Explore the vast range of titles available.

Possibilities of enhancing mechanical properties of brittle intermetallic containing high entropy alloys (HEAs) using novel processing and microstructural design strategies were investigated in the present work. For this purpose, homogenized CoCrFeNi 2.1 Nb 0.2 HEA consisting of FCC matrix and complex Laves phase particles was successfully processed by severe cold- or cryo-rolling to 90% reduction in thickness followed by annealing (800 °C/1 hour(h)). As compared to cold-rolling, cryo-rolling resulted in a finer lamellar nanostructure and decidedly greater fragmentation of the Laves phase. Upon annealing, the cold-rolled HEA showed a recrystallized FCC matrix dispersed with D0 19 structured ε nano-precipitates. In contrast, the finer nanostructure and greater driving force for accelerated precipitation of profuse nano-precipitates at the early stages of annealing inhibited recrystallization in the cryo-rolled HEA and resulted in the formation of heterogeneous microstructure consisting of retained deformed and recrystallized regions. The novel heterogeneous microstructure of the cryo-rolled and annealed HEA resulted in a remarkable enhancement in strength-ductility synergy. The present results indicated that cryo-rolling could be used as an innovative processing strategy for tailoring heterogeneous microstructure and achieving novel mechanical properties.

Hot flow behavior of hot isostatically processed experimental nickel-based superalloy is investigated over temperature and strain rate ranging from 1000–1200 °C and 0.001–1 s⁻¹, respectively by carrying out constant true strain rate isothermal compression tests up to true strain of 0.69. True stress–true strain curves corrected for adiabatic temperature rise exhibited rapid strain hardening followed by flow softening behavior irrespective of temperature and strain rate regimes investigated, although anomalous flow behavior is observed at 1200 °C. Variation of peak flow stress with temperature is corroborated to the microstructural changes pertaining to the morphology and relative volume fraction of the phases present. From the experimental results, constitutive model incorporating the effects of strain rate, strain, and temperature is established to describe the hot flow behavior of investigated alloy. Dependence of peak flow stress on strain rate and temperature described by Zener–Hollomon (Z) parameter indicated increase in peak flow stress with Z. Additionally Cingara-Queen equation is employed to predict flow curve up to peak stress. The reliability of developed constitutive models is validated statistically and the results indicate reasonable agreement with experimental findings.

Lung cancer poses a serious health risk, making early diagnosis essential for better survival outcomes. Detection of lung cancer involves a series of medical evaluations and imaging techniques to identify cancerous cells in the lungs. Computed Tomography (CT) images are most frequently used to recognize lung cancer since it has high resolution, enhanced clarity, and minimal noise and distortions. However, accurate detection of lung cancer is complex owing to variations in nodule size, shape, and boundary definition. Therefore, an innovative model named Wide Slice Residual Kronecker Network (WISeRKNet) has been developed to diagnose lung cancer from CT images. Initially, image pre-processing is applied by using homomorphic filtering. Subsequently, the extraction of nodules in the lung is performed by the Link-Net model. Subsequently, augmentation of the image is conducted, and then the process of feature extraction is applied to refine shape-based features. At last, diagnosing lung cancer is executed by the WISeRKNet and which combines the Wide Slice Residual Network (WISeR) and the Deep Kronecker Network (DKN). Moreover, the developed WISeRKNet model demonstrated superior performance, by achieving improved value in accuracy as 91.686%, True Positive Rate (TPR) as 90.485%, True Negative Rate (TNR) as 92.727%, Precision as 90.980% and F1 score as 90.484% on the Lung Cancer Computed Tomography Images database using 90% of the data for training.

Rice is a vital staple crop globally, and accurate estimation of rice area was crucial for effective agricultural management and food security. Synthetic Aperture Radar (SAR) data has emerged as a valuable remote sensing tool for rice area estimation due to its ability to penetrate cloud cover and capture backscattered signals from rice fields. The backscatter signature of rice showed a minimum dB value at agronomic flooding indicating the Start of Season (SoS). The parameters viz., the minimum values of −22.03 to −17.69 dB at the start of season, maximum value of −16.10 to −14.20 dB at the peak of season coinciding with heading and corresponding mean increase of 5.07 dB during growing stages were utilized for developing rule-based classification system. Rice area was estimated over the Cauvery Delta Zone of Tamil Nadu, India for the past six years during samba (August–January) season from 2017 to 2023 using Sentinel 1 A Synthetic Aperture Radar satellite data. Rice area maps were generated for the region utilizing parameterization with a classification accuracy of 88.5 to 94.5 per cent with a kappa score of 0.77 to 0.87 during the study period. The total classified rice area during samba season in the Cauvery Delta Zone was 508,581 ha, 456,601 ha, 506,844 ha, 511,714 ha, 524,723 ha and 476,586 ha for the years 2017–18 to 2022–23, respectively. The Start of Season (SoS) maps for samba season revealed that the major planting periods for rice were between the second fortnight of September to first fortnight of November in all the years except 2018 when early planting happened during the first fortnight of September due to favorable weather conditions and assured water supply. Near real-time information on rice area, start of season, and progress of planting derived using SAR satellite data will facilitate the development of decision support systems for sustaining the productivity of rice-based ecosystems.

