Search results for: data driven diagnosis

Authors: M. Mikušová

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The main aim of this paper is to present a clear and comprehensive picture of the process of a crisis in the organization which will help to better understand its possible developments. For a description of the sequence of individual steps and an indication of their causation and possible variants of the developments, a detailed flow diagram with verbal comment is applied. For simplicity, the process of the crisis is observed in four basic phases called: symptoms of the crisis, diagnosis, action and prevention. The model highlights the complexity of the phenomenon of the crisis and that the various phases of the crisis are interweaving.

Keywords: crisis, management, model, organization

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Authors: Dian Ariyawati, Romi Sukoco, Sinung Agung Joko

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Background: Postural Orthostatic Tachycardia Syndrome (POTS) is a form of orthostatic intolerance caused by autonomic dysfunction. POTS predominantly occurs in young women. Regular exercise has proven to improve the organ system functions, including autonomous systems. The aim of this research was to determine the correlation between exercise frequency and POTS in young women. Method: 510 young women (16-23 years of age) were screened. They were obtained by interview and physical examination. The diagnosis of POTS was performed with Active Stand Test (AST) and heart rate measurement using a pulsemeter. There were 29 young women who suffered from POTS. The exercise frequency was obtained by interview. Data was statistically analyzed using Spearman Correlation test. Result: The subjects’, who tested positive for POTS didn’t perform regular exercise. The Spearman correlation test showed there was a moderate negative correlation between exercise frequency and POTS in young women (r = -0.487, p < 0.00). Conclusion: There is a moderate reverse correlation between exercise frequency and POTS in young women. Further studies are suggested to develop an exercise program for young who suffered from POTS.

Keywords: POTS, autonomic dysfunction, exercise frequency, young woman

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Authors: Marzia Bilkiss, Muhammad J. A. Shiddiky, Mostafa K. Masud, Prabhakaran Sambasivam, Ido Bar, Jeremy Brownlie, Rebecca Ford

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A greater achievement in the Integrated Disease Management (IDM) to prevent the loss would result from early diagnosis and quantitation of the causal pathogen species for accurate and timely disease control. This could significantly reduce costs to the growers and reduce any flow on impacts to the environment from excessive chemical spraying. Necrotrophic fungal disease botrytis grey mould, caused by Botrytis cinerea and Botrytis fabae, significantly reduce temperate legume yield and grain quality during favourable environmental condition in Australia and worldwide. Several immunogenic and molecular probe-type protocols have been developed for their diagnosis, but these have varying levels of species-specificity, sensitivity, and consequent usefulness within the paddock. To substantially improve speed, accuracy, and sensitivity, advanced nanoparticle-based biosensor approaches have been developed. For this, two sets of primers were designed for both Botrytis cinerea and Botrytis fabae which have shown the species specificity with initial sensitivity of two genomic copies/µl in pure fungal backgrounds using multiplexed quantitative PCR. During further validation, quantitative PCR detected 100 spores on artificially infected legume leaves. Simultaneously an electro-catalytic assay was developed for both target fungal DNA using functionalised magnetic nanoparticles. This was extremely sensitive, able to detect a single spore within a raw total plant nucleic acid extract background. We believe that the translation of this technology to the field will enable quantitative assessment of pathogen load for future accurate decision support of informed botrytis grey mould management.

Keywords: biosensor, botrytis grey mould, sensitive, species specific

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Authors: Angelis P. Barlampas

