Search results for: risk probability

Authors: Omar Moafaq Saleh Aljanabi, Noradiva Hamzah, Ruhanita Maelah

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In today’s challenging global economy, which is driven by information and knowledge, risk management is undergoing a great change, as organizations shift from traditional and compartmental risk management to an enterprise-wide approach. Enterprise risk management (ERM), which aims at increasing the sustainability of an organization and achieving competitive advantage, is gaining global attention and fast becoming an essential concern in all industries. Furthermore, in order to be effective, ERM should be managed by managers with high-level skills and knowledge. Despite the importance of the knowledge embedded in, there remains a paucity of evidence concerning how human capital could influence the organization’s ERM. Responses from 116 public listed companies (PLCs) on the main market of Bursa Malaysia were analyzed using Structural Equation Modelling (SEM). This study found that there is a significant association between ERM and organizational performance. The results also indicate that human capital has a positive moderating effect on the relationship between ERM and performance. The study contributes to the ERM literature by providing empirical evidence on the relationship between ERM, human capital, and organizational performance. Findings from this study also provide guidelines for managers, policy makers, and the regulatory bodies, to evaluate the ERM practices in PLCs.

Keywords: enterprise risk management, human capital, organizational performance, Malaysian public listed companies

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Authors: P. Zarfam, M. Mansouri Baghbaderani

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In seismic design, the proper reaction to the earthquake and the correct and accurate prediction of its subsequent effects on the structure are critical. Choose a proper probability distribution, which gives a more realistic probability of the structure's damage rate, is essential in damage discussions. With the development of design based on performance, analytical method of modal push over as an inexpensive, efficacious, and quick one in the estimation of the structures' seismic response is broadly used in engineering contexts. In this research three concrete frames of 3, 6, and 13 stories are analyzed in non-linear modal push over by 30 different earthquake records by OpenSEES software, then the detriment indexes of roof's displacement and relative displacement ratio of the stories are calculated by two parameters: peak ground acceleration and spectra acceleration. These indexes are used to establish the value of damage relations with log-normal distribution and logistics distribution. Finally the value of these relations is compared and the effect of height on the mentioned damage relations is studied, too.

Keywords: modal pushover analysis, concrete structure, seismic damage, log-normal distribution, logistic distribution

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Authors: Peter David Reiss

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The concept of the psychosis prodrome has allowed for the identification of adolescent and young adult patients who have a significantly elevated risk of developing schizophrenia spectrum disorders. A number of different interventions have been tested in order to prevent or delay progression of symptoms. To date, there has been no consistent meta-analytical evidence to support efficacy of antipsychotic treatment for patients in the prodromal state, and their use remains therefore inconclusive. Although antipsychotics may manage symptoms transiently, they have not been found to prevent or delay onset of psychotic disorders. Furthermore, pharmacological intervention in high-risk individuals remains controversial, because of the antipsychotic side effect profile in a population in which only about 20 to 35 percent will eventually convert to psychosis over a two-year period, with even after two years conversion rates not exceeding 30 to 40 percent. This general estimate is additionally problematic, in that it ignores the fact that there is significant variation in individual risk among clinical high-risk cases. The current lack of reliable tests for at-risk patients makes it difficult to justify individual treatment decisions. Preventive treatment should ideally be dictated by an individual’s risk while minimizing potentially harmful medication exposure. This requires more accurate predictive assessments by using valid and accessible prognostic markers. The following will compare prediction and risk modification potential of behavioral biomarkers such as disturbances of basic sense of self and emotion awareness, neurocognitive biomarkers such as attention, working and declarative memory, and neurophysiological biomarkers such as glutamatergic abnormalities and NMDA receptor dysfunction. Identification of robust biomarkers could therefore not only provide more reliable means of psychosis prediction, but also help test and develop new clinical interventions targeted at the prodromal state.

Keywords: at-risk mental state, biomarkers, glutamatergic system, NMDA receptor, psychosis prodrome, schizophrenia

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Marcelo Dias Carvalho, Leticia Ishikawa

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Supply Chain Risk Management refers to a set of strategies used by companies to avoid supply chain disruption caused by damage at production facilities, natural disasters, capacity issues, inventory problems, incorrect forecasts, and delays. Many companies use the techniques of the Toyota Production System, which in a way goes against a better management of supply chain risks. This paper studies key events in some multinationals to analyze the trade-off between the best supply chain risk management techniques and management policies designed to create lean enterprises. The result of a good balance of these actions is the reduction of losses, increased customer trust in the company and better preparedness to face the general risks of a supply chain.

