Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensive Care in India in 2018–2019: The Second Indian Intensive Care Case Mix and Practice Patterns Study

Abstract Background We aimed to study organizational aspects, case mix, and practices in Indian intensive care units (ICUs) from 2018 to 2019, following the Indian Intensive Care Case Mix and Practice Patterns Study (INDICAPS) of 2010–2011. Methods An observational, 4-day point prevalence study was performed between 2018 and 2019. ICU, patient characteristics, and interventions were recorded for 24 hours, and ICU outcomes till 30 days after the study day. Adherence to selected compliance measures was determined. Data were analyzed for 4,669 adult patients from 132 ICUs. Results On the study day, mean age, acute physiology and chronic health evaluation (APACHE II), and sequential organ failure assessment (SOFA) scores were 56.9 ± 17.41 years, 16.7 ± 9.8, and 4.4 ± 3.6, respectively. Moreover, 24% and 22.2% of patients received mechanical ventilation (MV) and vasopressors or inotropes (VIs), respectively. On the study days, 1,195 patients (25.6%) were infected and 1,368 patients (29.3%) had sepsis during their ICU stay. ICU mortality was 1,092 out of 4,669 (23.4%), including 737 deaths and 355 terminal discharges (TDs) from ICU. Compliance for process measures related to MV ranged between 62.7 and 85.3%, 11.2 and 47.4% for monitoring delirium, sedation, and analgesia, and 7.7 and 25.3% for inappropriate transfusion of blood products. Only 34.8% of ICUs routinely used capnography. Large hospitals with ≥500 beds, closed ICUs, the APACHE II and SOFA scores, medical admissions, the presence of cancer or cirrhosis of the liver, the presence of infection on the study day, and the need for MV or VIs were independent predictors of mortality. Conclusions Hospital size and closed ICUs are independently associated with worse outcomes. The proportion of TDs remains high. There is a scope for improvements in processes of care. Registered at clinicaltrials.gov (NCT03631927). How to cite this article Divatia JV, Mehta Y, Govil D, Zirpe K, Amin PR, Ramakrishnan N, et al. Intensive Care in India in 2018–2019: The Second Indian Intensive Care Case Mix and Practice Patterns Study. Indian J Crit Care Med 2021;25(10):1093–1107.
Diagnostic Value of Bilateral Petrosal Sinus Sampling in Children with Cushing Disease: A Multi-center Study

Objective: Although the sensitivity and specificity of bilateral inferior petrosal sinus sampling (BIPSS) were shown to be quite high in adult patients, pediatric studies are limited in number and have conflicting results, since BIPSS is much less commonly performed in children. The aim of this study was to assess the role of BIPSS in the detection and accuracy of lateralization of pituitary adenomas in pediatric patients with Cushing disease (CD) and its possible advantage over other diagnostic methods. Methods: This was a multicenter, nationwide, web-based study. The diagnostic value of BIPSS in 16 patients, aged between four and 16.5 years with a confirmed diagnosis of CD, was evaluated retrospectively. The sensitivity and specificity of BIPSS and magnetic resonance imaging (MRI) were calculated, and compared statistically. Results: Standard tests, except for morning cortisol level, were effective in proving the presence of Cushing syndrome. While MRI findings were consistent with microadenoma in eight cases (50%), CD presence and lateralization was successfully predicted in 14 of 16 patients using BIPSS. BIPSS compared with MRI examination was significantly more accurate, both in pre-stimulation and post-stimulation results (p=0.047 and p=0.041, respectively). BIPSS showed a significantly higher sensitivity (92.8%) than MRI in detecting the pituitary source of adrenocorticotropic hormone secretion. Conclusion: These results suggest that BIPSS is superior to MRI for diagnostic work-up to confirm the diagnosis of CD. Moreover, in line with previous studies, BIPSS was shown to provide better information about adenoma location, which is vital for possible surgical intervention.
Type VI Secretion System and Its Effectors PdpC, PdpD, and OpiA Contribute to <italic toggle='yes'>Francisella</italic> Virulence in <named-content content-type='genus-species'>Galleria mellonella</named-content> Larvae

