Search results for: Glasgow Coma Scale

Authors: James Boylan, Denny Meyer, Won Sun Chen

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Background: Globally, there is an increasing trend of road traffic deaths, reaching 1.35 million in 2016 in comparison to 1.3 million a decade ago, and overall, road traffic injuries are ranked as the eighth leading cause of death for all age groups. The reported death rate for younger drivers aged 16-19 years is almost twice the rate reported for older drivers aged 25 and above, with a rate of 3.5 road traffic fatalities per annum for every 10,000 licenses held. Telematics refers to a system with the ability to capture real-time data about vehicle usage. The data collected from telematics can be used to better assess a driver's risk. It is typically used to measure acceleration, turn, braking, and speed, as well as to provide locational information. With the Australian government creating the National Telematics Framework, there has been an increase in the government's focus on using telematics data to improve road safety outcomes. The purpose of this study is to test the hypothesis that improvements in telematics measured driving behaviour to relate to improvements in road safety attitudes measured by the Driving Behaviour Questionnaire (DBQ). Methodology: 28 participants were recruited and given a telematics device to insert into their vehicles for the duration of the study. The participant's driving behaviour over the course of the first month will be compared to their driving behaviour in the second month to determine whether feedback from telematics devices improves driving behaviour. Participants completed the DBQ, evaluated using a 6-point Likert scale (0 = never, 5 = nearly all the time) at the beginning, after the first month, and after the second month of the study. This is a well-established instrument used worldwide. Trends in the telematics data will be captured and correlated with the changes in the DBQ using regression models in SAS. Results: The DBQ has provided a reliable measure (alpha = .823) of driving behaviour based on a sample of 23 participants, with an average of 50.5 and a standard deviation of 11.36, and a range of 29 to 76, with higher scores, indicating worse driving behaviours. This initial sample is well stratified in terms of gender and age (range 19-27). It is expected that in the next six weeks, a larger sample of around 40 will have completed the DBQ after experiencing in-vehicle telematics for 30 days, allowing a comparison with baseline levels. The trends in the telematics data over the first 30 days will be compared with the changes observed in the DBQ. Conclusions: It is expected that there will be a significant relationship between the improvements in the DBQ and the trends in reduced telematics measured aggressive driving behaviours supporting the hypothesis.

Keywords: telematics, driving behavior, young drivers, driving behaviour questionnaire

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Authors: Nermeen Saad Elbeltagy, Hoda Ghareeb, Hesham Adel Elsheshtawy, Nadim Hamed, Amany Ibrahim Mostafa, Sara Hazem Hassan

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Introduction: Depression is one of the most common mental health problems occurring in women during their child bearing years. Perinatal depression refers to major and minor depressive episodes that occur either during pregnancy or aer delivery. Although perinatal depression is common in developing countries, it is under-recognized in low and middle income countries making a substantial contribution to maternal and infant morbidity and mortality. About 12.5 - 42% of pregnant women and, 12 - 50% of post natal mothers in low and middle income countries such as Ethiopia had depression AIM OF THE WORK: To study prevalence, associated factors and impact of maternal perinatal depression in Alexandria. Patients and method: This study was conducted on 300 mothers at the postnatal ward in ElShatby Maternity Hospital from April 2022 unl October 2022. Females with past history of depression before pregnancy or females who receive medications inducing depression were excluded. The participants were asked to complete the questionnaire that includes the Edinburgh Postnatal Depression Scale (EPDS) as a screening test to obtain information concerning the current frame of mind at antepartum, partum and postpartum periods Results: The prevalence of perinatal depression was 22.3%. It was found that there is a significant negave moderate correlation between socioeconomic status and perinatal depression(r=-0.42). The present study revealed that about two thirds (60.7%) of postpartum women had low socioeconomic level. Also, less than one fourth (20%) of parents had high education and only one fourth (25.3%) of postpartum women were working. There was a statically significance difference between the number of previous abortions and perinatal depression (p=0.04). There was a significant moderate correlation between the amount of blood lost during delivery and an increased risk of developing postpartum depression. The prevalence of perinatal depression was high in cases of female neonates more than male ones. Conclusion: the prevalence of perinatal depression among the studied women was 22.3% of studied group. The significant factors identified in this study can be targeted to reduce the occurrence of perinatal depression among pregnant women in Alexandria through appropriate health interventions which includes perinatal depression screening, counseling, and the provision of support for pregnant women during antenatal care as well as lifestyle modification.

