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4,661 results on '"Vinod K"'

2. CosFairNet:A Parameter-Space based Approach for Bias Free Learning

Author

Dwivedi, Rajeev Ranjan, Kumari, Priyadarshini, and Kurmi, Vinod K

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Deep neural networks trained on biased data often inadvertently learn unintended inference rules, particularly when labels are strongly correlated with biased features. Existing bias mitigation methods typically involve either a) predefining bias types and enforcing them as prior knowledge or b) reweighting training samples to emphasize bias-conflicting samples over bias-aligned samples. However, both strategies address bias indirectly in the feature or sample space, with no control over learned weights, making it difficult to control the bias propagation across different layers. Based on this observation, we introduce a novel approach to address bias directly in the model's parameter space, preventing its propagation across layers. Our method involves training two models: a bias model for biased features and a debias model for unbiased details, guided by the bias model. We enforce dissimilarity in the debias model's later layers and similarity in its initial layers with the bias model, ensuring it learns unbiased low-level features without adopting biased high-level abstractions. By incorporating this explicit constraint during training, our approach shows enhanced classification accuracy and debiasing effectiveness across various synthetic and real-world datasets of different sizes. Moreover, the proposed method demonstrates robustness across different bias types and percentages of biased samples in the training data. The code is available at: https://visdomlab.github.io/CosFairNet/

Published
2024

3. Co-Design of 2D Heterojunctions for Data Filtering in Tracking Systems

Author

Oli, Tupendra, Olin-Ammentorp, Wilkie, Wu, Xingfu, Qian, Justin H., Sangwan, Vinod K., Hersam, Mark C., Habib, Salman, and Taylor, Valerie

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

As particle physics experiments evolve to achieve higher energies and resolutions, handling the massive data volumes produced by silicon pixel detectors, which are used for charged particle tracking, poses a significant challenge. To address the challenge of data transport from high resolution tracking systems, we investigate a support vector machine (SVM)-based data classification system designed to reject low-momentum particles in real-time. This SVM system achieves high accuracy through the use of a customized mixed kernel function, which is specifically adapted to the data recorded by a silicon tracker. Moreover, this custom kernel can be implemented using highly efficient, novel van der Waals heterojunction devices. This study demonstrates the co-design of circuits with applications that may be adapted to meet future device and processing needs in high-energy physics (HEP) collider experiments., Comment: 15 pages, 8 figures, 1 table

Published
2024

4. Towards Robust Few-shot Class Incremental Learning in Audio Classification using Contrastive Representation

Author

Singh, Riyansha, Nema, Parinita, and Kurmi, Vinod K

Subjects
Computer Science - Sound, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In machine learning applications, gradual data ingress is common, especially in audio processing where incremental learning is vital for real-time analytics. Few-shot class-incremental learning addresses challenges arising from limited incoming data. Existing methods often integrate additional trainable components or rely on a fixed embedding extractor post-training on base sessions to mitigate concerns related to catastrophic forgetting and the dangers of model overfitting. However, using cross-entropy loss alone during base session training is suboptimal for audio data. To address this, we propose incorporating supervised contrastive learning to refine the representation space, enhancing discriminative power and leading to better generalization since it facilitates seamless integration of incremental classes, upon arrival. Experimental results on NSynth and LibriSpeech datasets with 100 classes, as well as ESC dataset with 50 and 10 classes, demonstrate state-of-the-art performance., Comment: INTERSPEECH 2024 accepted

Published
2024

5. An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistors

Author

Wu, Xingfu, Oli, Tupendra, Qian, Justin H., Taylor, Valerie, Hersam, Mark C., and Sangwan, Vinod K.

