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Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment
Keerthikumara SM, Saikia B, Hiremath C. 2025. Landholding size, indebtedness, and crop insurance in India: A macro-level quantitative assessment. Asian J Agric 9: 377-390. Indian farmers continue to face structural distress driven by low income, high indebtedness, and inadequate risk protection. This study investigates the interrelationship between landholding size, agricultural credit, indebtedness, and crop insurance uptake using state-level secondary data from 2016 to 2023, drawn from Agricultural Statistics at a Glance, PMFBY/RWBCIS dashboards, and NCRB reports. Using descriptive statistics, linear regression, and paired t-tests, we identify key macro-level trends across 20 major Indian states. Results show that marginal and small farmers (less than 2 hectares) account for over 62.7% of all indebted farm households, but receive only 38.5% of total institutional agricultural credit. A bivariate regression reveals that a ?1,000 increase in monthly farm income is associated with a reduction of 1,314 indebted households (?=-0.445, p=0.016). Despite substantial credit disbursal in high-debt states like Andhra Pradesh and Telangana, farmer debt remains elevated, underscoring that credit alone does not reduce vulnerability. Crop insurance enrollment increased after the 2020 policy shift from mandatory to optional participation among loanee farmers, yet the change was not statistically significant (p=0.099). Actuarial analysis reveals that in several states, claim settlement ratios remain below 50%, with high premiums and delayed payouts fueling distrust. The study recommends fully subsidized premiums for marginal farmers, region-specific pricing, improved claim transparency, and financial literacy integration with agricultural extension. Effective risk mitigation in agriculture must go beyond insurance and integrate income and credit reforms to ensure equitable protection for Indias most vulnerable farmers. 2025, Smujo International. All rights reserved. -
Lane Detection using Kalman Filtering
Autonomous vehicles are the future of transportation. Modern high-tech vehicles use a sequence of cameras and sensors and in order to assess their atmosphere and aid to the driver by generating various alerts. While driving, it is always a challenging task for drivers to notice lane lines on the road, especially at night time, it becomes more difficult. This research proposes a novel way to recognize lanes in a variety of environments, including day and night. First various pre-processing techniques are used to improve and filter out the noise present in the video frames. Then, a sequence of procedure with respect to lane detection is performed. This stable lane detection is achieved by Kalman filter, by removing offset errors and predict future lane lines. 2023 Elsevier B.V.. All rights reserved. -
Language and identity formations of second-generation migrants in Deepak Unnikrishnan's temporary people
Decades of migration to the Gulf nations have led to the existence of second-generation migrants who were born and raised in migrant lands. The chapter uses the novel Temporary People (2017) by Deepak Unnikrishnan as a primary text to explore the role language plays in second-generation migrant identity formations and the assimilation process. The national language, Arabic, is situated in the specific socio-political context, a site where ideologies and power relations are reproduced. By identifying a gap in the language education policy, it reveals how migrant's inability to communicate in the Arabic language has complex implications on their identities and notions of belongingness. The chapter explores language's power to naturalize norms and hierarchical structures within society that can hinder the assimilation process and highlights the migrant-citizen divide. It shows how notions of temporariness and Othering in migrants are inherent within the language politics of the land. The chapter reaffirms language-identity relations and points to revaluating migrant language policies. 2023, IGI Global. All rights reserved. -
LANGUAGE CONTACT AND CHANGE: AN ANALYSIS OF HERITAGE KONKANI IN KERALA; [CONTACTE LINGSTIC I CANVI: UNA ANISI DEL PATRIMONI KONKANI A KERALA]; [CONTACTO LINGSTICO Y CAMBIO: UN ANISIS DEL PATRIMONIO KONKANI EN KERALA]
This paper analyses the extent of language contact induced change in the sound system of heritage Konkani community of Kerala, India. Heritage Konkanis, belonging to different castes namely Gowda Saraswat Brahmins (GSB), Saraswat non-brahmins, Konkan Sonars, Vaishya Vaniyar and Kudumbi, started migrating to Kerala in the late 13th century. The upper caste GSBs remained as a closed community until 20th century, which helped in the maintenance of their language. Linguistic data for the study was collected from 20 GSB youths of the age group 18-35 using Snowball sampling method. The analysis of the data shows loss of features such as aspiration and nasalization, which are inherent to Konkani. This indicates the vulnerable linguistic situation of the GSB community whose mother tongue exhibits linguistic variations, as a result of prolonged coexistence with the majority language, Malayalam. 2024 University of Barcelona. All rights reserved. -
Language, exempted?
