Search results for: risk estimation

Authors: N. Ayob, N. C. Nkosi, R. P. Burger, S. J. Piketh, F. Letlaila, O. Maphosa

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South African higher tertiary institution have been faced with high dropout rates. About 50 to 60% of first years drop out to due to various reasons one being inadequate academic support. Geography 111 (GEOG 111) module is historically known for having below 50% pass rate, high dropout rate and identified as a first year risk module. For the first time GEOG 111 (2021) on the Mahikeng Campus admitted 150 students pursuing more than 6 different qualifications (BA and BSc) from the Humanities Faculty and FNAS. First year students had difficulties transitioning from secondary to tertiary institutions as we shifted to remote learning while we navigate through the Covid-19 pandemic. The traditional method of teaching does not encourage students to help each other. With remote learning we do not have control over what the students share and perhaps this can be a learning opportunity to embrace peer learning and change the manner in which we assess the students. The purpose of this pilot study was to assist GEOG111 students with academic challenges whilst improving their University experience. This was a qualitative study open to all GEOG111, repeaters, students who are not confident in their Geographical knowledge and never did Geography at high school level. The selected 9 Golden Key International Honour Society Geography mentors attended an academic mentor training program with module lecturers. About 17.6% of the mentees did not have a geography background however, 94% of the mentees passed, 1 mentee had a mark of 38%. 11 of the participants had a mark >60% with one student that excelled 70%. It is evident that mentorship helped students reach their academic potential. Peer learning and mentoring are associated with improved academic performance and allows the students to take charge of their learning and academic experience. Thus an important element as we transform pedagogies at higher learning institutions.

Keywords: geography, risk module, peer mentoring, peer learning

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Authors: Yan-Ren Chen, Jenn-Kaie Lain

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This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

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Authors: Ossama Abdelmotaal, Olfat Shaker, Tarek Salman, Lamiaa Nabeel, Mostafa Shabayek

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Colorectal Cancer (CRC) is an important worldwide health problem. Colonoscopy is used in detecting CRC suffer from drawbacks where colonoscopy is an invasive method. This study validates easier and less time-consuming techniques to evaluate the usefulness of detecting miRNA-21, miRNA-215 and miRNA-378 in the sera of colorectal cancer patients as new diagnostic tools. This study includes malignant (Colo Rectal Cancer patients, n= 64)) and healthy (n=27) groups. The studied groups were subjected to colonoscopic examination and estimation of miRNA-21, miRNA-215 and miRNA-378 in sera by RT-PCR. miRNA-21 showed the statistically significantly highest median fold change. miRNA-378 showed statistically significantly lower value (Both showed over-expression). miRNA-215 showed the statistically significantly lowest median fold change (It showed down-regulation). Overall the miRNA (21-215 and 378) appear to be promising method of detecting CRC and evaluating its stages.

Keywords: colorectal cancer, miRNA-21, miRNA-215, miRNA-378

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Authors: Helen Huang, Francisco Javier Quesada Ocet, Blanca Quesada Oce, Javier Jimenez Bello, Victor Palanca Gil, Alba Cervero Rubio, Ana Paya Chaume, Alejandro Herreros-Pomares, Fernando Vidal-Vanaclocha, Rafael Paya Serrano, Aurelio Quesada Dorador, Monica Soliman

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Background: Cancer favors both the pro-inflammatory state and autonomic dysfunction, two important mechanisms in the genesis of AF. Atrial remodeling might be caused as a result of paraneoplastic conditions or the result of direct expression of neoplasia. Here, we hypothesize that cancer, through inflammatory mediators, may favor the appearance of AF and patients with the first episode of AF could have a higher risk of developing cancer. Method: Data was collected from patients who attended the emergency department of our hospital for the first episode of AF, diagnosed electrocardiographically, between 2010-2015 (n = 712). The minimum follow-up was 2 years, recording the appearance of cancer, total mortality, recurrences of AF and other events. Patients who developed cancer and those who did not during the 2 years after the onset of AF were compared, as well as with the incidence of cancer in Spain in 2012. Results: After 2 years, 35 patients (4.91%) were diagnosed with cancer, with an annual incidence of 2.45%. Hematological neoplasms were the most frequent (34.28%). The cancer group was older (76.68 +/-12.75 years vs 74.16 +/-12.71; p <0.05) and had fewer typical symptoms (palpitations) (33.38% vs 14.28% , p <0.05). The incidence of cancer in Spain during 2012 was 0.46%, much lower than our sample. When comparing the incidence by age, these differences were maintained both in those over 65 years of age and in those under 65 years of age (2.17% vs. 0.28%; 0.28% vs. 0.18% respectively). Discussion: Therefore, a high incidence of cancer in patients with the first episode of AF was observed (the annual incidence of 2.45% after the onset of AF is 6.1 times that of the general population). After the evaluation of patients with AF in their first detected episode, surveillance of the appearance of cancer should be considered in clinical practice.