Keywords: mental health, depression in pregnancy, mental disorders, psychology in pregnancy

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Authors: Angelica Corcoran, Fredrik Lind, Pavleta Knutsson, Henrik Thunman

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Solid waste volumes are at current predominately deposited on landfill. Furthermore, the impending climate change requires new solutions for a sustainable future energy mix. Currently, solid waste is globally utilized to small extent as fuel during combustion for heat and power production. Due to its variable composition and size, solid waste is considered difficult to combust and requires a technology with high fuel flexibility. One of the commercial technologies used for combustion of such difficult fuels is circulating fluidized beds (CFB). In a CFB boiler, fine particles of a solid material are used as 'bed material', which is accelerated by the incoming combustion air that causes the bed material to fluidize. The chosen bed material has conventionally been silica sand with the main purpose of being a heat carrier, as it transfers heat released by the combustion to the heat-transfer surfaces. However, the release of volatile compounds occurs rapidly in comparison with the lateral mixing in the combustion chamber. To ensure complete combustion a surplus of air is introduced, which decreases the total efficiency of the boiler. In recent years, the concept of partly or entirely replacing the silica sand with an oxygen carrier as bed material has been developed. By introducing an oxygen carrier to the combustion chamber, combustion can be spread out both temporally and spatially in the boiler. Specifically, the oxygen carrier can take up oxygen from the combustion air where it is in abundance and release it to combustible gases where oxygen is in deficit. The concept is referred to as oxygen carrier aided combustion (OCAC) where the natural ore ilmenite (FeTiO3) has been the oxygen carrier used. The authors have validated the oxygen buffering ability of ilmenite during combustion of biomass in Chalmers 12-MWth CFB boiler in previous publications. Furthermore, the concept has been demonstrated on full industrial scale during combustion of municipal solid waste (MSW) in E.ON’s 75 MWth CFB boiler. The experimental campaigns have showed increased mass transfer of oxygen inside the boiler when combustion both biomass and MSW. As a result, a higher degree of burnout is achieved inside the combustion chamber and the plant can be operated at a lower surplus of air. Moreover, the buffer of oxygen provided by the oxygen carrier makes the system less sensitive to disruptions in operation. In conclusion, combusting difficult fuels with OCAC results in higher operation stability and an increase in boiler efficiency.

Keywords: OCAC, ilmenite, combustion, CFB

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Authors: W. Q. Wang, Y. Yin, D. B. Zou, T. P. Yu, J. M. Ouyang, F. Q. Shao

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High-energy-density state, i.e., matter and radiation at energy densities in excess of 10^11 J/m^3, is related to material, nuclear physics, astrophysics, and geophysics. Laser-driven particle beams are better suited to heat the matter as a trigger due to their unique properties of ultrashort duration and low emittance. Compared to X-ray and electron sources, it is easier to generate uniformly heated large-volume material for the proton and ion beams because of highly localized energy deposition. With the construction of state-of-art high power laser facilities, creating of extremely conditions of high-temperature and high-density in laboratories becomes possible. It has been demonstrated that on a picosecond time scale the solid density material can be isochorically heated to over 20 eV by the ultrafast proton beam generated from spherically shaped targets. For the above-mentioned technique, the proton energy density plays a crucial role in the formation of warm dense matter states. Recently, several methods have devoted to realize the focusing of the accelerated protons, involving externally exerted static-fields or specially designed targets interacting with a single or multi-pile laser pulses. In previous works, two co-propagating or opposite direction laser pulses are employed to strike a submicron plasma-shell. However, ultra-high pulse intensities, accurately temporal synchronization and undesirable transverse instabilities for a long time are still intractable for currently experimental implementations. A mechanism of the focusing of laser-driven proton beams from two-ion-species arched targets is investigated by multi-dimensional particle-in-cell simulations. When an intense linearly-polarized laser pulse impinges on the thin arched target, all electrons are completely evacuated, leading to a Coulomb-explosive electric-field mostly originated from the heavier carbon ions. The lighter protons in the moving reference frame by the ionic sound speed will be accelerated and effectively focused because of this radially isotropic field. At a 2.42×10^21 W/cm^2 laser intensity, a ballistic proton bunch with its energy-density as high as 2.15×10^17 J/m^3 is produced, and the highest proton energy and the focusing position agree well with that from the theory.

Keywords: Coulomb explosion, focusing, high-energy-density, ion acceleration

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Authors: Vineet Barwal, Sajid Husain, Nanhe Kumar Gupta, Soumyarup Hait, Sujeet Chaudhary