Arent languages the most important, for, how else will students grasp, express, and practise the knowledge of the so-called core subjects? -
Lanthanide-based coordination polymers: a fluorometric Frontier in explosive sensing
In the pursuit of public safety, environmental protection, and counter-terrorism, significant advancements have been made in explosive detection techniques. However, challenges such as limited sensitivity, poor selectivity, and high operational costs remain, particularly for trace-level detection. In this study, we present a simple and scalable synthesis of lanthanide-based coordination polymers (Ln-COPs), denoted as Ho(DAB) and Tb(DAB), formed through the coordination of Ho(iii) and Tb(iii) ions, respectively, with the organic linker 3,3?-diaminobenzidine (DAB). Spectroscopic and electron microscopic analyses confirm their two-dimensional planar structure, resulting from the self-assembly of infinitely long polymeric strands. These luminescent Ln-COPs demonstrate exceptional performance as sensors for detecting both nitroaromatic and non-nitroaromatic explosives via fluorescence quenching. Notably, Tb(DAB) exhibits a remarkable limit of detection of 7.7 M for TNP. Furthermore, mechanistic insights into the quenching process are explored. These results underscore the sensitivity and practical applicability of Ln-COPs in advanced explosive detection systems. This journal is The Royal Society of Chemistry, 2025 -
Large Language Models in Economic Forecasting: A Comprehensive Analysis of Predictive Performance and Benchmarking Against Traditional Methods for India FY 2025-26
This study presents a comprehensive systematic evaluation of the performance of Large Language Models (LLMs) in economic forecasting, specifically examining their ability to predict key Indian macroeconomic indicators for the fiscal year 2025-26. Through a comparative analysis of ten prominent LLMs against traditional econometric models and expert forecasts from leading institutions, we assess the forecasting accuracy, reliability, and practical limitations of these models using a rigorous multistage validation framework. We validate predictions using actual quarterly data from Q1 and Q2 of FY 2025-26, providing a real-time assessment of forecasting capabilities with bootstrap confidence intervals and time series cross-validation techniques. Results reveal significant variations in LLM performance, with validation against Q1 2025-26 actual GDP growth of 6.7 per cent showing that several LLMs achieved superior accuracy (MAPE less than 3 per cent) compared to traditional ARIMA models (MAPE 13.58 per cent). Top-performing LLMs demonstrate forecasting capabilities that approach expert-level accuracy while maintaining computational efficiency and scalability. Statistical significance tests using the Diebold-Mariano framework confirm the superiority of ensemble LLM approaches over individual traditional methods. The findings demonstrate that leading LLMs can serve as valuable supplementary forecasting tools, positioning between conventional statistical methods and expert analysis in terms of accuracy, while offering advantages in processing qualitative information and adaptation to structural changes. 2025 IEEE. -
Large power factors in wide band gap semiconducting rFeO3 materials for high-temperature thermoelectric applications
While most of the thermoelectric materials work well only at low and mid temperatures, high-temperature thermoelectric materials (T > 900 K) are equally important for the operation of deep-spacecraft missions, nuclear reactors, and high-temperature industrial reactors. To accomplish this demand, this work provides insights into wide band gap semiconducting RFeO3 (rare-earth orthoferrites) for high-temperature thermoelectric applications. Using the first-principles density functional theory calculations, we have demonstrated the coexistence of extremely flat and corrugated flat bands near the Fermi region in a wide band gap material. The presence of such features enhances and sustains the thermopower, electrical conductivity, and power factor, which are the crucial factors for the efficiency of thermoelectric materials. Semiclassical Boltzmann formalism was then employed to study the transport properties of four orthorhombic RFeO3 materials (R = Pr, Nd, Sm, and Gd). Our results reveal high Seebeck coefficients (thermopower) along with the large electrical conductivities over the high hole doping carrier concentration and in the high-temperature region (T > 900 K). Furthermore, significantly large power factors are obtained with very low theoretical minimum lattice thermal conductivity in the range 1.41?1.51 W m?1 K?1. These huge power factors directly suggest the maximum power output in RFeO3, which we believe is a more appropriate performance index than the figure of merit, especially for high-temperature thermoelectric applications. We also emphasize that the outcomes of our work would be certainly useful for experimentalists in designing high-temperature thermoelectric materials. 2020 American Chemical Society -
