Search results for: clinical survey data simulation

Authors: Ariful Islam, Showkat Ahmad Lone

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Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

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Authors: Brendan Mooney

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Context: Feelings and emotions are commonly misunderstood and the terms often used interchangeably, leading to potential negative impacts on individuals' mental well-being and relationships. The distinction between these two fundamentally different experiences of human life is crucial for effective psychological practice and communication. Research Aim: The aim of this study is to outline the disparities between feelings and emotions, emphasising the significance of this differentiation in psychological practice to enhance clients' observation, decision-making, problem-solving, and communication skills. Methodology: This research utilises a conceptual model developed by the author in 2017 based on clinical experience, client observations, and feedback. The model serves to guide effective clinical practice by providing clear definitions and understanding of feelings versus emotions. Case study examples were utilised to support the efficacy of the model. Findings: The study highlights that recognising and expressing feelings rather than emotions is more empowering and conducive to resolving unresolved issues, thereby fostering better psychological well-being and interpersonal relationships. Theoretical Importance: This research underscores the importance of clarifying fundamental definitions related to feelings and emotions in enhancing psychological interventions and preventing various relationship conflicts and individual issues. Data Collection and Analysis Procedures: Data was collected through the author's clinical experience and interactions with clients, informing the development of the Feeling Emotions Mental (FEM) model. Analysis involved synthesising observations and feedback to elucidate the distinctions between feelings and emotions. Questions Addressed: What are the disparities between feelings and emotions? How does the confusion between these two fundamentally different experiences of human life impact individuals' mental well-being and relationships? Why is it essential to differentiate between feelings and emotions in psychological practice? Conclusion: The study advocates for a clear understanding of feelings versus emotions to support clients in addressing unresolved issues and improving their overall psychological functioning and communication skills, thereby preventing potential conflicts and relationship challenges.

Keywords: couples, mental, misinformation, misunderstanding, relationships

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Authors: J. Fernandez, R. Fernandez de Canete, J. Perea-Paizal, J. C. Ramos-Diaz

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The high prevalence of cardiovascular diseases has provoked a raising interest in the development of mathematical models in order to evaluate the cardiovascular function both under physiological and pathological conditions. In this paper, a physical model of the cardiovascular system with intrinsic regulation is presented and implemented by using the object-oriented Modelica simulation software tools.  For this task, a multi-compartmental system previously validated with physiological data has been built, based on the interconnection of cardiovascular elements such as resistances, capacitances and pumping among others, by following an electrohydraulic analogy. The results obtained under both physiological and pathological scenarios provide an easy interpretative key to analyze the hemodynamic behavior of the patient. The described approach represents a valuable tool in the teaching of physiology for graduate medical and nursing students among others.

Keywords: cardiovascular system, MODELICA simulation software, physical modelling, teaching tool

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Authors: Amber Elyse Corrigan, Alexander Smith, Anna Pennington, Ben Carter, Jonathan Hewitt

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Background and Purpose: Morbidity secondary to stroke is highly heterogeneous, but it is important to both patients and clinicians in post-stroke management and adjustment to life after stroke. The consideration of post-stroke morbidity clinically and from the patient perspective has been poorly measured. The patient-reported outcome measures (PROs) in morbidity assessment help improve this knowledge gap. The primary aim of this study was to consider the association between PRO outcomes and stroke predictors. Methods: A multicenter prospective cohort study assessed 549 stroke patients at 19 hospital sites across England and Wales during 2019. Following a stroke event, demographic, clinical, and PRO measures were collected. Prevalence of morbidity within PRO measures was calculated with associated 95% confidence intervals. Predictors of domain outcome were calculated using a multilevel generalized linear model. Associated P -values and 95% confidence intervals are reported. Results: Data were collected from 549 participants, 317 men (57.7%) and 232 women (42.3%) with ages ranging from 25 to 97 (mean 72.7). PRO morbidity was high post-stroke; 93.2% of the cohort report post-stroke PRO morbidity. Previous stroke, diabetes, and gender are associated with worse patient-reported outcomes across both the physical and cognitive domains. Conclusions: This large-scale multicenter cohort study illustrates the high proportion of morbidity in PRO measures. Further, we demonstrate key predictors of adverse outcomes (Diabetes, previous stroke, and gender) congruence with clinical predictors. The PRO has been demonstrated to be an informative and useful stroke when considering patient-reported outcomes and has wider implications for considerations of PROs in clinical management. Future longitudinal follow-up with PROs is needed to consider association of long-term morbidity.