Keywords: just in time, lean manufacturing, supply chain disruptions, supply chain management

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Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

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Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

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Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Sarah A. Harris, Fleur L. McIntyre, Paola T. Chivers, Benjamin G. Piggott, Fiona H. Farringdon

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Australian Rules Football (ARF) is an invasion based, contact field sport with over one million participants. The contact nature of the game increases exposure to all injuries, including head trauma. Evidence suggests that both concussion and sub-concussive traumas such as head knocks may damage the brain, in particular the prefrontal cortex. The prefrontal cortex may not reach full maturity until a person is in their early twenties with males taking longer to mature than females. Repeated trauma to the pre-frontal cortex during maturation may lead to negative social, cognitive and emotional effects. It is also during this period that males exhibit high levels of risk taking behaviours. Risk propensity and the incidence of injury is an unexplored area of research. Little research has considered if the level of player’s (especially younger players) risk propensity in everyday life places them at an increased risk of injury. Hence the current study, investigated if a relationship exists between risk propensity and self-reported injuries including diagnosed concussion and head knocks, among male ARF players aged 18 to 31 years. Method: The study was conducted over 22 weeks with one West Australian Football League (WAFL) club during the 2015 competition. Pre-season risk propensity was measured using the 7-item self-report Risk Propensity Scale. Possible scores ranged from 9 to 63, with higher scores indicating higher risk propensity. Players reported their self-perceived injuries (concussion, head knocks, upper body and lower body injuries) fortnightly using the WAFL Injury Report Survey (WIRS). A unique ID code was used to ensure player anonymity, which also enabled linkage of survey responses and injury data tracking over the season. A General Linear Model (GLM) was used to analyse whether there was a relationship between risk propensity score and total number of injuries for each injury type. Results: Seventy one players (N=71) with an age range of 18.40 to 30.48 years and a mean age of 21.92 years (±2.96 years) participated in the study. Player’s mean risk propensity score was 32.73, SD ±8.38. Four hundred and ninety five (495) injuries were reported. The most frequently reported injury was head knocks representing 39.19% of total reported injuries. The GLM identified a significant relationship between risk propensity and head knocks (F=4.17, p=.046). No other injury types were significantly related to risk propensity. Discussion: A positive relationship between risk propensity and head trauma in contact sports (specifically WAFL) was discovered. Assessing player’s risk propensity therefore, may identify those more at risk of head injuries. Potentially leading to greater monitoring and education of these players throughout the season, regarding self-identification of head knocks and symptoms that may indicate trauma to the brain. This is important because many players involved in WAFL are in their late teens or early 20’s hence, may be at greater risk of negative outcomes if they experience repeated head trauma. Continued education and research into the risks associated with head injuries has the potential to improve player well-being.

Keywords: football, head injuries, injury identification, risk

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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In India, landslides are the most frequently occurring disaster in the regions of the Himalayas and the Western Ghats. The steep slopes and land use in these areas are quite apprehensive. In the recent past, many landslide hazard zonation (LHZ) works have been carried out in the Himalayas. However, the preparation of LHZ maps considering temporal factors such as seismic ground shaking, seismic amplification at surface level, and rainfall are limited. Hence this study presents a comprehensive use of the multi-criteria decision-making (MCDM) method in landslide risk assessment. In this research, we conducted both geospatial and geotechnical analysis to minimize the danger of landslides. Geospatial analysis is performed using high-resolution satellite data to produce landslide causative factors which were given weightage using the MCDM method. The geotechnical analysis includes a slope stability check, which was done to determine the potential landslide slope. The landslide risk map can provide useful information which helps people to understand the risk of living in an area.

Keywords: landslide hazard zonation, PHA, AHP, GIS

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Authors: Rebecca M. Dagger, Katy Hadgraft, Matthew Teggart, Peter Angell