Keywords: cancer, cardiovascular outcomes, atrial fibrillation, inflammation

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Madeline Gibson

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Night shift workers make up an essential part of the modern workforce. However, night shift workers have higher incidences of late in life diseases and earlier mortality. Night shift workers are exposed to constant light and experience circadian rhythm disruption. Sleep disruption is thought to increase oxidative stress, defined as an imbalance of excess pro-oxidative factors and reactive oxygen species over anti-oxidative activity. Oxidative stress can damage cells, proteins and DNA and can eventually lead to varied chronic diseases such as cancer, diabetes, cardiovascular disease, Alzheimer’s and dementia. This review aimed to understand whether night shift workers were at greater risk of oxidative stress and to contribute to a consensus on this relationship. Twelve studies published in 2001-2019 examining 2,081 workers were included in the review. Studies compared both the impact of working a single shift and in comparisons between those who regularly work night shifts and only day shifts. All studies had evidence to support this relationship across a range of oxidative stress indicators, including increased DNA damage, reduced DNA repair capacity, increased lipid peroxidation, higher levels of reactive oxygen species, and to a lesser extent, a reduction in antioxidant defense. This research supports the theory that melatonin and the sleep-wake cycle mediate the relationship between shift work and oxidative stress. It is concluded that night shift work increases the risk for oxidative stress and, therefore, future disease. Recommendations are made to promote the long-term health of shift workers considering these findings.

Keywords: night shift work, coxidative stress, circadian rhythm, melatonin, disease, circadian rhythm disruption

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Authors: Lingxia Li, Frédéric Schnell, Shuzhe Ding, Solène Le Douairon Lahaye

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Background: The risk of sudden cardiac arret/death (SCA/D) in athletes is controversial. There is a lack of meta-analyses assessing the sex differences in the risk of SCA/D in competitive athletes. Purpose: The aim of the present study was to evaluate sex differences in the incidence of SCA/D in competitive athletes using meta-analyses. Methods: The systematic review was registered in the PROSPERO database (registration ID: CRD42023432022) and was conducted according to the PRISMA guidelines. PubMed, Embase, Scopus, SPORT Discus and Cochrane Library were searched up to July 2023. To avoid systematic bias in data pooling, only studies with data for both sexes were included. Results: From the 18 included studies, 2028 cases of SCA/D were observed (males 1821 (89.79%), females 207 (10.21%)). The age ranges from the adolescents (<26 years) to the elderly (>45 years). The incidence in male athletes was 1.32/100,000 AY (95% CI: [0.90, 1.93]) and in females was 0.26/100,000 AY (95% CI: [0.16, 0.43]), the incidence rate ratio (IRR) was 6.43 (95% CI: [4.22, 9.79]). The subgroup synthesis showed a higher incidence in males than in females in both age groups <25 years and ≤35 years, the IRR was 5.86 (95% CI: [4.69, 7.32]) and 5.79 (95% CI: [4.73, 7.09]), respectively. When considering the events, the IRR was 6.73 (95%CI: [3.06, 14.78]) among studies involving both SCA/D events and 7.16 (95% CI: [4.93, 10.40]) among studies including only cases of SCD. The available clinical evidence showed that cardiac events were most frequently seen in long-distance running races (26, 35.1%), marathon (16, 21.6%) and soccer (10, 13.5%). Coronary artery disease (14, 18.9%), hypertrophic cardiomyopathy (8, 10.8%), and arrhythmogenic right ventricular cardiomyopathy (7, 9.5%) are the most common causes of SCA/D in competitive athletes. Conclusion: The meta-analysis provides evidence of sex differences in the incidence of SCA/D in competitive athletes. The incidence of SCA/D in male athletes was 6 to 7 times higher than in females. Identifying the reasons for this difference may have implications for targeted the prevention of fatal evets in athletes.

