University of Delhi

Currently, sophisticated advanced electronics require ferroelectric materials with high dielectric response. Lead-free (1 −x)K 0.5Na 0.5NbO 3-xLiNbO 3 (KNN-xLiN) ceramics with x = 0.01, 0.03, and 0.05 were produced using a solid-state method, resulting in a greater dielectric constant, a lower impedance, and an increased conductivity. Compared to conventional ferroelectrics, KNN-0.01LiN ceramics have a greater activation energy (E r e l) of 1.33 eV and a large σ a c value of 10 − 3 − 10 − 2 S/m in the frequency range of 20 Hz–1 MHz. The peak that corresponds to the orthogonal–tetragonal (T O − T) phase shifts toward the lower temperature side and the peak that corresponds to T T − C shifts toward the higher temperature side as dopant percentage increases in the KNN-xLiN ceramics. The observed data may provide light on a key member of the team involved in the creation of upgraded ferroelectrics with improved performance. This result sheds light on the process underlying the improved characteristics of K 0.5Na 0.5NbO 3-based ceramics and may lead to the development of high performance ferroelectrics that will benefit a variety of functional materials.

Cesium (Cs) is a toxic alkaline metal affecting human health. Plant high-affinity K transporters (HAKs) involved in Cs uptake and transport have been identified in several plants. However, the molecular regulatory mechanisms of Cs uptake and transport, and homeostasis between Cs and K by HAKs remain unknown. In this study, TaHAK1 was overexpressed in rice (TaHAK1-OEs) to evaluate Cs absorption capacity and the Cs and K homeostasis mechanisms. Results showed that TaHAK1 promoted seedling growth by fixing Cs in the root cell wall and modifying Cs distribution. Transcriptome and bioinformatics analyses revealed that 37,828 differentially expressed genes (DEGs) were significantly induced in TaHAK1-OEs, of which the pathways involved in cell wall biosynthesis and ion absorption transport were notably affected including genes, XTHs, CSLEs, HAKs, and ABCs. Moreover, under Cs-contaminated soil, TaHAK1-OEs exhibited improved Cs tolerance by decreasing Cs accumulation and increasing K content in different tissues, particularly in the grains, indicating that TaHAK1 acts as a candidate gene for screening genetic modification of Cs phytoremediation and developing low-Cs-accumulation rice varieties. This study provides new insights into the uptake and translocation of Cs and the homeostasis of Cs and K in plants, and also supplies new strategy to improve phytoremediation efficiency.

Micro-Electro-Mechanical Systems (MEMS) technology based piezoresistive technique is a highly matured transduction technique. It is very popular for the MEMS devices used in various industries like automotive, process control, aerospace & avionics, consumer electronics, nuclear power plants, and many more. MEMS pressure sensors are one among them, and their deployment in nuclear power plant and aerospace are prominently increasing. Hence radiation-induced performance degradation of piezoresistive pressure sensors has been carried out, which is a prime concern for such industries. Therefore, a set of experiments for the investigation of irradiation driven performance degradation of MEMS pressure sensors are performed under varying doses of gamma radiations. An insignificant change in sensitivity was recorded which degraded up to a maximum of 0.78 %, while the linearity remained unchanged for a cumulative dose of 27.90 Mrad. However, the deviation in the offset voltage of the Wheatstone bridge configuration was significant and as recorded was 139% at a cumulative dose of 27.90 Mrad. This manuscript explains the degradation mechanism of MEMS piezoresistive sensors using the experiments and TCAD simulations.