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Background: There is a growing body of evidence that demonstrates the association between sedentary behaviour, cardiometabolic risk and all-cause mortality. Since full time working adults spend approximately 8 hours per day in the workplace, interventions to reduce sedentary behaviour at work may alleviate some of the negative health outcomes associated with sedentary behaviour. The aims of this pilot study were to assess the impacts of using a Sit-Stand workstation on markers of cardiometabolic health in a cohort of desk workers. Methods: Twenty eight participants were recruited and randomly assigned to a control (n=5 males, 9 females, mean age 37 years ± 9.4 years) or intervention group (n= 5 males, 9 females, mean age 42 years ± 12.7 years). All participants attended the labs on 2 occasion’s pre and post intervention, following baseline measurements the intervention participants had the Sit Stand Workstations (Ergotron, USA) installed for a 10 week intervention period. The Sit Stand workstations allow participants to stand or sit at their usual workstation and participants were encouraged to the use the desk in a standing position at regular intervals throughout the working day. Cardiometabolic risk markers assessed were body mass, body composition (using bio impedance analysis; Tanita, Tokyo), fasting blood Total Cholesterol (TC), lipid profiles (HDL-C, LDL-C, TC: HDL-C ratio), triglycerides and fasting glucose (Cholestech LDX), resting systolic and diastolic blood pressure and resting heart rate. ANCOVA controlling for baseline values was used to assess the group difference in changes in risk markers between pre and post intervention. Results: The 10 week intervention was associated with significant reductions in some cardiometabolic risk factors. There were significant group effects on change in body mass (F (1,25)=5.915, p<0.05), total body fat percentage (F(1,25)=12.615, p<0.01), total fat mass (F (1,25)=6.954, p<0.05), and systolic blood pressure (F (1,25)=5.012, p<0.05). There were no other significant group effects on changes in other cardiometabolic risk markers. Conclusion: This pilot study highlights the importance of reducing sedentary behaviour in the workplace for reduction in cardiometabolic risk markers. Further research is required to support these findings.

Keywords: sedentary behaviour, caridometabolic risk, evidence, risk makers

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Authors: A. O. Ogunkeyede, D. Amuchi, A. A. Adebayo

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Heavy metal contaminations in soil have received great attention. Anthropogenic activities such as vehicular emission, industrial activities and constructions have resulted in elevated concentration of heavy metals in the surface soils. The metal particles can be free from the surface soil when they are disturbed and re-entrained in air, which necessitated the need to investigate surface soil at market environment where adults and children are present on daily basis. This study assesses concentration of heavy metal pollution, ecological and health risk factors in surface soil at Effurun market. 8 samples were collected at household material (EMH), fish (EMFs), fish and commodities (EMF-C), Abattoir (EMA 1 & 2), fruit sections (EMF 1 & 2) and lastly main road (EMMR). The samples were digested and analyzed in triplicate for contents of Lead (Pb), Nickel (Ni), Cadmium (Cd) and Copper (Cu). The mean concentration of the Pb mg/kg (112.27 ± 1.12) and Cu mg/kg (156.14 ± 1.10) were highest in the abattoir section (EMA 1). The mean concentrations of the heavy metal were then used to calculate the ecological and health risk for people within the market. Pb contamination at EMMR, EMF 2, EMFs were moderately while Pb shows considerable contamination at EMH, EMA 1, EMA 2 and EMF-C sections of the Effurun market. The ecological risk factor varies between low to moderate pollution for Pb and EMA 1 has the highest potential ecological risk that falls within moderate pollution. The hazard quotient results show that dermal exposure pathway is the possible means of heavy metal exposure to the traders while ingestion is the least sources of exposure to adult. The ingestion suggested that children around the EMA 1 have the highest possible exposure to children due to hand-to-mouth and object-to-mouth behaviour. The results further show that adults at the EMA1 will have the highest exposure to Pb due to inhalation during burning of cow with tyre that contained Pb and Cu. The carcinogenic risk values of most sections were higher than acceptable values, while Ni at EMMR, EMF 1 & 2, EMFs and EMF-C sections that were below the acceptable values. The cancer risk for inhalation exposure pathway for Pb (1.01E+17) shows a significant level of contamination than all the other sections of the market. It suggested that the people working at the Abattoir were very prone to cancer risk.

Keywords: carcinogenic, ecological, heavy metal, risk

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Authors: Rajendra Kanojia

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Femoral components with inbuilt rotation require thicker flexion resection of the lateral femoral condyle and could potential risk to damage the popliteus tendon especially in the smaller Asian knees. We prospectively evaluated 10 patients with bilateral varus osteoarthritis knee to size the cuts and their location in relation to the popliteus tendon. Two different types of implant were used on either side, one side requires resection in 3° external rotation (group A) and other side femoral component with inbuilt external roation (group B). We had popliteus tendon injury in 3 knees all from group B. Risk of damaging the popliteus tendon was found higher in group B.

