AUTHOR]

A new hybrid technique for grid integration of solar photovoltaic system using modified incremental conductance maximum power point tracking algorithm with multi-output converter and multilevel inverter is proposed in the paper. The proposed hybrid technique is the joint execution of improved dolphin echolocation algorithm and gradient boosting decision trees and this way the proposed technique is named as IDE-GBDT technique. The novelty of the proposed work is the dolphin echolocation algorithm, which is integrated by the crossover and the mutation function so it is named as IDE. In the proposed technique, the multi-output converter is the combination of boost converter and switched capacitor function to generate different self-balanced output voltages. The utilization of multilevel inverter in the proposed system provides better quality of output voltage and current waveform thereby reducing the size of passive filters. Also, eliminates the requirement of bulky transformers for grid integration. Multicarrier unipolar phase disposition pulse width modulation technique is employed for triggering the switches of the multilevel inverter. The maximum power point tracking algorithm uses the estimated active power output of the generator as its input and generates command speed so that maximum power is transferred to the dc link. This control system also incorporates a loss minimization approach to minimize the losses in the generator and hence to improve the efficiency of the photovoltaic system. Finally, the performance of the proposed maximum power point tracking control of wind and photovoltaic power generation schemes is executed in Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. The proposed technique is compared with the existing techniques and the observed total harmonic distortion of the proposed technique in all the cases is 0.67%, 0.51%, 0.58%, 0.63%, 0.92%, and 1.03% and the total harmonic distortion is found to be very less compared with existing techniques. [ABSTRACT FROM AUTHOR]

In non-isolated bidirectional DC-DC converters (NIBIDC), voltage output of buck/boost mode is incongruous at lower and higher end due to the existing gain. In this paper, a novel NIBIDC is designed in such a way that it enhances the gain in both buck and boost mode of operation. The proposed NIBIDC is employed with four power switches (MOSFET) with an anti-parallel diode embodied, four inductors and three capacitors used as passive elements. The current flow in parallel connected inductor improves the circuit competence. Voltage gain of NIBIDC in buck operation is lower than conventional cascaded bidirectional buck/boost converter (CCBBC) whereas the voltage gain is higher than CCBBC in boost mode. The switching stress is same while the efficiency of NIBIDC is more than CCBBC. The topology structure of the NIBIDC is simple and easy to control. The performance analysis under steady-state condition of the novel converter is carried out and a detailed comparison with CCBBC is done in connection to switching stress, converter efficiency and duty ratios to output power, etc. The operation details for proposed NIBIDC in both mode is verified/validated by experimenting with 20 V input for different duty ratios in charging and discharging state of a battery and the results infer to be identical with theoretical analysis. [ABSTRACT FROM AUTHOR]

The problem of thermal radiation in the presence of nonuniform emissivity arising through different types surfaces involved in thermal-control systems is addressed. In particular, its effect on natural convection driven by an inner hot plate kept inside a square enclosure is studied. The enclosure considered is either horizontally or vertically cooled, and two different primary orientations of the inner hot plate are considered. The corresponding governing partial differential equations were solved by the finite volume method on a uniform and regular grid system. While doing so, the net radiation method was used to determine the radiative surface fluxes. The effect of two opposing emissivity contrasts between the inner hot plate and enclosure walls is studied for the Rayleigh numbers Ra ≤ 107. The flow and heat transfer mechanisms at the resulting steady state are discussed via isotherms, streamlines, and average Nusselt number N u ¯ . The findings arrived out of this comprehensive study shows that prominent heat transfer enhancement occurs when the emissivity of the inner hot plate is higher. Significant changes introduced by the emissivity contrast in the velocity and temperature fields can be seen for higher Rayleigh numbers. Moreover, better heat removal through the combined radiation and convection mechanism is observed invariably for the vertical hot plate in the presence of emissivity contrast. It is found that the heat transfer can be augmented up to around 35% through a good knowledge of the emissivity contrast. [ABSTRACT FROM AUTHOR]

This work is concerned with thermal dispersion through a rotating fissured porous medium. In particular, linear and nonlinear analyses are made to investigate centrifugation driven thermal convection in a bidisperse porous medium. The presence of micro-pores in addition to the usual ones in a porous medium is considered, which allows the possibility of momentum exchange between the two families of pores. The linear analysis is performed through the normal modes, whereas the nonlinear one is based on a suitably defined generalized energy functional. Sharp and unconditional nonlinear L2 stability limits are obtained through the variational principles. Compound matrix method based numerical solutions of the resulting eigenvalue problems are obtained, and the usefulness of nonlinear results is established in most parts of the parameter space. It is found that an increase in momentum exchange delays convection, however, depending on the ratio of permeabilities in the two families of pores. [ABSTRACT FROM AUTHOR]