Keywords: incidence, sudden cardiac arrest, sudden cardiac death, sex difference, athletes

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Authors: Hamid Abbasi, Neda Jourabchi, Ranasadat Abedi, Kiarash Tajernarenj, Mehdi Farhoudi, Sarvin Sanaie

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Background: Alpha lipoic acid (ALA), fat- and water-soluble, coenzyme with sulfuret content, has received considerable attention for its potential therapeutic role in diabetes, cardiovascular diseases, cancers, and central nervous disease. This investigation aims to evaluate the probable protective effects of ALA in stroke patients. Methods: Based on Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, This meta-analysis was performed. The PICO criteria for this meta-analysis were as follows: Population/Patients (P: stroke patients); Intervention (I: ALA); Comparison (C: control); Outcome (O: blood glucose, lipid profile, oxidative stress, inflammatory factors).In addition, Studies that were excluded from the analysis consisted of in vitro, in vivo, and ex vivo studies, case reports, quasi-experimental studies. Scopus, PubMed, Web of Science, EMBASE databases were searched until August 2023. Results: Of 496 records that were screened in the title/abstract stage, 9 studies were included in this meta-analysis. The sample sizes in the included studies vary between 28 and 90. The result of risk of bias was performed via risk of bias (RoB) in randomized-controlled trials (RCTs) based on the second version of the Cochrane RoB assessment tool. 8 studies had a definitely high risk of bias. Discussion: To the best of our knowledge, The present meta-analysis is the first study addressing the effectiveness of ALA supplementation in enhancing post-stroke metabolic markers, including lipid profile, oxidative stress, and inflammatory indices. It is imperative to acknowledge certain potential limitations inherent in this study. First of all, type of treatment (oral or intravenous infusion) could alter the bioavailability of ALA. Our study had restricted evidence regarding the impact of ALA supplementation on included outcomes. Therefore, further research is warranted to develop into the effects of ALA specifically on inflammation and oxidative stress. Funding: The research protocol was approved and supported by the Student Research Committee, Tabriz University of Medical Sciences (grant number: 72825). Registration: This study was registered in the International prospective register of systematic reviews (PROSPERO ID: CR42023461612).

Keywords: alpha-lipoic acid, lipid profile, blood glucose, inflammatory factors, oxidative stress, meta-analysis, post-stroke

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Authors: Kaige Shi, Chao Jiang, Xin Li

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The swirl gripper is an electrically activated noncontact handling device that uses swirling airflow to generate a lifting force. This force can be used to pick up a workpiece placed underneath the swirl gripper without any contact. It is applicable, for example, in the semiconductor wafer production line, where contact must be avoided during the handling and moving of a workpiece to minimize damage. When a workpiece levitates underneath a swirl gripper, the gap height between them is crucial for safe handling. Therefore, in this paper, we propose a method to estimate the levitation gap height by detecting pressure at two points. The method is based on theoretical model of the swirl gripper, and has been experimentally verified. Furthermore, the force between the gripper and the workpiece can also be estimated using the detected pressure. As a result, the nonlinear relationship between the force and gap height can be linearized by adjusting the rotating speed of the fan in the swirl gripper according to the estimated force and gap height. The linearized relationship is expected to enhance handling stability of the workpiece.

Keywords: swirl gripper, noncontact handling, levitation, gap height estimation

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Authors: Almutazballlah Bassam Qablan, Jihan M. Muhaidat, bana Abu Rajab

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Background: Acne vulgaris is considered one of the most common skin conditions encountered by dermatologists. It is a chronic inflammation affecting the pilosebaceous unit. Although acne vulgaris is not fatal, it leads to permanent scarring and disfigurement, and even without scarring, it has a huge effect on patients, causing negative health outcomes. Acne vulgaris patients experience psychological, and emotional ramifications as those with chronic health problems; they feel depressed, angry, anxious, and confused. Although acne is a popular disease, many thoughts and myths are still discussed about its origins and triggering factors. These myths can make you feel guilt as if you were somehow responsible for your acne. In this case control study, we want to define the relationship between two modifiable risk factors ;BMI and smoking, with acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Ramtha, Jordan in 2019/2020. A total number of 325 participants between 14 and 33 years of age were interviewed by the authors; including 163 acne vulgaris cases and 162 controls without acne vulgaris. Anthropometric measures and smoking for Acne patients and control participants were the independent variables used to assess acne. Univariate and multivariate analysis were used to compare the characteristics of people who reported acne with those with no acne. The collected data analyzed by using the Statistical Package for Social Sciences (SPSS). Results: Cigarette smoking was highly associated with controls; odds ratio 0.4 (95% CI: 0.2–0.9) , P-value = 0.018. BMI and waterpipe smoking were statistically insignificant with acne in the multivariate analysis. Conclusion: We found that cigarette smoking was protective against Acne. There was a statistically insignificant relation between BMI, waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, adolescents, BMI, smoking, case-control, risk factors