Keywords: morbidity, patient-reported outcome, PRO, stroke

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Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

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This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Debjyoti Bhakat, Indranil Mondal, Asish K. Mukhopadayay, Nabendu S. Chatterjee

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Enterotoxigenic Escherichia coli is one of the leading causes of diarrhea in infants and travelers in developing countries. Colonization factors play an important role in pathogenesis and are one of the main targets for Enterotoxigenic Escherichia coli (ETEC) vaccine development. However, ETEC vaccines had poorly performed in the past, as the prevalence of colonization factors is region-dependent. There are more than 25 classical colonization factors presently known to be expressed by ETEC, although all are not expressed together. Further, there are other multiple non-classical virulence factors that are also identified. Here the presence and expression of common classical and non-classical virulence factors were studied. Further studies were done on the expression of prevalent colonization factors in different strains. For the prevalence determination, multiplex polymerase chain reaction (PCR) was employed, which was confirmed by simplex PCR. Quantitative RT-PCR was done to study the RNA expression of these virulence factors. Strains negative for colonization factors expression were confirmed by SDS-PAGE. Among the clinical isolates, the most prevalent toxin was est+elt, followed by est and elt, while the pattern was reversed in the control strains. There were 29% and 40% strains negative for any classical colonization factors (CF) or non-classical virulence factors (NCVF) among the clinical and control strains, respectively. Among CF positive ETEC strains, CS6 and CS21 were the prevalent ones in the clinical strains, whereas in control strains, CS6 was the predominant one. For NCVF genes, eatA was the most prevalent among the clinical isolates and etpA for control. CS6 was the most expressed CF, and eatA was the predominantly expressed NCVF for both clinical and controlled ETEC isolates. CS6 expression was more in strains having CS6 alone. Different strains express CS6 at different levels. Not all strains expressed their respective virulence factors. Understanding the prevalent colonization factor, CS6, and its nature of expression will contribute to designing an effective vaccine against ETEC in this region of the globe. The expression pattern of CS6 also will help in examining the relatedness between the ETEC subtypes.

Keywords: classical virulence factors, CS6, diarrhea, enterotoxigenic escherichia coli, expression, non-classical virulence factors

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Authors: Kamonwat Suksumek, Seeronk Prichanont

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Access block refers to the situation where Emergency Department (ED) patients requiring hospital admission spend an unreasonable holding time in an ED because their access to a ward is blocked by the full utilization of the ward’s beds. Not only it delays the proper treatments required by the patients, but access block is also the cause of ED’s overcrowding. Clearly, access block is an inter-departmental problem that needs to be brought to management’s attention. This paper focuses on the analysis of strategies to address the access block problem, both in the operational and intermediate levels. These strategies were analyzed through a simulation model with a real data set from a university hospital in Thailand. The paper suggests suitable variable levels for each strategy so that the management will make the final decisions.

Keywords: access block, emergency department, health system analysis, simulation

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Authors: Siti Hajar Muhamad Rosli, Xin Yi Lim, Terence Yew Chin Tan, Muhammad nor Farhan Sa’At, Syazwani Sirdar Ali, Ami Fazlin Syed Mohamed

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A growing interest on therapeutic benefits of hemp (Cannabis sativa subsp. sativa) is evident in the pharmaceutical market, attributed to its lower levels of psychoactive constituent delta-9-tetrahydronannabidiol (THC). Deemed as a legal and safer alternative to its counterpart marijuana, the use of medicinal hemp is highly debatable as current scientific evidence on the efficacy for clinical use is yet to be established This study was aimed to provide an overview of the current landscape of hemp research, through recent clinical findings specific to the pharmacological properties of the hemp plant and its derived compounds. A systematic search was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis-ScR (PRISMA) checklist on electronic databases (MEDLINE, OVID, Cochrane Library Central, and Clinicaltrials.gov) for articles published from 2009 to 2019. With predetermined inclusion criteria, all human trials with hemp intervention were included. A total of 18 human trials were identified, investigating therapeutic effects on the neuronal, gastrointestinal, musculoskeletal and immune system, with sample sizes ranging from one to 194 subjects. Three randomised controlled trials showed hempseed pills (in Traditional Chinese Medicine formulation MaZiRenWan) consumption significantly improved spontaneous bowel movement in functional constipation. The use of commercial cannabidiol (CBD) sourced from hemp suggested benefits in cannabis dependence, epilepsy, and anxiety disorders. However, there was insufficient evidence to suggest analgesic or anxiolytics effects of hemp being equivalent to marijuana. All clinical trials reviewed varied in terms of test item formulation and standardisation, which made it challenging to confirm overall efficacy for a specific disease or condition. Published efficacy data on hemp are still at a preliminary level, with limited high quality clinical evidence for any specific therapeutic indication. With multiple variants of this plant having different phytochemical and bioactive compounds, future empirical research should focus on uniformity in experimental designs to further strengthen the notion of using medicinal hemp.

