Search results for: measurement bias

Authors: Rosemary Hiscock, Clive Sabel, David Manley, Sam Wren-Lewis

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As part of the Happy City Index Project, Happy City have developed a survey instrument to measure experienced wellbeing: how people are feeling and functioning in their everyday lives. The survey instrument, called the Happiness Pulse, was developed in partnership with the New Economics Foundation (NEF) with the dual aim of collecting citywide wellbeing data and engaging individuals and communities in the measurement and promotion of their own wellbeing. The survey domains and items were selected through a review of the academic literature and a stakeholder engagement process, including local policymakers, community organisations and individuals. The Happiness Pulse was included in the Bristol pilot of the Happy City Index (n=722). The experienced wellbeing items were subjected to factor analysis. A reduced number of items to be included in a revised scale for future data collection were again entered into a factor analysis. These revised factors were tested for reliability and validity. Among items to be included in a revised scale for future data collection three factors emerged: Be, Do and Connect. The Be factor had good reliability, convergent and criterion validity. The Do factor had good discriminant validity. The Connect factor had adequate reliability and good discriminant and criterion validity. Some age, gender and socioeconomic differentiation was found. The properties of a new scale to measure experienced wellbeing, intended for use by municipal authorities, are described. Happiness Pulse data can be combined with local data on wellbeing conditions to determine what matters for peoples wellbeing across a city and why.

Keywords: city wellbeing , community wellbeing, engaging individuals and communities, measuring wellbeing and happiness

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Authors: Masoud Ghahvechi Pour

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Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

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Authors: Kamrun N. Keya, Nasrin A. Kona, Ruhul A. Khan

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Pineapple leaf fiber (PALF) reinforced polypropylene (PP) based composites were fabricated by a conventional compression molding technique. In this investigation, PALF composites were manufactured using different percentages of fiber, which were varying from 25-50% on the total weight of the composites. To fabricate the PALF/PP composites, untreated and treated fibers were selected. A systematic study was done to observe the physical, mechanical and interfacial behavior of the composites. In this study, mechanical properties of the composites such as tensile, impact and bending properties were observed precisely. It was found that 45wt% of fiber composites showed better mechanical properties than others. Maximum tensile strength (TS) and bending strength (BS) was observed, 65 MPa and 50 MPa respectively, whereas the highest tensile modulus (TM) and bending modulus (BM) was examined, 1.7 GPa and 0.85 GPa respectively. The PALF/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (2.5 kGy to 10 kGy). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 5.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray ) gamma dose showed better mechanical properties than other doses. The values of TS, BS, TM, and BM of the irradiated (5.0 kGy) composites were found to improve by 19%, 23%, 17% and 25 % over non-irradiated composites. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated PALF/PP based composites showed better fiber-matrix adhesion and interfacial bonding than untreated PALF/PP based composites. Water uptake and soil degradation tests of untreated and treated composites were also investigated.

Keywords: PALF, polypropylene, compression molding technique, gamma radiation, mechanical properties, scanning electron microscope

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Authors: M. R. Akbari, H. Yousefnia, A. Ghasemi

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Al2O3:C,Mg fluorescent nuclear track detector (FNTD) and Al2O3:C optically stimulated luminescence detector (OSLD) are becoming two of the applied detectors in ion dosimetry. Therefore, the response of these detectors to hadron beams is highly of interest in radiation therapy (RT) using ion beams. In this study, these detectors' responses to proton and Helium-4 ion beams were compared using Monte Carlo simulations. The calculated data for proton beams were compared with Markus ionization chamber (IC) measurement (in water phantom) from M.D. Anderson proton therapy center. Monte Carlo simulations were performed via the FLUKA code (version 2011.2-17). The detectors were modeled in cylindrical shape at various depths of the water phantom without shading each other for obtaining relative depth dose in the phantom. Mono-energetic parallel ion beams in different incident energies (100 MeV/n to 250 MeV/n) were collided perpendicularly on the phantom surface. For proton beams, the results showed that the simulated detectors have over response relative to IC measurements in water phantom. In all cases, there were good agreements between simulated ion ranges in the water with calculated and experimental results reported by the literature. For proton, maximum peak to entrance dose ratio in the simulated water phantom was 4.3 compared with about 3 obtained from IC measurements. For He-4 ion beams, maximum peak to entrance ratio calculated by both detectors was less than 3.6 in all energies. Generally, it can be said that FLUKA is a good tool to calculate Al2O3:C,Mg FNTD and Al2O3:C OSLD detectors responses to therapeutic proton and He-4 ion beams. It can also calculate proton and He-4 ion ranges with a reasonable accuracy.