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Introduction: The term phantom lung mass describes the ovoid collection of fluid within the interlobular fissure, which initially creates the impression of a mass. The problem of correct differential diagnosis is great, especially in plain radiography. A case is presented with three nodular pulmonary foci, the shape, location, and density of which, as well as the presence of chronic loculated pleural effusions, suggest the presence of multiple phantom tumors of the lung. Purpose: The aim of this paper is to draw the attention of non-experienced and non-specialized physicians to the existence of benign findings that mimic pathological conditions and vice versa. The careful study of a radiological examination and the comparison with previous exams or further control protect against quick wrong conclusions. Methods: A hospitalized patient underwent a non-contrast CT scan of the chest as part of the general control of her situation. Results: Computed tomography revealed pleural effusions, some of them loculated, increased cardiothoracic index, as well as the presence of three nodular foci, one in the left lung and two in the right with a maximum density of up to 18 Hounsfield units and a mean diameter of approximately five centimeters. Two of them are located in the characteristical anatomical position of the major interlobular fissure. The third one is located in the area of the right lower lobe’s posterior basal part, and it presents the same characteristics as the previous ones and is likely to be a loculated fluid collection, within an auxiliary interlobular fissure or a cyst, in the context of the patient's more general pleural entrapments and loculations. The differential diagnosis of nodular foci based on their imaging characteristics includes the following: a) rare metastatic foci with low density (liposarcoma, mucous tumors of the digestive or genital system, necrotic metastatic foci, metastatic renal cancer, etc.), b) necrotic multiple primary lung tumor locations (squamous epithelial cancer, etc. ), c) hamartomas of the lung, d) fibrotic tumors of the interlobular fissures, e) lipoid pneumonia, f) fluid concentrations within the interlobular fissures, g) lipoma of the lung, h) myelolipomas of the lung. Conclusions: The collection of fluid within the interlobular fissure of the lung can give the false impression of a lung mass, particularly on plain chest radiography. In the case of computed tomography, the ability to measure the density of a lesion, combined with the provided high anatomical details of the location and characteristics of the lesion, can lead relatively easily to the correct diagnosis. In cases of doubt or image artifacts, comparison with previous or subsequent examinations can resolve any disagreements, while in rare cases, intravenous contrast may be necessary.

Keywords: phantom mass, chest CT, pleural effusion, cancer

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Authors: Jongsoo Jurng

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The drive to expand renewable energies is often in direct conflict with sustainable development goals. Thus, it is important that energy policies account for potential trade-offs. We assess the interlinkages between energy, food, water, and land, for two case studies, Suwon and Seoul. We apply a range of assessment methods and study their usefulness as tools to identify trade-offs and to compare the sustainability performance. We calculate cross-sectoral footprints, self-sufficiency ratios and perform a simplified Energy-Water-Food nexus analysis. We use the latter for assessing scenarios to increase energy and food self-sufficiency in Suwon, while we use ecosystem service (ESS) accounting for Seoul. For Suwon, we find that constraints on the energy, food and water sectors urgently call for integrated approaches to energy policy; for Seoul, the further expansion of renewables comes at the expense of cultural and supporting ESS, which could outweigh gains from increased energy exports. We recommend a general upgrade to indicators and visualization methods that look beyond averages and a fostering of infrastructure for data on sustainable development based on harmonized international protocols. We warn against rankings of countries or regions based on benchmarks that are neither theory-driven nor location-specific.

Keywords: ESS, renewable energy, energy-water-food nexus, assessment

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Authors: SHWETA SRIKUMAR

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Winter stratospheric dynamics is a highly variable and spectacular field of research in middle atmosphere. It is well believed that the interaction of energetic planetary waves with mean flow causes the temperature to increase in the stratosphere and associated circulation reversal. This wave driven sudden disturbances in the polar stratosphere is defined as Sudden Stratospheric Warming. The main objective of the present work is to investigate the mid-winter major stratospheric warming events on equatorial dynamics over Peninsular India. To explore the effect of mid-winter stratospheric warming on Indian region (60oE -100oE), we have selected the winters 2003/04, 2005/06, 2008/09, 2012/13 and 2018/19. This study utilized the data from ERA-Interim Reanalysis, Outgoing Longwave Radiation (OLR) from NOAA and TRMM satellite data from NASA mission. It is observed that a sudden drop in OLR (averaged over Indian Region) occurs during the course of warming for the winters 2005/06, 2008/09 and 2018/19. But in winters 2003/04 and 2012/13, drop in OLR happens prior to the onset of major warming. Significant amplitude of planetary wave activity is observed in equatorial lower stratosphere which indicates the propagation of extra-tropical planetary waves from high latitude to equator. During the course of warming, a strong downward propagation of EP flux convergence is observed from polar to equator region. The polar westward wind reaches upto 20oN and the weak eastward wind dominates the equator during the winters 2003/04, 2005/06 and 2018/19. But in 2012/13 winter, polar westward wind reaches upto equator. The equatorial wind at 2008/09 is dominated by strong westward wind. Further detailed results will be presented in the conference.

