51 research outputs found

    Enlarging the Domain of Attraction of Local Dynamic Mode Decomposition with Control Technique: Application to Hydraulic Fracturing

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    Local Dynamic Mode Decomposition with control (LDMDc) technique combines the concept of unsupervised learning and DMDc technique to extract the relevant local dynamics associated with highly nonlinear processes to build temporally local reduced-order models (ROMs). But the limited domain of attraction (DOA) of LDMDc hinders its widespread use in prediction. To systematically enlarge the DOA of the LDMDc technique, we utilize both the states of the system and the applied inputs from the data generated using multiple ‘training’ inputs. We implement a clustering strategy to divide the data into clusters, use DMDc to build multiple local ROMs, and implement the k-nearest neighbors technique to make a selection amongst the set of ROMs during prediction. The proposed algorithm is applied to hydraulic fracturing to demonstrate the enlarged DOA of the LDMDc technique

    A Case Report on Viral Meningoencephalitis with Radiculoneuropathy

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    Meningoencephalitis is an inflammation of brain and its surrounding membranes. It can be caused by bacteria, viruses, fungi, protozoa and by various other etiology. Radiculoneuropathy, also commonly referred to as pinched nerve, refers to a set of conditions in which one or more nerves are affected. The classic triad of fever, stiff neck and altered sensorium are seen in <50% of all patients with meningitis. Clinical presentation of viral encephalitis includes a prodrome of fever, headache, myalgia, and mild respiratory infection. Altered mentation, focal neurological deficits and seizures usually follow. Patient was brought to emergency department of hospital. He provided with empirical anti-biotic therapy and supportive care. Laboratory investigation like CSF analysis, liver function test, renal function test. Blood test like complete blood picture, dengue Ag. Microbiological test was also carried out. Radiological imaging like MRI of Brain, MRI of spine, Chest X-Ray. Upon clinical diagnosis patient was provided with antibiotic, antiviral and supportive care. Patient was also provided with mechanical ventilator. He was treated for 14 days. Keywords: meningoencephalitis, CSF analysis, classical triad

    Hybrid Modeling Approaches Integrating Physics-Based Models with Machine Learning for Predictive Control of Biological and Chemical Processes

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    Recently, there has been growing interest in data-based modeling as the amount of data available has increased tremendously. One such method is Dynamic Mode Decomposition with Control technique, which builds temporally local linear models using data. But its limited domain of applicability (DA) hinders its use for prediction purposes. To overcome this challenge, we proposed an algorithm that utilizes multiple "local" training datasets, and it was applied successfully to hydraulic fracturing. Although data-based modeling offers simplicity and ease of construction, it lacks robustness and parametric interpretability, unlike first-principles modeling. To balance the advantages and disadvantages of data-based models and first-principles models, hybrid modeling was proposed using artificial neural networks (ANNs). Since then, Machine Learning (ML) has advanced where deep neural networks (DNNs) with more than three layers can be trained to approximate any function accurately. In this work, we proposed a deep hybrid modeling (DHM) framework that integrates first-principles with DNNs and successfully applied it to two complex processes, i.e., hydraulic fracturing and full-scale fermentation reactor. Similarly, Universal Differential Equations (UDEs) was proposed in ML where DNNs are represented as ODEs and solved using ODE solvers. We utilized UDEs to successfully build a DHM using simulation and experimental data for batch production of ϐ-carotene. One limitation of DHM is that its DA is affected by the DNN within it, and its accuracy is high within its DA. Therefore, it is important to consider its DA when designing a model-based controller. To this end, we proposed a Control Lyapunov-Barrier Function (CLBF)-MPC to stabilize and ensure that the closed-loop system stays within DA of DHM. Theoretical guarantees were provided for the CLBF-MPC controller, and it was successfully implemented on a CSTR. The idea of integrating physics with ML can be extended to Reinforcement Learning (RL). In case when model-based controller design is not possible, we proposed a model-free Deep RL (DRL) controller that utilizes prior knowledge in its reward function to quicken the learning process. This DRL controller was successfully applied to hydraulic fracturing wherein Nolte’s law was included in the reward function for fast convergence

    Biological network analysis with CentiScaPe: centralities and experimental dataset integration

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    The growing dimension and complexity of the available experimental data generating biological networks have increased the need for tools that help in categorizing nodes by their topological relevance. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes used for the identification of the most important nodes in a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be integrated with data set from lab experiments, like expression or phosphorylation levels for each protein represented in the network. Our app opens new perspectives in the analysis of biological networks, since the integration of topological analysis with lab experimental data enhance the predictive power of the bioinformatics analysis

    Development and Use of a Survey Tool to Prioritize and Catalyze Change Surrounding Faculty Wellness in a Department of Pediatrics