Subjects
Computer Science - Machine Learning, Computer Science - Performance
Abstract

Support Vector Machine (SVM) is a state-of-the-art classification method widely used in science and engineering due to its high accuracy, its ability to deal with high dimensional data, and its flexibility in modeling diverse sources of data. In this paper, we propose an autotuning-based optimization framework to quantify the ranges of hyperparameters in SVMs to identify their optimal choices, and apply the framework to two SVMs with the mixed-kernel between Sigmoid and Gaussian kernels for smart pixel datasets in high energy physics (HEP) and mixed-kernel heterojunction transistors (MKH). Our experimental results show that the optimal selection of hyperparameters in the SVMs and the kernels greatly varies for different applications and datasets, and choosing their optimal choices is critical for a high classification accuracy of the mixed kernel SVMs. Uninformed choices of hyperparameters C and coef0 in the mixed-kernel SVMs result in severely low accuracy, and the proposed framework effectively quantifies the proper ranges for the hyperparameters in the SVMs to identify their optimal choices to achieve the highest accuracy 94.6\% for the HEP application and the highest average accuracy 97.2\% with far less tuning time for the MKH application., Comment: presented in SC24 Workshop on Extreme-Scale Experiment-in-the-Loop Computing (XLOOP2024)

Published
2024

10. Enhancing Edge Intelligence with Highly Discriminant LNT Features

Author

Wang, Xinyu, Mishra, Vinod K., and Kuo, C. -C. Jay

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

AI algorithms at the edge demand smaller model sizes and lower computational complexity. To achieve these objectives, we adopt a green learning (GL) paradigm rather than the deep learning paradigm. GL has three modules: 1) unsupervised representation learning, 2) supervised feature learning, and 3) supervised decision learning. We focus on the second module in this work. In particular, we derive new discriminant features from proper linear combinations of input features, denoted by x, obtained in the first module. They are called complementary and raw features, respectively. Along this line, we present a novel supervised learning method to generate highly discriminant complementary features based on the least-squares normal transform (LNT). LNT consists of two steps. First, we convert a C-class classification problem to a binary classification problem. The two classes are assigned with 0 and 1, respectively. Next, we formulate a least-squares regression problem from the N-dimensional (N-D) feature space to the 1-D output space, and solve the least-squares normal equation to obtain one N-D normal vector, denoted by a1. Since one normal vector is yielded by one binary split, we can obtain M normal vectors with M splits. Then, Ax is called an LNT of x, where transform matrix A in R^{M by N} by stacking aj^T, j=1, ..., M, and the LNT, Ax, can generate M new features. The newly generated complementary features are shown to be more discriminant than the raw features. Experiments show that the classification performance can be improved by these new features., Comment: 2023 IEEE International Conference on Big Data, AI and Adaptive Computing for Edge Sensing and Processing Workshop

Published
2023

14. All-antiferromagnetic electrically controlled memory on silicon featuring large tunneling magnetoresistance

Author

Shi, Jiacheng, Lopez-Dominguez, Victor, Arpaci, Sevdenur, Sangwan, Vinod K., Mahfouzi, Farzad, Kim, Jinwoong, Athas, Jordan G., Hamdi, Mohammad, Aygen, Can, Phatak, Charudatta, Carpentieri, Mario, Jiang, Jidong S., Grayson, Matthew A., Kioussis, Nicholas, Finocchio, Giovanni, Hersam, Mark C., and Amiri, Pedram Khalili

Subjects
Physics - Applied Physics
Abstract

Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and reading of information, which are also compatible with established silicon-based manufacturing. Recent experiments have shown tunneling magnetoresistance (TMR) readout in epitaxial AFM tunnel junctions. However, these TMR structures were not grown using a silicon-compatible deposition process, and controlling their AFM order required external magnetic fields. Here we show three-terminal AFM tunnel junctions based on the noncollinear antiferromagnet PtMn3, sputter-deposited on silicon. The devices simultaneously exhibit electrical switching using electric currents, and electrical readout by a large room-temperature TMR effect. First-principles calculations explain the TMR in terms of the momentum-resolved spin-dependent tunneling conduction in tunnel junctions with noncollinear AFM electrodes.