Keywords: cannabis, complementary medicine, hemp, herbal medicine.

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Authors: Ayesha Ali, Emilia Lindquist, Arif Jalal, Hannah Yusuf, Kayan Cheung, Rowan Eastabrook

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It is currently estimated that over a third of deaths in children under five in Tanzania are caused by acute respiratory infections (ARIs). However, despite being one of the leading causes of morbidity and mortality across the developing world, its risk factors are poorly understood. Therefore, a systematic review of the literature published between 2015 and 2020 was conducted, focusing on risk factors for ARI in Tanzanian children under the age of five. 2015 Demographic and Health Survey (DHS) for Tanzania was analysed to supplement these findings with national data. 2224 papers were retrieved from two databases and were analysed by three independent reviewers. Thirteen papers were eligible for inclusion, covering a wide range of risk factors among which comorbidities (n=6), malnutrition (n=5), lack of parental education (n=4), poor socio-economic status (n=3), and delay in seeking healthcare (n=3) were the most cited risk factors. The risk factors with the highest reported risk ratios/odds ratios were lack of parental education (RR=11.5-14.5), followed by enrolment in school (RR=4.4), delay in seeking healthcare (RR=3.8) and cooking indoors (aOR =1.8-RR=5.5). The DHS data provided local context to these risk factors. For instance, the number of children experiencing symptoms of ARI in both urban and rural areas ranged between 4.5-5% in the two weeks prior to the survey. However, 79% of symptomatic children in Zanzibar received antibiotics for treatment compared to just 34% of those in the Southern Highlands. As demonstrated by both the systematic review and the DHS analysis, risk factors for ARI are predominantly socially determined, with Tanzania’s poorer rural children possessing the highest risk for ARI and more adverse health outcomes. Therefore, the burden of ARIs in Tanzanian children may be alleviated through the provision of appropriate treatment and parental education in rural areas.

Keywords: acute respiratory infection, child, health education, morbidity, mortality, pneumonia, Tanzania

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Authors: Xiaoyuan Chen

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Background: This study aimed to characterize the epidemiological and clinical features of five rare subtypes of hepatocellular carcinoma (HCC) and to create a competing risk nomogram for predicting cancer-specific survival. Methods: This study used the Surveillance, Epidemiology, and End Results database to analyze the clinicopathological data of 50,218 patients with classic HCC and five rare subtypes (ICD-O-3 Histology Code=8170/3-8175/3) between 2004 and 2018. The annual percent change (APC) was calculated using Joinpoint regression, and a nomogram was developed based on multivariable competing risk survival analyses. The prognostic performance of the nomogram was evaluated using the Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve. Decision curve analysis was used to assess the clinical value of the models. Results: The incidence of scirrhous carcinoma showed a decreasing trend (APC=-6.8%, P=0.025), while the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality plateau in all subtypes during the period. Clear cell carcinoma was the most common subtype (n=551, 1.1%), followed by fibrolamellar (n=241, 0.5%), scirrhous (n=82, 0.2%), spindle cell (n=61, 0.1%), and pleomorphic (n=17, ~0%) carcinomas. Patients with fibrolamellar carcinoma were younger and more likely to have non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro clinical characteristics and outcomes as classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were identified as independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice. Conclusion: The rare subtypes of HCC had distinct clinicopathological features and biological behaviors compared with classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could accurately predict prognoses, which is beneficial for individualized management.

Keywords: hepatocellular carcinoma, pathological subtype, fibrolamellar carcinoma, scirrhous carcinoma, clear cell carcinoma, spindle cell carcinoma, pleomorphic carcinoma

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Authors: Ben Tappin, Ryan McKay