The present investigation was conducted to study the nature of inheritance of MYMV among intra-specific crosses among three MYMV susceptible and five MYMV resistant genotypes of green gram. The molecular screening and hotspot evaluation is carried out in fifteen F1 progenies and 8 F2 families, respectively. The yellow mosaic-affected leaf samples gave positive results with MYMIV specific primer pairs YFP1/YRP1 and YFP2/YRP2 amplified fragments having size of 704bp and 648 bp, respectively. Coat protein gene sequence analysis revealed that the identified virus is homologous to MYMV. The inheritance study based on F2 data indicated the ratio of MYMV resistant plants and susceptible plants showed a good fit to expected 3:1 (Susceptible: Resistant) suggesting a typical monogenic recessive gene governing resistant reaction to MYMV besides resting the susceptibility from the susceptible parents. [ABSTRACT FROM AUTHOR]

A hybrid on-chip approach based on the variants of soft computing techniques is proposed in this work to evaluate the performance metrics of a 6T static random access memory (SRAM) cell in 45-nm technology. The performance metric evaluated for the SRAM cell is the data retention voltage (DRV) with optimal memory requirements. Each of the SRAM memory cells intends the chip to possess low density but operates at high speed. This paper formulates a hybrid soft computing framework comprising a deep backpropagation neural network which trains the fuzzy inference system to determine the performance metrics of 6T SRAM cell. The weight and bias parameters of the deep learning neural framework are optimized through a cat swarm optimization algorithm so as to reduce the elapsed convergence time of the new hybrid soft computing model. Evaluation process is executed based on the driven outputs from deep learning model to the fuzzy inference system (FIS) module so as to achieve the best values of DRV. Data retention voltage plays a major role in reducing the substantial leakage current and static noise margin intends to retain the data without losing them. Deep backpropagation neural network gets trained with deep learning procedures and optimizes the rule parameters and membership parameters of the FIS design structure. The performance metric DRV under various constraints prove to be better and effective in comparison with the solutions from the existing literature works for the same configuration of 6T SRAM cell using 45-nm technology. [ABSTRACT FROM AUTHOR]

An experiment was conducted to retrieve some useful chlorophyll mutants in two groundnut varieties of TMV (Gn)13 and TMV 7. The mutagenic efficiency and effectiveness were calculated by using the chlorophyll mutants. In M1 generation, the seedling height was decreased with an increased rate of doses/concentration while lethality and pollen sterility were increased with an increased rate of doses/concentration in both the varieties on both the treatments. In the present study, the chlorophyll mutants were observed in M2. The four different chlorophyll mutants observed were albino, chlorina, xantha and striata at different crop stages of crop growth. On perusal of data, it was inferred that chlorina occurred at large followed by xantha and albino. Mutagenic effectiveness were significantly higher in gamma rays for TMV(Gn)13 and TMV 7 (4.24 and 2.64) than the EMS which registered as 3.69 and 2.19 respectively. The mutagenic efficiency was increased for injury and decreased for lethality and pollen sterility with an increased rate of doses/concentration. [ABSTRACT FROM AUTHOR]

A study was conducted in cowpea (Vigna ungiculata) varieties, VBN 3 and CO(CP) 7 to find the efficiency and effectiveness of physical (Gamma rays and Electron beam) and chemical (EMS) mutagens. A wide range of chlorophyll mutants and viable mutants were observed in the field. Overall chlorophyll mutant and viable mutant frequency was higher in EMS treatments in both the varieties. Mutagenic efficiency and effectiveness was also found to be higher in EMS treatments followed by electron beam and gamma rays. Mutagenic effectiveness and efficiency decreased with increase in doses of all mutagenic treatments. [ABSTRACT FROM AUTHOR]

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 km2, 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. [ABSTRACT FROM AUTHOR]

Internet speed is important in many applications. Mobile signal strength of − 110 to − 120 dBm provides poor internet speed by mobile phones. Mobile makes less signal strength and less internet speed from mobile towers. Signal strength ranges between − 30 and − 65 dBm must be maintained to achieve high-speed internet through mobile phones. Good antenna design is necessary to maintain good signal strength and to improve high-speed internet from weak internet speed in required applications. In this work, an FM radio receiver antenna and parabolic dish antenna with a winding helical coil is proposed for the design of an antenna (FMDH antenna) in order to improve weak internet signals to enable high-speed internet signal. Cell tower radiation is normally reduced at a distance of 1000 m, with a weak signal resulting in slow internet speeds. The reduced radiation signal density from the cell tower causes slower internet speeds in mobile. The winding coil of a helical antenna receives the weaker internet signal from the cell towers to increase gain and signal strength between − 30 and − 65 dBm, improving internet to high-speed performance. The FM radio receiver antenna length is increased, so the gain in the main lobe radiation pattern improves internet speed. High-speed internet is needed for computers through mobile internet. Most computers work through mobile internet connections. Wi-Fi connection signal strength should be − 30 to − 60 dBm for maintaining high-speed internet. The FMDH antenna design is proposed in this paper improves mobile Wi-Fi internet, increasing internet signal strength and internet speed. [ABSTRACT FROM AUTHOR]