Keywords: popliteaus tendon injury, TKA, orthopaedic surgery, biomechanics and clinical applications

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Authors: Christopher G. Harris, Guy D. Eslick

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Purpose: Lobular carcinoma in situ (LCIS) is a known risk factor for breast cancer of unclear significance when detected in association with invasive carcinoma. This meta-analysis aims to determine the impact of LCIS on local recurrence risk for individuals with breast cancer treated with breast conservation therapy to help guide appropriate treatment strategies. Methods: We identified relevant studies from five electronic databases. Studies were deemed suitable for inclusion where they compared patients with invasive breast cancer and concurrent LCIS to those with breast cancer alone, all patients underwent breast conservation therapy (lumpectomy with adjuvant radiation therapy), and local recurrence was evaluated. Recurrence data were pooled by use of a random effects model. Results: From 1488 citations screened by our search, 8 studies were deemed suitable for inclusion. These studies comprised of 908 cases and 10638 controls. Median follow-up time was 90 months. There was a significantly increased overall risk of local breast cancer recurrence for individuals with LCIS in association with breast cancer following breast conservation therapy [pOR 1.87; 95% CI 1.14-3.04; p = 0.012]. The risk of local recurrence was non-significantly increased at 5 [pOR 1.09; 95% CI 0.48-2.48; p = 0.828] and 10 years [pOR 1.90; 95% CI 0.89-4.06; p = 0.096]. Conclusions: Individuals with LCIS in association with invasive breast cancer have an increased risk of local recurrence following breast conservation therapy. This supports consideration of aggressive local control of LCIS by way of completion mastectomy or re-excision for certain high-risk patients.

Keywords: breast cancer, breast conservation therapy, lobular carcinoma in situ, lobular neoplasia, local recurrence, meta-analysis

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Authors: Herlena Hayati, Diyan Reni Jayathi, Hairida Anggun, Citra Amelia

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This systematic review research is aimed to find out anemia maternal during pregnancy as a risk factor of low birth weight. This research was done by searching some journals which have associated to maternal anemia during pregnancy with low birth weight that had been published in journal accreditation and scopus index. Study literature that researcher had been done by March – April 2016 through online library of UI. The journals that had been selected according to inclusive criteria and exclusive criteria had been through the critial appraisal process. This systematic review towards 4 journals that had been selected and published showed the significant result statistically that anemia maternal is one of the risk factors which causes low birth weight. Anemia maternal on the first-trimester pregnancy showed significant association with low birth weight. Moderate anemia and severe anemia also showed significant association with low birth weight. Meanwhile, mild anemia doesn’t have an association with low birth weight. The conclusion of this study is anemia maternal (as an independent risk factor) have an influence towards low birth weight.

Keywords: anemia maternal, low birth weight, pregnancy, systematic review

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Authors: Joseph Paul Chunga

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The investment universe is awash with a myriad of financial choices that investors have to opt for, which principally culminates into a duality between aggressive or conservative approaches. Howbeit, it is pertinent to emphasize that the investment vehicles with an aggressive approach tend to take on more risk than the latter group in an effort to generate higher future returns for their respective investors. This study examines the conditionality effect that such partiality in financing has on the High-Tech and Public Utility companies listed on the Shenzhen Stock Exchange (SSE). Specifically, it examines the significance of the relationship between capitalization ratios of Total Debt Ratio (TDR), Degree of Financial Leverage (DFL) and profitability ratios of Earnings per Share (EPS) and Returns on Equity (ROE) on the Financial Risk of the two industries. We employ a modified version of the Panel Regression Model used by Rahman (2017) to estimate the relationship. The study finds that there is a significant positive relationship between the capitalization ratios on the financial risk of Public Utility companies more than High-Tech companies and a substantial negative relationship between the profitability ratios and the financial risk of the former than the latter companies. This then spells an important insight for prospective investors with regards to the volatility of earnings of such companies.

Keywords: financial leverage, debt financing, conservative firms, aggressive firms

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Authors: Guadalupe Fuentes-Lombardo, Manuel Carlos Vallejo-Martos, Rubén Fernández-Ortiz, Miriam Cano-Rubio

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The different ways in which companies enter foreign markets, exporting their products and direct investment and using strategic alliances or not, are influenced by a series of peculiarities specific to family businesses. In these companies, different systems, such as the family, property, and business overlap; giving them unique and specific characteristics which on occasions can enhance the development of cooperation agreements and in other situations can hinder them. Previous research has shown that these companies are more likely to enter into strategic alliances with certain specific features, and are more reluctant to take part in others in which some of the advantages of the family business are put at risk, such as control of ownership and decision-making over the company by the family, among others. These arguments show that there is a wide range of interesting aspects and peculiarities in the process of internationalization of the family business, although the research objectives of this paper focus on three in particular. Our first objective will be to discover why family businesses decide to establish or not strategic alliances in their internationalization processes in comparison with other companies that are not family owned. Secondly we will be identifying the idiosyncratic aspects of family businesses that favor or hinder the use of strategic alliances as a means of entering foreign markets. Our third and final objective will be to define the types of strategic alliance most commonly used by family businesses and the reasons why they choose these particular forms of alliance rather than others. We chose these research objectives for three main reasons. Firstly because research on this subject shows that alliances are the best way to begin the international expansion process, among other reasons because they provide the partners with different kinds of resources and capacity, so increasing the probability of successful internationalization. Secondly, because family and non-family businesses are often equipped with different types of resources and strategic alliances, offer them the chance to acquire resources less frequently found in family businesses. Thirdly, because the strengths and weaknesses of these companies could affect their decisions whether or not to use strategic alliances in their international expansion process and the success achieved in these alliances. As a result, these companies prefer to enter into cooperation agreements with conditions that do not put their specific status as family companies at risk.