Published
2023

15. Disease modeling and pharmacological rescue of autosomal dominant retinitis pigmentosa associated with RHO copy number variation

Author

Kandoi, Sangeetha, Martinez, Cassandra, Chen, Kevin Xu, Mehine, Miika, Reddy, L Vinod K, Mansfield, Brian C, Duncan, Jacque L, and Lamba, Deepak A

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Rare Diseases, Genetics, Neurodegenerative, Neurosciences, Biotechnology, Eye Disease and Disorders of Vision, Aetiology, 2.1 Biological and endogenous factors, Eye, Good Health and Well Being, Aged, Humans, Male, DNA Copy Number Variations, Organoids, Retinitis Pigmentosa, Rhodopsin, retinitis pigmentosa, disease modeling, rhodopsin, iPSC, organoids, stem cells, Human, human, regenerative medicine, Biochemistry and Cell Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Retinitis pigmentosa (RP), a heterogenous group of inherited retinal disorder, causes slow progressive vision loss with no effective treatments available. Mutations in the rhodopsin gene (RHO) account for ~25% cases of autosomal dominant RP (adRP). In this study, we describe the disease characteristics of the first-ever reported mono-allelic copy number variation (CNV) in RHO as a novel cause of adRP. We (a) show advanced retinal degeneration in a male patient (68 years of age) harboring four transcriptionally active intact copies of rhodopsin, (b) recapitulated the clinical phenotypes using retinal organoids, and (c) assessed the utilization of a small molecule, Photoregulin3 (PR3), as a clinically viable strategy to target and modify disease progression in RP patients associated with RHO-CNV. Patient retinal organoids showed photoreceptors dysgenesis, with rod photoreceptors displaying stunted outer segments with occasional elongated cilia-like projections (microscopy); increased RHO mRNA expression (quantitative real-time PCR [qRT-PCR] and bulk RNA sequencing); and elevated levels and mislocalization of rhodopsin protein (RHO) within the cell body of rod photoreceptors (western blotting and immunohistochemistry) over the extended (300 days) culture time period when compared against control organoids. Lastly, we utilized PR3 to target NR2E3, an upstream regulator of RHO, to alter RHO expression and observed a partial rescue of RHO protein localization from the cell body to the inner/outer segments of rod photoreceptors in patient organoids. These results provide a proof-of-principle for personalized medicine and suggest that RHO expression requires precise control. Taken together, this study supports the clinical data indicating that RHO-CNV associated adRPdevelops as a result of protein overexpression, thereby overloading the photoreceptor post-translational modification machinery.

Published
2024

18. Spectrum of orbital fat necrosis in rhino-orbital-cerebral mucormycosis in post-COVID-19 patients

Author

Akanksha Agrawal, Preeti Diwaker, Sonali Dixit, Jolly Rohatgi, and Vinod K Arora

Subjects
exenteration, fat necrosis, mucormycosis, rocm, suppurative granuloma, Ophthalmology, RE1-994
Abstract

Purpose: Rhino-orbital-cerebral mucormycosis (ROCM) is the most common presentation of mucormycosis. Sinonasal–orbital debridement with exenteration is a life-saving procedure in ROCM patients in view of severe involvement of sinuses and the eyeball. Following the second wave of coronavirus disease 2019 (COVID-19), there was a massive surge in mucormycosis cases in India in post-COVID-19 patients. Of over 300 cases of mucormycosis admitted in our hospital, many underwent exenteration and these specimens were evaluated histopathologically, where fat necrosis was found to be a prominent finding. The spectrum of fat necrosis in ROCM in orbital fat has not been described in literature. Hence, we sought to evaluate the significance and spectrum of orbital fat necrosis in ROCM. Methods: This 3-month retrospective study included 15 cases of ROCM which underwent exenteration. Clinical data, radiologic details, and histopathologic findings were tabulated. Sections were also subjected to Periodic acid Schiff (PAS) and Gomori’s methenamine silver (GMS) stains for confirming the fungus. Results: All 15 cases showed fat stranding on computed tomography (CT) scan. On histopathologic examination, various tissue reaction patterns observed included acute/chronic inflammatory infiltrate, suppurative granulomas with giant cells, coagulative and fat necrosis, broad aseptate fungal hyphae with or without angioinvasion, and neural invasion. Fungal hyphae were confirmed with PAS and GMS stains. The spectrum of fat necrosis observed in all the cases included 1) acute necrotizing fat necrosis, 2) ghost adipocytes with or without saponification, and 3) crystalline/gouty fat necrosis. Conclusion: Fat necrosis is a significant finding in ROCM, both on CT scan and histopathology. All three patterns of fat necrosis may be observed simultaneously in a case of ROCM.