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Authors: Thitima Plejai

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The practice in the operating room has been continually performed according to standards of services; however, undesirable incidents from surgical services are found such as surgical complications in the operating room. This participation action research aimed to develop practice guidelines for surgical safety management to reduce undesirable incidents from surgical services in the operating room of Songkhla Hospital. The target population was all 84 members of the multidisciplinary team who were involved in surgical services in the operating room consisting of 28 surgeons from five branches of surgery, 27 anesthetists and nurse anesthetists, and 29 surgical nurses. The data were collected through in-depth interviews, and non-participatory observations. The research instrument was tested by three experts, and the steps of the development consisted of four cycles, each consisting of assessment, planning, practice, practice reflection, and improvement until every step is practicable. The data were validated through triangulation research method, analyzed through content analysis and statistical analysis with number and percentage. The results of the development of practice guidelines surgical safety management to reduce undesirable incidents from surgical services could be concluded as follows. 1) The multidisciplinary team in surgery participated in the needs assessment for development of practice guidelines for surgical patient safety, and agreed on adapting the WHO Surgical Safety Checklists for use. 2) The WHO Surgical Safety Checklists was implemented, and meetings were held for the multidisciplinary team in surgery and the organizational risk committee to improve the practice guidelines to make them more practicable. 3) The multidisciplinary team consisting of surgeons from five branches of surgery, anesthetists, nurse anesthetists, surgical nurses, and the organizational risk committee announced policy on safety for surgical patients; the organizational risk committee designated the Surgical Safety Checklist as an instrument for surgical patient safety. The results of the safety management found that the surgical team members who could follow 100 percent of the guidelines were: professional nurses who checked patient identity and information before taking the patient to the operating room and kept complete records of data on the patients; surgical nurses who checked readiness of the patient before surgery; nurse anesthetists who assessed readiness before administering anesthetic drugs, and confirmed correctness of the patient; and circulating perioperative nurses who gave confirmation to the surgical team after completion of the surgery. The rates of undesirable incidents (surgical complications rates) before and after the implementation of the surgical safety management were 1.60 percent and 0.66 percent, respectively. The satisfaction of the surgery-related teams towards the use of the guidelines was 89 percent. The practice guidelines for surgical safety management to reduce undesirable incidents were taken as guidelines for surgical safety that the multidisciplinary team involved in the surgical process implemented correctly and in the same direction and clearly reduced undesirable incidents in surgical patients.

Keywords: practice guidelines, surgical safety management, reduce undesirable incidents, operating Room

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Authors: Maryam Nazari, Atefeh Ghanbari, Saghar Noorinia

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Obesity, as an abnormal or excessive accumulation of fat, is caused by genetic, behavioral and environmental factors. Recently, obesity surgeries, such as bariatric surgery, as the last measure to control obesity, have attracted experts and society, especially women, attention, so knowing the possible complications of this major surgery and their control in reproductive age is of particular importance due to its effects on pregnancy outcomes. Bariatric surgery reduces the risk of diabetes and high blood pressure associated with pregnancy, premature birth, macrosomia, stillbirth and dumping syndrome. Although in the first months after surgery, nausea and vomiting caused by changes in intra-abdominal pressure are associated with an increased risk of malabsorption of micronutrients such as folic acid, iron, vitamin B1, D, calcium, selenium and phosphorus and finally, fetal growth disorder. Moreover, serum levels of micronutrients such as vitamin D, calcium, and iron in mothers who used to have bariatric surgery and their babies have been shown to be lower than in mothers without a history of bariatric surgery. Moreover, vitamin A deficiency is shown to be more widespread in pregnancies after bariatric surgery, which leads to visual problems in newborns and premature delivery. However, complications such as the duration of hospitalization of newborns in the NICU, disease rate in the first 28 days of life and congenital anomalies are not significantly different in babies born to mothers undergoing bariatric surgery compared to the control group. In spite of the vast advantages following obesity surgeries, due to the catabolic conditions and severe weight loss followed by such major intervention and the probability of nutrients malnutrition in a pregnant woman and her baby, after having surgery, at least 12 to 18 months should be considered to get pregnant as a recovery period. In addition, taking essential supplements before and at least 6 months after this approach is recommended.