Keywords: comparison, FNTD and OSLD detectors response, light ion beams, Monte Carlo simulations

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Authors: Adrian Hang Yue Siu, Matthew Holyland, Sharon Carey, Daniel Steffens, Nabila Ansari, Cherry E. Koh

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Introduction: Peritoneal malignancies are challenging cancers to manage. While cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS and HIPEC) may offer a cure, it’s considered radical and morbid. Pre-emptive identification of deconditioned patients for optimization may mitigate the risks of surgery. However, the difficulty lies in the scarcity of validated predictive tools to identify high-risk patients. In recent times, there has been growing interest in sarcopenia, which can occur as a result of malnutrition and malignancies. Therefore, the purpose of this study was to assess the utility of sarcopenia in predicting post-operative outcomes. Methods: A single quaternary-center retrospective study of CRS and HIPEC patients between 2017-2020 was conducted to determine the association between pre-operative sarcopenia and post-operative outcomes. Lumbar CT images were analyzed using Slice-o-matic® to measure sarcopenia. Results : Cohort (n=94) analysis found that 40% had sarcopenia, with a majority being female (53.2%) and a mean age of 55 years. Sarcopenia was statistically associated with decreased weight compared to non-sarcopenia patients, 72.7kg vs. 82.2kg (p=0.014) and shorter overall survival, 1.4 years vs. 2.1 years (p=0.032). Post-operatively, patients with sarcopenia experienced more post-operative complications (p=0.001). Conclusion: Complex procedures often require optimization to prevent complications and improve survival. While patient biomarkers – BMI and weight – are used for optimization, this research advocates for the identification of sarcopenia status for pre-operative planning. Sarcopenia may be an indicator of advanced disease requiring further treatment and is an emerging area of research. Larger studies are required to confirm these findings and to assess the reversibility of sarcopenia after surgery.

Keywords: sarcopaenia, cytoreductive surgery, hyperthermic intraperitoneal chemotherapy, surgical oncology

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Authors: Yahya Asanoglu, Celaletdin Ergun

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Ceramic-matrix composites (CMC) have significant prominence in various engineering applications because of their heat resistance associated with an ability to withstand the brittle type of catastrophic failure. In this study, specific raw materials have been chosen for the purpose of having suitable CMC material for high-temperature dielectric applications. CMC material will be manufactured through the polymer infiltration and pyrolysis (PIP) method. During the manufacturing process, vacuum infiltration and autoclave will be applied so as to decrease porosity and obtain higher mechanical properties, although this advantage leads to a decrease in the electrical performance of the material. Time and temperature adjustment in pyrolysis parameters provide a significant difference in the properties of the resulting material. The mechanical and thermal properties will be investigated in addition to the measurement of dielectric constant and tangent loss values within the spectrum of Ku-band (12 to 18 GHz). Also, XRD, TGA/PTA analyses will be employed to prove the transition of precursor to ceramic phases and to detect critical transition temperatures. Additionally, SEM analysis on the fracture surfaces will be performed to see failure mechanism whether there is fiber pull-out, crack deflection and others which lead to ductility and toughness in the material. In this research, the cost-effectiveness and applicability of the PIP method will be proven in the manufacture of CMC materials while optimization of pyrolysis time, temperature and cycle for specific materials is detected by experiment. Also, several resins will be shown to be a potential raw material for CMC radome and antenna applications. This research will be distinguished from previous related papers due to the fact that in this research, the combination of different precursors and fabrics will be experimented with to specify the unique cons and pros of each combination. In this way, this is an experimental sum of previous works with unique PIP parameters and a guide to the manufacture of CMC radome and antenna.

Keywords: CMC, PIP, precursor, quartz

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Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

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Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Renata Roma, Christine Tardif-Williams