Published
2024
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19. Global Practice Patterns in the Evaluation of Non-Obstructive Azoospermia: Results of a World-Wide Survey and Expert Recommendations

Author

Rupin Shah, Amarnath Rambhatla, Widi Atmoko, Marlon Martinez, Imad Ziouziou, Priyank Kothari, Nicholas Tadros, Nguyen Ho Vinh Phuoc, Parviz Kavoussi, Ahmed Harraz, Gianmaria Salvio, Murat Gul, Taha Hamoda, Tuncay Toprak, Ponco Birowo, Edmund Ko, Mohamed Arafa, Ramy Abou Ghayda, Vilvapathy Senguttuvan Karthikeyan, Ramadan Saleh, Giorgio Ivan Russo, Germar-Michael Pinggera, Eric Chung, Missy Savira, Giovanni M. Colpi, Wael Zohdy, Edoardo Pescatori, Hyun Jun Park, Shinichiro Fukuhara, Akira Tsujimura, Cesar Rojas-Cruz, Angelo Marino, Siu King Mak, Edouard Amar, Wael Ibrahim, Puneet Sindhwani, Naif Alhathal, Gian Maria Busetto, Manaf Al Hashimi, Ahmed El-Sakka, Asci Ramazan, Fotios Dimitriadis, Massimiliano Timpano, Davor Jezek, Baris Altay, Daniel Suslik Zylbersztejn, Michael YC Wong, Du Geon Moon, Christine Wyns, Safar Gamidov, Hamed Akhavizadegan, Alessandro Franceschelli, Kaan Aydos, Vinh Nguyen Quang, Shedeed Ashour, Adel Al Dayel, Mohamed S. Al-Marhoon, Sava Micic, Saleh Binsaleh, Alayman Hussein, Haitham Elbardisi, Taymour Mostafa, Emad Taha, Jonathan Ramsay, Athanasios Zachariou, Islam Fathy Soliman Abdelrahman, Osvaldo Rajmil, Arif Kalkanli, Juan Manuel Corral Molina, Kadir Bocu, Gede Wirya Kusuma Duarsa, Gokhan Ceker, Ege Can Serefoglu, Fahmi Bahar, Nazim Gherabi, Shinnosuke Kuroda, Abderrazak Bouzouita, Ahmet Gudeloglu, Erman Ceyhan, Mohamed Saeed Mohamed Hasan, Muhammad Ujudud Musa, Ahmad Motawi, Cho Chak-Lam, Hisanori Taniguchi, Christopher Chee Kong Ho, Jesus Fernando Solorzano Vazquez, Shingai Mutambirwa, Nur Dokuzeylul Gungor, Marion Bendayan, Carlo Giulioni, Aykut Baser, Marco Falcone, Luca Boeri, Gideon Blecher, Alireza Kheradmand, Tamilselvi Sethupathy, Ricky Adriansjah, Nima Narimani, Charalampos Konstantinidis, Tuan Thanh Nguyen, Andrian Japari, Parisa Dolati, Keerti Singh, Cevahir Ozer, Selcuk Sarikaya, Nadia Sheibak, Ndagijimana Jean Bosco, Mehmet Serkan Özkent, Sang Thanh Le, Ioannis Sokolakis, Darren Katz, Ryan Smith, Manh Nguyen Truong, Tan V. Le, Zhongwei Huang, Muslim Dogan Deger, Umut Arslan, Gokhan Calik, Giorgio Franco, Ayman Rashed, Oguzhan Kahraman, Sotiris Andreadakis, Rosadi Putra, Giancarlo Balercia, Kareim Khalafalla, Rossella