Francisella tularensis causes the deadly zoonotic disease tularemia in humans and is able to infect a broad range of organisms including arthropods, which are thought to play a major role in Francisella transmission. However, while mammalian in vitro and in vivo infection models are widely used to investigate Francisella pathogenicity, a detailed characterization of the major Francisella virulence factor, a noncanonical type VI secretion system (T6SS), in an arthropod in vivo infection model is missing. Here, we use Galleria mellonella larvae to analyze the role of the Francisella T6SS and its corresponding effectors in F. tularensis subsp. novicida virulence. We report that G. mellonella larvae killing depends on the functional T6SS and infectious dose. In contrast to other mammalian in vivo infection models, even one of the T6SS effectors PdpC, PdpD, or OpiA is sufficient to kill G. mellonella larvae, while sheath recycling by ClpB is dispensable. We further demonstrate that treatment by polyethylene glycol (PEG) activates Francisella T6SS in liquid culture and that this is independent of the response regulator PmrA. PEG-activated IglC secretion is dependent on T6SS structural component PdpB but independent of putative effectors PdpC, PdpD, AnmK, OpiB1, OpiB2, and OpiB3. The results of larvae infection and secretion assay suggest that AnmK, a putative T6SS component with unknown function, interferes with OpiA-mediated toxicity but not with general T6SS activity. We establish that the easy-to-use G. mellonella larvae infection model provides new insights into the function of T6SS and pathogenesis of Francisella.
IMPACT OF INFLATION ON SPENDING HABITS OF MIDDLE-INCOME GROUPS: A STUDY IN INDIA

The rise in inflation affects different categories of people. From the point of view of the common man, inflation means increase in the price of goods and services on a day-to-day basis. People with fixed incomes, both in public or private sector organizations or self-employed, working in the unorganized sector are considered victims of rising inflation, as inflation affects households' consumption, expenditure and investment practices. This study includes correlation and regression analysis to find out the relationship as well as significant impact of inflation on spending habits of middle-income groups in India. The purpose of this study is to assess the relationship between inflation and consumer spending habits in India. The empirical findings of this study complement economic theories and evidence that inflation also increases the price of living goods, reducing the chances of obtaining commodity jobs. This situation directly affects a consumer's income and their spending habits.
Sarcomotion: IMM Used Across the Learning Spectrum

Frustration at trying to lecture to a large first-year health science student audience about skeletal muscle led to the development of a computer animation of the microscopic process of muscle contraction. The animation was used as a moving overhead projection in a lecture setting, and was played from various points before being stepped through frame by frame to highlight the different parts of the process. The trial and evaluation of the use of this animation in Semester 1, 1995 was well-received by students and staff. The second product of this work is an Interactive Multimedia (IMM) tutorial, called Sarco motion , which provides information and explanations of parts of the contraction process, plus background information relating to skeletal muscle contraction, calcium metabolism and energy turnover. The animation forms the user interface by which the students access the tutorial. Students explore the moving animation with the mouse to get basic descriptive information, and click to access more specific information on each individual topic. Navigation through the specific information is provided by a series of questions, based on actual experience of the range of questions typically asked of the lecturer by the students. The tutorial is designed to allow for access to a range of resources outside the scope of the tutorial itself. This is achieved by a link from the tutorial to a World-Wide Web home page. This leads to the concept of finger food multimedia, where a platter of other resources on the Web are served as finger food, from which the student can choose to use as little or as much as they wish. This paper describes the development approach and formative evaluation of the first prototypes of the Sarco motion program.
Accounting for noise when estimating Variance Explained

