搜索结果：Indian pediatrics

We conducted this study to document the female participation in the administrative and academic affairs of the Indian Academy of Pediatrics (IAP). Of 45 IAP Presidents till date, 7 (15.6%) were women. Females comprised 6% (2/31), 8.8% (3/31), 5.4% (2/37), and 2.3% (1/44) of IAP executive board members in 1990, 1995, 2000, and 2005, respectively. Only once (out of 10), a woman was appointed as the Editor-in-Chief of Indian Pediatrics; of 4 Editor-in-chiefs of IJPP till date, none was a female. Of 181 heads of the department of Pediatrics at different medical colleges, 58 (32%) are women. Overall female authorship in articles published in Indian Pediatrics has increased from 23.1% (133/576) in 1990 to 43% (154/358) in 2005 (P < 0.001). We conclude that there is a definite increase in the female participation in academic matters of IAP; however, the gender gap is persisting in the administrative domain.

JUSTIFICATION: Persistence of intense wild poliovirus (WPV) transmission, particularly type 3 in northern India necessitated the Indian Academy of Pediatrics (IAP) to convene a National Consultative Meeting to review its earlier recommendations on polio eradication and improvement of routine immunization. PROCESS: More than thirty experts were invited and intense deliberations were held over two days to draw consensus statements on various issues related with polio eradication. OBJECTIVES: To review the ongoing strategy, identify the existing challenges, and suggest modifications to the current strategy for eradication of poliomyelitis in India. RECOMMENDATIONS: IAP reiterates its support to ongoing efforts on polio eradication but demand some flexibility in the strategy. The immediate challenges identified include persistent WPV type 1 transmission in Uttar Pradesh (UP) and Bihar, intense type 3 transmission also in UP and Bihar, and maintaining polio-free status of all other states. Circulating vaccine derived poliovirus (cVDPV), particularly type 2, was identified as a great future threat. Neglect of routine immunization (RI), poor efficacy of oral polio vaccine (OPV), operational issues, and inadequate uptake of OPV in the 2 endemic states are the main reasons of failure to interrupt transmission of WPV 1 and 3. However, for the first time in history the intensity of WPV 1 circulation is very low in western UP. IAP suggests that high-quality, uniform and consistent performance of supplementary immunization activities (SIAs) in all districts of western UP, particularly using mOPV1(monovalent OPV1) should be maintained to avoid reestablishment of circulation of type 1 poliovirus. A judicious mix of mOPV1 and mOPV3, given sequentially or even simultaneously (after validating the efficacies) will be necessary to address the upsurge of WPV3. Re-establishing routine immunization should be the foremost priority. IAP strongly recommends to Government of India (GOI) to take urgent measures to attain coverage of a minimum of 90% against all UIP antigens in all the states by the end of 2008. In view of the need to simultaneously raise immunity levels to protect against WPVs 1, 3 and cVDPV2, IPV may be given immediate consideration as an additional tool. IPV will be essential in the postWPVeradication phase; it can play a useful role even in the current WPV eradication phase. IAP urges the GOI to urgently sort out various issues associated with implementation of the proposal to use IPV. More transparency is needed on cases of vaccine associated paralytic poliomyelitis (VAPP). Further improvement in stool collection rates is also warranted to minimize the tally of compatible cases. IAP urges the social mobilization network to address the issues of waning interest and shifting focus and negative media coverage. Alternate tactics like reduced numbers of SIAs applied in the low transmission season, along with IPVDTP combination vaccine in RI can also be considered. IAP believes it will be risky to stop vaccination against poliomyelitis in postWPV eradication phase. The best option is to gradually introduce IPV starting now, so that a switch to IPV following high-performance national immunization days (NIDs) can be made to ensure sustained high immunity against all polioviruses, wild and vaccine derived. IAP requests the global polio eradication initiative (GPEI) to continue relevant research to inform on various aspects related to polio eradication, defined as zero incidence of any poliovirus infection. IAP also urges GOI to take immediate measures for improvement of environmental sanitation.

