Gravity and magnetic surveys were carried out in southwestern part of Cuddapah basin (CB) covering an area of ~3660 km2. Southwestern part of CB gained lot of attention after discovery of second most important uranium province in India. Some non-metallic industrial minerals and base metal occurrence are also reported in the study area. Present study with high spatial resolution gravity-magnetic survey aims to decipher detail basin geometry, nature of sediments, along with possible mineral deposits in SW part of CB. The gravity survey comprising short and long wavelength anomalies brought out sedimentary characteristics and basement architecture underneath the sediments. The long wavelength features of the gravity map shows gneissic basement, which is characterized by both basic and acid magmatic intrusive. Residual gravity anomaly map shows good correspondence with the exposed high density basaltic rock units and also brought out occurrence of concealed high density litho-units, which have significance for mineral prospecting. The magnetic map shows that both sediments and underneath basement are non-magnetic in nature except SW part of the study area, where study suggests occurrence of concealed mafic lensoid body. Euler solutions and combined gravity-magnetic modelling further facilitated for understanding of structural feature and basement geometry. Based on the integrated gravity and magnetic study mineral prospecting zones have been delineated for further detailed study.

Cardiovascular diseases (CVDs) remain the principal cause of all global death and disabilities worldwide. Cardiac MR Images play an important role in diagnosing and treating cardiac ailments in patients. Automatic segmentation of Cardiac Magnetic Resonance Imaging (Cardiac MRI) is an essential application in clinical practice. In this paper, Cardiac MRI segmentation is performed using a convolutional neural network. ACDC Challenge 2017 dataset is used the training and testing purpose. It consists of data of 100 subjects, including the End Systole and End Diastole phase. The model's performance is measured using the Dice coefficient, achieving an accuracy of 0.90. The results for basal as well as with apical slices are pretty encouraging.

The spent catalysts discarded during chemical manufacturing can be a source of pollution and are classified as hazardous waste. Looking at the bright sides of the mission of waste management, such as recycling and reducing, reuse such types of the spent catalyst can be chemically treated to extract valuable salts and metals. Such a process not only reduces waste disposal issues but also promotes a circular economy ecosystem. This present study aims to extract MoO3 from the spent petroleum catalyst, Mo–Ni/Al2O3, and further processing of Mo‐metal organic framework (MOF) particles using extracted MoO3 and imidazole acting as an organic binder. The structural, morphology, and thermal properties of Mo‐MOF are evaluated. The surface roughness and positive surface potential of the Mo‐MOF are achieved. The Mo‐MOF/Kapton‐based triboelectric nanogenerators (TENG) generate a 148 V voltage, 470 nA current, and 17 nC charge. Further, TENG is utilized to charge the capacitors, and powering of the electronic devices is demonstrated. The repetition of the boxing punches and exercises can be monitored using TENGs and paves the way toward intelligent sports or healthcare.

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