Large scale extinction maps with UVIT
Astrophysics and Space Science Vol.343, No.2 ISSN No. 0004-640X -
Large scale extinction maps with UVIT
The Ultraviolet Imaging Telescope (UVIT) is scheduled to be launched as a part of the ASTROSAT satellite. As part of the mission planning for the instrument we have studied the efficacy of UVIT observations for interstellar extinction measurements. We find that in the best case scenario, the UVIT can measure the reddening to an accuracy of about 0. 02 magnitudes, which combined with the derived distances to the stars, will enable us to model the three-dimensional distribution of extinction in our Galaxy. The knowledge of the distribution of the ISM will then be used to study distant objects, affected by it. This work points the way to further refining the UVIT mission plan to best satisfy different science studies. 2013 Springer Science+Business Media Dordrecht. -
Large Scale Transportation Data Analysis and Distributed Computational Pipeline for Optimal Metro Passenger Flow Prediction
Transportation has a signifcant impact on controlling traffc around a busy city. Among the transport system, metro rails became the backbone by operating above the traffc. For this reason, we have to take special consideration of the passenger and#64258;ow in the transport system and, by understanding the needs, take timely actions for smooth running. Every metro system stores information about the and#64258;ow of passengers in the form of transactions known as Automatic Fare Collection (AFC) data. For this research, AFC data is taken as the primary newlinesource of information to identify the passenger and#64258;ow within the metro rail platform. Each metro system generates massive data throughout its running period and stores data within the system and considering the size of data generated, the analytic platform has to process them in a distributed paradigm to handle quotBig Dataquot. Artifcial Intelligence (AI) algorithms can derives information, insights, and patterns from this data. The patterns in time series can be identifed from the passenger and#64258;ow data using exploratory analysis. The step is an essential step in data science for understanding the underlying properties of the raw data. The research uses a data platform with a distributed computing and storage mechanism called the JP-DAP. The research leverages the above mentioned platform to extract passenger and#64258;ow data from AFC Ticketing data. After the data engineering, the results of passenger and#64258;ow information underwent further visualization and trend analysis. Based on the facts or patterns identifed from the passenger and#64258;ow information, a decision is taken for forecasting. The initial study will reveal the characteristics of metro usage and practices within the system and fnally derive a solution with machine learning-based forecasting method. The passenger and#64258;ow newlineforecasts based on the above patterns depend on factors like seasonality, trends, cyclicity, location, events, and random effects. -
Large-Scale Proteomics Reveals New Candidate Biomarkers for Late-Onset Preeclampsia
BACKGROUND: Preeclampsia is classified as either a more severe early onset or a more prevalent late-onset form. Lower PlGF (placental growth factor) and increased sFlt-1 (fms-like tyrosine kinase-1) in maternal circulation are promising biomarkers, yet they lack specificity for preeclampsia. METHODS: We quantified ?7000 proteins in 673 samples collected from 89 patients with late-onset preeclampsia and 91 controls at T1 (1522), T2 (2230), and T3 (3042) weeks. Elastic net and random forest models were fitted and evaluated by cross-validation. Differential abundance analysis followed by functional profiling, was used to identify and interpret protein changes. RESULTS: An increase in protein differential abundance in late-onset preeclampsia was observed with advancing gestation, reaching 806 proteins at T3 related to angiogenesis, cell adhesion, and extracellular matrix remodeling. FAAH2 (fatty acid amide hydrolase 2), SIGLEC6 (sialic acid-binding Ig-like lectin-6), IL17RC (interleukin-17 receptor C), HTRA1 (serine protease), sFlt-1, and 47 other proteins dysregulated at T3 were validated in a reanalysis of a ?5000 protein Norwegian data set. Random forest models with 20 proteins showed high accuracy at T3 (area under the curve [AUC], 0.83 [0.770.89], sensitivity 59%) even in cases not yet diagnosed at sampling (n=31, AUC, 0.80 [0.710.90], sensitivity 58%), outperforming sFlt-1 and PlGF. Moderate accuracy was obtained at T1 (AUC, 0.63 [0.540.72], sensitivity 33%) and T2 (AUC, 0.59 [0.500.68], sensitivity 17%). Combining maternal characteristics and obstetric history with proteomics data increased accuracy at T1 (AUC, 0.68 [0.590.77], sensitivity 28%), T2 (AUC, 0.68 [0.600.77], sensitivity 31%), and T3 (AUC, 0.87 [0.810.92], sensitivity 69%). CONCLUSIONS: The findings confirm the involvement of abnormal trophoblast invasion, angiogenesis, and extracellular matrix remodeling in late-onset preeclampsia, while highlighting new protein alterations consistent across diverse cohorts. 2025 American Heart Association, Inc. -