Keywords: family business, internationalization, strategic alliances, olive-oil and wine industry

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Authors: Athina Thanou, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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The problem of museum visitor experience and congestion management – in various forms - has come increasingly under the spotlight over the last few years, since overcrowding can significantly decrease the quality of visitors’ experience. Evidence suggests that on busy days the amount of time a visitor spends inside a crowded house museum can fall by up to 60% compared to a quiet mid-week day. In this paper we consider the aforementioned problem, by treating museums as evolving social systems that induce constraints. However, in a cultural heritage space, as opposed to the majority of social environments, the momentum of the experience is primarily controlled by the visitor himself. Visitors typically behave selfishly regarding the maximization of their own Quality of Experience (QoE) - commonly expressed through a utility function that takes several parameters into consideration, with crowd density and waiting/visiting time being among the key ones. In such a setting, congestion occurs when either the utility of one visitor decreases due to the behavior of other persons, or when costs of undertaking an activity rise due to the presence of other persons. We initially investigate how visitors’ behavioral risk attitudes, as captured and represented by prospect theory, affect their decisions in resource sharing settings, where visitors’ decisions and experiences are strongly interdependent. Different from the majority of existing studies and literature, we highlight that visitors are not risk neutral utility maximizers, but they demonstrate risk-aware behavior according to their personal risk characteristics. In our work, exhibits are organized into two groups: a) “safe exhibits” that correspond to less congested ones, where the visitors receive guaranteed satisfaction in accordance with the visiting time invested, and b) common pool of resources (CPR) exhibits, which are the most popular exhibits with possibly increased congestion and uncertain outcome in terms of visitor satisfaction. A key difference is that the visitor satisfaction due to CPR strongly depends not only on the invested time decision of a specific visitor, but also on that of the rest of the visitors. In the latter case, the over-investment in time, or equivalently the increased congestion potentially leads to “exhibit failure”, interpreted as the visitors gain no satisfaction from their observation of this exhibit due to high congestion. We present a framework where each visitor in a distributed manner determines his time investment in safe or CPR exhibits to optimize his QoE. Based on this framework, we analyze and evaluate how visitors, acting as prospect-theoretic decision-makers, respond and react to the various pricing policies imposed by the museum curators. Based on detailed evaluation results and experiments, we present interesting observations, regarding the impact of several parameters and characteristics such as visitor heterogeneity and use of alternative pricing policies, on scalability, user satisfaction, museum capacity, resource fragility, and operation point stability. Furthermore, we study and present the effectiveness of alternative pricing mechanisms, when used as implicit tools, to deal with the congestion management problem in the museums, and potentially decrease the exhibit failure probability (fragility), while considering the visitor risk preferences.

Keywords: museum resource and visitor management, congestion management, propsect theory, cyber physical social systems

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Authors: Wan-Ling Jiang, Hsin Chi, Jia-Lu Cheng, Ming-Fang Cheng