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    Introduction: Physician wellness is an important factor in the delivery of safe, effective and humanistic patient care. There is compelling data describing the widespread prevalence of physician burnout and its subsequent adverse impact on patient care, healthcare costs, and relationships. Initiatives to improve wellness are necessary to maintain the healthcare work force as well as to ensure high-quality care. This project investigated faculty physicians’ attitudes and priorities regarding physician wellness within the department of Pediatrics at a single-center academic institution. Methods: A survey was created and distributed via e-mail to all faculty physicians employed within the Department of Pediatrics in 2019. Participants were asked to rate their agreement with statements regarding workplace wellness and to prioritize the potential allocation of resources designed to improve their satisfaction and wellness at work. Data were analyzed using Excel™ for quantitative and descriptive statistics. Results: 87 (74%) faculty members responded to the survey, with respondents representing all faculty tracks and ranks, male and female gender identities, and a wide range of years of employment. Sixty-eight percent of physicians (n=59) identified physician wellness as a problem. Faculty overwhelmingly identified “time,” “EMR” (electronic medical record) and “overworked” as the greatest impediments to workplace wellness. Thirty-nine percent (n=34) wrote “colleagues” to describe the single most positive contributing factor to their workplace wellness; and 72% (n=63) of docs indicated that resources should go to improve efficiency of practice. There was a correlation with feeling respected in the workplace and having the resources needed (R=0.28, p \u3c 0.001), as well as feeling recognized by leaders (R=0.38, p \u3c 0.001). Weak correlation was also identified between perceptions of wellness as a priority in the department and agreement with feeling respected (R=0.1, p \u3c 0.001). Conclusion: This study reveals the priorities for allocation of resources that best support Pediatric faculty wellness. Overall, the majority of respondents (72%) strongly preferred interventions that improve efficiency of practice over those that improve the culture of wellness or personal resilience. The emphasis on expanding clinical resources available to faculty members offers important insight into effective practice change for academic institutions. While improving personal resilience has become a hallmark of ‘wellness’ in the medical field, this data suggests that improving workplace efficiency is more representative of physician needs and priorities

    Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015)

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    Burden of non-communicable diseases among adolescents aged 10–24 years in the EU, 1990–2019: a systematic analysis of the Global Burden of Diseases Study 2019

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    Background Disability and mortality burden of non-communicable diseases (NCDs) have risen worldwide; however, the NCD burden among adolescents remains poorly described in the EU. Methods Estimates were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Causes of NCDs were analysed at three different levels of the GBD 2019 hierarchy, for which mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) were extracted. Estimates, with the 95% uncertainty intervals (UI), were retrieved for EU Member States from 1990 to 2019, three age subgroups (10–14 years, 15–19 years, and 20–24 years), and by sex. Spearman's correlation was conducted between DALY rates for NCDs and the Socio-demographic Index (SDI) of each EU Member State. Findings In 2019, NCDs accounted for 86·4% (95% uncertainty interval 83·5–88·8) of all YLDs and 38·8% (37·4–39·8) of total deaths in adolescents aged 10–24 years. For NCDs in this age group, neoplasms were the leading causes of both mortality (4·01 [95% uncertainty interval 3·62–4·25] per 100 000 population) and YLLs (281·78 [254·25–298·92] per 100 000 population), whereas mental disorders were the leading cause for YLDs (2039·36 [1432·56–2773·47] per 100 000 population) and DALYs (2040·59 [1433·96–2774·62] per 100 000 population) in all EU Member States, and in all studied age groups. In 2019, among adolescents aged 10–24 years, males had a higher mortality rate per 100 000 population due to NCDs than females (11·66 [11·04–12·28] vs 7·89 [7·53–8·23]), whereas females presented a higher DALY rate per 100 000 population due to NCDs (8003·25 [5812·78–10 701·59] vs 6083·91 [4576·63–7857·92]). From 1990 to 2019, mortality rate due to NCDs in adolescents aged 10–24 years substantially decreased (–40·41% [–43·00 to –37·61), and also the YLL rate considerably decreased (–40·56% [–43·16 to –37·74]), except for mental disorders (which increased by 32·18% [1·67 to 66·49]), whereas the YLD rate increased slightly (1·44% [0·09 to 2·79]). Positive correlations were observed between DALY rates and SDIs for substance use disorders (rs=0·58, p=0·0012) and skin and subcutaneous diseases (rs=0·45, p=0·017), whereas negative correlations were found between DALY rates and SDIs for cardiovascular diseases (rs=–0·46, p=0·015), neoplasms (rs=–0·57, p=0·0015), and sense organ diseases (rs=–0·61, p=0·0005)

    The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

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    Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

    A Case Report on Iactrogenic Cushing Syndrome with Scabies and Oral Candidiasis

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    Cushing syndrome is a condition characterized by high blood levels of cortisol or other exogenous compounds of glucocorticoids. This can be iatrogenic or endogenous cortisol secretion, due to the either an adrenal tumor or hyper secretion of adrenotropic hormone by the pituitary gland. Due immunosuppression patient are prone to more infectious diseases. Here the patient is diagnoses with oral candidiasis and scabies. Clinical investigation was carried out and laboratory investigations like Cortisol level in morning and evening, complete blood picture. He was provided with treatment of hydrocortisone, anti-fungal agents, anti-parasitic agents and skin moisturizer. Keywords: Iactrogenic Cushing syndrome, Candidiasis, Scabies, Cortisol, Corticosteroid