Larval descriptions and natural history of two endemic frogs (Amphibia: Anura) from the Western Ghats, India
Western Ghats of India is known for its high anuran diversity; however, the larvae of many anurans are still unknown. Studies on anuran larvae can provide insights into their natural history and evolution, help identify cryptic species and aid in amphibian conservation. In this study, we describe the tadpoles of two poorly known species Indirana bhadrai and Micrixalus candidus from the Western Ghats, India using morphology and molecular techniques and provide details on their natural history. The morphology of the tadpoles reflected their habitats. The tadpole of Indirana bhadrai was semiterrestrial, adapted to wet rocky slopes while the tadpole of Micrixalus candidus was fossorial, found under small rocks and sand in slow-flowing streams. Molecular analysis using the 16S rRNA gene showed 100% identity between tadpoles of Indirana bhadrai, and Micrixalus candidus with their adults respectively. The larval descriptions provided in this study can help understand the ecology of the frogs from the Western Ghats. Copyright 2025 Magnolia Press. -
Laser Scribing Turns Plastic Waste into a Biosensor via the Restructuration of Nanocarbon Composites for Noninvasive Dopamine Detection
The development of affordable and compact noninvasive point-of-care (POC) dopamine biosensors for the next generation is currently a major and challenging problem. In this context, a highly sensitive, selective, and low-cost sensing probe is developed by a simple one-step laser-scribing process of plastic waste. A flexible POC device is developed as a prototype and shows a highly specific response to dopamine in the real sample (urine) as low as 100 pmol/L in a broad linear range of 10?1010?4 mol/L. The 3D topological feature, carrier kinetics, and surface chemistry are found to improve with the formation of high-density metal-embedded graphene-foam composite driven by laser irradiation on the plastic-waste surface. The development of various kinds of flexible and tunable biosensors by plastic waste is now possible thanks to the success of this simple, but effective, laser-scribing technique, which is capable of modifying the matrixs electronic and chemical composition. 2023 by the authors. -
Latency Reduction and Input Prediction for Cloud Gaming Clients
Cloud gaming enables access to high-quality games on thin clients by streaming rendered content from remote servers, but network-induced latency remains a critical barrier to responsive gameplay. This paper presents a browser-based system that profiles user input in real-time, employs a lightweight machine learning model to predict actions, and dynamically compensates for lag by speculative input. Our solution reduces perceived lag by up to 25% and maintains a 94%+ prediction accuracy, fully within a free-tier cloud environment. Compared to traditional infrastructure-based approaches, our method imposes no proprietary hardware requirements and offers platform-wide scalability. 2025 IEEE. -
Lateral Load Behavior of Unreinforced Masonry Spandrels
Spandrels, are usually classified as secondary elements and even though their behaviour has not received adequate focus unlike piers, they significantly affect the seismic capacity of the structure. Masonry spandrels are often damaged and the first structural components that crack within Unreinforced Masonry structures. Despite this, existing analytical methods typically consider a limit case in which the strength of spandrels is either neglected, considered to be infinitely rigid and strong or treated as rotated piers. It is clearly evident that such an assumption is not plausible. Hence, reliable predictive strength models are required. This thesis attempts to re-examine the flexural behaviour of spandrels and proposes an analytical model. The model is based on the interlocking phenomena of the joints at the end-sections of the spandrel and the contiguous masonry. The proposed analytical model is incorporated within a simplified approach to account for the influence of spandrel response on global capacity estimate of URM buildings. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Lattice Distortion Suppressed in MoO3 by Incorporating Minor Impurities of rGO: Strategy for Enhanced Electrocatalytic Hydrogen Evolution