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Engaging in daily walks with a dog (f.e. Canis lupus familiaris) during the COVID-19 pandemic may be linked to feelings of greater social-connectedness and global self-worth, and lower stress after controlling for mental health issues, lack of physical contact with others, and other stressors associated with the current pandemic. Therefore, maintaining a routine of dog walking might mitigate the effects of stressors experienced during the pandemic and promote well-being. However, many dog owners do not walk their dogs for many reasons, which are related to the owner’s and the dog’s personalities. Note that the consistency of certain personality characteristics among dogs demonstrates that it is possible to accurately measure different dimensions of personality in both dogs and their human counterparts. In addition, behavioural ratings (e.g., the dog personality questionnaire - DPQ) are reliable tools to assess the dog’s personality. Clarifying the relevance of personality factors in the context of young adult-dog relationships can shed light on interactional aspects that can potentially foster protective behaviours and promote well-being among young adults during the pandemic. This study examines if and how nine combinations of dog- and young adult-related personality characteristics (e.g., neuroticism-fearfulness) can amplify the influence of personality factors in the context of dog walking during the COVID-19 pandemic. Responses to an online large-scale survey among 440 (389 females; 47 males; 4 nonbinaries, Mage=20.7, SD= 2.13 range=17-25) young adults living with a dog in Canada were analyzed using structural equation modeling (SEM). As extraversion, conscientiousness, and neuroticism, measured through the five-factor model (FFM) inventory, are related to maintaining a routine of physical activities, these dimensions were selected for this analysis. Following an approach successfully adopted in the field of dog-human interactions, the FFM was used as the organizing framework to measure and compare the human’s and the dog’s personality in the context of dog walking. The dog-related personality dimensions activity/excitability, responsiveness to training, and fearful were correlated dimensions captured through DPQ and were added to the analysis. Two questions were used to assess dog walking. The actor-partner interdependence model (APIM) was used to check if the young adult’s responses about the dog were biased; no significant bias was observed. Activity/excitability and responsiveness to training in dogs were greatly associated with dog walking. For young adults, high scores in conscientiousness and extraversion predicted more walks with the dog. Conversely, higher scores in neuroticism predicted less engagement in dog walking. For participants high in conscientiousness, the dog’s responsiveness to training (standardized=0.14, p=0.02) and the dog’s activity/excitability (standardized=0.15, p=0.00) levels moderated dog walking behaviours by promoting more daily walks. These results suggest that some combinations in young adult and dog personality characteristics are associated with greater synergy in the young adult-dog dyad that might amplify the impact of personality factors on young adults’ dog-walking routines. These results can inform programs designed to promote the mental and physical health of young adults during the Covid-19 pandemic by highlighting the impact of synergy and reciprocity in personality characteristics between young adults and dogs.

Keywords: Covid-19 pandemic, dog walking, personality, structural equation modeling, well-being

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Authors: Pakawhat Khumkhreung, Yottana Khunatorn

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The flow pattern inside rectangular intake air duct of 300 MW lignite coal-fired power plant is investigated in order to analyze and reduce overall inlet system pressure drop. The system consists of the 45-degree inlet elbow, the flow instrument, the 90-degree mitered elbow and fans, respectively. The energy loss in each section can be determined by Bernoulli’s equation and ASHRAE standard table. Hence, computational fluid dynamics (CFD) is used in this study based on Navier-Stroke equation and the standard k-epsilon turbulence modeling. Input boundary condition is 175 kg/s mass flow rate inside the 11-m² cross sectional duct. According to the inlet air flow rate, the Reynolds number of airstream is 2.7x10⁶ (based on the hydraulic duct diameter), thus the flow behavior is turbulence. The numerical results are validated with the real operation data. It is found that the numerical result agrees well with the operating data, and dominant loss occurs at the flow rate measurement device. Normally, the air flow rate is measured by the airfoil and it gets high pressure drop inside the duct. To overcome this problem, the airfoil is planned to be replaced with the other type measuring instrument, such as the average pitot tube which generates low pressure drop of airstream. The numerical result in case of average pitot tube shows that the pressure drop inside the inlet airstream duct is decreased significantly. It should be noted that the energy consumption of inlet air system is reduced too.

Keywords: airfoil, average pitot tube, combustion air, CFD, pressure drop, rectangular duct

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Authors: Viveka Jackson, Erouscilla Joseph, Denise Beckles, Thomas Christopher

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Sulphur Dioxide (SO2) has been defined as a non-flammable, non-explosive, colourless gas, having a pungent, irritating odour, and is one of the main gases emitted from volcanoes. Sulphur dioxide has been recorded in concentrations hazardous to humans (0.25 – 0.5 ppm (~650 – 1300 μg/m3), downwind of many volcanoes and hence warrants constant air-quality monitoring around these sites. It has been linked to an increase in chronic respiratory disease attributed to long-term exposures and alteration in lung and other physiological functions attributed to short-term exposures. Sulphur Springs in Saint Lucia is a highly active geothermal area, located within the Soufrière Volcanic Centre, and is a park widely visited by tourists and locals. It is also a current source of continuous volcanic emissions via its many fumaroles and bubbling pools, warranting concern by residents and visitors to the park regarding the effects of exposure to these gases. In this study, we introduce a novel SO2 measurement system for the monitoring and quantification of ambient levels of airborne volcanic SO2 using low-cost technology. This work involves the extensive production of low-cost SO2 monitors/samplers, as well as field examination in tandem with standard commercial samplers (SO2 diffusion tubes). It also incorporates community involvement in the volcanic monitoring process as non-professional users of the instrument. We intend to present the preliminary monitoring results obtained from the low-cost samplers, to identify the areas in the Park exposed to high concentrations of ambient SO2, and to assess the feasibility of the instrument for non-professional use and application in volcanic settings

Keywords: ambient SO2, community-based monitoring, risk-reduction, sulphur springs, low-cost

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Authors: Nisha Harry, Keshia Sing