Background MCRs are one of the most significant tools in the synthesis of organic compounds. MCR is a rapid chemical technique that uses three or more reactants to produce products that sustain all structural and substructural properties of the initial components. MCRs are useful in all fields of synthetic chemistry because of their rapid rate of reaction, simple procedure and excellent yields. We reported an efficient and environmentally friendly domino approach for the synthesis of spiroheterocycles spiro annulated with indeno[1,2-b]quinoline. Method The spiroheterocycles with privileged heterocyclic substructures have been synthesized using taurine (2-aminoethanesulfonic acid) as a green, sustainable, bio-organic and recyclable catalyst in a three-component reaction of isatins, 1,3-diketones, and 1-napthylamine in aqueous media. The present synthetic method is probably the first report to synthesize spiroheterocycles, spiroannulated with indeno[1,2-b]quinoline. Furthermore, the approach is valuable because of the excellent yield that results from the reaction in 15-20 min. Result The optimization of reaction conditions is an important case of efficient synthesis. The solvent, temperature, time and catalyst loading were all examined. The reusability of the catalyst was also investigated experimentally. The used catalyst taurine has a high activity as well as good reusability. The present synthetic protocol will be extended to synthesise a library of hybrid compounds. The present synthetic approach is cost-effective, and time-efficient with an easy-workup methodology that gives outstanding yields (80–95%) in 15–20 min. Conclusion Taurine-catalyzed multicomponent reaction is a novel and efficient method for the synthesis of spiroannulated indeno[1,2-b]quinolines. The high catalytic activity of taurine as a catalyst with water as a green solvent makes the process environmentally friendly. The special features of the synthetic protocol include synthetic efficiency, operational simplicity, and reusability of the catalyst and it is expected to make significant contributions not only to drug discovery studies but also to pharmaceutical and therapeutic chemistry in view of introducing molecular diversity in the synthesized molecules.

Congratulations, you’re a machine learning expert! Surprised? Don’t be. Every day, through the most mundane of decisions, from guessing the next song on your playlist to predicting the victor in a cockroach race, you’re employing the core principles of machine learning. This article isn’t about turning you into a data scientist overnight. Instead, it’s about showing you that your brain is the OG machine learner, and your daily routines are its training data.

Accurate breast cancer prognosis prediction is crucial for efficient treatment planning and improving patient outcomes. While significant progress has been made in treating primary breast cancer, the development of robust predictive models remains a critical challenge. This study introduces multi-modal prognostic approach for enhanced Metastatic Breast Cancer prediction. Recognizing the limitations of relying solely on uni-modal data, our approach leverages the power of multi-modal datasets. The images are taken from breast ultrasound scans dataset and mammograms are resized into 224 × 224, and finally, data pre-processing steps are used. This study presents a two-stage model: first, a convolutional neural network is used to extract salient features from the multi-modal data. These extracted features are further concatenated for feature-fusion and served as an input for a dual transfer learning hybrid model in the second stage by combining EfficientNetB4 and InceptionV3, thus enabling robust and accurate prognosis prediction. The outputs are flattened and concatenated followed by implementation of Deep_dense layers to learn the weights of the combined models. The proposed hybrid approach effectively categorizes medical images for the prognostics of breast-cancer. Evaluations demonstrate the superior performance of our proposed model, achieving an accuracy of 99.12%, precision of 95%, recall of 93%, and F1 score of 98.12%.

Bone marrow aspirate concentrate (BMAC) is considered one of the biological treatments for knee osteoarthritis (KOA). Patient selection remains a key factor to ensure that optimal treatment benefit and body mass index (BMI) are one of the key factors to be considered. This study aims to evaluate the influence of obesity on the duration of treatment benefit of BMAC for KOA. This prospective cohort study enrolled 68 patients who underwent a single BMAC injection for early stage KOA. The patients were categorized based on their BMI into normal, overweight, and obese groups. Visual Analog Scale (VAS) for pain and Knee Injury and Osteoarthritis Outcome Score (KOOS) were the outcomes analysed. The duration of treatment benefit is estimated by Kaplan–Meier survival analysis. Sixty-eight patients (normal BMI = 43, overweight BMI = 15, obese BMI = 10) were enrolled in the study for analysis. While significant improvement in the outcome scores was noted compared to the baseline throughout the study period in the normal BMI and overweight group, the obese group returned to baseline parameters at 3 months follow-up. Patients in the normal BMI group demonstrated significant improvement in VAS (p < 0.001) and KOOS (p < 0.001) outcomes compared to the overweight and obese group. Survival analysis demonstrated a significant decline in the mean treatment benefit of 9.8 (95%CI [6.151–13.431], p = 0.027) months in normal BMI group to 6.6 (95%CI [3.473–9.727]) months and 4.1 (95%CI [2.760–5.440]) months in overweight and obese groups, respectively. BMI is a significant factor that influences the benefit of BMAC injection for early knee OA. Hence, BMAC injection must be used with caution in individuals with high BMI.