Keywords: bariatric surgery, pregnancy, malnutrition, vitamin and mineral deficiency

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, linear mixed model, multivariate conditional autoregressive model, spatial time series

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Authors: Shima Nikanjam, Badiossadat Hassanpour, Adi Irfan Che Ani

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The design process in architecture education is based upon the Learning-by-Doing method, which leads students to understand how to design by practicing rather than studying. First-year design studios, as starting educational stage, provide integrated knowledge and skills of design for newly jointed architecture students. Within the basic design studio environment, students are guided to transfer their abstract thoughts into visual concrete decisions under the supervision of design educators for the first time. Therefore, introductory design studios have predominant impacts on students’ operational thinking and designing. Architectural design thinking is quite different from students’ educational backgrounds and learning habits. This educational challenge at basic design studios creates a severe need to study the reality of design education at foundation year and define appropriate educational methods with convenient project types with the intention of enhancing architecture education quality. Material for this study has been gathered through long-term direct observation at a first year second semester design studio at the faculty of architecture at EMU (known as FARC 102), fall and spring academic semester 2014-15. Distribution of a questionnaire among case study students and interviews with third and fourth design studio students who passed through the same methods of education in the past 2 years and conducting interviews with instructors are other methodologies used in this research. The results of this study reveal a risk of a mismatch between the implemented teaching method, project type and scale in this particular level and students’ learning styles. Although the existence of such risk due to varieties in students’ profiles could be expected to some extent, recommendations can support educators to reach maximum compatibility.

Keywords: architecture education, basic design studio, educational method, forms creation skill

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

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Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: remote sensing, GIS, permanent residence, decision tree, Lebanon

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Authors: Naci Büyükkaracığan

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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, minimum flows, probability distribution

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

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Authors: Sundaresan Soundararajan, Chor Ngee Tan

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Introduction: Pyogenic spondylitis, otherwise treated conservatively with long term antibiotics, would require surgical debridement and reconstruction in about 10% to 20% of cases. The classical approach adopted many surgeons have always been anterior approach in ensuring thorough and complete debridement. This, however, comes with high rates of morbidity due to the nature of its access. Direct lateral retroperitoneal approach, which has been growing in usage in degenerative lumbar diseases, has the potential in treating pyogenic spondylitis with its ease of approach and relatively low risk of complications. Aims/Objectives: The objective of this study was to evaluate the effectiveness and clinical outcome of using lateral approach surgery in the surgical management of pyogenic spondylitis of the lumbar spine. Methods: Retrospective chart analysis was done on all patients who presented with pyogenic spondylitis (lumbar discitis/vertebral osteomyelitis) and had undergone direct lateral retroperitoneal lumbar vertebral debridement and posterior instrumentation between 2014 and 2016. Data on blood loss, surgical operating time, surgical complications, clinical outcomes and fusion rates were recorded. Results: A total of 6 patients (3 male and 3 female) underwent this procedure at a single institution by a single surgeon during the defined period. One patient presented with infected implant (PLIF) and vertebral osteomyelitis while the other five presented with single level spondylodiscitis. All patients underwent lumbar debridement, iliac strut grafting and posterior instrumentation (revision of screws for infected PLIF case). The mean operating time was 308.3 mins for all 6 cases. Mean blood loss was reported at 341cc (range from 200cc to 600cc). Presenting symptom of back pain resolved in all 6 cases while 2 cases that presented with lower limb weakness had improvement of neurological deficits. One patient had dislodged strut graft while performing posterior instrumentation and needed graft revision intraoperatively. Infective markers normalized for all patients subsequently. All subjects also showed radiological evidence of fusion on 6 months follow up. Conclusions: Lateral approach in treating pyogenic spondylitis is a viable option as it allows debridement and reconstruction without the risk that comes with other anterior approaches. It allows efficient debridement, short surgical time, moderate blood loss and low risk of vascular injuries. Clinical outcomes and fusion rates by this approach also support its use as practical MIS option surgery for such infection cases.

Keywords: lateral approach, minimally invasive, pyogenic spondylitis, XLIF

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Authors: Tadesse Melaku Abegaz, Akshaya Srikanth Bahagavathula, Abdulla Shehab Sheab, Asim Hassen