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Orientation: The Multifactor Leadership Questionnaire (MLF) and the sense of coherence-29 (SCS) is an effective tools to assess the prevalence and underlying structures of empirically based taxonomies related to leadership and wellbeing. Research purpose: The purpose of the study was to test the psychometric properties of the SCS and Multifactor Leadership Questionnaire (MLQ) to screen for psychological wellness indices within the banking industry in South Africa. Motivation for the study: The contribution of these two instruments for the purpose of determining psychological wellness in a banking work environment is unique. Research design, approach, or method: The sample consisted of (N = 150) financial staff employed in a South African banking organisation. The age of the sample was: 37% (30 -40 yrs), 31% (20-30 yrs), 26% (40- 50 yrs), and 6% (50+yrs), of which 52% were males, 48% were females. The white race group was the majority at 29%, African at 26%, Coloured at 23%, and Indian was 22%. Main findings: Results from the exploratory factor analysis revealed a two-factor structure as the most satisfactory. Confirmatory factor analyses revealed the two-factor model displayed better good of-fit indices. Practical implications: The factor structure of the Sense of Coherence-29 scale (SCS), and the Multifactor Leadership Questionnaire (MLQ), have a value-added focus to determine psychological wellness within banking staff. It is essential to take into account these constructs when developing employee wellness interventions. Contribution/value add: Understanding the psychometric properties of the SCS, the self-reported form, and the MLQ questionnaire contributes to screening psychological wellness indices such as coping within the banking industry in a developing country like South Africa. Leaders are an important part of the implementation process of organisational employee wellness practices.

Keywords: factorial structure, leadership, measurement invariance, psychological wellness, sense of coherence

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Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

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This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarness^TM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HR_max). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: physiological status monitoring (PSM), heart rate (HR), breathing rate (BR), Arabian Gulf

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Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Arzyana Sunkar, Yanto Santosa

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The expansions of independent smallholdings in Indonesia are feared to increase the negative ecological impacts of oil palm plantation on biodiversity. Hence, research is required to identify the conservation importance of independent smallholder oil palm plantations on biodiversity. This paper discussed the role of independent smallholdings in the conservation of biodiversity in oil palm plantations and to compare it with High Conservation Value Forest as a conservation standard of RSPO. The research was conducted from March to April 2016. Data on biodiversity were collected on 16 plantations and 8 private oil palm plantations in the Districts of Kampar, Pelalawan, Kuantan, Singingi and Siak of Riau Province, Indonesia. In addition, data on community environmental perceptions of both smallholder plantation and High Conservation Value (HCV) Forest were also collected. Species that were observed were birds and earthworms. Data on birds were collected using transect method, while identification of earthworm was determine by taking some soil samples and counting the number of individual earthworm found for each worm species. The research used direct interview with oil palm owners and community members, as well as direct observation to examine the environmental conditions of each plantation. In general, field observation and measurement have found that birds species richness was higher in the forested HCV Forest. Nevertheless, if compared to non-forested HCV, bird’s species richness was higher in the independent smallholdings. On the other hand, different results were observed for earthworm, where the density was higher in the independent smallholdings than in the HCV. It can be concluded from this research that managing independent smallholder oil palm plantations and forested HCV forest could enhance biodiversity conservation. The results of this study justified the importance of retaining forested area to safeguard biodiversity in oil palm plantation.

Keywords: biodiversity conservation, high conservation value forest, independent smallholdings, oil palm plantations

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Authors: Alabi Olushola John, Ogbiko Anthonia, Tsado Daniel Nma, Mbajiorgu Ejike Felix, Adama Theophilus Zubairu

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A total of thirty (30) goats weighting between 5.8 and 7.3 kg were used to determine the growth performance, body linear measurements and body condition score of Semi intensively manged Savanna Brown goats fed enzyme treated sawdust diets (ETSD). They divided into five dietary treatments (T) groups with three replications using a completely randomized design. Treatment one (1) comprises of animals fed diet on 0 % enzyme treated sawdust while Treatment 2 (T2), Treatment 3 (T3), Treatment 4 (T4) and Treatment 5 (T5) comprises of animals fed diets containing 10, 20, 30 and 40 % enzyme treated sawdust diets, respectively. The study lasted 16 weeks. Data on growth performance parameters, body linear measurement (height at wither, body length, chest girth, hind leg length, foreleg length, facial length) and body condition score were collected and analyzed using one way analysis of variance. No significant difference (p>0.05) was observed in the all growth performance parameters and linear body measurements. However, significant difference was observed in body length and daily body length gains with highest value observed in animals fed the control diets (7.38 and 0.08 cm respectively) and animals on 30 % ETSD (7.25 and 0.07 cm respectively) and lowest values (4.75 and 0.05 cm respectively) were observed in animals fed 10 % ETSD among the treatment groups. It was, therefore, concluded that enzyme treated sawdust can be used in the diets of Savanna Brown goats up to 40 % replacement for maize offal since this treatment improved the body length and daily body length gains.