We show that a slowly varying Newton’s constant, consistent with existing bounds, can potentially explain a host of observations pertaining to gravitational effects or phenomena across distances spanning from planetary to the cosmological, relying neither on the existence of dark matter or (and) dark energy, nor on any expected high proportions of either of them in the Universe. It may also have implications at very short distances or quantum gravity scales.

In this paper, we determine sharp bounds on some Hankel determinants involving initial coefficients, inverse coefficients, and logarithmic inverse coefficients for two associated subclasses of Sakaguchi functions related to the lemniscate of Bernoulli and exponential function. Further, we compute sharp bounds on the second-order Hermitian–Toeplitz determinants involving logarithmic coefficients and logarithmic inverse coefficients for such subclasses. We also discuss the invariance property for the obtained estimates with respect to various coefficients.

The proliferation of renewable energy (RE) and increasing electrical demand stress the existing generation and transmission systems. Moreover, due to environmental concerns, the proper utilization of small-scale renewable distributed energy resources (DERs) has become essential. DERs can play a pivotal role in evolving grids by reducing emissions and improving energy delivery by providing system services like voltage maintenance. Optimal sizing and sitting of these DERs into the distribution system promise various benefits and a viable solution to overcome the limitations of large transmission and conventional generation systems and provide better voltage maintenance. Besides, utilizing realistic data generation from working plants and varying load patterns allows for better insights into power system operations under growing RE. This work presents a profit-based optimal sizing and sitting of DERs into the distribution system while considering environmental costs. An improved Harmony Search algorithm has been applied to optimize the proposed cost-based objective function, which consists of various costs in generating distributed energy while simultaneously considering the environmental expenses incurred due to the release of different pollutant gasses. Also, the generation data of working solar and wind plants and realistic varying loads across seasons, weekdays, and weekend days have been considered to explore real operating scenarios. Efficacy has been verified from the optimization results that illustrate its capability to allocate DERs in conjunction with reduced costs and emissions, facilitating optimal system operations. The algorithm has been tested for two standard distribution systems focusing on reducing overall generation costs, social costs labelled due to emissions, improvement in voltage profile, and reduction in overall losses of the system.

The dominant political discourse in India situates Ambedkar in opposition to the ideology of Hindutva. Ambedkar criticised Hindu religious texts on the ground of sanctioning graded inequality in the Hindu social order. This further gets traction with demands of Ambedkar to treat depressed classes as non-Hindus or protestant Hindus. The twenty-one commandants read out at the time of his conversion also denounced key Hindu gods and goddesses. All this goes against the basic tenets of Hindutva ideology. Therefore, any overtures by Hindutva protagonists in favour of Ambedkar are interpreted as attempts to appropriate him for electoral reasons. This article counters this narrative and argues that there are several political and ideological issues on which both Ambedkar and Hindu nationalists converge. The author has used the discourse analysis method to identify those issues that bring Ambedkar close to Hindu nationalists.

This article examines the corruption scandal that exploded in 1889 with the apprehension of Arthur Crawford and the dismissal of several Mamlatdars in colonial western India. Using Ian Hacking's concept of “making up people” and the “looping effect,” this article demonstrates the instability of categories such as corruption and suggests that the everyday life of empire was undergirded by the colonial construction of deviancy to normalize the exceptionality of foreign rule. Additionally, the Crawford-Mamlatdar corruption scandal undercut the imperial ideology of the modernizing state. The corruption network revealed the simultaneity of imperial bureaucratic rationality along with the traditional patronage structures based on indigenous sexual and filial (caste) ties. It was precisely the British investigation that also revealed the reality of the homosocial empire and its privileging of caste recruitments. The Indian challenge to the case brought together rural and urban groups signalling the ascendance of a nationalistic solidarity. The Indians queried the imperial claims of moral superiority. At the same time, they acknowledged “native vulnerabilities” towards corruption, confirming the British stereotype of Indians as inherently corrupt. These selective claims, indicative of the emergence of upper caste, urban, and bourgeois notion of public virtue, signified the iterative nature of the “looping effect.”