Constructing models of biological systems, e.g. in systems neuroscience, mostly aims at providing functional descriptions, not fundamental physical laws. It seems likely that any parametric model of signal processing in single neurons can be ruled out given a sufﬁcient amount of data. Rather than only testing the statistical validity of a particular mathematical formulation against data, e.g. by using a χ 2 -test, it is equally important to know how much of the signal, or variance, in the data is explained by the model. This is commonly measured by Variance Explained (VE). A fundamental problem of the traditional estimator for VE is its bias in the presence of measurement noise in the data: since the total variance in the data consists of the true underlying variance and that due to noise, the traditional estimator yields a systematic underestimation of the true VE of the model in the absence of noise (David & Gallant 2005, Sahani & Linden 2003). We derive an analytical expression for the dependence of VE on sampling noise and present a more accurate estimator of the true VE in the presence of noise. We tested it in a wide range of simulations ﬁtting various functions to simulated data with varying amounts of noise. The data were drawn from models that were identical to the one ﬁtted (true VE = 100% ) or different (true VE < 100% ). For our new estimator we ﬁnd that the root-mean-square error (RMSE, of the difference between the true VE in the absence of noise and the estimated VE in the presence of noise) is reduced by up to 80% in typical applications and never worse than the RMSE of the original, widely-used formula. We compare the new estimator with the traditional formula by testing the performance of the binocular energy model in explaining the responses of disparity-selective neurons in primate V1. Our comprehensive data set currently includes 51 neurons for each of which we measured responses to a) disparity in drifting gratings with frequencies covering most of the spatial frequency tuning curve and b) correlated and anticor-related random dot stereograms. Based on these data
Online Transaction Fraud Detection using Hidden Markov Model & Behavior Analysis

Card payment are mostly preferred by many for transactions instead of cash. Due to its convenience, it is the most accepted payment method for offline as well as online purchases, irrespective of region or country the purchase is made. Currently, cards are used for everyday activities, such as online shopping, bill pays, subscriptions, etc. Consequently, there are more chances of fraudulent transactions. Online transactions are the prime target as it does not require real card, only card details are enough and can be stored digitally. The current system detects the fraud transaction after the transaction is completed. Proposed system in this paper, uses Hidden Markov Model (HMM), which is one of the statistical stochastic models used to model randomly changing systems. Using Hidden Markov Model, a fraud transaction can be detected during the time of transaction itself and after 3 attempts of verification card can blocked at the same time. Behavior Analysis (BA) helps to understand the spending habits of cardholder. Hidden Markov Model helps to acquire high-level fraud analysis with a low false alarm ratio.
Monitoring of the Use of Veterinary Medicines Containing Antibiotics in Côte d'Ivoire in 2013

Copyright: © Konan BA (2020). This Article is distributed under the terms of Creative Commons Attribution 4.0 International License *Corresponding Author(s): Brou André Konan Doctor in Animal Physiology and Pharmacology, Senior Lecturer, Laboratory of Biology and Health, UPR-Nutrition and Pharmacology, UFR-Biosciences, University Félix HOUPHOUËT-BOIGNY, 22 BP 582 Abidjan 22, Côte d’Ivoire Email: akonanb@yahoo.fr & brou.konan@ufhb.edu. ci Journal of Veterinary Medicine and Animal Sciences
The relationship between the neutrophil-lymphocyte ratio and platelet- lymphocyte ratio and tumor characteristics in patients with breast cancer

DOI: 10.4328/ACAM.20518 Received: 2021-02-03 Accepted: 2021-03-12 Published Online: 2021-03-28 Printed: 2021-08-15 Ann Clin Anal Med 2021;12(Suppl 3): S274-277 Corresponding Author: Şeref Dokcu, Surgical oncology department, Ankara University Faculty of Medicine, Cebeci Research and Application Hospital, Balkiraz, Cebeci, No:6, 06620 Çankaya/Ankara,Turkey. E-mail: serefdokcu@hotmail.com P: +90 5334434333 Corresponding Author ORCID ID: https://orcid.org/0000-0003-1807-8108 Abstract Aim: Many studies nowadays increasingly enlighten the nature of relationship between cancer and inflammation. NLR and PLR are proinflammatory indicators that are related to many clinicopathological characteristics of many types of cancer. In this study, we aimed to find out the relationship between NLR and PLR values and tumor characteristics in patients with breast cancer that are operated with help of basic and inexpensive peripheral blood test results. Material and Methods: A database of 94 female patients who were operated in the Department of Surgical Oncology of the Medical School of Ankara University was studied. All blood sample tests, pathology reports, immunohistochemical staining results of the patients were retrospectively scanned. Patient demographics and pathological properties of tumor obtained from the database. The NLR and PLR values were taken from the peripheral blood cell count. Data were presented as average value±standart deviation(SD), and maximum-minimum values. Later data were analyzed. Results: NLR values were significantly different accordingly to T stage of tumor ( =11.452; p=0.022). On the other hand, the PLR value did not show a significant differentiation according to tumor size ( =5.865; p=0.209). It has been seen that this differentiation is between T1 and T2; T1 and T3 statistically. (U= 251.000 p=0.003; U=54.000, p=0.021). Discussion: The NLR value is significantly related to the tumor size. But further research is needed to see the clinical reflection and added value to the clinical practice of these results.
Concept analysis of loneliness in older adults: A hybrid model