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The political left and right appear to disagree not only over questions of value but, also, over questions of fact—over what is true “out there” in society and the world. Alarmingly, a large body of survey data collected during the past decade suggests that this disagreement tends to be greatest among the most educated and most cognitively sophisticated opposing partisans. In other words, the data show that these individuals display the widest political polarization in their reported factual beliefs. Explanations of this polarization pattern draw heavily on cultural and political factors; yet, the large majority of the evidence originates from one cultural and political context—the United States, a country with a rather unique cultural and political history. One consequence is that widening political polarization conditional on education and cognitive sophistication may be due to idiosyncratic cultural, political or historical factors endogenous to US society—rather than a more general, international phenomenon. We examined widening political polarization conditional on education across Europe, over a topic that is culturally and politically contested; immigration. To do so, we analyzed data from the European Social Survey, a premier survey of countries in and around the European area conducted biennially since 2002. Our main results are threefold. First, we see widening political polarization conditional on education over beliefs about the economic impact of immigration. The foremost countries showing this pattern are the most influential in Europe: Germany and France. However, we also see heterogeneity across countries, with some—such as Belgium—showing no evidence of such polarization. Second, we find that widening political polarization conditional on education is a product of sorting. That is, highly educated partisans exhibit stronger within-group consensus in their beliefs about immigration—the data do not support the view that the more educated partisans are more polarized simply because the less educated fail to adopt a position on the question. Third, and finally, we find some evidence that shocks to the political climate of countries in the European area—for example, the “refugee crisis” of summer 2015—were associated with a subsequent increase in political polarization over immigration conditional on education. The largest increase was observed in Germany, which was at the centre of the so-called refugee crisis in 2015. These results reveal numerous insights: they show that widening political polarization conditional on education is not restricted to the US or native English-speaking culture; that such polarization emerges in the domain of immigration; that it is a product of within-group consensus among the more educated; and, finally, that exogenous shocks to the political climate may be associated with subsequent increases in political polarization conditional on education.

Keywords: beliefs, Europe, immigration, political polarization

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Authors: Jiajia Peng, Danni Cheng, Jianqing Qiu, Yufang Rao, Minzi Mao, Ke Qiu, Junhong Li, Fei Chen, Feng Liu, Jun Liu, Xiaosong Mu, Wenxin Yu, Wei Zhang, Wei Xu, Yu Zhao, Jianjun Ren

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Background: Currently, primary B-cell non-Hodgkin lymphoma (B-NHL) and T/NK-cell non-Hodgkin lymphoma (NKT-NHL) originated from the nasal cavity (NC), nasopharynx (NP) and nasal sinus (NS) distinguished unclearly in the clinic. Objective: We sought to compare the clinical and survival differences of B-NHL and NKT-NHL that occurred in NC, NP, and NS, respectively. Methods: Retrospective data of patients diagnosed with nasal cavity lymphoma (NCL), nasopharyngeal lymphoma (NPL), and nasal sinus lymphoma (NSL) between 1975 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database were collected. We identified the B/NKT-NHL patients based on the histological type and performed univariate, multivariate, and Kaplan-Meier analyses to investigate the survival rates. Results: Of the identified 3,101 B-NHL and 738 NKT-NHL patients, those with B-NHL in NP were the majority (43%) and had better cancer-specific survival than those in NC and NS from 2010 to 2017 (5-year-CSS, NC vs. NP vs. NS: 81% vs. 83% vs. 82%). In contrast, most of the NKT-NHL originated from NC (68%) and had the highest CSS rate in the recent seven years (2010-2017, 5-year-CSS: 63%). Additionally, the survival outcomes of patients with NKT-NHL-NP (HR: 1.34, 95% CI: 0.62-2.89, P=0.460) who had received surgery were much worse than those of patients with NKT-NHL-NC (HR: 1.07, 95% CI: 0.75-1.52, P=0.710) and NKT-NHL-NS (HR: 1.11, 95% CI: 0.59-2.07, P=0.740). NKT-NHL-NS patients who had radiation performed (HR: 0.38, 95% CI: 0.19-0.73, P=0.004) showed the highest survival rates, while chemotherapy performed (HR: 1.01, 95% CI: 0.43-2.37, P=0.980) presented opposite results. Conclusions: Although B-NHL and NKT-NHL originating from NC, NP and NS had similar anatomical locations, their clinical characteristics, treatment therapies, and prognoses were different in this study. Our findings may suggest that B-NHL and NKT-NHL in NC, NP, and NS should be treated as different diseases in the clinic.

Keywords: nasopharyngeal lymphoma, nasal cavity lymphoma, nasal sinus lymphoma, B-cell non-Hodgkin lymphoma, T/NK-cell non-Hodgkin lymphoma

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Authors: D. Naranchimeg, G. Ulziisaikhan

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Student dropout problem has not been recently investigated within the Mongolian higher education. A student dropping out is a personal decision, but it may cause unemployment and other social problems including low quality of life because students who are not completed a degree cannot find better-paid jobs. The research aims to determine percentage of at-risk students, and understand reasons for dropouts and to find a way to predict. The study based on the students of the Mongolian National University of Education including its Arkhangai branch school, National University of Mongolia, Mongolian University of Life Sciences, Mongolian University of Science and Technology, Mongolian National University of Medical Science, Ikh Zasag International University, and Dornod University. We conducted the paper survey by method of random sampling and have surveyed about 100 students per university. The margin of error - 4 %, confidence level -90%, and sample size was 846, but we excluded 56 students from this study. Causes for exclusion were missing data on the questionnaire. The survey has totally 17 questions, 4 of which was demographic questions. The survey shows that 1.4% of the students always thought to dropout whereas 61.8% of them thought sometimes. Also, results of the research suggest that students’ dropouts from university do not have relationships with their sex, marital and social status, and peer and faculty climate, whereas it slightly depends on their chosen specialization. Finally, the paper presents the reasons for dropping out provided by the students. The main two reasons for dropouts are personal reasons related with choosing wrong study program, not liking the course they had chosen (50.38%), and financial difficulties (42.66%). These findings reveal the importance of early prevention of dropout where possible, combined with increased attention to high school students in choosing right for them study program, and targeted financial support for those who are at risk.