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Objectives: Non-adherence and discontinuation of anticoagulant therapy lead to increased ischemic stroke risk and contributes to suboptimal outcomes of the anticoagulant treatment. This systematic review and meta-analysis were aimed to investigate the adherence to NOACs and adverse events in patients with AF. Methods: Original research articles conducted on patients with AF and using any NOACs (dabigatran, rivoraxaban and apixaban) reporting adherence for at least 35 days were included. Scientific databases including PubMed, Web of Science, and Google Scholar were searched using MeSH keywords to obtaining literature researched between 2008 to till June, 2016. Study characteristics, patient’s sociodemographic and clinical characteristics, medication adherence levels and bleeding events reported were recorded. Results: The overall sample size of the six studies is 1,640,157, with CHADS2 scores < 2 in 551 patients, CHADS2-VASc ≥ 2 in 62,232 AF patients. Three-forth [75.6% (95%CI= 66.5-84.8), p < 0.001] are adherent to NOACs. However, a higher rate [72.7% (62.5-82.9), p < 0.001] of adherence was observed with Dabigatran than Apixaban [59.9% (3.2-123.1), p=0.063] and Rivaroxaban [59.3% (38.7-80.0), p<0.001]. Sub-group analysis revealed that nearly 57% of the AF patients on NOACs have CHADS2 scores < 2 and 20% of these patients were non-adherent to NOACs. Overall bleeding events rate associated with NOACs non-adherent AF patients was found to be 7.5% (0.2-14.8), p=0.045. However, nearly 11.2% of AF patients experienced bleeding events were non-adherent to NOAC medications. A higher proportion of bleeding events were noticed with Dabigatran (14.7%). Conclusions: Adherence rates, while uniformly suboptimal, nevertheless varied considerably, lowest at 59.3% for rivaroxaban and 59.9% for apixaban, followed by dabigatran (75.6%). Overall bleeding events associated with NOACs rates were 7.5%. However, lower adherence to NOACs was associated with worse outcomes among patients with greater stroke risk.

Keywords: atrial fibrillation, bleeding events, meta-analysis, novel oral anticoagulants

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Authors: Gal Friedman-Hauser, Carmit Katz

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Children and youth with disabilities (CWD) are at increased risk of experiencing sexual abuse compared to their peer group. This phenomenon is prevalent in both physical and online spaces, with the latter becoming an increasingly common platform for such abuse due to recent technological advances. Despite their heightened risk, the processes of disclosure and reporting of online child sexual abuse (OCSA) for CWD remain largely unexamined, leaving significant gaps in understanding how to effectively address their needs. The current study seeks to bridge this gap by examining aspects of disclosure and reporting of OCSA among CWD. The study aimed to identify patterns of reporting and disclosure, explore reactions of children's immediate social circle, and critically analyze the content of the reports, emphasizing both addressed and absent aspects. Using a qualitative-critical methodology, the study involved thematic content analysis of 25 case reports from a hotline in Israel dedicated to uncovering online crimes against children. The reports detailed cases of online sexual abuse involving children aged 11–17. Each report was accompanied by a statistical file classifying the child as having a disability. The findings of the study reveal a silenced phenomenon requiring urgent attention. Most cases of abuse were discovered by chance, often by parents, as children hesitated to disclose the abuse due to fears of negative reactions from family and society—fears that were often realized. Reporting was frequently delayed due to three main factors: lack of trust in the validity of the abuse claims attempts to resolve the situation without involving authorities, and a lack of understanding of the severity of the abuse. In addition, the findings have highlighted the reports primarily reflected parents' perspectives, with a limited representation of the children's voices. Moreover, the aspect of disability was mentioned only in general terms, without in-depth consideration. These findings underscore the marginalization of children with disabilities and the pressing need for tailored recognition of their needs in intervention and treatment processes following OCSA. The analysis of these findings provides a comprehensive understanding of the barriers faced by CWD who experience OCSA. To address these challenges, it is crucial to adopt an approach that simultaneously acknowledges the uniqueness of CWD and affirms their right to equal treatment. Such an approach must account for their increased risk of sexual abuse, the prevalence of underreporting, and the negative societal attitudes they often encounter. By recognizing CWD as both equal and different, interventions can more effectively support their specific needs and promote justice and protection in cases of OCSA

Keywords: children with disabilities, disclosure and reporting, online child sexual abuse, qualitative analysis

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Authors: Wei-Chih Huang, Pei-Lung Chung, Ching-Heng Lin, Hsuan-Chia Yang, Der-Ming Liou