Background: Loneliness is an ontological structure in human existence that can occur in all stages of life. The purpose of this qualitative study was to clarify the meaning and the nature of loneliness in Iranian older adults.Methods: Loneliness in older adults was examined in three phases: (1) the theoretical phase; (2) the fieldwork and (3) the analytical phase. The hybrid concept analysis method was performed to explore the data and synthesis the findings on three key issues including attributes, antecedents, and consequences. Finally, a working definition was synthesized.Results: The critical attributes of loneliness included a variety of topics including suffering, and feeling of worthlessness. Antecedents included distal and proximal factors. The consequences of loneliness in most instances were negative and disturbing. The final definition originated from the theoretical phase and fieldwork was as follows: ‘loneliness is an unpleasant, negative, annoying, hard, scary and painful personal experience that causes feeling of despair, uselessness, hopelessness, depression, anxiety and seeing the world in black’. Conclusion: The findings from this study introduce a new definition for loneliness that includes a combination of attributes, antecedents and consequences for the concept.
Functionalization of gold nanoparticles for biomedical and catalytic applications

The design and molecular engineering of multi-functional gold nanoparticles (AuNPs) is of considerable interest towards applications in nanomedicine, molecular recognition, sensing and catalysis in aqueous environments. This thesis has been devoted to a variety of functionnalizations, in particular with the copper(I)-catalyzed Alkyne Azide cycloaddition (CuAAC) using thecatalyst [Cu(I)(hexabenzyltren] Br for the introduction of polyethylene glycol,carborane, ferrocene, coumarin, cyclodextrin, drugs and fluorescent probes. The so called “clicked” ligands, 1,4 -bifunctional triazoles, that were formed in this way have been exensively used to stabilize AuNPs for biomedical and catalytic collaborative applications.
Pre-conceptional Maternal Vitamin B12 Supplementation Improves Offspring Neurodevelopment at 2 Years of Age: PRIYA Trial

Background: The first thousand days window does not include the pre-conceptional period. Maternal pre-conceptional health has a profound influence on early embryonic development (implantation, gastrulation, placentation etc). Nutrition provided by B-complex vitamins is important for fetal growth, especially neural development. We report effects of a maternal pre-conceptional vitamin B12 and multi micronutrient (MMN) supplementation on offspring neurodevelopmental performance. Methods: In the Pune Rural Intervention in Young Adolescents trial (PRIYA), adolescents (N = 557, 226 females) were provided with vitamin B12 (2 μg/day) with or without multiple micronutrients, or a placebo, from preconception until delivery. All groups received mandatory iron and folic acid. We used the Bayley's Scale of Infant Development (BSID-III) at 24–42 months of age to investigate effects on offspring neurodevelopment. Results: Participants had similar baseline B12 levels. The levels improved in the B12 supplemented groups during pre-conception and pregnancy (28 weeks gestation), and were reflected in higher cord blood holotranscobalamin (holo-TC) levels compared to the placebo group. Neurodevelopmental outcomes in the B12 alone group (n = 21) were better than the placebo (n = 27) in cognition (p = 0.044) and language (p = 0.020) domains (adjusted for maternal baseline B12 levels). There was no difference in neurodevelopmental outcomes between the B12 + MMN (n = 26) and placebo group. Cord blood Brain Derived Neurotrophic Factor (BDNF) levels were highest in the B12 alone group, though not significant. Conclusion: Pre-conceptional vitamin B12 supplementation improved maternal B12 status and offspring neurodevelopment at 2 years of age. The usefulness of cord BDNF as a marker of brain development needs further investigation. Our results highlight the importance of intervening during pre-conception.
A periodic homogenization problem with defects rare at infinity