暂无摘要（点击查看原文获取完整内容）

Fifty years ago, American Indian and Alaska Native children faced an overwhelming burden of disease, especially infectious diseases such as pneumonia, meningitis, tuberculosis, hepatitis A and B, and gastrointestinal disease. Death rates of American Indian/Alaska Native infants between 1 month and 1 year were much higher than in the US population as a whole, largely because of these infectious diseases. The health care of American Indian/Alaska Native patients was transferred to the Department of Health, Education, and Welfare in 1955 and placed under the administration of an agency soon to be known as the Indian Health Service. The few early pediatricians in the Indian Health Service recognized the severity of the challenges facing American Indian/Alaska Native children and asked for help. The American Academy of Pediatrics responded by creating the Committee on Indian Health in 1965. In 1986 the Committee on Native American Child Health replaced the Committee on Indian Health. Through the involved activity of these committees, the American Academy of Pediatrics participated in and influenced Indian Health Service policies and services and, combined with improved transportation, sanitation, and access to vaccines and direct services, led to vast improvements in the health of American Indian/Alaska Native children. In 1965, American Indian/Alaska Native postneonatal mortality was more than 3 times that of the general population of the United States. It is still more than twice as high as in other races but has decreased 89% since 1965. Infectious diseases, which caused almost one fourth of all American Indian/Alaska Native child deaths in 1965, now cause <1%. The Indian Health Service and tribal health programs, authorized by the Indian Self-Determination and Education Assistance Act of 1976 (Pub L. 93-638), continue to seek American Academy of Pediatrics review and assistance through the Committee on Native American Child Health to find and implement interventions for emerging child health problems related to pervasive poverty of many American Indian/Alaska Native communities. Acute infectious diseases that once were responsible for excess morbidity and mortality now are replaced by excess rates resulting from harmful behaviors, substance use, obesity, and injuries (unintentional and intentional). Through strong working partnerships such as that of the American Academy of Pediatrics and the Indian Health Service, progress hopefully will occur to address this "new morbidity." In this article we document the history of the Indian Health Service and the American Academy of Pediatrics committees that have worked with it and present certain statistics related to American Indian/Alaska Native child health that show the severity of the health-status disparities challenging American Indian/Alaska Native children and youth.

In this paper we present our work on a case study between Statistical Machien Transaltion (SMT) and Rule-Based Machine Translation (RBMT) systems on English-Indian langugae and Indian to Indian langugae perspective. Main objective of our study is to make a five way performance compariosn; such as, a) SMT and RBMT b) SMT on English-Indian langugae c) RBMT on English-Indian langugae d) SMT on Indian to Indian langugae perspective e) RBMT on Indian to Indian langugae perspective. Through a detailed analysis we describe the Rule Based and the Statistical Machine Translation system developments and its evaluations. Through a detailed error analysis, we point out the relative strengths and weaknesses of both systems. The observations based on our study are: a) SMT systems outperforms RBMT b) In the case of SMT, English to Indian language MT systmes performs better than Indian to English langugae MT systems c) In the case of RBMT, English to Indian langugae MT systems perofrms better than Indian to Englsih Language MT systems d) SMT systems performs better for Indian to Indian language MT systems compared to RBMT. Effectively, we shall see that even with a small amount of training corpus

India is a founder-member country to participate in the construction of the international multipurpose accelerator facility called the Facility for Antiproton and Ion Research (FAIR) at Darmstadt, Germany. Bose Institute, Kolkata, has been designated as the Indian shareholder of the FAIR GmbH and the nodal Indian Institution for co-ordinating Indian participation in the FAIR programme. Indian participation in FAIR is twofold. Firstly, the advancement of knowledge in nuclear astrophysics and reaction, high-energy nuclear physics, atomic \&amp; plasma physics and application through the participation of Indian researchers, engineers and students in various experiments planned at FAIR. In addition to this, India is also contributing high-tech accelerator equipment as in-kind contribution to FAIR. Our active involvement include the designing, manufacturing and supply of in-kind accelerator items e.g. power converters, vacuum chamber, beam catchers, IT diagnostic cables among them and coordinating the participation of Indian scientists in the FAIR experiments including detector development, physics simulation, experimental data analysis. Indian researchers have been participating in the