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Background: In-Hospital Cardiac Arrest (IHCA) threaten life of the inpatients, cause serious effect to patient safety, quality of inpatients care and hospital service. Health providers must identify the signs of IHCA early to avoid the occurrence of IHCA. This study will consider the potential association between early signs of IHCA and the essence of patient care provided by nurses and other professionals before an IHCA occurs. The aim of this study is to identify significant associations between nursing interventions and abnormal early evaluation results of IHCA that can assist health care providers in monitoring inpatients at risk of IHCA to increase opportunities of IHCA early detection and prevention. Materials and Methods: This study used one of the data mining techniques called association rules mining to compute associations between nursing interventions and abnormal early evaluation results of IHCA. The nursing interventions and abnormal early evaluation results of IHCA were considered to be co-occurring if nursing interventions were provided within 24 hours of last being observed in abnormal early evaluation results of IHCA. The rule based methods were utilized 23.6 million electronic medical records (EMR) from a medical center in Taipei, Taiwan. This dataset includes 733 concepts of nursing interventions that coded by clinical care classification (CCC) codes and 13 early evaluation results of IHCA with binary codes. The values of interestingness and lift were computed as Q values to measure the co-occurrence and associations’ strength between all in-hospital patient care measures and abnormal early evaluation results of IHCA. The associations were evaluated by comparing the results of Q values and verified by medical experts. Results and Conclusions: The results show that there are 4195 pairs of associations between nursing interventions and abnormal early evaluation results of IHCA with their Q values. The indication of positive association is 203 pairs with Q values greater than 5. Inpatients with high blood sugar level (hyperglycemia) have positive association with having heart rate lower than 50 beats per minute or higher than 120 beats per minute, Q value is 6.636. Inpatients with temporary pacemaker (TPM) have significant association with high risk of IHCA, Q value is 47.403. There is significant positive correlation between inpatients with hypovolemia and happened abnormal heart rhythms (arrhythmias), Q value is 127.49. The results of this study can help to prevent IHCA from occurring by making health care providers early recognition of inpatients at risk of IHCA, assist with monitoring patients for providing quality of care to patients, improve IHCA surveillance and quality of in-hospital care.

Keywords: in-hospital cardiac arrest, patient safety, nursing intervention, association rule mining

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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Authors: Fasil Wagnew, Kerri Viney, Kefyalew Addis Alene, Matthew Kelly, Darren Gray

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Background: Undernutrition is a risk factor for tuberculosis (TB), including poor treatment outcomes. However, evidence regarding the effect of undernutrition on TB treatment outcomes is not well understood. We aimed to evaluate the effect of undernutrition on sputum culture conversion and treatment outcomes among people with multi-drug resistance (MDR)-TB. Methods: We searched for publications in the Medline, Embase, Scopus, and Web of Science databases without restrictions on geography or year of publication. We conducted a random-effect meta-analysis to estimate the effects of undernutrition on sputum culture conversion and treatment outcomes. Two reviewers independently assessed the study eligibility, extracted the necessary information, and assessed the risk of bias. Depending on the nature of the data, odds ratio (OR) and hazard ratio (HR) with 95% confidence intervals (CIs) were used to summarize the effect estimates. Potential publication bias was checked using funnel plots and Egger’s tests. Results: Of 2358 records screened, 59 studies comprising a total of 31,254 people with MDR-TB were included. Undernutrition was significantly associated with a lower sputum culture conversion rate (HR 0·7, 95% CI 0·6–0·9, I2=67·1%) and a higher rate of mortality (OR 2·9, 95%CI 2·1–3·8, I2=23·7%) and unfavourable treatment outcomes (OR 1·8, 95%CI 1·5–2·0, I2=72·7%). There was no statistically significant publication bias in the included studies. Three studies were low, forty-two studies were moderate, and fourteen studies were high quality. Interpretations: Undernutrition was significantly associated with unfavourable treatment outcomes, including mortality and lower sputum culture conversion among people with MDR-TB. These findings have implications for supporting targeted nutritional interventions alongside standardised second-line TB drugs.

Keywords: undernutrition, MDR-TB, sputum culture conversion, treatment outcomes, meta-analysis

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Marianna Iaroslavska

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ChatGPT is becoming commonplace. However, only a few people think about the legal risks of using Large Language Model in their daily work. The main dilemmas concern the following areas: who owns the copyright to what somebody creates through ChatGPT; what can OpenAI do with the prompt you enter; can you accidentally infringe on another creator's rights through ChatGPT; what about the protection of the data somebody enters into the chat. This paper will present these and other legal risks of using large language models at work using dogmatic methods and case studies. The paper will present a legal analysis of AI risks against the background of European Union law and Polish law. This analysis will answer questions about how to protect data, how to make sure you do not violate copyright, and what is at stake with the AI Act, which recently came into force in the EU. If your work is related to the EU area, and you use AI in your work, this paper will be a real goldmine for you. The copyright law in force in Poland does not protect your rights to a work that is created with the help of AI. So if you start selling such a work, you may face two main problems. First, someone may steal your work, and you will not be entitled to any protection because work created with AI does not have any legal protection. Second, the AI may have created the work by infringing on another person's copyright, so they will be able to claim damages from you. In addition, the EU's current AI Act imposes a number of additional obligations related to the use of large language models. The AI Act divides artificial intelligence into four risk levels and imposes different requirements depending on the level of risk. The EU regulation is aimed primarily at those developing and marketing artificial intelligence systems in the EU market. In addition to the above obstacles, personal data protection comes into play, which is very strictly regulated in the EU. If you violate personal data by entering information into ChatGPT, you will be liable for violations. When using AI within the EU or in cooperation with entities located in the EU, you have to take into account a lot of risks. This paper will highlight such risks and explain how they can be avoided.