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Background: Investigating the risk factors for the fecal carriage of third-generation cephalosporin-resistant E.coli could contribute to further disease prevention. Previous research on third-generation cephalosporin-resistant prevalence in children in different regions of Taiwan is limited. This project aims to explore the risk factors and regional differences in the prevalence of third-generation cephalosporin-resistant and other antibiotic-resistant E. coli in the northern, southern, and eastern regions of Taiwan. Methods: We collected data from children aged 0 to 18 from community or outpatient clinics from July 2022 to May 2023 in southern, northern, and eastern Taiwan. The questionnaire was designed to survey the characteristics of participants and possible risk factors, such as clinical information, household environment, drinking water, and food habits. After collecting fecal samples and isolating stool culture with E.coli, antibiotic sensitivity tests and MLST typing were performed. Questionnaires were used to analyze the risk factors of third-generation cephalosporin-resistant E. coli in the three different regions of Taiwan. Results: In the total 246 stool samples, third-generation cephalosporin-resistant E.coli accounted for 37.4% (97/246) of all isolates. Among the three different regions of Taiwan, the highest prevalence of fecal carriage with third-generation cephalosporin-resistant E.coli was observed in southern Taiwan (42.7%), followed by northern Taiwan (35.5%) and eastern Taiwan (28.4%). Multi-drug resistant E. coli had prevalence rates of 51.9%, 66.3%, and 37.1% in the northern, southern, and eastern regions, respectively. MLST typing revealed that ST131 was the most prevalent type (11.8%). The prevalence of ST131 in northern, southern, and eastern Taiwan was 10.1%, 12.3%, and 13.2%, respectively. Risk factors analysis identified lower paternal education, overweight status, and non-vegetarian diet as statistical significance risk factors for third-generation cephalosporin-resistant E.coli. Conclusion: The fecal carriage rates of antibiotic-resistant E. coli among Taiwanese children were on the rise. This study found regional disparities in the prevalence of third-generation cephalosporin-resistant and multi-drug-resistant E. coli, with southern Taiwan having the highest prevalence. Lower paternal education, overweight, and non-vegetarian diet were the potential risk factors of third-generation cephalosporin-resistant E. coli in this study.

Keywords: Escherichia coli, fecal carriage, antimicrobial resistance, risk factors, prevalence

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Authors: C. A. Bradley, D. Patsios, D. Berridge

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This paper presents evidence to better understand the risk and protective factors related to sibling conflict and the patterns of association between sibling conflict and negative adjustment outcomes by incorporating additional familial and societal factors within statistical models of risk and adjustment. It was conducted through the secondary analysis of a large representative cross-sectional dataset of children in the UK. The original study includes proxy interviews for young children and self-report interviews for adolescents. The study applies an ecological systems framework for the analyses. Hierarchical regression models assess risk and protective factors and adjustment outcomes associated with sibling conflict. Interactions reveal differential effect between contextual risk factors and the social context of influence. The general pattern of findings suggested that, although factors affecting likelihood of experiencing sibling conflict were often determined by child age, some remained consistent across childhood. These factors were often conditional on each other, reinforcing the importance of an ecological framework. Across both age-groups, sibling conflict was associated with siblings closer in age; male sibling groups; most advantaged socio-economic group; and exposure to community violence, such as witnessing violent assault or robbery. The study develops the evidence base on the influence of ethnicity and socio-economic group on sibling conflict by exploring interactions between social context. It also identifies key new areas of influence – such as family structure, disability, and community violence in exacerbating or reducing risk of conflict. The study found negative associations between sibling conflict and young children’s mental well-being and adolescents' mental well-being and anti-social behaviour, but also more context specific associations – such as sibling conflict moderating the negative impact of adversity and high risk experiences for young children such as parental violence toward the child.

Keywords: adjustment, conflict, ecological systems, family systems, risk and protective factors, sibling

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Authors: Raquel Dafouz Neus Cáceres, Javier Fernandez-Rubio, Belinda Huerta José Luis Rodríguez-Gil, Nicola Mastroianni, Miren López de Alda, Damià Barceló, Yolanda Valcárcel