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High perpendicular magnetic anisotropy (PMA) and low damping constant (α) in ferromagnets are one of the few necessary requirements for their potential applications in the field of spintronics. In this regards, ferromagnetic τ-phase of MnAl possesses the highest PMA (Ku > 107 erg/cc) at room temperature, high saturation magnetization (Ms~800 emu/cc) and a Curie temperature of ~395K. In this work, we have investigated the magnetotransport behaviour of this potentially useful binary system MnₓAl₁₋ₓ films were synthesized by co-sputtering (pulsed DC magnetron sputtering) on Si/SiO₂ (where SiO₂ is native oxide layer) substrate using 99.99% pure Mn and Al sputtering targets. Films of constant thickness (~25 nm) were deposited at the different growth temperature (Tₛ) viz. 30, 300, 400, 500, and 600 ºC with a deposition rate of ~5 nm/min. Prior to deposition, the chamber was pumped down to a base pressure of 2×10⁻⁷ Torr. During sputtering, the chamber was maintained at a pressure of 3.5×10⁻³ Torr with the 55 sccm Ar flow rate. Films were not capped for the purpose of electronic transport measurement, which leaves a possibility of metal oxide formation on the surface of MnAl (both Mn and Al have an affinity towards oxide formation). In-plane and out-of-plane transverse magnetoresistance (MR) measurements on films sputtered under optimized growth conditions revealed non-saturating behavior with MR values ~6% and 40% at 9T, respectively at 275 K. Resistivity shows a parabolic dependence on the field H, when the H is weak. At higher H, non-saturating positive MR that increases exponentially with the strength of magnetic field is observed, a typical character of hopping type conduction mechanism. An anomalous decrease in MR is observed on lowering the temperature. From the temperature dependence of reistivity, it is inferred that the two competing states are metallic and semiconducting, respectively and the energy scale of the phenomenon produces the most interesting effects, i.e., the metal-insulator transition and hence the maximum sensitivity to external fields, at room temperature. Theory of disordered 3D systems effectively explains the crossover temperature coefficient of resistivity from positive to negative with lowering of temperature. These preliminary findings on the MR behavior of MnAl thin films will be presented in detail. The anomalous large MR in mixed phase MnAl system is evidently useful for future spintronic applications.

Keywords: magnetoresistance, perpendicular magnetic anisotropy, spintronics, thin films

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Authors: Mark A. S. Laidlaw, Howard W. Mielke

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In California between the late 1920’s and 1986 the lead concentrations in urban soils and dust climbed rapidly following the deposition of greater than 387,000 tonnes of lead emitted from gasoline. Previous research indicates that when children are lead exposed around 90% of the lead is retained in their bones and teeth due to the substitution of lead for calcium. Lead in children’s bones has been shown to accumulate over time and is highest in inner-city urban areas, lower in suburban areas and lowest in rural areas. It is also known that women’s bones demineralize during pregnancy due to the foetus's high demand for calcium. Lead accumulates in women’s bones during childhood and the accumulated lead is subsequently released during pregnancy – a lagged response. This results in calcium plus lead to enter the blood stream and cross the placenta to expose the foetus with lead. In 1970 in the United States, the average age of a first‐time mother was about 21. In 2008, the average age was 25.1. In this study, it is demonstrated that in California there is a forward lagged relationship between the accumulated emissions of lead from vehicle fuel additives and later autism prevalence trends between the 1990’s and current time period. Regression analysis between a 24 year forward lag of accumulated lead emissions and autism prevalence trends in California are associated strongly (R2=0.95, p=0.00000000127). It is hypothesized that autism in genetically susceptible children may stem from vehicle fuel lead emission exposures of their mothers during childhood and that the release of stored lead during subsequent pregnancy resulted in lead exposure of foetuses during a critical developmental period. It is furthermore hypothesized that the 24 years forward lag between lead exposures has occurred because that is time period is the average length for women to enter childbearing age. To test the hypothesis that lead in mothers bones is associated with autism, it is hypothesized that retrospective case-control studies would show an association between the lead in mother’s bones and autism. Furthermore, it is hypothesized that the forward lagged relationship between accumulated historical vehicle fuel lead emissions (or air lead concentrations) and autism prevalence trends will be similar in cities at the national and international scale. If further epidemiological studies indicate a strong relationship between accumulated vehicle fuel lead emissions (or accumulated air lead concentrations) and lead in mother’s bones and autism rates, then urban areas may require extensive soil intervention to prevent the development of autism in children.

Keywords: autism, bones, lead, gasoline, petrol, prevalence

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Authors: Zexiao Zheng, Irene M. C. Lo

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Organic pollutants, ammonia, and bacteria are major contaminants in sewage, which may adversely impact ecosystems without proper treatment. Conventional wastewater treatment plants (WWTPs) are operated to remove these contaminants from sewage but suffer from high carbon emissions and are powerless to remove emerging organic pollutants (EOPs). Herein, we have developed a low operational carbon emissions multifunctional photoelectrochemical (PEC) system for saline sewage treatment to simultaneously remove organic compounds, ammonia, and bacteria, coupled with H2 evolution. A reduced BiVO4 (r-BiVO4) with improved PEC properties due to the construction of oxygen vacancies and V4+ species was developed for the multifunctional PEC system. The PEC/r-BiVO4 process could treat saline sewage to meet local WWTPs’ discharge standard in 40 minutes at 2.0 V vs. Ag/AgCl and completely degrade carbamazepine (one of the EOPs), coupled with significant evolution of H2. A remarkable reduction in operational carbon emissions was achieved by the PEC/r-BiVO4 process compared with large-scale WWTPs, attributed to the restrained direct carbon emissions from the generation of greenhouse gases. Mechanistic investigation revealed that the PEC system could activate chloride ions in sewage to generate reactive chlorine species and facilitate •OH production, promoting contaminants removal. The PEC system exhibited operational feasibility at different pH and total suspended solids concentrations and has outstanding reusability and stability, confirming its promising practical potential. The study combined the simultaneous removal of three major contaminants from saline sewage and H2 evolution in a single PEC process, demonstrating a viable approach to supplementing and extending the existing wastewater treatment technologies. The study generated profound insights into the in-situ activation of existing chloride ions in sewage for contaminants removal and offered fundamental theories for applying the PEC system in sewage remediation with low operational carbon emissions. The developed PEC system can fit well with the future needs of wastewater treatment because of the following features: (i) low operational carbon emissions, benefiting the carbon neutrality process; (ii) higher quality of the effluent due to the elimination of EOPs; (iii) chemical-free in the operation of sewage treatment; (iv) easy reuse and recycling without secondary pollution.