Keywords: Equatorial dynamics, Outgoing Longwave Radiation, Sudden Stratospheric Warming, Planetary Waves

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Authors: Asmae Chraibi, Rachid Lghoul, Nabil Rhiati

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In the era of Industry 4.0, enterprises are increasingly employing digital technologies in order to improve their product development processes. This research focuses on the strategic deployment of Product Lifecycle Management (PLM) solutions during production as a key tracker of traceability and digital transformation activities. The study explores the integration of PLM within a larger organizational framework, examining its impact on product lifecycle efficiency, corporation, and innovation. Through a comprehensive analysis of a real case study from the automotive industry, this project evaluates the critical success factors and challenges associated with implementing PLM solutions for digital transformation. Moreover, it explores the synergic relationship between PLM and emerging technologies such as 3D experience and SOLIDWORKS, elucidating their combined potential in optimizing production workflows and enabling data-driven decision-making. The study's findings provide global approaches for firms looking to embark on a digital transformation journey by implementing PLM technologies. This research contributes to a better understanding of how PLM can be effectively used to foster innovation and competitiveness in the changing landscape of modern industry by shining light on best practices, critical considerations, and potential obstacles.

Keywords: product lifecyle management (PLM), industry 4.0, traceability, digital transformation, solution, innovation, 3D experience, SOLIDWORKS

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Authors: Aline Giardin, Ana Fontoura, Thomas Anderson

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Transsexuality is a condition that requires the work of professionals from various fields for diagnosis and treatment. The correct diagnosis is very important because the surgery is irreversible. Diagnostic elements are essentially clinical and an observation period of two years prior to surgery is recommended. In this review article, we discuss the importance of psychiatric nursing for the care of transgender patients, as well as their mental health. Transsexuality is a phenomenon that contrasts our common understandings of sexuality, but it is not a sexual issue. Also called gender dysphoria is a mismatch between the anatomical sex of an individual and their gender identity. In relation to mental health, among transsexuals, we find variations ranging from psychoses to total normality. As the etiology is still controversial, there is no biological marker and only the clinical criteria can be used. Portaria nº 2803, of November 19, 2013, Brazil, regulates the surgical reassignment of sex by the SUS and the nurse started to work also in operational groups (transsexuals who wish to perform surgery and other procedures of reassignment of sex). Health and education, establishes links and guides the care that female and male transsexual patients will have to have before and after surgery. It is also important to say that the work of health education is not only concerned with aspects related to the sexual reassignment surgery, but also with the mental health of its patients and with the family. One of the main complaints of patients is the impression that professionals seem to find them strange and feel extremely uncomfortable when they talk about their desire to undergo sex-change surgery: Investigate the role of nursing in the process of change sexual. Our methodology was a review of articles produced between 1994 and 2015. It was concluded that nursing should specialize for this new demand, which is growing more and more in our health services. We believe that nursing is specializing to enter this context and the expectations are good for the professionals and for the reception of the transsexual patient.

Keywords: transex, nursing, importance, patient

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Authors: R. Ghasemi, M. R. Rahimi Khoygani

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This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller.