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The region of Galicia, found in north-western (NW) Spain, is a national and world leader in shellfish, especially mussel production, and recognized for its fishing industry. Few studies have evaluated the presence of emerging contaminants in NW Spain, with those published mainly concerning the continental aquatic environment. The objective of this study was to identify the environmental risk posed by the presence of pharmaceuticals and drugs of abuse in this important coastal region. The presence of sixteen pharmaceuticals (benzodiazepines, anxiolytics, and caffeine), and 19 drugs of abuse (cocainics, amphetamine-like compounds, opiates and opioids, lysergic compounds, and cannabinoids) was assessed in 23 sites located in the Rías (Coastal inlets) of Muros, Arousa, and Pontevedra (NW Spain). Twenty-two of these locations were affected by waste-water treatment plant (WWTP) effluents, and one represented the effluent of one of these WWTPs. Venlafaxine was the pharmaceutical compound detected at higher concentration in the three Rías, with a maximum value of 291 ng/L at the site Porto do Son (Ría de Muros). Total concentration in the three Rías was 819,26 ng/L. Next, citalopram and lorazepam were the most prevalent compounds detected. Metabolite of cocaine benzoylecgonine was the drug of abuse with the highest concentration, measured at 972 ng/L in the Ría of Noia WWTP (no dilution). This compound was also detected at 142 ng/L in the site La Isla de Aros, Ría of Pontevedra. Total concentration for the three Rías was 1210 ng/L. Ephedrine was also detected at high level in the three Rías, with a total concentration of 579,28 ng/L. The results obtained for caffeine show maximum and average concentrations of 857 ng/L Isla de Arosa, Ría de Pontevedra the highest measured in seawater in Spain. A preliminary hazard assessment was carried out by comparing these measured environmental concentrations (MEC) to predicted no-effect concentrations (PNECs) for aquatic organisms. Six out of the 22 seawater samples resulted in a Hazard Quotient (HQ) from chronic exposure higher than 1 with the highest being 17.14, indicating a high probability of adverse effects in the aquatic environment. In addition, the risk was assessed on the basis of persistence, bioaccumulation, and toxicity (PBT). This work was financially supported by the Spanish Ministry of Economy and Competitiveness through the Carlos III Health Institute and the program 'Proyectos de Investigacion en Salud 2015-2017' FIS (PI14/00516), the European Regional Development Fund (ERDF), the Catalan Government (Consolidated Research Groups '2014 SGR 418 - Water and Soil Quality Unit' and 2014 SGR 291 - ICRA), and the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 603437. The poster entitled 'Environmental Risk of Pharmaceuticals, Drugs of Abuse and Stimulant Caffeine in Marine Water: A Case Study in the North-Western of Spain'.

Keywords: drug of abuse, pharmaceuticals, caffeine, environmental risk, seawater

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Authors: Shruti Chopra, Vikas Rao Vadi

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In the era of the digital world, the Internet of Things (IoT) has been receiving significant attention. Its ubiquitous connectivity between humans, machines to machines (M2M) and machines to humans provides it a potential to transform the society and establish an ecosystem to serve new dimensions to the economy of the country. Thereby, this study has attempted to identify the challenges that seem prevalent in IoT adoption in India through the literature survey. Further, the data has been collected by taking the opinions of experts to conduct the foresight analysis and it has been analyzed with the help of scenario planning process – Micmac, Mactor, Multipol, and Smic-Prob. As a methodology, the study has identified the relationship between variables through variable analysis using Micmac and actor analysis using Mactor, this paper has attempted to generate the entire field of possibilities in terms of hypotheses and construct various scenarios through Multipol. And lastly, the findings of the study include final scenarios that are selected using Smic-Prob by assigning the probability to all the scenarios (including the conditional probability). This study may help the practitioners and policymakers to remove the obstacles to successfully implement the IoT in India.

Keywords: Internet of Thing (IoT), foresight analysis, scenario planning, challenges, policymaking

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Authors: Roberto Rubem Silva-Brandao, Aurea Maria Zollner Ianni

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This article discusses the use and the incorporation of Pre-exposure Prophylaxis for HIV (PrEP) within a risk society context. Considering contemporary social theoreticians, we discuss implications of biotechnological uses for health enhancement. Firstly, we explore examples of biological manipulation and its consequences of use on given ecological dynamics, particularly taking into account other Sexually Transmitted Infections. In addition, we discuss how HIV resistance cases occurred with people on PrEP and its possible consequences on population-based interventions. Moreover, we present recent studies that analyze biological modifications on bodies of those who are on consistent use of PrEP, and how these body modifications are addressed on common practices of Public Health. Secondly, we present our theoretical references, which are intended to the analysis that situates our contemporary society in the reflexive stage of modernization. We discuss limits of biological use by individuals and how this can fabric feelings of freedom and autonomy within the individualization process and health. Finally, we argue that biotechnological uses on health, specifically on Public Health, tackling the risk aspects of its application, shows that another sanitary pact is needed.

Keywords: PrEP, public health, social sciences, risk society

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Authors: Yas Barzegaar, Atrin Barzegar

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: S. Zhang, L. Zhang, X. Chen