Keywords: contaminants removal, H2 evolution, multifunctional PEC system, operational carbon emissions, saline sewage treatment, r-BiVO4 photoanodes

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Authors: Hsiu-Tsu Cho

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Collective efficacy refers to a group’s sense of its capacity to complete a task successfully or to reach objectives. Little effort has been expended on investigating the relationship between the emotion expression of a leader and collective efficacy. In this study, we examined the impact of the different emotions and emotion expression of a group leader on collective efficacy and explored whether the emotion–expressive effects differed under conditions of negative and positive emotions. A total of 240 undergraduate and graduate students recruited using Facebook and posters at a university participated in this research. The participants were separated randomly into 80 groups of four persons consisting of three participants and a confederate. They were randomly assigned to one of five conditions in a 2 (pride vs. guilt) × 2 (emotion expression of group leader vs. no emotion expression of group leader) factorial design and a control condition. Each four-person group was instructed to get the reward in a group competition of solving the five-disk Tower of Hanoi puzzle and making decisions on an investment case. We surveyed the participants by employing the emotional measure revised from previous researchers and collective efficacy questionnaire on a 5-point scale. To induce an emotion of pride (or guilt), the experimenter announced whether the group performance was good enough to have a chance of getting the reward (ranking the top or bottom 20% among all groups) after group task. The leader (confederate) could either express or not express a feeling of pride (or guilt) following the instruction according to the assigned condition. To check manipulation of emotion, we added a control condition under which the experimenter revealed no results regarding group performance in maintaining a neutral emotion. One-way ANOVAs and post hoc pairwise comparisons among the three emotion conditions (pride, guilt, and control condition) involved assigning pride and guilt scores (pride: F(1,75) = 32.41, p < .001; guilt: F(1,75) = 6.75, p < .05). The results indicated that manipulations of emotion were successful. A two-way between-measures ANOVA was conducted to examine the predictions of the main effects of emotion types and emotion expression as well as the interaction effect of these two variables on collective efficacy. The experimental findings suggest that pride did not affect collective efficacy (F(1,60) = 1.90, ns.) more than guilt did and that the group leader did not motivate collective efficacy regardless of whether he or she expressed emotion (F(1,60) = .89, ns.). However, the interaction effect of emotion types and emotion expression was statistically significant (F(1,60) = 4.27, p < .05, ω2 = .066); the effects accounted for 6.6% of the variance. Additional results revealed that, under the pride condition, the leader enhanced group efficacy when expressing emotion, whereas, under the guilt condition, an expression of emotion could reduce collective efficacy. Overall, these findings challenge the assumption that the effect of expression emotion are the same on all emotions and suggest that a leader should be cautious when expressing negative emotions toward a group to avoid reducing group effectiveness.

Keywords: collective efficacy, group leader, emotion expression, pride, guilty

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Authors: Shih-Huang Pan, Tsuyoshi Miyazaki, Minoru Otani, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Ammonia (NH₃) is crucial in renewable energy and agriculture, yet its traditional production via the Haber-Bosch process faces challenges due to the inherent inertness of nitrogen (N₂) and the need for high temperatures and pressures. The electrocatalytic nitrogen reduction (ENRR) presents a more sustainable option, functioning at ambient conditions. However, its advancement is limited by selectivity and efficiency challenges due to the competing hydrogen evolution reaction (HER). The critical roles of protonation of N-species and HER highlight the necessity of selecting optimal catalysts and solvents to enhance ENRR performance. Notably, transition metal oxides, with their adjustable electronic states and excellent chemical and thermal stability, have shown promising ENRR characteristics. In this study, we use density functional theory (DFT) methods to investigate the ENRR mechanisms on IrO₂ (110), a material known for its tunable electronic properties and exceptional chemical and thermal stability. Employing the constant electrode potential (CEP) model, where the electrode - electrolyte interface is treated as a polarizable continuum with implicit solvation, and adjusting electron counts to equalize work functions in the grand canonical ensemble, we further incorporate the advanced 3D Reference Interaction Site Model (3D-RISM) to accurately determine the ENRR limiting potential across various solvents and pH conditions. Our findings reveal that the limiting potential for ENRR on IrO₂ (110) is significantly more favorable than for HER, highlighting the efficiency of the IrO₂ catalyst for converting N₂ to NH₃. This is supported by the optimal *NH₃ desorption energy on IrO₂, which enhances the overall reaction efficiency. Microkinetic simulations further predict a promising NH₃ production rate, even at the solution's boiling point¸ reinforcing the catalytic viability of IrO₂ (110). This comprehensive approach provides an atomic-level understanding of the electrode-electrolyte interface in ENRR, demonstrating the practical application of IrO₂ in electrochemical catalysis. The findings provide a foundation for developing more efficient and selective catalytic strategies, potentially revolutionizing industrial NH₃ production.