<p style='text-indent:20px;'>We consider a homogenization problem for the diffusion equation <inline-formula><tex-math id="M1">\begin{document}$ -\operatorname{div}\left(a_{\varepsilon} \nabla u_{\varepsilon} \right) = f $\end{document}</tex-math></inline-formula> when the coefficient <inline-formula><tex-math id="M2">\begin{document}$ a_{\varepsilon} $\end{document}</tex-math></inline-formula> is a non-local perturbation of a periodic coefficient. The perturbation does not vanish but becomes rare at infinity in a sense made precise in the text. We prove the existence of a corrector, identify the homogenized limit and study the convergence rates of <inline-formula><tex-math id="M3">\begin{document}$ u_{\varepsilon} $\end{document}</tex-math></inline-formula> to its homogenized limit. </p>
xGQA: Cross-Lingual Visual Question Answering

Recent advances in multimodal vision and language modeling have predominantly focused on the English language, mostly due to the lack of multilingual multimodal datasets to steer modeling efforts. In this work, we address this gap and provide xGQA, a new multilingual evaluation benchmark for the visual question answering task. We extend the established English GQA dataset to 7 typologically diverse languages, enabling us to detect and explore crucial challenges in cross-lingual visual question answering. We further propose new adapter-based approaches to adapt multimodal transformer-based models to become multilingual, and—vice versa—multilingual models to become multimodal. Our proposed methods outperform current state-of-the-art multilingual multimodal models (e.g., M3P) in zero-shot cross-lingual settings, but the accuracy remains low across the board; a performance drop of around 38 accuracy points in target languages showcases the difficulty of zero-shot cross-lingual transfer for this task. Our results suggest that simple cross-lingual transfer of multimodal models yields latent multilingual multimodal misalignment, calling for more sophisticated methods for vision and multilingual language modeling.
AdaK-NER: An Adaptive Top-K Approach for Named Entity Recognition with Incomplete Annotations

State-of-the-art Named Entity Recognition (NER) models rely heavily on large amounts of fully annotated training data. However, accessible data are often incompletely annotated since the annotators usually lack comprehensive knowledge in the target domain. Normally the unannotated tokens are regarded as non-entities by default, while we underline that these tokens could either be non-entities or part of any entity. Here, we study NER modeling with incomplete annotated data where only a fraction of the named entities are labeled, and the unlabeled tokens are equivalently multi-labeled by every possible label. Taking multi-labeled tokens into account, the numerous possible paths can distract the training model from the gold path (ground truth label sequence), and thus hinders the learning ability. In this paper, we propose AdaK-NER, named the adaptive top-K approach, to help the model focus on a smaller feasible region where the gold path is more likely to be located. We demonstrate the superiority of our approach through extensive experiments on both English and Chinese datasets, averagely improving 2% in F-score on the CoNLL-2003 and over 10% on two Chinese datasets compared with the prior state-of-the-art works.
Cross Domain Robot Imitation with Invariant Representation

Animals are able to imitate each others' behavior, despite their difference in biomechanics. In contrast, imitating other similar robots is a much more challenging task in robotics. This problem is called cross domain imitation learning (CDIL). In this paper, we consider CDIL on a class of similar robots. We tackle this problem by introducing an imitation learning algorithm based on invariant representation. We propose to learn invariant state and action representations, which align the behavior of multiple robots so that CDIL becomes possible. Compared with previous invariant representation learning methods for similar purposes, our method does not require human-labeled pairwise data for training. Instead, we use cycle-consistency and domain confusion to align the representation and increase its robustness. We test the algorithm on multiple robots in the simulator and show that unseen new robot instances can be trained with existing expert demonstrations successfully. Qualitative results also demonstrate that the proposed method is able to learn similar representations for different robots with similar behaviors, which is essential for successful CDIL.