Effects of aerosols such as black carbon (BC) on climate and buildup of the monsoon over the Indian Ocean are insufficiently quantified. Uncertain contributions from various natural and anthropogenic sources impede our understanding. Here, we use observations over 5 y of BC and its isotopes at a remote island observatory in northern Indian Ocean to constrain loadings and sources during little-studied monsoon season. Carbon-14 data show a highly variable yet largely fossil (65 ± 15%) source mixture. Combining carbon-14 with carbon-13 reveals the impact of African savanna burning, which occasionally approach 50% (48 ± 9%) of the total BC loadings. The BC mass-absorption cross-section for this regime is 7.6 ± 2.6 m²/g, with higher values during savanna fire input. Taken together, the combustion sources, longevity, and optical properties of BC aerosols over summertime Indian Ocean are different than the more-studied winter aerosol, with implications for chemical transport and climate model simulations of the Indian monsoon.

This work introduces the design and analysis of a Bandgap Reference (BGR) circuit with better temperature stability and reduced process variation. The second-order compensation method is implemented for design through an optimized error amplifier and a resistor network with a significantly better temperature coefficient performance. The startup mechanism is carefully designed for ensured strong and stable circuit performance under every variation of process-voltage-temperature (PVT). The proposed BGR is compared with conventional methods such as CM-BGR, Cascaded CM-BGR, Operational Amplifier based-BGR, and Sub-BGR with respect to Temperature Coefficient (TC), Power Supply Rejection Ratio (PSRR), and line regulation. The proposed Sub-BGR is shown to provide 3.33 ppm/°C (58.97–78.79% less) temperature coefficient, 1.12×–6.02× improvement in PSRR, and 96% improved line regulation with 723 µV variation, thus showing improved performance compared to Operational Amplifier based-BGR and Sub-BGR techniques, rendering the proposed BGR highly appropriate for high-precision analog and mixed-signal applications. The proposed BGR is simulated and implemented by Synopsys custom compile using 32 nm CMOS technology.

The Himalayan cryosphere comprises a large concentration of glaciers that feed numerous perennial rivers, providing food and water security to millions of people living in the downstream regions. To understand the effect of changing climate on these glaciers, an assessment of the mass loss in the glacier is crucial. In this study, the volume of 279 glaciers in the Parvati basin of the Himalaya in the year 2000 was estimated as 21.3 ± 3.8 km 3 using the Laminar flow and scaling methods. The regional mass loss of the glaciers over the period 2000–2015 was calculated using the Improved Accumulation Area Ratio (IAAR) and Geodetic methods. The IAAR method’s estimate was based on meteorological data, whereas the geodetic method’s assessment was based on Cartosat-1 satellite data for three years (2011, 2014, 2015) and SRTM DEM for 2000. The mean elevation difference based on the aforementioned DEMs was − 4.6 ± 0.26 m, whereas the mass loss for the glaciers was 14% in the Parvati basin between 2000 and 2015. The mass balance of the glaciers in the basin is estimated as − 0.44 ± 0.23 m w.e.a −1 and − 0.30 ± 0.23 m w.e.a −1 , using the IAAR and Geodetic methods, respectively. These methods provide synergetic means to analyze the basin-wide mass changes of glaciers over multiple (annual and long-term) temporal scales. The volume of ice stored in the glaciers of the Parvati basin and their mass changes are quantified at a regional scale to help understand their spatial heterogeneity over those timescales.

Synergizing satellite remote sensing data with vertical profiles of atmospheric thermodynamics and regional climate model simulations, we investigate the relative importance, transport pathways, and seasonality of contribution of dust from regional (Thar Desert and adjoining arid regions) and remote (southwest Asia and northeast Africa) sources over the northeast Indian Ocean [i.e., the Bay of Bengal (BOB)]. We show that while over the northern BOB dust from the regional sources contribute more than 50% to the total dust load during the southwest monsoon period (June–September), interestingly; the remote dust sources dominate rest of the year. On the other hand, over the southern BOB, dust transported from the remote-source regions dominate throughout the year. During June, the dry elevated layer (at altitudes between 850 and 700 hPa) of dust, transported across the Indo-Gangetic Plain to the northern BOB, arises primarily from the Thar Desert. Dust from remote sources in the far west reaches the southern BOB after traversing over and around the southern Indian Peninsula. Since dust from these distinct source regions have different mineral composition (hence optical properties) and undergo distinct changes during atmospheric transport, it is important to understand source-specific dust contribution and transport pathways to address dust–climate feedback.

Ni-Fe superalloy SUPERNI 718 with superior mechanical properties is processed through conventional forming methods for producing critical rotating aeroengine components, however for realizing large sized components, alternate industrial scale processing methods like incremental superplastic rolling forming (SPRF) method is explored to counteract the requirement of large tonnage forging facilities. In order to meet the essential prerequisite of superplasticity for SPRF, establishing viable severe plastic deformation methods for processing fine grained structure in bulk materials is challenging. This work is focused on achieving fine grained structure by severe plastically deforming IN718 superalloy through elevated temperature multiaxial forging (MAF) which involves repetitive imposition of compressive deformation. Solution-treated SUPERNI 718 superalloy samples are subjected to isothermal MAF up to 3 cycles thereby imparting total effective strain of 3.3. Microstructural evolution of deformed samples characterized employing multiple techniques like light microcopy, scanning electron microscopy, and electron back scattered diffraction revealed the formation of fine grains (~0.9 µm) after 3 cycles of MAF aided by discontinuous dynamic recrystallization along with deformation induced δ precipitates. The room temperature tensile behavior indicated significant improvement in yield strength and tensile strength by twice and 1.3 times, respectively, driven by continuous grain refinement. The Hall-Petch relationship is elucidated and the yield strength of the deformed SUPERNI 718 is modeled and benchmarked.