Keywords: density functional theory, electrocatalyst, nitrogen reduction reaction, electrochemistry

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

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Authors: Katarzyna Pawęska, Aleksandra Bawiec, Ewa Burszta-Adamiak, Wiesław Fiałkiewicz

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The water shortage becomes a serious problem not only in African and Middle Eastern countries, but also recently in the European Union. Scarcity of water means that not all agricultural, industrial and municipal needs will be met. When the annual availability of renewable freshwater per capita is less than 1,700 cubic meters, countries begin to experience periodic or regular water shortages. The phenomenon of water stress is the result of an imbalance between the constantly growing demand for water and its availability. The constant development of industry, population growth, and climate changes make the situation even worse. The search for alternative water sources and independent supplies is becoming a priority for many countries. Data enabling the assessment of country’s condition regarding water resources, water consumption, water price, wastewater volume, forecasted climate changes e.g. temperature, precipitation, are scattered and their interpretation by common entrepreneurs may be difficult. For this purpose, a digital tool has been developed to support decisions related to the implementation of water and wastewater re-use systems, as a result of an international research project “Framework for organizational decision-making process in water reuse for smart cities” (SMART-WaterDomain) funded under the EIG-CONCERT Japan call on Smart Water Management for Sustainable Society. The developed geo-visualization tool graphically presents, among others, data about the capacity of wastewater treatment plants and the volume of water demand in the private and public sectors for Poland, Germany, and the Czech Republic. It is expected that such a platform, extended with economical water management data and climate forecasts (temperature, precipitation), will allow in the future independent investigation and assessment of water use rate and wastewater production on the local and regional scale. The tool is a great opportunity for small business owners, entrepreneurs, farmers, local authorities, and common users to analyze the impact of climate change on the availability of water in the regions of their business activities. Acknowledgments: The authors acknowledge the support of the Project Organisational Decision Making in Water Reuse for Smart Cities (SMART- WaterDomain), funded by The National Centre for Research and Development and supported by the EIG-Concert Japan.

Keywords: circular economy, digital tool, geo-visualization, wastewater re-use

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Authors: Carolina Beltran, Carlos De Los Reyes

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Acquired brain injury (ABI) is any physical and functional injury secondary to events that affect the brain tissue. It is one of the biggest causes of disability in the world and it has a high annual incidence in the pediatric population. There are several causes of ABI such as traumatic brain injury, central nervous system infection, stroke, hypoxia, tumors and others. The consequences can be cognitive, behavioral, emotional and functional. The cognitive rehabilitation is necessary to achieve the best outcomes for pediatric people with ABI. Cognitive orientation to daily occupational performance (CO-OP) is an individualized client-centered, performance-based, problem-solving approach that focuses on the strategy used to support the acquisition of three client-chosen goals. It has demonstrated improvements in the pediatric population with other neurological disorder but not in Spanish speakers with ABI. Aim: The main objective of this study was to determine the efficacy of cognitive orientation to daily occupational performances (CO-OP) adapted to Spanish speakers, in the level of independence and behavior in a pediatric population with ABI. Methods: Case studies with measure pre/post-treatment were used in three children with ABI, sustained at least before 6 months assessment, in school, aged 8 to 16 years, age ABI after 6 years old and above average intellectual ability. Twelve sessions of CO-OP adapted to Spanish speakers were used and videotaped. The outcomes were based on cognitive, behavior and functional independence measurements such as Child Behavior Checklist (CBCL), Behavior Rating Inventory of Executive Function (BRIEF), The Vineland Adaptive Behavior Scales (VINELAND, Social Support Scale (MOS-SSS) and others neuropsychological measures. This study was approved by the ethics committee of Universidad del Norte in Colombia. Informed parental written consent was obtained for all participants. Results: children were able to identify three goals and use the global strategy ‘goal-plan-do-check’ during each session. Verbal self-instruction was used by all children. CO-OP showed a clinically significant improvement in goals regarding with independence level and behavior according to parents and teachers. Conclusion: The results indicated that CO-OP and the use of a global strategy such as ‘goal-plan-do-check’ can be used in children with ABI in order to improve their specific goals. This is a preliminary version of a big study carrying in Colombia as part of the experimental design.