Cannarella, Anh Đặng Tuấn, Amr El Meliegy, Birute Zilaitiene, Marlene Lizbeth Zamora Ramirez, Filippo Giacone, Aldo E. Calogero, Konstantinos Makarounis, Sunil Jindal, Bac Nguyen Hoai, Ravi Banthia, Marcelo Rodriguez Peña, Dharani Moorthy, Aram Adamyan, Deniz Kulaksiz, Hussein Kandil, Nikolaos Sofikitis, Ciro Salzano, Andreas Jungwirth, Surendra Reddy Banka, Tiago Cesar Mierzwa, Tahsin Turunç, Divyanu Jain, Armen Avoyan, Pietro Salacone, Ateş Kadıoğlu, Chirag Gupta, Haocheng Lin, Iman Shamohammadi, Nasser Mogharabian, Trenton Barrett, Yavuz Onur Danacıoğlu, Andrea Crafa, Salima Daoud, Vineet Malhotra, Abdulmalik Almardawi, Osama Mohamed Selim, Mohamad Moussa, Saeid Haghdani, Mesut Berkan Duran, Yannic Kunz, Mirko Preto, Elena Eugeni, Thang Nguyen, Ahmed Rashad Elshahid, Seso Sulijaya Suyono, Dyandra Parikesit, Essam Nada, Eduardo Gutiérrez Orozco, Florence Boitrelle, Nguyen Thi Minh Trang, Mounir Jamali, Raju Nair, Mikhail Ruzaev, Franco Gadda, Charalampos Thomas, Raphael Henrique Ferreira, Umit Gul, Serena Maruccia, Ajay Kanbur, Ella Kinzikeeva, Saad Abumelha, Nguyen Quang, Raghavender Kosgi, Fatih Gokalp, Mohammad Ayodhia Soebadi, Gustavo Marquesine Paul, Hesamoddin Sajadi, Deepak Gupte, Rafael F. Ambar, Emrullah Sogutdelen, Karun Singla, Ari Basurkano, Shannon Hee Kyung Kim, Mohammad Ali Sadighi Gilani, Koichi Nagao, Sakti Ronggowardhana Brodjonegoro, Andri Rezano, Mohamed Elkhouly, Rossella Mazzilli, Hasan M. A. Farsi, Hung Nguyen Ba, Hamed Alali, Dimitrios Kafetzis, Tran Quang Tien Long, Sami Alsaid, Hoang Bao Ngoc Cuong, Knigavko Oleksandr, Akhmad Mustafa, Herik Acosta, Hrishikesh Pai, Bahadır Şahin, Eko Arianto, Colin Teo, Sanjay Prakash Jayaprakash, Rinaldo Indra Rachman, Mustafa Gurkan Yenice, Omar Sefrioui, Smit Paghdar, Shivam Priyadarshi, Marko Tanic, Noor Kareem Alfatlawy, Fikri Rizaldi, Ranjit B. Vishwakarma, George Kanakis, Dinesh Thomas Cherian, Joe Lee, Raisa Galstyan, Hakan Keskin, Jana Wurzacher, Doddy Hami Seno, Bambang S. Noegroho, Ria Margiana, Qaisar Javed, Fabrizio Castiglioni, Raman Tanwar, Ana Puigvert, Coşkun Kaya, Medianto Purnomo, Chadi Yazbeck, Azwar Amir, Edson Borges, Marina Bellavia, Isaac Ardianson Deswanto, Vinod K V, Giovanni Liguori, Dang Hoang Minh, Kashif Siddiqi, Fulvio Colombo, Armand Zini, Niket Patel, Selahittin Çayan, Ula Al-Kawaz, Maged Ragab, Guadalupe Hernández Hebrard, Ivan Hoffmann, Ozan Efesoy, Barış Saylam, and Ashok Agarwal