Perovskite-structured materials have been extensively studied for sensing applications on account of their good thermal stability and 3–4 eV bandgap. They have been utilized to detect traces of O2, NO, CO, NO2, CO2, H2O, CH4, H2 and similar smaller gas molecules such as C2H5OH etc. In addition, other sensing applications are optical sensing, I-V fluctuations, strain sensors, electromechanical sensors, sensing of metal ions, etc. Perovskite-structured halides are reported for sensing of metal ions, toxic gases, Volatile Organic Compounds (VOCs), detection of fungicides, pesticides, explosives, cellular imaging, radiation detection and humidity and temperature sensing.

Due to climate change the drop in spring-water discharge poses a serious issue in the Himalayan region, especially in the higher section of Himachal Pradesh. This study used different climatic factors along with long-term rainfall data to understand the decreasing trend in spring-water discharge. It was determined which climate parameter was most closely correlated with spring discharge volumes using a general as well as partial correlation plot. Based on 40 years (1981–2021) of daily average rainfall data, a rainfall-runoff model was utilised to predict and assess trends in spring-water discharge using the MIKE 11 NAM hydrological model. The model’s effectiveness was effectively proved by the validation results (NSE = 0.79, R² = 0.944, RMSE = 0.23, PBIAS = 32%). Model calibration and simulation revealed that both observed and simulated spring-water runoff decreased by almost 29%, within the past 40 years. Consequently, reduced spring-water discharge is made sensitive to the hydrological (groundwater stress, base flow, and stream water flow) and environmental entities (drinking water, evaporation, soil moisture, and evapotranspiration). This study will help researchers and policymakers to think and work on the spring disappearance and water security issues in the Himalayan region.

The study investigates the weak-form market efficiency within the Indian equity market considering the two approaches i.e., absolute and evolving market efficiency. This work provides an in-depth examination of weak-form market efficiency using a combination of linear and nonlinear statistical tests, including Ljung and Box, runs test, Bartel test, Variance ratio test, and BDS test,.In contrast to earlier research, which frequently used subsample analysis, the study considered rolling window analysis with the 500 observations to precisely capture the evolving efficiency. There is ample evidence that the efficiency of the Indian equity market varies across time, exhibiting both efficient and inefficient periods. To put it briefly, the research suggested that the Adaptive Market Hypothesis (AMH) provides a more holistic understanding of emerging market behavior compared to the EMH.

Biodiesel, a promising alternative to conventional fossil fuels, garners increased attention for its potential in mitigating pollution and reducing greenhouse gas emissions. In a recent study, the impact of blending biodiesel (10–30%) derived from native mixed algal biomass with petroleum diesel on emission characteristics was assessed using a VCR 4-stroke engine. Emissions were analyzed with an AVL444 di-gas analyzer, measuring CO and CO2, along with exhaust temperature, at various engine loads (0, 20, 40, 60, 80, 100, and 120 kg). Results indicated that CO and CO2 emissions were consistently lower than petro-diesel across all load conditions, decreasing further with an increased percentage of algal biodiesel in the blend. Unburned hydrocarbon levels decreased, except for a slight rise at 30% biodiesel until the 40 kg load, dropping sharply thereafter and reaching a minimum of 14 ppm at overload (120 kg). Notably, NOx emissions exceeded those of petro-diesel at all loads due to higher heat generation in the combustion chamber from algal biodiesel’s elevated cetane number. Mitigation strategies, such as additives or de-NOx catalysts, were suggested. By substituting fossil fuels with biodiesel from native mixed algal biomass or their blends, a substantial reduction in pollutant release into the atmosphere is achievable. This shift contributes significantly to global pollution control, offering environmental and public health benefits. The widespread adoption of biodiesel aligns with global efforts to combat pollution and fosters a more sustainable and eco-friendly energy future.