Keywords: performance, sawdust, enzyme treated, semi-intensively, replacement

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Authors: Arya Farjand

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The Nihewan Basin is a critical region in order to understand the Plio-Pleistocene paleoenvironment and its fauna in Northern China. The rich fossiliferous, fluvial-lacustrine sediments around the Nihewan Village hosted the specimens known as the Classic Nihewan Fauna. The primary excavations in the early 1920-30s produced more than 2000 specimens housed in Tianjin and Paris Museum. Nevertheless, the exact locality of excavations, fossil beds, and the reliable ages remained ambiguous until recent paleomagnetic studies and extensive work in conjunction sites. In this study, for the first time, we successfully relocated some of the original excavation sites. We reexamined more than 1500 specimens held in Tianjin Museum and cited their locality numbers and properties. During the field-season of 2017-2019, we visited the Xiashagou Valley. By reading the descriptions of the original site, utilization of satellite pictures, and comparing them with the current geomorphology of the area, we ensured the exact location of 26 of these sites and 17 fossil layers. Furthermore, by applying the latest technologies, such as GPS, Compass, digital barometers, laser measurer, and Abney level, we ensured the accuracy of the measurement. We surveyed 133-meter thickness of the deposits. Ultimately by applying the available Paleomagnetic data for this section, we estimated the ages of different horizons. The combination of our new data and previously published researches present a unique age control for the Classic Nihewan Fauna. These findings prove the hypothesis in which the Classic Nihewan Fauna belongs to different horizons, ranging from before Reunion up to after Olduvai earth geomagnetic field excursion (2.2-1.7 Mya).

Keywords: classic Nihewan basin fauna, Olduvai excursion, Pleistocene, stratigraphy

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Authors: Claudia Martínez-Araneda, Mariella Gutiérrez, Pedro Gómez, Diego Maldonado, Alejandra Segura, Christian Vidal-Castro

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The purpose of this document is to showcase the preliminary work in developing an EduChatbot-type tool and measuring the effects of its use aimed at providing effective feedback to students in programming courses. This bot, hereinafter referred to as tutorBot+, was constructed based on chatGPT and is tasked with assisting and delivering timely positive feedback to students in the field of computer science at the Universidad Católica de Concepción. The proposed working method consists of four stages: (1) Immersion in the domain of Large Language Models (LLMs), (2) Development of the tutorBot+ prototype and integration, (3) Experiment design, and (4) Intervention. The first stage involves a literature review on the use of artificial intelligence in education and the evaluation of intelligent tutors, as well as research on types of feedback for learning and the domain of chatGPT. The second stage encompasses the development of tutorBot+, and the final stage involves a quasi-experimental study with students from the Programming and Database labs, where the learning outcome involves the development of computational thinking skills, enabling the use and measurement of the tool's effects. The preliminary results of this work are promising, as a functional chatBot prototype has been developed in both conversational and non-conversational versions integrated into an open-source online judge and programming contest platform system. There is also an exploration of the possibility of generating a custom model based on a pre-trained one tailored to the domain of programming. This includes the integration of the created tool and the design of the experiment to measure its utility.

Keywords: assessment, chatGPT, learning strategies, LLMs, timely feedback

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Authors: Tugba Sevinc Gamsiz, Emine Koroglu, Ozcan Keskin

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Aim: Nonalcoholic fatty liver disease (NAFLD) is considered the most common chronic liver disease in the general population. The higher mortality and morbidity among NAFLD patients and lack of symptoms makes early detection and management important. In our study, we aimed to evaluate the relationship between noninvasive imaging and biochemical markers in diabetic and nondiabetic patients diagnosed with NAFLD. Materials and Methods: The study was conducted from (September 2017) to (December 2017) on adults admitted to Internal Medicine and Gastroenterology outpatient clinics with hepatic steatosis reported on ultrasound or transient elastography within the last six months that exclude patients with other liver diseases or alcohol abuse. The data were collected and analyzed retrospectively. Number cruncher statistical system (NCSS) 2007 program was used for statistical analysis. Results: 116 patients were included in this study. Diabetic patients compared to nondiabetics had significantly higher Controlled Attenuation Parameter (CAP), Liver Stiffness Measurement (LSM) and fibrosis values. Also, hypertension, hepatomegaly, high BMI, hypertriglyceridemia, hyperglycemia, high A1c, and hyperuricemia were found to be risk factors for NAFLD progression to fibrosis. Advanced fibrosis (F3, F4) was present in 18,6 % of all our patients; 35,8 % of diabetic and 5,7 % of nondiabetic patients diagnosed with hepatic steatosis. Conclusion: Transient elastography is now used in daily clinical practice as an accurate noninvasive tool during follow-up of patients with fatty liver. Early diagnosis of the stage of liver fibrosis improves the monitoring and management of patients, especially in those with metabolic syndrome criteria.