Subjects
azoospermia, diagnosis, guideline, infertility, male, surveys and questionnaires, Medicine, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Purpose: Non-obstructive azoospermia (NOA) represents the persistent absence of sperm in ejaculate without obstruction, stemming from diverse disease processes. This survey explores global practices in NOA diagnosis, comparing them with guidelines and offering expert recommendations. Materials and Methods:Materials and Methods: A 56-item questionnaire survey on NOA diagnosis and management was conducted globally from July to September 2022. This paper focuses on part 1, evaluating NOA diagnosis. Data from 367 participants across 49 coun-tries were analyzed descriptively, with a Delphi process used for expert recommendations. Results:Results: Of 336 eligible responses, most participants were experienced attending physicians (70.93%). To diagnose azoosper-mia definitively, 81.7% requested two semen samples. Commonly ordered hormone tests included serum follicle-stimulating hormone (FSH) (97.0%), total testosterone (92.9%), and luteinizing hormone (86.9%). Genetic testing was requested by 66.6%, with karyotype analysis (86.2%) and Y chromosome microdeletions (88.3%) prevalent. Diagnostic testicular biopsy, distinguishing obstructive azoospermia (OA) from NOA, was not performed by 45.1%, while 34.6% did it selectively. Differ-entiation relied on physical examination (76.1%), serum hormone profiles (69.6%), and semen tests (68.1%). Expectations of finding sperm surgically were higher in men with normal FSH, larger testes, and a history of sperm in ejaculate. Conclusions:Conclusions: This expert survey, encompassing 367 participants from 49 countries, unveils congruence with recommended guidelines in NOA diagnosis. However, noteworthy disparities in practices suggest a need for evidence-based, international consensus guidelines to standardize NOA evaluation, addressing existing gaps in professional recommendations.

Published
2024
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20. Evaluating the precision of ultrasound versus computed tomography-guided measurement of cricoid cartilage diameter for double-lumen tube selection in thoracic surgery: A randomised comparative study

Author

Roshni M. Mathew, Shefali Gautam, Rajesh Raman, Anurag Rai, Vinod K. Srivastava, and Manish K. Singh

Subjects
airway management, computed tomography, cricoid cartilage, double-lumen tube, thoracic surgery, ultrasonography, Anesthesiology, RD78.3-87.3
Abstract

Background and Aims: Precise airway management is vital in thoracic surgeries to ensure patient safety and optimal outcomes. Choosing the correct double-lumen tube (DLT) size is challenging, as it typically relies on height, gender and subjective experience. This study investigates using ultrasonography (USG) and computed tomography (CT) to measure cricoid cartilage diameter for objective DLT sizing. Methods: In a randomised study, 120 adult patients undergoing elective thoracic surgery were randomised to three groups: Group A (DLT size determined by USG), Group B (DLT size determined by CT) and Group C (DLT size determined by conventional methods based on height and gender). The primary outcome variable was the appropriateness of DLT size. Secondary outcome variables were the degree of lung collapse and sore throat. Student’s t-test and ꭓ2 test were used to analyse continuous and dichotomous variables, respectively. Results: DLT sizing based on cricoid cartilage diameter improved the accuracy, with inappropriate sizes found in 25% in the conventional group, 5% in the USG group and 2.5% in the CT group (P < 0.05). Lung collapse was better in the USG (excellent in 92.5%) and CT (95%) groups compared to the conventional group (70%) (P < 0.05). Moderate sore throat was higher in the conventional group (37.5%) compared to the USG (5%) and CT groups (7.5%). Conclusion: The study demonstrates that USG- and CT-guided measurements of cricoid cartilage diameter are reliable and effective methods for determining DLT size in thoracic surgery compared to conventional methods.