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Due to the large uncertainty on the mechanical properties of FRP (fibre reinforced plastic), the reliability evaluation of FRP structures are currently receiving much attention in industry. However, possible statistical correlation between ply mechanical properties has been so far overlooked, and they are mostly assumed to be independent random variables. In this study, the statistical correlation between ply mechanical properties of uni-directional and plain weave composite is firstly analyzed by a combination of Monte-Carlo simulation and finite element modeling of the FRP unit cell. Large linear correlation coefficients between the in-plane mechanical properties are observed, and the correlation coefficients are heavily dependent on the uncertainty of the fibre volume ratio. It is also observed that the correlation coefficients related to Poisson’s ratio are negative while others are positive. To experimentally achieve the statistical correlation coefficients between in-plane mechanical properties of FRP, all concerned in-plane mechanical properties of the same specimen needs to be known. In-plane shear modulus of FRP is experimentally derived by the approach suggested in the ASTM standard D5379M. Tensile tests are conducted using the same specimens used for the shear test, and due to non-uniform tensile deformation a modification factor is derived by a finite element modeling. Digital image correlation is adopted to characterize the specimen non-uniform deformation. The preliminary experimental results show a good agreement with the numerical analysis on the statistical correlation. Then, failure probability of laminate plates is calculated in cases considering and not considering the statistical correlation, using the Monte-Carlo and Markov Chain Monte-Carlo methods, respectively. The results highlight the importance of accounting for the statistical correlation between ply mechanical properties to achieve accurate failure probability of laminate plates. Furthermore, it is found that for the multi-layer laminate plate, the statistical correlation between the ply elastic properties significantly affects the laminate reliability while the effect of statistical correlation between the ply strength is minimal.

Keywords: failure probability, FRP, reliability, statistical correlation

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Authors: Iyanujesu Adereti, Tajudeen Basiru, Ayodamola Olanipekun

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Background: Substance abuse among adolescents is of public health concern globally. Despite being the most abused by adolescents, there are limited studies on the prevalence of alcohol use and cigarette smoking among adolescents in Mauritius. Objectives: To determine the prevalence of cigarette smoking, alcohol use and associated correlates among school-going adolescents in Mauritius. Methodology: Data obtained from 2017 WHO Global School-based Student Health Survey (GSHS) survey of 3,012 school-going adolescents in Mauritius was analyzed using STATA. Descriptive statistics were used to obtain prevalence. Bivariate and multivariate logistic regression analysis was used to evaluate predictors of cigarette smoking and alcohol use. Results: Prevalence of alcohol consumption and cigarette smoking were 26.0% and 17.1%, respectively. Smoking and alcohol use was more prevalent among males, younger adolescents, and those in higher school grades (p-value <.000). In multivariable logistic regression, male gender was associated with a higher risk of cigarette smoking (adjusted Odds Ratio (aOR) [95%Confidence Interval (CI)]= 1.51[1.06-2.14]) but lower risk of alcohol use (aOR[95%CI]= 0.69[0.53-0.90]) while older age (mid and late adolescence) and parental smoking were found to be associated with increased risk of alcohol use (aOR[95%CI]= 1.94[1.34-2.99] and 1.36[1.05-1.78] respectively). Marijuana use, truancy, being in a fight and suicide ideation were associated with increased odds of alcohol use (aOR[95%CI]= 3.82[3.39-6.09]; 2.15[1.62-2.87]; 1.83[1.34-2.49] and 1.93[1.38-2.69] respectively) and cigarette smoking (aOR[95%CI]= 17.28[10.4 - 28.51]; 1.73[1.21-2. 49]; 1.67[1.14-2.45] and 2.17[1.43-3.28] respectively) while involvement in sexual activity was associated with reduced risk of alcohol use (aOR[95%CI]= 0.50[0.37-0.68]) and cigarette smoking (aOR[95%CI]= 0.47[0.33-0.69]). Parental support and parental monitoring were uniquely associated with lower risk of cigarette smoking (aOR[95%CI]= 0.69[0.47-0.99] and 0.62[0.43-0.91] respectively). Conclusion: The high prevalence of alcohol use and cigarette smoking in this study shows the need for the government of Mauritius to enhance policies that will help address this issue putting into accounts the various risk and protective factors.

Keywords: adolescent health, alcohol use, cigarette smoking, global school-based student health survey

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Authors: Andre Slonopas, Zona Kostic, Warren Thompson

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Obfuscation is one of the most useful tools to prevent network compromise. Previous research focused on the obfuscation of the network communications between external-facing edge devices. This work proposes the use of two edge devices, external and internal facing, which communicate via private IPv4 addresses in a software-defined pseudo-random IP hopping. This methodology does not require additional IP addresses and/or resources to implement. Statistical analyses demonstrate that the hopping surface must be at least 1e3 IP addresses in size with a broad standard deviation to minimize the possibility of coincidence of monitored and communication IPs. The probability of breaking the hopping algorithm requires a collection of at least 1e6 samples, which for large hopping surfaces will take years to collect. The probability of dropped packets is controlled via memory buffers and the frequency of hops and can be reduced to levels acceptable for video streaming. This methodology provides an impenetrable layer of security ideal for information and supervisory control and data acquisition systems.

Keywords: moving target defense, cybersecurity, network security, hopping randomization, software defined network, network security theory

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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