In this paper, the hardness and wear properties of pure ceramic particles like silicon carbide, boron carbide and graphite are considered in micron size with the reinforced aluminium LM30 metal matrix composites. The stir casting setup is used to prepare the matrix alloy of different compositions i.e. 2, 4 and 6 % of silicon carbide, boron carbide and graphite respectively. The rate of wear in E24 steel disc is found by placing a pin over disc wear test machine under the dry condition. This paper is intended to study the hardness and wear characteristics of all the casted ceramics. The results show that hardness and wear of casted ceramics with RA-MMC has increased in loading and in unloading conditions. Further, it is proved that casting material after stir casting attains a better wear rate and hardness due to better dispersal of micro powder. [ABSTRACT FROM AUTHOR]

The present investigation was undertaken to retrieve information on the nature and extent of genetic diversity among 110 mungbean genotypes for yield related traits by using Mahalanobis's D2 statistics. One hundred and ten genotypes could be grouped under 15 clusters, cluster XV showed maximum intra-cluster distance while the highest inter-cluster distance was observed between cluster VI and XIII. Seed yield exhibited a maximum contribution to genetic divergence (72.02 per cent) followed by days to 50 per cent flowering (15.33 per cent) and plant height (4.24 per cent) while the other traits viz., the number of clusters per plant, the number of pods per cluster, pod length and seeds per pod exhibited insignificant values for contribution to genetic divergence. The maximum and minimum cluster value for seed yield ranged from 5.83 to 19.13. The greater the distance between two clusters, the wider the genetic diversity between the varieties. Keeping this in view, it is indicated that hybridization between the varieties (SML 171/1, AGG 11-013, FRM 1320, EC 396114 and SML 138) of cluster VI and cluster XIII (CO 4, VPM 50 and PLM 501), cluster VIII (V4, V2 and CO 7) and cluster VI (CO 4, VPM 50 and PLM 501), cluster II (AGG 10-850 and EC 396118) with cluster VI (SML 171/1, AGG 11-013, FRM 1320, EC 396114 and SML 138) would produce a better seed yield along with earliness in green gram. [ABSTRACT FROM AUTHOR]

The present study attempts to study the influences of piston geometry, butanol fumigation, EGR, injection pressure and injection timing upon the performance and emissions of a light-duty DI diesel engine fuelled with diesel, Jatropha methyl ester (JME) and 20% by vol. of n-butanol/diesel blends. Experiments were designed based on Taguchi L 18 orthogonal array that considered main fuel injection timing, EGR, premixing ratio of n-butanol with diesel, injection pressure, secondary injection timing, piston geometry, main injection fuel and secondary injection fuel as factors and NOx emission, smoke opacity and BSFC as responses. The best combination of the above factor levels were predicted by using desirability function. Results indicated that B20 injected at 20°CA bTDC with an injection pressure of 200 bar under 10% EGR alongside 40% by vol. of butanol/diesel fumigation with a premixing ratio of 20% at 9°CA aTDC in the engine fitted with a torroidal piston was predicted to deliver 359.13 ppm of NOx emissions, 74.83% of smoke opacity with 1.127kg/kWh of BSFC. The tests revealed that the predictions by using desirability function were within a reasonable accuracy of 10%. • Combined effect eight factors on Emission control of diesel engine. • Combined effect design and fuel factors on Emission control of diesel engine. • Influence of different higher alcohols on emission control. • Multi-response optimization of eight factors for NOx and smoke emission. • Influence of primary and secondary injection fuel in PPCCI engine. [ABSTRACT FROM AUTHOR]

Background and Aim: Foot-and-mouth disease (FMD) is an acute viral infection affecting cloven-hoofed animals causing vesicular erosions in the oral cavity and interdigital space. The present study was undertaken to ascertain the timedependent changes in clinical, hematological, and biochemical profiles in different breeds of cattle following experimental infection. Materials and Methods: The animals were inoculated with 1.0×104 50% bovine tongue infectious dose (BTID50) by intradermolingual route. Clinical signs were observed, and blood/serum samples were collected at different time intervals. Results: The white blood cell count declined sharply on days 7-13 and recovered on day 14 post-FMD infection. Biochemical analysis of serum markers for vital organ profile revealed no marked damage. However, a significant increase in blood urea nitrogen (BUN) value indicated pre-renal azotemia. Transient hyperthyroidism was indicated by the rise in T3 and T4 that can be correlated with a decrease in triglyceride and total cholesterol levels. In the cardiac damage assessment study, a distinct breed difference was observed wherein Malnad Gidda calves showed no cardiac damage. Conclusion: Except thyroid profile, BUN, and creatine kinase-myocardial band, all other serum biochemical parameters showed no significant abnormalities, whereas lymphopenia is the only hematological change and it is suggested that effective ameliorative measures should be targeted mainly on the feed/water intake, thyroid gland, and the level of lymphocytes. [ABSTRACT FROM AUTHOR]