Published
2024
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21. Insights from a 19-year field study: optimizing long-term nutrient supply strategies for enhanced crop productivity and nutritional security in rice–wheat systems

Author

Sunita K. Meena, Brahma S. Dwivedi, Mahesh C. Meena, Siba P. Datta, Vinod K. Singh, Rajendra P. Mishra, Debashish Chakraborty, Renu Singh, Abir Dey, Mohammad Hasanain, and Vijay Singh Meena

Subjects
Nutrient management, Rice–wheat systems, Integrated plant nutrient system, Crop productivity, Nutrient uptake, Climate resilience, Science (General), Q1-390
Abstract

Abstract What nutrient supply options can ensure maximum productivity and optimize the nutrient uptake of rice–wheat system (R-W system)? an experiment started in the year 1998 (19-year-old) to examine the impact of optimal nutrient supply (NS) strategies to maximize crop productivity and nutritional security in R-W system. To determine the best nutrient management strategies (BNMS), seven different NS methods were tested. These included (organic and mineral fertilizers), as well as combinations such as integrated plant nutrition system (IPNS), IPNS + B (berseem), and IPNS + C (cowpea), with the aim of enhancing the productivity and nutrient absorption of R-W system. Results showed that rice grain yield notably wide-ranging from 1.61 to 5.81 t ha−1 under different NS options and highest rice grain yield (mean of 19 years) was observed at IPNS + C (5.81 t ha−1), which was at par with IPNS (5.79 t ha−1), STCR (soil test crop response) (5.76 t ha−1) and IPNS + B (5.67 t ha−1) followed by 100% recommended dose fertilizer NPK (4.41 t ha−1), which equality with OF (organic farming) (4.04 t ha−1) and lowest was recorded in control plot (1.61 t ha−1). Wheat grain yield varied significantly from 1.43 to 5.86 t ha−1 under different NS options. The highest yield (mean of 19 years) was observed in treatments IPNS + B (5.86 t ha−1), IPNS (5.77 t ha−1), IPNS + C (5.48 t ha−1), and STCR (5.45 t ha−1), followed by OF at 4.49 t ha−1, NPK at 3.76 t ha−1, with the lowest in the control plot at 1.43 t ha−1. Additionally, total phosphorus and sulfur accumulation in rice (grain: 8.41 to 39.09 kg ha−1; straw: 6.02 to 23.54 kg ha−1) varied significantly across nutrient supply treatments. Overall, adoption of IPNS integration with legumes (IPNS + B and IPNS + C), can significantly improve productivity and nutrient accumulation in R-W systems. Incorporating legumes into farming practices is advised for sustained productivity and nutritional benefits.

Published
2024
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22. Sale Of Residential Property A 5 1, , Developed By Kendriya Utpaad Seema Shulk Karamcharee Grah Nirman Sahakree Samiti, In The Name Of Custom Colony, Village Akbarpur, Kolar Road, Huzur, Bhopal, In The Name Of Vinod K Nda

Subjects
Punjab National Bank, Banking industry, Banking industry, Business, international
Abstract

Tenders are invited for Sale of residential property a 5 1, , developed by kendriya utpaad seema shulk karamcharee grah nirman sahakree samiti, in the name of custom colony, village [...]

Published
2023

30. Click Chemistry in Nucleic Acids

Author

Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, Singh, Sumit K., Thakur, Vijay Kumar, Series Editor, Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, and Singh, Sumit K.

Published
2024
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39. Click Chemistry in Polymer Science

Author

Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, Singh, Sumit K., Thakur, Vijay Kumar, Series Editor, Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, and Singh, Sumit K.

Published
2024
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40. Click Chemistry in Lipid Modification

Author

Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, Singh, Sumit K., Thakur, Vijay Kumar, Series Editor, Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, and Singh, Sumit K.

Published
2024
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41. Click Chemistry in Dendrimer Synthesis

Author

Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, Singh, Sumit K., Thakur, Vijay Kumar, Series Editor, Tiwari, Vinod K., Jaiswal, Manoj K., Rajkhowa, Sanchayita, and Singh, Sumit K.

Published
2024
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