Keywords: adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

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Authors: Nyimas Annissa Mutiara Andini

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Every year, children develop hydrocephalus during the first year of life. If it is not treated, hydrocephalus can lead to brain damage, a loss in mental and physical abilities, and even death. To be treated, first, we have to do a proper diagnosis using some examinations especially to detect hydrocephalus earlier. One of the examination that could be done is using a head circumference measurement. Increased head circumference is a first and main sign of hydrocephalus, especially in infant (0-1 year age). Head circumference is a measurement of a child's head largest area. In this measurement, we want to get the distance from above the eyebrows and ears and around the back of the head using a measurement tape. If the head circumference of an infant is larger than normal, this infant might potentially suffer hydrocephalus. If early diagnosis and timely treatment of hydrocephalus could be done most children can recover successfully. There are some problems with early detection of hydrocephalus using regular tape for head circumference measurement. One of the problem is the infant’s comfort. We need to make the infant feel comfort along the head circumference measurement to get a proper result of the examination. For that, we can use a helpful stuff, like a hat. This paper is aimed to describe the possibility of using a head circumference measuring instrument for early detection of hydrocephalus in an infant with a mike hat, coloured-tape-in-hat. In the first life, infants’ head size is about 35 centimeters. First three months after that infants will gain 2 centimeters each month. The second three months, infant’s head circumference will increase 1 cm each month. And for the six months later, the rate is 0.5 cm per month, and end up with an average of 47 centimeters. This formula is compared to the WHO’s head circumference growth chart. The shape of this tape-in-hat is alike an upper arm measurement. This tape-in-hat diameter is about 47 centimeters. It contains twelve different colours range by age. If it is out of the normal colour, the infant potentially suffers hydrocephalus. This examination should be done monthly. If in two times of measurement there still in the same range abnormal of head circumference, or a rapid growth of the head circumference size, the infant should be referred to a pediatrician. There are the pink hat for girls and blue hat for boys. Based on this paper, we know that this measurement can be used to help early detection of hydrocephalus in an infant.

Keywords: head circumference, hydrocephalus, infant, mike hat

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Authors: Christopher Muhawe, Masooda Bashir

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With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Soma Kanta Baral

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Background: Since 1981, when the first AIDS case was reported, worldwide, more than 34 million people have been infected with HIV. Almost 95 percent of the people infected with HIV live in developing countries. As HBV & HIV share similar routes of transmission by sexual intercourse or drug use by parenteral injection, co-infection is common. Because of the limited access to healthcare & HIV treatment in developing countries, HIV-infected individuals are present late for care. Enumeration of CD4+ T cell count at the time of diagnosis has been useful to initiate the therapy in HIV infected individuals. The baseline CD4+ T cell count shows high immunological variability among patients. Methods: This prospective study was done in the serology section of the Department of Microbiology over a period of one year from august 2012 to July 2013. A total of 13037 individuals subjected for HIV test were included in the study comprising of 4982 males & 8055 females. Blood sample was collected by vein puncture aseptically with standard operational procedure in clean & dry test-tube. All blood samples were screened for HIV as described by WHO algorithm by Immuno-chromatography rapid kits. Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. After informed consent, HIV positive individuals were screened for HBsAg by Immuno-chromatography rapid kits (Hepacard). Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. EDTA blood samples were collected from the HIV sero-positive individuals for baseline CD4+ T count. Then, CD4+ T cells count was determined by using FACS Calibur Flow Cytometer (BD). Results: Among 13037 individuals screened for HIV, 104 (0.8%) were found to be infected comprising of 69(66.34%) males & 35 (33.65%) females. The study showed that the high infection was noted in housewives (28.7%), active age group (30.76%), rural area (56.7%) & in heterosexual route (80.9%) of transmission. Out of total HIV infected individuals, distribution of HBV co-infection was found to be 6(5.7%). All co- infected individuals were married, male, above the age of 25 years & heterosexual route of transmission. Baseline CD4+ T cell count of HIV infected patient was found higher (mean CD4+ T cell count; 283cells/cu.mm) than HBV co-infected patients (mean CD4+ T cell count; 91 cells/cu.mm). Majority (77.2%) of HIV infected & all co-infected individuals were presented in our center late (CD4+ T cell count;< 350/cu. mm) for diagnosis and care. Majority of co- infected 4 (80%) were late presented with advanced AIDS stage (CD4+ count; <200/cu.mm). Conclusions: The study showed a high percentage of HIV sero-positive & co- infected individuals. Baseline CD4+ T cell count of majority of HIV infected individuals was found to be low. Hence, more sustained and vigorous awareness campaigns & counseling still need to be done in order to promote early diagnosis and management.