Keywords: diabetes, elastography, fatty liver, fibrosis, metabolic syndrome

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

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Authors: Nehal Adel Khalil, Amel Foad Ketat, Fairouz Elsayed Mohamed Ali, Nahla Abdelmoneim Hamid, Hazem Farag Manaa

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Background: Chronic myeloid leukemia (CML) represents 15% of adult leukemias. Imatinib Mesylate (IM) is the gold standard treatment for new cases of CML. Treatment with IM results in improvement of the majority of cases. However, about 25% of cases may develop resistance. Sensitive and specific early predictors of IM resistance in CML patients have not been established to date. Aim: To investigate the value of miR-451 in CML as an early predictor for IM resistance in Egyptian CML patients. Methods: The study employed Real time Polymerase Reaction (qPCR) technique to investigate the leucocytic expression of miR-451 in fifteen newly diagnosed CML patients (group I), fifteen IM responder CML patients (group II), fifteen IM resistant CML patients (group III) and fifteen healthy subjects of matched age and sex as a control group (group IV). The response to IM was defined as < 10% BCR-ABL transcript level after 3 months of therapy. The following parameters were assessed in subjects of all the studied groups: 1- Complete blood count (CBC). 2- Measurement of plasma level of miRNA 451 using real-time Polymerase Chain Reaction (qPCR). 3- Detection of BCR-ABL gene mutation in CML using qPCR. Results: The present study revealed that miR-451 was significantly down-regulated in leucocytes of newly diagnosed CML patients as compared to healthy subjects. IM responder CML patients showed an up-regulation of miR- 451 compared with IM resistant CML patients. Conclusion: According to the data from the present study, it can be concluded that leucocytic miR- 451 expression is a useful additional follow-up marker for the response to IM and a promising prognostic biomarker for CML.

Keywords: chronic myeloid leukemia, imatinib resistance, microRNA 451, Polymerase Chain Reaction

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Authors: Siddharatha Sharma

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With the advent of technology and machines, the role of biometrics in society is taking an important place for secured living. Security issues are the major concern in today’s world and continue to grow in intensity and complexity. Biometrics based recognition, which involves precise measurement of the characteristics of living beings, is not a new method. Fingerprints are being used for several years by law enforcement and forensic agencies to identify the culprits and apprehend them. Biometrics is based on four basic principles i.e. (i) uniqueness, (ii) accuracy, (iii) permanency and (iv) peculiarity. In today’s world fingerprints are the most popular and unique biometrics method claiming a social benefit in the government sponsored programs. A remarkable example of the same is UIDAI (Unique Identification Authority of India) in India. In case of fingerprint biometrics the matching accuracy is very high. It has been observed empirically that even the identical twins also do not have similar prints. With the passage of time there has been an immense progress in the techniques of sensing computational speed, operating environment and the storage capabilities and it has become more user convenient. Only a small fraction of the population may be unsuitable for automatic identification because of genetic factors, aging, environmental or occupational reasons for example workers who have cuts and bruises on their hands which keep fingerprints changing. Fingerprints are limited to human beings only because of the presence of volar skin with corrugated ridges which are unique to this species. Fingerprint biometrics has proved to be a high level authentication system for identification of the human beings. Though it has limitations, for example it may be inefficient and ineffective if ridges of finger(s) or palm are moist authentication becomes difficult. This paper would focus on uniqueness of fingerprints to the human beings in comparison to other living beings and review the advancement in emerging technologies and their limitations.

Keywords: fingerprinting, biometrics, human beings, authentication

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Authors: Sylwia Gieraltowska, Lukasz Wachnicki, Bartlomiej S. Witkowski, Marek Godlewski

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Oxide layers doped with rare-earth (RE) ions in optimized way can absorb short (ultraviolet light), which will be converted to visible light by so-called down-conversion. Down-conversion mechanisms are usually exploited to modify the incident solar spectrum. In down conversion, multiple low-energy photons are generated to exploit the energy of one incident high-energy photon. These RE-doped oxide materials have attracted a great deal of attention from researchers because of their potential for optical manipulation in optical devices (detectors, temperature sensors, and compact solid-state lasers, light-emitting diodes), bio-analysis, medical therapy, display technologies, and light harvesting (such as in photovoltaic cells). The zirconium dioxide (ZrO2) doped RE ions (Eu, Tb, Ce) multilayer structures were tested as active layers, which can convert short wave emission to light in the visible range (the down-conversion mechanism). For these applications original approach of deposition ZrO2 layers using the Atomic Layer Deposition (ALD) method and doping these layers with RE ions using the spin-coating technique was used. ALD films are deposited at relatively low temperature (well below 250°C). This can be an effective method to achieve the white-light emission and to improve on this way light conversion efficiency, by an extension of absorbed spectral range by a solar cell material. Photoluminescence (PL), X-ray diffraction (XRD), scanning electron microscope (SEM) and atomic force microscope (AFM) measurement are analyzed. The research was financially supported by the National Science Centre (decision No. DEC-2012/06/A/ST7/00398 and DEC- 2013/09/N/ST5/00901).