Keywords: EU, AI act, copyright, polish law, LLM

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

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Natural hazard assessment and monitoring are crucial in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. For wildfire risk assessment, a scalar wildfire occurrence risk index is created based on the predictions of machine learning models. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. A reliable forecast of fire danger is a key component of integrated forest fire management and is heavily influenced by various factors that affect fire ignition and spread. The fire risk model is validated by the sensitivity and specificity metric. For flood risk assessment, a multi-faceted approach is employed, including the application of remote sensing techniques, the collection and processing of data from the most recent population and building census, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which will finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. Validation is carried out through historical flood events using remote sensing data and records from the civil protection authorities. For geohazards monitoring (e.g., landslides, subsidence), Synthetic Aperture Radar (SAR) and optical satellite imagery are combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. Validation is carried out through both geotechnical expert evaluations and visual inspections. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through capacity building activities, fostering continuous collaboration between Greek and Cypriot experts. Apart from the knowledge transfer, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the region's resilience to disasters. EXCELSIOR project funds knowledge exchange, demonstration actions and capacity-building activities and is committed to empower Cyprus with the tools and expertise to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgement:Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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Authors: Matthias Leitner, Gernot Pottlacher

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Experimental determination of critical point data like critical temperature, critical pressure, critical volume and critical compressibility of high-melting metals such as niobium is very rare due to the outstanding experimental difficulties in reaching the necessary extreme temperature and pressure regimes. Experimental techniques to achieve such extreme conditions could be diamond anvil devices, two stage gas guns or metal samples hit by explosively accelerated flyers. Electrical pulse-heating under increased pressures would be another choice. This technique heats thin wire samples of 0.5 mm diameter and 40 mm length from room temperature to melting and then further to the end of the stable phase, the spinodal line, within several microseconds. When crossing the spinodal line, the sample explodes and reaches the gaseous phase. In our laboratory, pulse-heating experiments can be performed under variation of the ambient pressure from 1 to 5000 bar and allow a direct determination of critical point data for low-melting, but not for high-melting metals. However, the critical point also can be estimated by extrapolating the liquid phase density according to theoretical models. A reasonable prerequisite for the extrapolation is the existence of data that cover as much as possible of the liquid phase and at the same time exhibit small uncertainties. Ohmic pulse-heating was therefore applied to determine thermal volume expansion, and from that density of niobium over the entire liquid phase. As a first step, experiments under ambient pressure were performed. The second step will be to perform experiments under high-pressure conditions. During the heating process, shadow images of the expanding sample wire were captured at a frame rate of 4 × 105 fps to monitor the radial expansion as a function of time. Simultaneously, the sample radiance was measured with a pyrometer operating at a mean effective wavelength of 652 nm. To increase the accuracy of temperature deduction, spectral emittance in the liquid phase is also taken into account. Due to the high heating rates of about 2 × 108 K/s, longitudinal expansion of the wire is inhibited which implies an increased radial expansion. As a consequence, measuring the temperature dependent radial expansion is sufficient to deduce density as a function of temperature. This is accomplished by evaluating the full widths at half maximum of the cup-shaped intensity profiles that are calculated from each shadow image of the expanding wire. Relating these diameters to the diameter obtained before the pulse-heating start, the temperature dependent volume expansion is calculated. With the help of the known room-temperature density, volume expansion is then converted into density data. The so-obtained liquid density behavior is compared to existing literature data and provides another independent source of experimental data. In this work, the newly determined off-critical liquid phase density was in a second step utilized as input data for the estimation of niobium’s critical point. The approach used, heuristically takes into account the crossover from mean field to Ising behavior, as well as the non-linearity of the phase diagram’s diameter.

Keywords: critical point data, density, liquid metals, niobium, ohmic pulse-heating, volume expansion

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