Keywords: HIV/AIDS, HBsAg, co-infection, CD4+

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Luqman Afolabi

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This paper measures the impacts of trade and institutions on environmental quality in Sub-Saharan Africa (SSA). To examine the direction and the magnitude of the effects, the study employs the pooled mean group (PMG) estimation technique on the panel data obtained from the World Bank’s World Development and Governance Indicators, between 1996 and 2018. The empirical estimates validate the environmental Kuznets curve hypothesis (EKC) for the region, even though there have been inconclusive results on the environment – growth nexus. Similarly, a positive coefficient is obtained on the impact of trade on the environment, while the impact of the institutional indicators produce mixed results. A significant policy implication is that the governments of the SSA countries pursue policies that tend to increase economic growth, so that pollutants may be reduced. Such policies may include the provision of incentives for sustainable growth-driven industries in the region. In addition, the governance infrastructures should be improved in such a way that appropriate penalties are imposed on the pollutants, while advanced technologies that have the potentials to reduce environmental degradation should be encouraged. Finally, it is imperative from these findings that the governments of the region should promote their trade relations and the competitiveness of their local industries in order to keep pace with the global markets.

Keywords: environmental quality, institutional quality sustainable development goals, trade

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Authors: Chuping Lo

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This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: Saleh Nabiyev

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Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Ghada Esheba, Ebtisam Aljerayan, Afnan Al-Ghamdi, Atheer Alsharif, Hanan alzahrani

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Background: Primary ovarian neoplasms comprise a heterogeneous group of tumors of three main subtypes: surface epithelial, germ cell, and sex cord-stromal. The wide morphological variation within and between these groups can result in diagnostic difficulties. Gonadal sex cord-stromal tumors (SCST) represent one of the most heterogeneous categories of human neoplasms, because they may contain various combinations of different gonadal sex cord and stromal element. Aim: The aim of this work is to highlight the clinicopathological characteristics of SCST and to assess the value of alpha-inhibin and calretinin in the distinction between SCST and their mimics. Material and methods: This study was carried out on 100 cases using full tissue sections; 70 cases were SCST and 30 cases were histological mimics of SCST. The cases were studied using immunohistochemically using alpha-inhibin. In addition, an ovarian tissue microarray containing 170 benign and malignant ovarian neoplasms was also studied immunohistochemically for calretinin expression. The ovarian microarray included 14 SCST, 59 ovarian serous borderline tumors, 17 mucinous borderline tumors, 10 mucinous adenocarcinomas, 32 endometrioid adenocarcinomas, 34 clear cell carcinomas, and 4 germ cell tumors. Results: 99% of SCST examined using full tissue sections exhibited positive cytoplasmic staining for inhibin. On the contrary, only 7% of the histological mimics (P value < 0.0001). 86% of SCST in the tissue microarray were positive for calretinin with nuclear and/or cytoplasmic staining compared to only 7% of the other tumor types (P value < 0.0001). Conclusions: SCST have characteristic clinicopathological and immunohistochemical features and their recognition is crucial for proper diagnosis and treatment. Alpha-inhibin and calretinin are of great help in the diagnosis of sex cord-stromal tumors.

Keywords: calretinin, granulosa cell tumor, inhibin, sex cord-stromal tumors

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Authors: Amirreza Razzaghipour Sorkhab