Structural stability is critical for improving the electronic properties and charge-transfer efficiency of the catalyst, directly contributing to its enhanced electrocatalytic hydrogen evolution reaction (HER) activity. In this study, orthorhombic MoO3 and rGO-MoO3 catalysts were synthesized by using a straightforward hydrothermal method, and they demonstrated excellent activity for electrochemical water splitting for hydrogen generation. In this study, conventional laboratory techniques, except for Raman spectroscopy, were unable to clearly detect or differentiate the presence and impact of a very small amount (0.5%) of rGO in MoO3. However, X-ray absorption fine structure analysis performed at the synchrotron facility provided definitive confirmation of the influence of minor rGO incorporation in this study. The analysis revealed that the incorporation of rGO suppresses lattice distortions and enhances the stability of local atomic coordination within the MoO3 framework. The Tafel slopes for MoO3 and rGO-MoO3 composite nanorods are 205 and 173 mV/dec, indicating improved reaction kinetics with rGO incorporation. The estimated specific capacitance values from the linear fit of CV at different scan rates are 2.0 mF/cm2 for MoO3 and 6.7 mF/cm2 for the rGO-MoO3 composite nanorods. Therefore, this study provides valuable insights into tuning the structural properties of materials and enhancing the HER performance through the incorporation of trace amounts of carbon-based materials, effectively suppressing lattice distortions. 2025 American Chemical Society. -
Lattice thermal conduction in cadmium arsenide
Lattice thermal conductivity (LTC) of cadmium arsenide (Cd3As2) is studied over a wide temperature range (1-400 K) by employing the Callaway model. The acoustic phonons are considered to be the major carriers of heat and to be scattered by the sample boundaries, disorder, impurities, and other phonons via both Umklapp and normal phonon processes. Numerical calculations of LTC of Cd3As2 bring out the relative importance of the scattering mechanisms. Our systematic analysis of recent experimental data on thermal conductivity (TC) of Cd3As2 samples of different groups, presented in terms of LTC, ? L, using a nonlinear regression method, reveals good fits to the TC data of the samples considered for T < ? 50 K, and suggests a value of 0.2 for the Gruneisen parameter. It is, however, found that for T > 100 K the inclusion of the electronic component of TC, ? e, incorporating contributions from relevant electron scattering mechanisms, is needed to obtain good agreement with the TC data over the wide temperature range. More detailed investigations of TC of Cd3As2 are required to better understand its suitability in thermoelectric and thermal management devices. 2022 Chinese Physical Society and IOP Publishing Ltd. -
Lattice thermal conduction in suspended molybdenum disulfide monolayers with defects
In this study, we investigated the effect of lattice defects comprising vacancies and boundaries on the lattice thermal conductivity (LTC), ? p , of suspended molybdenum disulfide monolayers (MLs) over a wide temperature range (1 < T < 500 K). Using the phonon Boltzmann formalism, the acoustic phonons were considered to be scattered by the sample and grain boundaries, isotopic impurities, vacancies, and other phonons via Umklapp and normal (N-) processes. ? p was evaluated using a modified Callaway model by considering the in-plane longitudinal acoustic and transverse acoustic phonons, and out-of-plane flexural acoustic phonon modes. We demonstrated the need to include the often neglected non-resistive N-processes when evaluating the LTC. Numerical calculations of the temperature dependence of the LTC for crystalline and polycrystalline MoS 2 MLs showed the dominance of sample-dependent scattering mechanisms at low temperatures (T < 100 K) and of phonon-phonon scattering at higher temperatures, where the N-processes played an important role. The effects of vacancies and boundaries were to alter the behavior and suppress the magnitude of the LTC. The suppression due to vacancies was greater in crystalline MLs with specular surfaces and in polycrystalline MLs with larger grain sizes. The calculations compared well with recent thermal conductivity data obtained for polycrystalline samples. The need for further investigations is suggested. 2018 Elsevier Ltd -
Launch power determination algorithm for dynamic traffic provisioning in mixed-line-rate optical wavelength division multiplexed networks
In transparent mixed-line-rate (MLR) optical networks, different line rates, on different wavelengths, can coexist on the same fibre. However, along the path, signal experiences various physical layer impairments (PLIs), and its quality also degrades. A major factor that affects transmission quality is launch power of the optical signal. On one hand, power must be high enough to ensure less noise at receiver; on the other hand, it must be lower than the limit where PLIs start to distort the signal. Further, high launch power is disruptive to both, the actual lightpath and its neighbours. In this study, we investigate the problem of determining appropriate launch power for provisioning dynamic connection requests in transparent MLR networks. We propose a heuristic that determines the appropriate launch power of a lightpath. The PLI-average (PLI-A) approach is based on the optical reach of signals, is practical, and can adapt to the needs of network operators. Results show that performances of the proposed approach are better than the existing schemes. Copyright 2015 Inderscience Enterprises Ltd.