Keywords: cognitive rehabilitation, acquired brain injury, pediatric population, cognitive orientation to daily occupational performance

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Authors: Hyo Seon Choi, Ju Sun Kim, DY Kim

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Introduction: This study was aimed to evaluate temporo-spatial patterns during the reach and grasp task in hemiplegic stroke patients and to identify movement pattern according to severity of motor impairment. Method: 29 subacute post-stroke patients were enrolled in this study. The temporo-spatial and kinematic data were obtained during reach and grasp task through 3D motion analysis (VICON). The reach and grasp task was composed of four sub-tasks: reach (T1), transport to mouth (T2), transport back to table (T3) and return (T4). The movement time, joint angle and sum of deviation angles from normative data were compared between affected side and unaffected side. They were also compared between two groups (mild to moderate group: 28~66, severe group: 0~27) divided by upper-Fugl-Meyer Assessment (FMA) scale. Result: In affected side, total time and durations of all four tasks were significantly longer than those in unaffected side (p < 0.001). The affected side demonstrated significant larger shoulder abduction, shoulder internal rotation, wrist flexion, wrist pronation, thoracic external rotation and smaller shoulder flexion during reach and grasp task (p < 0.05). The significant differences between mild to moderate group and severe group were observed in total duration, durations of T1, T2, and T3 in reach and grasp task (p < 0.01). The severe group showed significant larger shoulder internal rotation during T2 (p < 0.05) and wrist flexion during T2, T3 (p < 0.05) than mild to moderate group. In range of motion during each task, shoulder abduction-adduction during T2 and T3, shoulder internal-external rotation during T2, elbow flexion-extension during T1 showed significant difference between two groups (p < 0.05). The severe group had significant larger total deviation angles in shoulder internal-external rotation and wrist extension-flexion during reach and grasp task (p < 0.05). Conclusion: This study suggests that post-stroke hemiplegic patients have an unique temporo-spatial and kinematic patterns during reach and grasp task, and the movement pattern may be related to affected upper limb severity. These results may be useful to interpret the motion of upper extremity in stroke patients.

Keywords: Fugl-Meyer Assessment (FMA), motion analysis, reach and grasp, stroke

Procedia PDF Downloads 239

Authors: R. Hurtado-Ortiz, D. Clermont, M. Schüngel, C. Bizet, D. Smith, E. Stackebrandt

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Microbiological resources and their derivatives are the essential raw material for the advancement of human health, agro-food, food security, biotechnology, research and development in all life sciences. Microbial resources, and their genetic and metabolic products, are utilised in many areas such as production of healthy and functional food, identification of new antimicrobials against emerging and resistant pathogens, fighting agricultural disease, identifying novel energy sources on the basis of microbial biomass and screening for new active molecules for the bio-industries. The complexity of public collections, distribution and use of living biological material (not only living but also DNA, services, training, consultation, etc.) and service offer, demands the coordination and sharing of policies, processes and procedures. The Microbial Resource Research Infrastructure (MIRRI) is an initiative within the European Strategy Forum Infrastructures (ESFRI), bring together 16 partners including 13 European public microbial culture collections and biological resource centres (BRCs), supported by several European and non-European associated partners. The objective of MIRRI is to support innovation in microbiology by provision of a one-stop shop for well-characterized microbial resources and high quality services on a not-for-profit basis for biotechnology in support of microbiological research. In addition, MIRRI contributes to the structuring of microbial resources capacity both at the national and European levels. This will facilitate access to microorganisms for biotechnology for the enhancement of the bio-economy in Europe. MIRRI will overcome the fragmentation of access to current resources and services, develop harmonised strategies for delivery of associated information, ensure bio-security and other regulatory conditions to bring access and promote the uptake of these resources into European research. Data mining of the landscape of current information is needed to discover potential and drive innovation, to ensure the uptake of high quality microbial resources into research. MIRRI is in its Preparatory Phase focusing on governance and structure including technical, legal governance and financial issues. MIRRI will help the Biological Resources Centres to work more closely with policy makers, stakeholders, funders and researchers, to deliver resources and services needed for innovation.

Keywords: culture collections, microbiology, infrastructure, microbial resources, biotechnology