Climate change is a global phenomenon being witnessed by the communities of all nations at different scales and in a varied manner. South Asia being a tropical territory characterized by high population numbers and low per capita incomes, faces challenges when tackling the impacts associated with climate change. It is also a geologically sensitive region considering the existence of the Himalayas at the top and the massive Indian Ocean marking its bottom boundaries. These factors contribute to the vulnerability of the region. In the Indian subcontinent, the impacts of climate change have already been felt across its territory. Since climate change is a natural phenomenon, it is leading to unpredictable short as well as long-term changes in the weather as well, which is contributing to increased incidences and extent of natural disasters. For the past few decades, India has adopted several measures to mitigate and adapt to climate change through various plans, policies, and missions at various levels of governance. The paper aims to analyze such plans and policies in pursuance of its objective of identifying the existing legal framework for climate change in India and explore if it incorporates the important aspect of climate change-induced disaster risk management.

This research work studies the complete integrability, bright-dark solitons, and rogue waves of a recently formed variable coefficient generalized (4+1)-dimensional Kadomtsev-Petviashvili equation. It analyses the integrability of the investigated generalized equation by applying the Painlevé test with arbitrary choices and fulfilling the condition for compatibility for the resonances. It generates the bilinear equation with the Cole-Hopf transformation in the auxiliary function and, by using the bilinear differential operator, constructs Hirota’s bilinear form of this equation. Utilizing Hirota’s bilinear technique for N-soliton solutions, we obtain soliton solutions and their X-type and Y-type interactions for 1-, 2-, and 3-soliton solutions under the obtained restrictions and showcase their analytic dynamics. Also, it obtains the N-rogue wave solutions up to second order with center-controlled parameters with appropriate parameters and the variable coefficients and displays the dynamical structures. We form the bright-dark solitons and rogue waves with appropriate choices of parameters in the third and second order, respectively. By applying the computer algebra system software Mathematica, it displays the dynamical structures for the generated solutions with several chosen parameter values. Solitons appear in different fields of nonlinear sciences, such as fluid mechanics, nonlinear optics, oceanography, plasma physics, water waves, and other sciences.

Inorganic nanoparticles (NPs) have been increasingly utilized across various fields due to their unique properties and versatile applications. They offer small size, enhanced tunability, permeability, surface functionalization and are more stable in comparison to organic materials. They have gained widespread attention for their application in therapeutic and diagnostic systems for drug delivery, imaging, sensing and biomedical implants. There are several chemical methods for synthesizing inorganic nanoparticles. These methods involve the use of chemical surfactants like Sodium dodecyl sulphate (SDS), Sodium dodecylbenzene sulfonate (SDBS) and Cetyltrimethylammonium bromide (CTAB) as reducing, stabilizing and capping agents. However, these chemicals are hazardous and produce toxic byproducts posing risks to health and the environment. Green nanoparticle synthesis involves adopting sustainable and eco-friendly techniques to produce nanoparticles, aiming to decrease the environmental footprint of the process. Biosurfactants are amphiphilic compounds produced by microorganisms, plants, or animals. They are derived from renewable resources and are biodegradable. This makes the synthesis process more environmentally friendly and reduces the potential harmful impact on ecosystems. Biosurfactants can act as environmentally benign precursors, reducing agents and help in stabilizing the nanoparticles. In this paper, we have reviewed the recent studies in the green synthesis of inorganic nanoparticles using bio-surfactants. Further, parameters which affect the formation of NPs while using biosurfactants have been discussed. In addition, emergence of machine learning and other computational tools for nanoparticle formation have been explored. The challenges and the future prospectives in this direction have also been highlighted.