Keywords: at risk students, dropout, faculty climate, Mongolian universities, peer climate

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Authors: Alaa Abdullah Altaee

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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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Authors: Hsin-Yun Lee

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In this study, the pedestrian simulation VISWALK integration and application platform ant algorithms written program made to construct a renovation engineering schedule planning mode. The use of simulation analysis platform construction site when the user running the simulation, after calculating the user walks in the case of construction delays, the ant algorithm to find out the minimum delay time schedule plan, and add volume and unit area deactivated loss of business computing, and finally to the owners and users of two different positions cut considerations pick out the best schedule planning. To assess and validate its effectiveness, this study constructed the model imported floor of a shopping mall floor renovation engineering cases. Verify that the case can be found from the mode of the proposed project schedule planning program can effectively reduce the delay time and the user's walking mall loss of business, the impact of the operation on the renovation engineering facilities in the building to a minimum.

Keywords: pedestrian, renovation, schedule, simulation

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Authors: Siddhartha Paul, Debabrata Das

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Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

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Authors: Steffen Schieweck, Johannes Dregger, Sascha Kaczmarek, Michael ten Hompel

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Logistics distributors face the issue of having to provide increasing service levels while being forced to reduce costs at the same time. Same-day delivery, quick order processing and rapidly growing ranges of articles are only some of the prevailing challenges. One key aspect of the performance of an intra-logistics system is how often and in which amplitude congestions and dysfunctions affect the processing operations. By gaining knowledge of the so called ‘performance availability’ of such a system during the planning stage, oversizing and wasting can be reduced whereas planning transparency is increased. State of the art for the determination of this KPI are simulation studies. However, their structure and therefore their results may vary unforeseeably. This article proposes a concept for the establishment of ‘certified’ and hence reliable and comparable simulation models.

Keywords: intra-logistics, performance availability, simulation, warehousing

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Authors: Nassim Salmi

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Postoperative mobilization is an important part of fundamental care. Increased mobilization has a positive effect on recovery, but immobilization is still a challenge in postoperative care. Aims: To report how the establishment of a national nursing database was used to measure postoperative mobilization in patients undergoing surgery for ovarian cancer. Mobilization was defined as at least 3 hours out of bed on postoperative day 1, with the goal set at achieving this in 60% of patients. Clinical nurses on 4400 patients with ovarian cancer performed data entry. Findings: 46.7% of patients met the goal for mobilization on the first postoperative day, but variations in duration and type of mobilization were observed. Of those mobilized, 51.8% had been walking in the hallway. A national nursing database creates opportunities to optimize fundamental care. By comparing nursing data with oncological, surgical, and pathology data, it became possible to study mobilization in relation to cancer stage, comorbidity, treatment, and extent of surgery.

Keywords: postoperative care, gynecology, nursing documentation, database

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Authors: Tharaki Hetti Arachchi

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Sri Lanka has undergone numerous changes in the fields of social-economic and cultural processors during the past decades. Consequently, the Sri Lankan construction industry was subjected to rapid growth while contributing a considerable amount to the national economy. The prevailing situation under the Covid-19 pandemic exhibited challenges to almost all of the sectors of the country in attaining success. Although productivity is one of the dimensions that measure the degree of project success, achieving sufficient productivity has become challengeable due to the Covid-19 outbreak. As employee motivation is an influential factor in defining productivity, the present study becomes significant in discovering ways of enhancing construction productivity via employee motivation. The study has adopted a combination of qualitative and quantitative methodologies in attaining the study objectives. While the research population refers to construction professionals in Sri Lanka, the study sample is aimed at Quantity Surveyors in the bottom and middle managements of organizational hierarchies. The data collection was implemented via primary and secondary sources. The primary data collection was accomplished by undertaking semi-structured interviews and online questionnaire surveys while sampling the overall respondents based on the purposive sample method. The responses of the questionnaire survey were gathered in a form of a ‘Likert Scale’ to examine the degree of applicability on each respondent. Overall, 76.36% of primary data were recovered from the expected count while obtaining 60 responses from the questionnaire survey and 24 responses from interviews. Secondary data were obtained by reviewing sources such as research articles, journals, newspapers, books, etc. The findings suggest adopting and enhancing sixteen motivational factors in achieving greater productivity in the Sri Lankan construction sector.