Procedia PDF Downloads 446

Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

Procedia PDF Downloads 183

Authors: Yi-Tung Lin

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Researchers commonly assess implicit self-esteem with the Implicit Association Test (IAT). The IAT’s measure, often referred to as the IAT effect, indicates the strengths of automatic preferences for the self relative to others, which is often considered an index of implicit self-esteem. However, based on the Dual-process theory, the IAT does not rely entirely on the automatic process; it is also influenced by a controlled process. The present study, therefore, analyzed the IAT data with the Quad model, separating four processes on the IAT performance: the likelihood that automatic association is activated by the stimulus in the trial (AC); that a correct response is discriminated in the trial (D); that the automatic bias is overcome in favor of a deliberate response (OB); and that when the association is not activated, and the individual fails to discriminate a correct answer, there is a guessing or response bias drives the response (G). The AC and G processes are automatic, while the D and OB processes are controlled. The AC parameter is considered as the strength of the association activated by the stimulus, which reflects what implicit measures of social cognition aim to assess. The stronger the automatic association between self and positive valence, the more likely it will be activated by a relevant stimulus. Therefore, the AC parameter was used as the index of implicit self-esteem in the present study. Meanwhile, the relationship between implicit self-esteem and depression is not fully investigated. In the cognitive theory of depression, it is assumed that the negative self-schema is crucial in depression. Based on this point of view, implicit self-esteem would be negatively associated with depression. However, the results among empirical studies are inconsistent. The aims of the present study were to examine the psychometric properties of the AC (i.e., test-retest reliability and its correlations with explicit self-esteem and depression) and compare it with that of the IAT effect. The present study had 105 patients with depressive disorders completing the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II and the IAT on the pretest. After at least 3 weeks, the participants completed the second IAT. The data were analyzed by the latent-trait multinomial processing tree model (latent-trait MPT) with the TreeBUGS package in R. The result showed that the latent-trait MPT had a satisfactory model fit. The effect size of test-retest reliability of the AC and the IAT effect were medium (r = .43, p < .0001) and small (r = .29, p < .01) respectively. Only the AC showed a significant correlation with explicit self-esteem (r = .19, p < .05). Neither of the two indexes was correlated with depression. Collectively, the AC parameter was a satisfactory index of implicit self-esteem compared with the IAT effect. Also, the present study supported the results that implicit self-esteem was not correlated with depression.

Keywords: cognitive modeling, implicit association test, implicit self-esteem, quad model

Procedia PDF Downloads 128

Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

Procedia PDF Downloads 63

Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

Procedia PDF Downloads 267

Authors: Eric Bates

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Higher education is recognised as being of critical importance in Ireland and has been linked as a vital factor to national well-being. Statistics show that Ireland has one of the highest rates of higher education participation in Europe. However, student retention and progression, especially in Institutes of Technology, is becoming an issue as rates on non-completion rise. Both within Ireland and across Europe student retention is seen as a key performance indicator for higher education and with these increasing rates the Irish higher education system needs to be flexible and adapt to the situation it now faces. The author is a Programme Chair on a Level 6 full time undergraduate programme and experience to date has shown that the first year undergraduate students take some time to identify themselves as a group within the setting of a higher education institute. Despite being part of a distinct class on a specific programme some individuals can feel isolated as he or she take the first step into higher education. Such feelings can contribute to students eventually dropping out. This paper reports on an ongoing initiative that aims to accelerate the bonding experience of a distinct group of first year undergraduates on a programme which has a high rate of non-completion. This research sought to engage the students in dynamic interactions with their peers to quickly evolve a group sense of coherence. Two separate modules – a Research Module and a Communications module - delivered by the researcher were linked across two semesters. Students were allocated into random groups and each group was given a topic to be researched. There were six topics – essentially the six sub-headings on the DIT Graduate Attribute Statement. The research took place in a computer lab and students also used the library. The output from this was a document that formed part of the submission for the Research Module. In the second semester the groups then had to make a presentation of their findings where each student spoke for a minimum amount of time. Presentation workshops formed part of that module and students were given the opportunity to practice their presentation skills. These presentations were video recorded to enable feedback to be given. Although this was a small scale study preliminary results found a strong sense of coherence among this particular cohort and feedback from the students was very positive. Other findings indicate that spreading the initiative across two semesters may have been an inhibitor. Future challenges include spreading such Initiatives College wide and indeed sector wide.

Keywords: first year experience, student retention, group work, presentation workshops

Procedia PDF Downloads 229

Authors: Jian Yu

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Carbo dioxide (CO2) from fossil fuel combustion is a prime green-house gas emission. It can be mitigated by microalgae through conventional photosynthesis. The algal oil is a feedstock of biodiesel, a carbon neutral liquid fuel for transportation. The conventional CO2 fixation, however, is quite slow and affected by the intermittent solar irradiation. It is also a technical challenge to reform the bio-oil into a drop-in liquid fuel that can be directly used in the modern combustion engines with expected performance. Here, an artificial photosynthesis system is presented to produce a biopolyester and liquid fuels from CO2, water, and solar power. In this green process, solar energy is captured using photovoltaic modules and converted into hydrogen as a stable energy source via water electrolysis. The solar hydrogen is then used to fix CO2 by Cupriavidus necator, a hydrogen-oxidizing bacterium. Under the autotrophic conditions, CO2 was reduced to glyceraldehyde-3-phosphate (G3P) that is further utilized for cell growth and biosynthesis of polyhydroxybutyrate (PHB). The maximum cell growth rate reached 10.1 g L-1 day-1, about 25 times faster than that of a typical bio-oil-producing microalga (Neochloris Oleoabundans) under stable indoor conditions. With nitrogen nutrient limitation, a large portion of the reduced carbon is stored in PHB (C4H6O2)n, accounting for 50-60% of dry cell mass. PHB is a biodegradable thermoplastic that can find a variety of environmentally friendly applications. It is also a platform material from which small chemicals can be derived. At a high temperature (240 - 290 oC), the biopolyester is degraded into crotonic acid (C4H6O2). On a solid phosphoric acid catalyst, PHB is deoxygenated via decarboxylation into a hydrocarbon oil (C6-C18) at 240 oC or so. Aromatics and alkenes are the major compounds, depending on the reaction conditions. A gasoline-grade liquid fuel (77 wt% oil) and a biodiesel-grade fuel (23 wt% oil) were obtained from the hydrocarbon oil via distillation. The formation routes of hydrocarbon oil from crotonic acid, the major PHB degradation intermediate, are revealed and discussed. This work shows a novel green process from which biodegradable plastics and high-grade liquid fuels can be directly produced from carbon dioxide, water and solar power. The productivity of the green polyester (5.3 g L-1 d-1) is much higher than that of microalgal oil (0.13 g L-1 d-1). Other technical merits of the new green process may include continuous operation under intermittent solar irradiation and convenient scale up in outdoor.