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Hearing loss is one of the greatest common chronic health situations of older people. Hearing aids are the common treatment, and they recover the quality of life in older adults. Even so, comparatively few older adults with simple, mild to moderate, adult-onset, sensorineural hearing loss use hearing aids. It shouldn’t be expected that more expensive hearing aids always produce better outcomes. Given the importance of quality pledge, approaches of quantifying hearing aid fitting achievement are needed. Studies showed an important reduction in handicap following 3 weeks of hearing aid use, signifying the feasibility of using the Hearing Hindrance Inventory for the Elderly as an outcome measure for hearing aid success after a brief interval of hearing aid use. The results showed important development of the quality of life after three months of using a hearing aid in all members and improvement of their most important problems, i.e., the communication and exchange of data. Hearing loss can impair the conversation of information and so decreases the quality of life. Hearing aids have progressivemeaningfully over the past decade, chiefly due to the growing of digital technology. The next decade should see an even greater number of innovations to hearing aid technology. Development in digital hearing aids will be driven by investigate advances in the next fields such as wireless technology, hearing science, and cognitive scienceMoreover, emerging trends such as connectivity and individuation will also drive new technology. We hope that the advancement of technology will be enough to meet the needs of people with hearing aids.

Keywords: hearing loss, hearing aid, hearing aid technology, health

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

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Authors: Vineet Agrawal, Deepanjali S., Medha R., Subitha L.

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Background. Hospital malnutrition is a highly prevalent issue and is known to increase the morbidity, mortality, length of hospital stay, and cost of care. In India, studies on hospital malnutrition have been restricted to ICU, post-surgical, and cancer patients. We designed this study to assess the impact of hospital malnutrition on 30-day post-discharge and in-hospital mortality in patients admitted in the general medicine department, irrespective of diagnosis. Methodology. All patients aged above 18 years admitted in the medicine wards, excluding medico-legal cases, were enrolled in the study. Nutritional assessment was done within 72 h of admission, using Subjective Global Assessment (SGA), which classifies patients into three categories: Severely malnourished, Mildly/moderately malnourished, and Normal/well-nourished. Anthropometric measurements like Body Mass Index (BMI), Triceps skin-fold thickness (TSF), and Mid-upper arm circumference (MUAC) were also performed. Patients were followed-up during hospital stay and 30 days after discharge through telephonic interview, and their final diagnosis, comorbidities, and cause of death were noted. Multivariate logistic regression and cox regression model were used to determine if the nutritional status at admission independently impacted mortality at one month. Results. The prevalence of malnourishment by SGA in our study was 67.3% among 395 hospitalized patients, of which 155 patients (39.2%) were moderately malnourished, and 111 (28.1%) were severely malnourished. Of 395 patients, 61 patients (15.4%) expired, of which 30 died in the hospital, and 31 died within 1 month of discharge from hospital. On univariate analysis, malnourished patients had significantly higher morality (24.3% in 111 Cat C patients) than well-nourished patients (10.1% in 129 Cat A patients), with OR 9.17, p-value 0.007. On multivariate logistic regression, age and higher Charlson Comorbidity Index (CCI) were independently associated with mortality. Higher CCI indicates higher burden of comorbidities on admission, and the CCI in the expired patient group (mean=4.38) was significantly higher than that of the alive cohort (mean=2.85). Though malnutrition significantly contributed to higher mortality on univariate analysis, it was not an independent predictor of outcome on multivariate logistic regression. Length of hospitalisation was also longer in the malnourished group (mean= 9.4 d) compared to the well-nourished group (mean= 8.03 d) with a trend towards significance (p=0.061). None of the anthropometric measurements like BMI, MUAC, or TSF showed any association with mortality or length of hospitalisation. Inference. The results of our study highlight the issue of hospital malnutrition in medicine wards and reiterate that malnutrition contributes significantly to patient outcomes. We found that SGA performs better than anthropometric measurements in assessing under-nutrition. We are of the opinion that the heterogeneity of the study population by diagnosis was probably the primary reason why malnutrition by SGA was not found to be an independent risk factor for mortality. Strategies to identify high-risk patients at admission and treat malnutrition in the hospital and post-discharge are needed.