Keywords: ALD, oxide layers, photovoltaics, thin films

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Authors: Yu Guan, Song Lu, Wei Yuan, Heping Zhang

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Gas fire extinguishing system is widely used due to its cleanliness and efficiency, and since its spray will be affected by many factors such as convection and obstacles in jetting region, so in order to evaluate its effectiveness, detecting concentration distribution in the jetting area is indispensable, which is commonly achieved by aspirating concentration detection technique. During the concentration measurement, the response time of detector is a very important parameter, especially for those fire-extinguishing systems with rapid gas dispersion. Long response time will not only underestimate its concentration but also prolong the change of concentration with time. Therefore it is necessary to analyze the factors influencing the response time. In the paper, an aspirating concentration detection method was introduced, which is achieved by using a small critical nozzle and a laminar flowmeter, and because of the response time is mainly related to the gas transport process from sampling site to the sensor, the effects of exhaust pipe size, gas flow rate, and gas concentration on its response time were analyzed. During the research, Bromotrifluoromethane (CBrF₃) was used. The effect of the sampling tube was investigated with different length of 1, 2, 3, 4 and 5 m (5mm in pipe diameter) and different pipe diameter of 3, 4, 5, 6 and 8 mm (3m in length). The effect of gas flow rate was analyzed by changing the throat diameter of the critical nozzle with 0.5, 0.682, 0.75, 0.8, 0.84 and 0.88 mm. The effect of gas concentration on response time was studied with the concentration range of 0-25%. The result showed that the response time increased with the increase of both the length and diameter of the sampling pipe, and the effect of length on response time was linear, but for the effect of diameter, it was exponential. It was also found that as the throat diameter of critical nozzle increased, the response time reduced a lot, in other words, gas flow rate has a great influence on response time. For the effect of gas concentration, the response time increased with the increase of the CBrF₃ concentration, and the slope of the curve was reduced.

Keywords: aspirating concentration detection, fire extinguishing, gaseous agent, response time

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Authors: A. M. Maruthesh, B. M. Anandakumar, O. Kumara, Akshatha Gombi, S. R. Rajini

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Women play a vital role in ensuring proper development and growth of children. They also contribute significantly towards income generation, food preparation and health. Nutritional status reflects the health of a person and is influenced by the quality of foods eaten and the ability of the body to utilize these foods to meet its needs it is affected by various socio-economic factors including income, family size, occupation and educational status of the people. The study was undertaken on nutritional status of rural women in Heggadehalli of Doddaballapurtaluk and Venkathalli of Devanahallitaluk in Bengaluru rural district with the sample size of 200 respondents. The prevalence of symptoms of malnutrition in a community is in turn a reflection of dietary consumption of its members. Mean anthropometric measurement of rural women were 153.8 cm of height, 46.8 kg of weight. In comparison with the mean BMI standards, it was observed that 20 percent of women were under nourished, 64 percent of women were normal and 16 percent women were obese. In comparison with the mean waist/hip ratio with standards, it was observed that 84 percent were in normal category and 16 percent were obese. Education, land holding, income and age had significant positive association with anthropometric measurements of rural women. The deficient level of haemoglobin existed in 53 percent of rural women, low in 20 percent and only 27 percent had acceptable level. The occurrence of morbidity symptoms was higher in rural women, its illness reported among women in the study were pain in hands and legs, backache, headache, pain in abdomen, fever, weakness, cold and cough and acidity. This may be due to considerable amount of workload on women who spend 8 to 9 hours at work and after returning continue their day’s work at home also.