This paper presents a novel approach to compute food composition data for Indian recipes using a knowledge graph for Indian food (FKG[.]in) and LLMs. The primary focus is to provide a broad overview of an automated food composition analysis workflow and describe its core functionalities: nutrition data aggregation, food composition analysis, and LLM-augmented information resolution. This workflow aims to complement FKG[.]in and iteratively supplement food composition data from verified knowledge bases. Additionally, this paper highlights the challenges of representing Indian food and accessing food composition data digitally. It also reviews three key sources of food composition data: the Indian Food Composition Tables, the Indian Nutrient Databank, and the Nutritionix API. Furthermore, it briefly outlines how users can interact with the workflow to obtain diet-based health recommendations and detailed food composition information for numerous recipes. We then explore the complex challenges of analyzing Indian recipe information across dimensions such as structure, multilingualism, and uncertainty as well as present our ongoing work on LLM-based solutions to address these issues. T

Object detection is a well-known problem in computer vision. Despite this, its usage and pervasiveness in the traditional Indian food dishes has been limited. Particularly, recognizing Indian food dishes present in a single photo is challenging due to three reasons: 1. Lack of annotated Indian food datasets 2. Non-distinct boundaries between the dishes 3. High intra-class variation. We solve these issues by providing a comprehensively labelled Indian food dataset- IndianFood10, which contains 10 food classes that appear frequently in a staple Indian meal and using transfer learning with YOLOv4 object detector model. Our model is able to achieve an overall mAP score of 91.8% and f1-score of 0.90 for our 10 class dataset. We also provide an extension of our 10 class dataset- IndianFood20, which contains 10 more traditional Indian food classes.

Although the star formation process has been studied for decades, many important aspects of the physics involved remain unsolved. Recent advancement of instrumentation in the infrared, far-infrared and sub-millimetre wavelength regimes have contributed to a significantly improved understanding of processes in the interstellar medium (ISM) leading to star formation. The future of research on the ISM and star formation looks exciting with instruments like the JWST, ALMA, etc., already contributing to the topic by gathering high-resolution high-sensitivity data and with several larger ground- and space-bound facilities either being planned or constructed. India has a sizable number of astronomers engaged in research on topics related to the ISM and star formation. In this white paper invited by the Astronomical Society of India to prepare a vision document for Indian astronomy, we review the Indian contributions to the global understanding of the star formation process and suggest areas that require focused efforts both in creating observing facilities and in theoretical front in India, in order to improve the impact of our research in the coming decades.

In this paper, we introduce Neural Information Retrieval resources for 11 widely spoken Indian Languages (Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, and Telugu) from two major Indian language families (Indo-Aryan and Dravidian). These resources include (a) INDIC-MARCO, a multilingual version of the MSMARCO dataset in 11 Indian Languages created using Machine Translation, and (b) Indic-ColBERT, a collection of 11 distinct Monolingual Neural Information Retrieval models, each trained on one of the 11 languages in the INDIC-MARCO dataset. To the best of our knowledge, IndicIRSuite is the first attempt at building large-scale Neural Information Retrieval resources for a large number of Indian languages, and we hope that it will help accelerate research in Neural IR for Indian Languages. Experiments demonstrate that Indic-ColBERT achieves 47.47% improvement in the MRR@10 score averaged over the INDIC-MARCO baselines for all 11 Indian languages except Oriya, 12.26% improvement in the NDCG@10 score averaged over the MIRACL Bengali and Hindi Language baselines, and 20% improvement in the MRR@100 Score over the Mr.Tydi Bengali Language baseline.