Keywords: Covid 19 pandemic, motivation, quantity surveying, Sri Lanka

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Kingston Rajiah, Mari Kannan Maharajan, Si Jen Yeen, Sara Lew

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder with evolving layers of complexity. Both motor and non-motor symptoms of PD may affect patients’ quality of life (QoL). Life expectancy for an individual with Parkinson’s disease depends on the level of care the individual has access to, can have a direct impact on length of life. Therefore, improvement of the QoL is a significant part of therapeutic plans. Patients with PD, especially those who are in advanced stages, are in great need of assistance, mostly from their family members or caregivers in terms of medical, emotional, and social support. The role of a caregiver becomes increasingly important with the progression of PD, the severity of motor impairment and increasing age of the patient. The nature and symptoms associated with PD can place significant stresses on the caregivers’ burden. As the prevalence of PD is estimated to more than double by 2030, it is important to recognize and alleviate the burden experienced by caregivers. This study focused on the impact of the clinical features on the QoL of PD patients, and of their caregivers. This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale (MDS-UPDRS); the Hoehn and Yahr Staging of Parkinson's Disease were used to assess the severity and Parkinson's disease activities of daily living scale were used to assess the disability of Parkinson’s disease patients. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden. At least one of the clinical features affected PD patients’ QoL, and at least one of the QoL domains affected the caregivers’ burden. Clinical features ‘Saliva and Drooling’, and ‘Dyskinesia’ explained 29% of variance in QoL of PD patients. The QoL domains ‘stigma’, along with ‘emotional wellbeing’ explained 48.6% of variance in caregivers’ burden. Clinical features such as saliva, drooling and dyskinesia affected the QoL of PD patients. The PD patients’ QoL domains such as ‘stigma’ and ‘emotional well-being’ influenced their caregivers’ burden.

Keywords: carers, quality of life, clinical features, Malaysia

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Authors: Monika Jurkeviciute, Amia Enam, Johanna Torres Bonilla, Henrik Eriksson

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Introduction: Many evaluations of eHealth interventions conclude that the evidence for improved clinical outcomes is limited, especially when the intervention is short, such as one year. Often, evaluation design does not address the feasibility of achieving clinical outcomes. Evaluations are designed to reflect upon clinical goals of intervention without utilizing the opportunity to illuminate effects on organizations and cost. A comprehensive design of evaluation can better support decision-making regarding the effectiveness and potential transferability of eHealth. Hence, the purpose of this paper is to present a feasible and comprehensive design of evaluation for eHealth intervention, including the design process in different contexts. Methodology: The situation of limited feasibility of clinical outcomes was foreseen in the European Union funded project called “DECI” (“Digital Environment for Cognitive Inclusion”) that is run under the “Horizon 2020” program with an aim to define and test a digital environment platform within corresponding care models that help elderly people live independently. A complex intervention of eHealth implementation into elaborate care models in four different countries was planned for one year. To design the evaluation, a participative approach was undertaken using Pettigrew’s lens of change and transformations, including context, process, and content. Through a series of workshops, observations, interviews, and document analysis, as well as a review of scientific literature, a comprehensive design of evaluation was created. Findings: The findings indicate that in order to get evidence on clinical outcomes, eHealth interventions should last longer than one year. The content of the comprehensive evaluation design includes a collection of qualitative and quantitative methods for data gathering which illuminates non-medical aspects. Furthermore, it contains communication arrangements to discuss the results and continuously improve the evaluation design, as well as procedures for monitoring and improving the data collection during the intervention. The process of the comprehensive evaluation design consists of four stages: (1) analysis of a current state in different contexts, including measurement systems, expectations and profiles of stakeholders, organizational ambitions to change due to eHealth integration, and the organizational capacity to collect data for evaluation; (2) workshop with project partners to discuss the as-is situation in relation to the project goals; (3) development of general and customized sets of relevant performance measures, questionnaires and interview questions; (4) setting up procedures and monitoring systems for the interventions. Lastly, strategies are presented on how challenges can be handled during the design process of evaluation in four different countries. The evaluation design needs to consider contextual factors such as project limitations, and differences between pilot sites in terms of eHealth solutions, patient groups, care models, national and organizational cultures and settings. This implies a need for the flexible approach to evaluation design to enable judgment over the effectiveness and potential for adoption and transferability of eHealth. In summary, this paper provides learning opportunities for future evaluation designs of eHealth interventions in different national and organizational settings.