Keywords: anthrometry, body index, hemoglobin, nutrient deficiency, rural women, nutritional status

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Authors: Lubena Achmad, Herman Kristanto, Julian Dewantiningrum

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Background: The Bishop score is a standard method used to predict the success of induction. This examination tends to be subjective with high inter and intraobserver variability, so it was presumed to have a low predictive value in terms of the outcome of labor induction. Cervical length measurement using transvaginal ultrasound is considered to be more objective to assess the cervical length. Meanwhile, this examination is not a complicated procedure and less invasive than vaginal touché. Objective: To compare transvaginal ultrasound and Bishop score in predicting successful induction. Methods: This study was a prospective cohort study. One hundred and twenty women with singleton pregnancies undergoing induction of labor at 37 – 42 weeks and met inclusion and exclusion criteria were enrolled in this study. Cervical assessment by both transvaginal ultrasound and Bishop score were conducted prior induction. The success of labor induction was defined as an ability to achieve active phase ≤ 12 hours after induction. To figure out the best cut-off point of cervical length and Bishop score, receiver operating characteristic (ROC) curves were plotted. Logistic regression analysis was used to determine which factors best-predicted induction success. Results: This study showed significant differences in terms of age, premature rupture of the membrane, the Bishop score, cervical length and funneling as significant predictors of successful induction. Using ROC curves found that the best cut-off point for prediction of successful induction was 25.45 mm for cervical length and 3 for Bishop score. Logistic regression was performed and showed only premature rupture of membranes and cervical length ≤ 25.45 that significantly predicted the success of labor induction. By excluding premature rupture of the membrane as the indication of induction, cervical length less than 25.3 mm was a better predictor of successful induction. Conclusion: Compared to Bishop score, cervical length using transvaginal ultrasound was a better predictor of successful induction.

Keywords: Bishop Score, cervical length, induction, successful induction, transvaginal sonography

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Authors: Chun Yu, Tahlia M. Farrant, Max G. Marschall

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Most of Australia’s school classrooms are equipped with operable windows and occupant-controlled air-conditioners that do not provide fresh air. This can result in insufficient ventilation and high indoor CO₂ levels, which comes at a detriment to occupant productivity and health. This paper reports on the results of an in-situ study capturing indoor CO₂ levels in classrooms at a school in Victoria, Australia. The study consisted of 3 measurement periods: First, CO₂ levels pre-pandemic were measured, finding that the readings exceeded the recommended ASHRAE threshold of 1000 ppm more than 50% of the time, with levels often rising as high as 5000 ppm. Then, after the staff had been informed of the poor indoor air quality and the Victorian government had put COVIDSAFE measures in place, a second data set was captured; the impact was significant, with now only about 30% of readings above the ASHRAE threshold, and values rarely exceeding 2500 ppm. Finally, devices were installed that gave the occupants visual feedback when CO₂ levels were high, thus prompting them to open the windows; this further improved the air quality, with now less than 20% of readings above the threshold and values rarely exceeding 1500 ppm. The study suggests that, while relying on occupants to operate windows can lead to poor indoor air quality due to insufficient ventilation, it is possible to considerably influence occupant behavior through education and feedback devices. While these interventions alone did not mitigate the problem of inadequate ventilation entirely, they were sufficient to keep CO₂ levels within a generally healthy range. Considering the large energy savings that are possible by foregoing mechanical ventilation, it is evident that natural ventilation is a feasible operation method for school buildings in temperate climates, as long as classrooms are equipped with CO₂ feedback devices.

Keywords: COVID, CO₂, education, feedback devices, health, indoor air quality, natural ventilation, occupant behaviour

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Vahab Behmanesh

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Metabolic syndrome is defined as having at least three of the five metabolic risk factors, including abdominal obesity, high blood pressure, high triglycerides, low HDL, and insulin resistance. Lifestyle changes towards reducing physical activity, unhealthy eating habits Especially the high-fat and high-carbohydrate diet is directly related to metabolic syndrome, and due to the epidemic of overweight and sedentary life, metabolic syndrome is a serious problem worldwide. On the other hand, vitamin D deficiency is considered as one of the most common problems in the world, which is related to the dysfunction of beta cells and insulin resistance, and therefore, vitamin D deficiency is considered as a factor in the occurrence of metabolic syndrome. 40 subjects (age: 16.12 ± 4.4 years and body mass index 25.61 ± 4.4 kg/m2) were randomly assigned to groups of aerobic exercise and placebo, aerobic exercise and vitamin D and placebo (no exercise) were divided. Vitamin D was taken at a dose of 50,000 units per week in a double-blind format for eight weeks, and the daily aerobic exercise program was performed for 50 to 60 minutes, three doses per week, with an intensity of 50-60% of the maximum heart rate. From one-way analysis of variance, Factorial variance analysis (2x2) repeated measurement and correlated t-test were used for data analysis. Aerobic exercise and vitamin D intake reduced all metabolic risk indicators and blood insulin (P < 0.05). However, the subjective feeling of hunger did not change significantly (P < 0.05). Regarding waist circumference and blood glucose, the effect of exercise combined with vitamin D consumption was greater than the corresponding effect in the vitamin D group (P < 0.05). Aerobic exercises and vitamin D intake are safe and effective for improving cardiometabolic health, Imam adds vitamin D to the exercise program has more benefits for weight and blood sugar control, which suggests prescribing it for patients with metabolic syndrome.

Keywords: vitamin D, aerobic exercise, metabolic control, adolescents

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