Keywords: hospitalization outcome, length of hospital stay, mortality, malnutrition, subjective global assessment (SGA)

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Authors: Drago Bratkovic, Curtis Gravance, David Ketteridge, Ravi Krishnan, Michael Imperiale

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The mucopolysaccharidoses (MPSs) are a group of lysosomal storage diseases that have a common defect in the catabolism of glycosaminoglycans (GAGs). MPS I is the most common of the MPS diseases. Manifestations of MPS I include coarsening of facial features, corneal clouding, developmental delay, short stature, skeletal manifestations, hearing loss, cardiac valve disease, hepatosplenomegaly, and umbilical and inguinal hernias. Treatments for MPS I restore or activate the missing or deficient enzyme in the case of enzyme replacement therapy (ERT) and haematopoietic stem cell transplantation (HSCT). Pentosan polysulfate sodium (PPS) is a potential treatment to improve bone and joint manifestations of MPS I. The mechanisms of action of PPS that are relevant to the treatment of MPS I are the ability to: (i) Reduce systemic and accumulated GAG, (ii) Reduce inflammatory effects via the inhibition of NF-kB, resulting in the reduction in pro-inflammatory mediators. (iii) Reduce the expression of the pain mediator nerve growth factor in osteocytes from degenerating joints. (iv) Inhibit the cartilage degrading enzymes related to joint dysfunction in MPS I. PPS is being evaluated as an adjunctive therapy to ERT and/or HSCT in an open-label, single-centre, phase 2 study. Patients are ≥ 5 years of age with a diagnosis of MPS I and previously received HSCT and/or ERT. Three white, female, patients with MPS I-Hurler, ages 14, 15, and 19 years, and one, white male patient aged 15 years are enrolled. All were diagnosed at ≤2 years of age. All patients received HSCT ≤ 6 months after diagnosis. Two of the patients were treated with ERT prior to HSCT, and 1 patient received ERT commencing 3 months prior to HSCT. Two patients received 0.75mg/kg and 2 patients received 1.5mg/kg of PPS. PPS was well tolerated at doses of 0.75 and 1.5 mg/kg to 47 weeks of continuous dosing. Of the 19 adverse events (AEs), 2 were related to PPS. One AE was moderate (pre-syncope) and 1 was mild (injection site bruising), experienced in the same patient. All AEs were reported as mild or moderate. There have been no SAEs. One subject experienced a COVID-19 infection and PPS was interrupted. The MPS I signature GAG fragments, sulfated disaccharide and UA-HNAc S, tended to decrease in 3 patients from baseline through Week 25. Week 25 GAG data are pending for the 4th patient. Overall, most biomarkers (inflammatory, cartilage degeneration, and bone turnover) evaluated in the 3 patients with 25-week assessments have indicated either no change or a reduction in levels compared to baseline. In 3 patients, there was a trend toward improvement in the 2MWT from baseline to Week 48 with > 100% increase in 1 patient (01-201). In the 3 patients that had Week 48 assessments, patients and proxies reported improvement in PGIC, including “worthwhile difference” (n=1), or “made all the difference” (n=2).

Keywords: MPS I, pentosan polysulfate sodium, clinical study, 2MWT, QoL

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Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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Authors: Yoonjung An, Yongtae Park

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Knowledge flows are a critical source of faster technological progress and stouter economic growth. Knowledge flows have been accelerated dramatically with the establishment of a patent system in which each patent is required by law to disclose sufficient technical information for the invention to be recreated. Patent analysis, thus, has been widely used to help investigate technological knowledge flows. However, the existing research is limited in terms of both subject and approach. Particularly, in most of the previous studies, business method (BM) patents were not covered although they are important drivers of knowledge flows as other patents. In addition, these studies usually focus on the static analysis of knowledge flows. Some use approaches that incorporate the time dimension, yet they still fail to trace a true dynamic process of knowledge flows. Therefore, we investigate dynamic patterns of knowledge flows driven by BM patents using a Hidden Markov Model (HMM). An HMM is a popular statistical tool for modeling a wide range of time series data, with no general theoretical limit in regard to statistical pattern classification. Accordingly, it enables characterizing knowledge patterns that may differ by patent, sector, country and so on. We run the model in sets of backward citations and forward citations to compare the patterns of knowledge utilization and knowledge dissemination.

Keywords: business method patents, dynamic pattern, Hidden-Markov Model, knowledge flow

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