Keywords: ehealth, elderly, evaluation, intervention, multi-cultural

Procedia PDF Downloads 327

Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

Procedia PDF Downloads 129

Authors: Farouk Lawan Gambo

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Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning.

Keywords: data analysis, compression techniques, learning content, traditional learning approach

Procedia PDF Downloads 351

Authors: L. Agneni, F. Carta, C. Micheletta, V. Tersigni

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The development of a qualitative method to profile jobseekers is needed to improve the quality of the Public Employment Services (PES) in Italy. This is why the National Agency for Active Labour Market Policies (ANPAL) decided to introduce a Qualitative Profiling Service in the context of the activities carried out by local employment offices’ operators. The qualitative profiling service provides information and data regarding the jobseeker’s personal transition status, through a semi-structured questionnaire administered to PES clients during the guidance interview. The questionnaire responses allow PES staff to identify, for each client, proper activities and policy measures to support jobseekers in their reintegration into the labour market. Data and information gathered by the qualitative profiling tool are the following: frequency, modalities and motivations for clients to apply to local employment offices; clients’ expectations and skills; difficulties that they have faced during the previous working experiences; strategies, actions undertaken and activated channels for job search. These data are used to assess jobseekers’ personal and career characteristics and to measure their employability level (qualitative profiling index), in order to develop and deliver tailor-made action programmes for each client. This paper illustrates the use of the above-mentioned qualitative profiling service on the national territory and provides an overview of the main findings of the survey: concerning the difficulties that unemployed people face in finding a job and their perception of different aspects related to the transition in the labour market. The survey involved over 10.000 jobseekers registered with the PES. Most of them are beneficiaries of the “citizens' income”, a specific active labour policy and social inclusion measure. Furthermore, data analysis allows classifying jobseekers into a specific group of clients with similar features and behaviours, on the basis of socio-demographic variables, customers' expectations, needs and required skills for the profession for which they seek employment. Finally, the survey collects PES staff opinions and comments concerning clients’ difficulties in finding a new job and also their strengths. This is a starting point for PESs’ operators to define adequate strategies to facilitate jobseekers’ access or reintegration into the labour market.

Keywords: labour market transition, public employment services, qualitative profiling, vocational guidance

Procedia PDF Downloads 145

Authors: Pisit Poolprasert, Auttpol Nakwa, Keerati Tanruean, Ezra Mongkolchaichana, Ezra Mongkolchaichana, Sinlapachai Senarat, Mark Tunmore

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This present preliminary study aimed to observe the butterfly species diversity in two selected subdistricts i.e., Mae Klong and Umphang of Umphang district, Tak province, northern Thailand, during May to September 2018. A survey method using sweep net was employed along line transects between 10.00-12.00 a.m. and 13.00-15.00 p.m. A total of 337 butterflies representing 37 species, 26 genera in five families were encountered. The family Nymphalidae held the highest species richness (15 species), followed by Papilionidae (9 species) and Pieridae (6 speices), respectively. Herein, four uncommon species, namely Junonia iphita iphita, Tanaecia julii odilina, Penthema darlisa melema, and Papilio alcmenor alcmenor, were discovered in this time. The Shannon diversity (H’) for all samples obtained from the pooled data set of this observation valued 2.563 with relatively high values of Evenness (J’= 0.710) and Simpson index and (D = 0.829). For similarity index (Ss), the assemblage recorded of butterfly species between Mae Klang-Umphang shared about 0.629, implying that the environmental conditions in both surveyed zones were alike. Additionally, the accumulation curve in both locations of the butterfly was still increasing gradually when the collection ended, indicating that the lepidopteran species would be raised if we continue to survey more in next month. Nevertheless, to gain more butterfly taxa, observing different plant communities covering every season and using several survey techniques should be considered for further investigation.

Keywords: butterfly, biodiversity, tak province, thailand

Procedia PDF Downloads 118

Authors: Masoumeh Khailghi Sikaroudi, Mohsen Masoodi, Fazad Shidfar, Meghdad Sedaghat

