Dicynodont (Therapsida) bone histology: phylogenetic and physiological implications

The bone histology of humeri of a number of taxonomically well established and easily definable dicynodont genera is described and compared. The bone of Aulacephalodon, Cistecephalus, Dicynodon, Endothiodon, Lystrosaurus, Kannemeyeria and Oudenodon consists of alternating fibro-lamellar and lamellated bone tissue, while that of Diictodon consists only of fibro-lamellar tissue. The presence of fibro-lamellar bone in all the genera studied, indicates that the bone was deposited rapidly, but the occurrence of lamellated bone tissue suggests that all the genera except Diictodon, also had intermittent periods of slow growth. This is the first time that a comparative study of bone histology of different dicynodont genera has been attempted by using one particular bone element to standardise intergeneric comparisons

Liver Tumor Prediction with Advanced Attention Mechanisms Integrated into a Depth-Based Variant Search Algorithm

In recent days, Deep Learning (DL) techniques have become an emerging transformation in the field of machine learning, artificial intelligence, computer vision, and so on. Subsequently, researchers and industries have been highly endorsed in the medical field, predicting and controlling diverse diseases at specific intervals. Liver tumor prediction is a vital chore in analyzing and treating liver diseases. This paper proposes a novel approach for predicting liver tumors using Convolutional Neural Networks (CNN) and a depth-based variant search algorithm with advanced attention mechanisms (CNN-DS-AM). The proposed work aims to improve accuracy and robustness in diagnosing and treating liver diseases. The anticipated model is assessed on a Computed Tomography (CT) scan dataset containing both benign and malignant liver tumors. The proposed approach achieved high accuracy in predicting liver tumors, outperforming other state-of-the-art methods. Additionally, advanced attention mechanisms were incorporated into the CNN model to enable the identification and highlighting of regions of the CT scans most relevant to predicting liver tumors. The results suggest that incorporating attention mechanisms and a depth-based variant search algorithm into the CNN model is a promising approach for improving the accuracy and robustness of liver tumor prediction. It can assist radiologists in their diagnosis and treatment planning. The proposed system achieved a high accuracy of 95.5% in predicting liver tumors, outperforming other state-of-the-art methods

Wireless Channel Models for Indoor Environments

Wireless networks have made significant advancement in recent times by adding a new dimension to theway people communicate. Development of wireless standards have constantly aimed at providing higher datarates even under complex environments using smart antennas, multiple-input, and multiple-output systems.This has necessitated an understanding of the indoor propagation channel. Channel models describe acommunication channel and are essential in developing efficient wireless communication networks. This papersurveys different channel models used to characterise wireless indoor environment. This survey may be usefulfor the army, where the communication over wide areas during wargames that they hold periodically, isnecessary. Moreover, it may also be useful for communication near the border areas for surveillance operations.Defence Science Journal, 2008, 58(6), pp.771-777, DOI:http://dx.doi.org/10.14429/dsj.58.170

Spectrophotometric Determination of Iron(II) and Cobalt(II) by Direct, Derivative, and Simultaneous Methods Using 2-Hydroxy-1-Naphthaldehyde-p-Hydroxybenzoichydrazone

Optimized and validated spectrophotometric methods have been proposed for the determination of iron and cobalt individually and simultaneously. 2-hydroxy-1-naphthaldehyde-p-hydroxybenzoichydrazone (HNAHBH) reacts with iron(II) and cobalt(II) to form reddish-brown and yellow-coloured [Fe(II)-HNAHBH] and [Co(II)-HNAHBH] complexes, respectively. The maximum absorbance of these complexes was found at 405 nm and 425 nm, respectively. For [Fe(II)-HNAHBH], Beer's law is obeyed over the concentration range of 0.055–1.373 μg mL−1 with a detection limit of 0.095 μg mL−1 and molar absorptivity ɛ, 5.6 × 104 L mol−1 cm−1. [Co(II)-HNAHBH] complex obeys Beer's law in 0.118–3.534 μg mL−1 range with a detection limit of 0.04 μg mL−1 and molar absorptivity, ɛ of 2.3 × 104 L mol−1 cm−1. Highly sensitive and selective first-, second- and third-order derivative methods are described for the determination of iron and cobalt. A simultaneous second-order derivative spectrophotometric method is proposed for the determination of these metals. All the proposed methods are successfully employed in the analysis of various biological, water, and alloy samples for the determination of iron and cobalt content

Clinical profile and response to tuberculosis treatment in patients with chronic kidney disease