As global interest in diverse culinary experiences grows, food image models are essential for improving food-related applications by enabling accurate food recognition, recipe suggestions, dietary tracking, and automated meal planning. Despite the abundance of food datasets, a noticeable gap remains in capturing the nuances of Indian cuisine due to its vast regional diversity, complex preparations, and the lack of comprehensive labeled datasets that cover its full breadth. Through this exploration, we uncover Khana, a new benchmark dataset for food image classification, segmentation, and retrieval of dishes from Indian cuisine. Khana fills the gap by establishing a taxonomy of Indian cuisine and offering around 131K images in the dataset spread across 80 labels, each with a resolution of 500x500 pixels. This paper describes the dataset creation process and evaluates state-of-the-art models on classification, segmentation, and retrieval as baselines. Khana bridges the gap between research and development by providing a comprehensive and challenging benchmark for researchers while also serving as a valuable resource for developers creating real-world applications that leverage the ri

Large language models (LLMs) and vision-augmented LLMs (VLMs) have significantly advanced medical informatics, diagnostics, and decision support. However, these models exhibit systematic biases, particularly age bias, compromising their reliability and equity. This is evident in their poorer performance on pediatric-focused text and visual question-answering tasks. This bias reflects a broader imbalance in medical research, where pediatric studies receive less funding and representation despite the significant disease burden in children. To address these issues, a new comprehensive multi-modal pediatric question-answering benchmark, PediatricsMQA, has been introduced. It consists of 3,417 text-based multiple-choice questions (MCQs) covering 131 pediatric topics across seven developmental stages (prenatal to adolescent) and 2,067 vision-based MCQs using 634 pediatric images from 67 imaging modalities and 256 anatomical regions. The dataset was developed using a hybrid manual-automatic pipeline, incorporating peer-reviewed pediatric literature, validated question banks, existing benchmarks, and existing QA resources. Evaluating state-of-the-art open models, we find dramatic performan

Despite the extensive amount of scholarly work done on Indian mathematics in the last 200 years, the conditions under which it originated and evolved is still not clear. Often, one reads the ancient texts with the present concepts and methods in mind. The fact of absence of script over a long stretch of Indian history in ancient times also gets overlooked in such readings. The purpose of this article is to explore the journey of mathematics by examining what the ancient texts tell us about the nature of mathematics in their times. What one finds from the investigation of arithmetic, geometry and algebra is that while it was concrete and context bound, rooted in solving practical problems in ancient times, Indian mathematics transitioned to context free, abstract stage with the advent of algebra supported by writing.

This study examines the impact of the foreign exchange rate, i.e., US Dollar to Indian Rupee (USD/INR) on the Indian Stock Market Index (Nifty 50) during the demonetization of high denomination Indian currencies. A daily rate of return of Foreign exchange rate (USD/INR) and the Indian Stock Market Index (Nifty 50) were considered for the study. The Dummy variable was used to measure the effect of demonetization during Nov/Dec 2016. The period of study was restricted to 243 days from 1st April 2016 to 31st March 2017. The study reveals that there was an upward trend observed in the Indian Stock Market and the Indian currency was strengthened with the decrease in the Foreign exchange rate (USD/INR).

In this paper, we present a 170.83 hour Indian English spontaneous speech dataset. Lack of Indian English speech data is one of the major hindrances in developing robust speech systems which are adapted to the Indian speech style. Moreover this scarcity is even more for spontaneous speech. This corpus is crowd sourced over varied Indian nativities, genders and age groups. Traditional spontaneous speech collection strategies involve capturing of speech during interviewing or conversations. In this study, we use images as stimuli to induce spontaneity in speech. Transcripts for 23 hours is generated and validated which can serve as a spontaneous speech ASR benchmark. Quality of the corpus is validated with voice activity detection based segmentation, gender verification and image semantic correlation. Which determines a relationship between image stimulus and recorded speech using caption keywords derived from Image2Text model and high occurring words derived from whisper ASR generated transcripts.