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Background: The hypertonicity of internal anal sphincter resting pressure is one of the main reasons for chronic anal fissures. The aim of this study is to assess the effect of oral administration of L-arginine on anal fissure symptom improvement by relaxation of the internal anal sphincter. Method: Seventy-six chronic anal fissure patients (age: 18-65 years) took part in this randomized, double-blind, placebo-controlled trial study from February 2019 to October 2020 at Rasoul-e-Akram Hospital, Tehran, Iran. Participants were allocated into treatment (L-arginine) or placebo groups. They took a 1000 mg capsule three times a day for one month and were followed up at the end of the first and third months after receiving the intervention. Clinical symptoms, anal sphincter resting pressure, and quality of life (QoL) were completed at baseline and the end of the study. Result: The analysis of data was shown significant improvement in bleeding, fissure size, and pain within each group; however, this effect was more seen in the arginine group compared to the control group at the end of the study (P-values<0.001). Following that, a significant increase in QoL was seen just in patients who were treated with arginine (P-value=0.006). Also, the comparison of anal pressures to baseline and between groups at the end of the study showed a significant reduction in sphincter pressure in treated patients (P-value<0.001, =0.049; respectively). Conclusion: Oral administration of 3000 mg L-arginine can heal chronic anal fissures by reducing anal internal sphincter pressure with fewer side effects. However, a long-term study with more follow-up is recommended.

Keywords: L-arginine, anal fissure, sphincter pressure, clinical symptoms, quality of life

Procedia PDF Downloads 75

Authors: Amando A. Radomes Jr., LLoyd Jun Benjamin T. Embernatre, Cherssy Kaye F. Eviota, Krizia Allyn L. Nunez, Jose Thaddeus B. Roble III

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Sitio Kantaling is one of the 34 villages in Danao City, Cebu, in the central Philippines. As of 2015, the eight households in the mountainous village extending over 40 hectares of land area, including 12 hectares of arable land, are the source of over a fifth of the agricultural products that go into the city. Over the years, however, the local government had been concerned with the decline in agricultural productivity because increasing number of residents are migrating into the urban areas of the region to look for better employment opportunities. One of the major reasons for the agricultural productivity decline is underdeveloped irrigation infrastructure. The local government had partnered with the University of San Carlos to conduct research on developing an irrigation system that could sustainably meet both agricultural and household consumption needs. From a macro-perspective, a dynamic simulation model was developed to understand the long-term behavior of the status quo and proposed the system. Data on population, water supply and demand, household income, and urban migration were incorporated in the 20-year horizon model. The study also developed a smart irrigation system design. Instead of using electricity to pump water, a network of aqueducts with three main nodes had been designed and strategically located to take advantage of gravity to transport water from a spring. Simulation results showed that implementing a sustainable irrigation system would be able to significantly contribute to the socio-economic progress of the local community.

Keywords: agriculture, aqueduct, simulation, sustainable irrigation system

Procedia PDF Downloads 172

Authors: Tobias Huttche, Marco Canipa-Valdez, Corinne Mühlebach

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This article discusses the role of leasing on the digital transformation process of companies and corresponding economic effects. Based on the traditional mechanisms of leasing, this article focuses in particular on the benefits of leasing as financing instrument with regard to the innovation potential of companies. Practical examples demonstrate how leasing can become an integral part of new business models. Especially, with regard to the digital transformation and corresponding investments in know-how and infrastructure, leasing can play an important role. Furthermore, findings of an empirical survey are presented dealing with the usage of leasing in Switzerland in an international context. The survey shows not only the benefits of leasing against the backdrop of digital transformation but gives guidance on how other countries can benefit from promoting leasing in their legislation and economy. Based on a simulation model for Switzerland, the economic effect of an increase in leasing volume is being calculated. Again, the respective results underline the substantial growth potential. This holds true especially for economies where asset-based lending is rarely used because of a lack of entrepreneurial or private security of the borrower (cash-based financing for developing and emerging countries). Overall, the authors found that leasing using companies are more productive and tend to grow faster than companies using less or none leasing. The positive effects of leasing on emerging digital challenges for companies and entire economies should encourage other countries to facilitate access to leasing as financing instrument by decreasing legal-, tax- and accounting-related requirements in the respective jurisdiction.

Keywords: Cash-Based financing, digital transformation, financing instruments, growth, innovation, leasing

Procedia PDF Downloads 259

Authors: H. A. Mansour

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The objective of this research work is studying the water use prediction, prediction technology for water use by action agencies, and others involved in conservation, planning, and environmental assessment of the Water Erosion Prediction Project (WEPP) simulation model. Models the important physical, processes governing erosion in Egypt (climate, infiltration, runoff, ET, detachment by raindrops, detachment by flowing water, deposition, etc.). Simulation of the non-uniform slope, soils, cropping/management., and Egyptian databases for climate, soils, and crops. The study included important parameters in Egyptian conditions as follows: Water Balance & Percolation, Soil Component (Tillage impacts), Plant Growth & Residue Decomposition, Overland Flow Hydraulics. It could be concluded that we can adapt the WEPP simulation model to determining the previous important parameters under Egyptian conditions.

Keywords: WEPP, adaptation, soil properties, tillage impacts, water balance, soil percolation

Procedia PDF Downloads 302