Introduction: Tuberculosis (TB) is a major public health problem, especially in the developing countries Patients with CKD have a weakened immune system due to the chronic inflammatory state due to CKD per se, also due to long term renal replacement therapy. Aims of The Study To study the clinical profile of tuberculosis in chronic kidney disease patients To study the response to anti tubercular treatment including adverse effects. Methodology: This study was carried out in the Department of Nephrology at Government Stanley Medical College and Hospital, Chennai during the period between October 2018-May 2019. A detailed history was taken, Age, symptomatology, non CKD risk factors like smoking, alcoholism, previous history of pulmonary TB, presence of diabetes mellitus, other infections like HCV, and in case of post-transplant patients, use of induction therapy, any graft dysfunction etc. was noted. The definitions for cure, treatment completed, and treatment failure being used in the study. Results: There were a total of 55 patients with CKD diagnosed as tuberculosis by various means-clinical, histopathologic, biochemical, microbiologic, radiologic or a combination of factors. Conclusion: Tuberculosis is a common infection among Chronic Kidney disease patients, due the immunosuppressed state, hence a high index of suspicion should be maintained, with ways of early screening to be followed based on clinical grounds. Risk factors, namely, smoking, alcoholism, diabetes mellitus predisposes CKD patients to Tuberculosis in addition to the immunosuppressed state of CKD

Study of breast lesions in cytology and its histopathological correlation

Background: Breast cancer is commonly diagnosed malignancy in females and is leading cause of death. Malignant lesions mostly occur after menopause. Fine needle aspiration cytology is minimally invasive technique, used in triple test and produces speedy results. It can able to differentiate between benign and malignant lesions of breast lump. Our study aims to categorize the breast lesion and to correlate FNAC with histopathological studies. Methods: This retrospective study was done in department of pathology from July 2021 to May 2023.107 cases were undergone FNAC and slides were examined and lesions were categorized. Tissue biopsies were obtained, processed and histological sections were made and examined. The FNAC findings were correlated and analyzed with histological findings. Results: Right breast lesions (55%) were more in our study than left breast lesions (42%). Totally 77 cases were diagnosed as benign lesions by FNAC of which 37 cases were biopsied and histological diagnosis of all cases shown as benign category. 6 cases were diagnosed as proliferative breast disease with atypia of which only one case was received for biopsy and diagnosed as atypical ductal hyperplasia. 12 cases were diagnosed as malignancy and 6 biopsies were received with 5 cases were diagnosed as malignant lesions. Sensitivity and Specificity of FNAC in breast lesions were 100% and 97.43% respectively. Conclusions: FNAC is rapid and valuable tool with high sensitivity, specificity and low false positivity. It is useful in preoperative evaluation and avoids unnecessary surgical intervention

Weathered High Density Polyethylene Microplastics Induce Proximate Imbalance in the Post Larval Stages of Litopenaeus vannamei

Introduction: The fast rise in anthropogenic activity, particularly in the aquatic ecosystem, has resulted in microplastic contamination in recent years. A wide range of harsh environmental circumstances can cause stress to aquatic organisms. Aim of the Works: This study aims to better understand the changes in proximate constituents that occur in the post larval stage on long term exposure by using a wide range of biomarkers to identify distinct and individual patterns of Litopenaeus vannamei responses to high density polyethylene microplastics. Methodology: The post larval stage of Litopenaeus vannamei were exposed to wHDPE-MP for 45 days in order to evaluate changes in proximate constituents such as crude protein, fibre, amino acids ash and moisture contents were measured during the period of exposure. Similar measurements were made following a 15-day recovery interval to track any changes that might take place during depuration periods. Results: The proximate constituents including crude protein, fats, fibre and ash contents decreased significantly following exposure of L. vannamei to 0.2 mg/L of wHDPE-MP for 45 days. These values during depuration demonstrated notable variations from the corresponding control group and did not indicate any recovery from the microplastic-induced stress. Conclusions: The current study found a significant correlation between stress and alterations in the proximate constituents. Post larval stages exposed to wHDPE-MP had changes in the growth pattern and proximate constituents. Overall, the results indicate to post larval stages as the most vulnerable to wHDPE-MP, which will have an impact on white prawn growth and have repercussions for the aquaculture sector

Extent of Awareness of Distance Learners of Tamil Nadu Agricultural University

The present research was framed to assess the awareness level of distance learners of Tamil Nadu Agricultural University. Three certificate courses were selected based on maximum number of enrollment, viz, Gardening & landscaping, Mushroom production & Solid waste management and vermicomposting. Ex-post facto research design was employed. A total of 150 respondents were selected from the three courses by equal allocation method proportionate random sampling. A well-structured questionnaire was prepared and the information was collected by sending questionnaires through post. The 108 individuals who responded were taken as the sample for the study. The results of the research pointed out that nearly three- fourths of the respondents possessed medium level of awareness on selected technologies