Keywords: bioplastics, carbon dioxide fixation, drop-in liquid fuels, green process

Procedia PDF Downloads 189

Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Doris F. Rabelo

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Introduction: Endotracheal Intubation (ETI) is a procedure for clinical management of patients with severe clinical presentation of COVID-19 disease. Realistic simulation (RS) is an active learning methodology utilized for clinical skill's improvement. To improve ETI skills of public health network's physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was planned and carried out. Training scenario included the Nasco Lifeform realistic simulator, and three actions were simulated: ETI procedure, sedative drugs management, and bougie guide utilization. Training intervention occurred between May and June 2020, as an interinstitutional cooperation between the Health's Department of Bahia State and the Federal University from Recôncavo da Bahia. Objective: The main objective is to report the effects on participants' self-confidence perception for ETI procedure after RS based training. Methods: This is a descriptive study, with secondary data extracted from questionnaires applied throughout RS training. Priority workplace, time from last intubation, and knowledge about bougie were reported on a preparticipation questionnaire. Additionally, participants completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding self-confidence perception in performing each of simulated actions. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's Exact Test. Results: 36 physicians participated of training, 25 (69%) from primary care setting, 25 (69%) performed ETI over a year ago, and only 4 (11%) had previous knowledge about the bougie guide utilization. There was an increase in self-confidence medians for all three simulated actions. Medians (variation) for self-confidence before and after training, for each simulated action were as follows: ETI [5 (1-9) vs. 8 (6-10) (p < 0.0001)]; Sedative drug management [5 (1-9) vs. 8 (4-10) (p < 0.0001)]; Bougie guide utilization [2.5 (1-7) vs. 8 (4-10) (p < 0.0001)]. Among those who performed ETI over a year ago (n = 25), an increase in self-confidence greater than 3 points for ETI was reported by 23 vs. 2 physicians (p = 0.0002), and by 21 vs. 4 (p = 0.03) for sedative drugs management. Conclusions: RS training contributed to self-confidence increase in performing ETI. Among participants who performed ETI over a year, there was a significant association between RS training and increase of more than 3 points in self-confidence, both for ETI and sedative drug management. Training with RS methodology is suitable for ETI confidence enhancement during COVID-19 outbreak.

Keywords: confidence, COVID-19, endotracheal intubation, realistic simulation

Procedia PDF Downloads 141

Authors: Moshiur Rahman, Tahmida Jakia

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Bangladesh, a densely populated South Asian country is home to more than 160 million people. In two decades ago, the people of this developing nation drank heavily contaminated surface water. Over the past thirty years, the country, and its development partners, has undertaken extensive efforts to provide microbiologically safe groundwater based drinking water through the use of tube-wells. About 85% of the people now drink tube-well water from about 11 million tube-wells/hand pumps. However, diarrhoeal and other water-related diseases are still reported among the major causes of morbidity and mortality among Bangladeshi children. This implies that the mode of transmission of pathogens through water and/or other modes continue. In addition, massive scale arsenic contamination has been recently reported in the ground water. Thirty five million people may be at risk of consuming arsenic contaminated water exceeding 0.05 mg/l in Bangladesh. Drinking of arsenic contaminated water has been linked with skin problems, cancer, cardiovascular diseases, neurological diseases, eye problems, cancer of the internal organs, and other diseases. In the study area, Narail district, recent investigations about existing water quality situations indicated presence of low to high levels of arsenic, salinity, iron, manganese and bacteriological contamination risks. As challenges for safe water exist; it is likely that sanitation and food hygiene practices are poor which lead threat to ensure food security.The main attempt of this study is to find out the challenges to ensure food security andprovide probable solutions to ensure food safety towards 0.7 million of people in study area. A survey has been conducted at Lohagara and Kalia sub district of Narail district with a pretested questionnaire. Primary data are collected through a questionnaire, while secondary data are collected from pertinent offices as well as academic journals. FGD has also been done to know the knowledge regarding water, sanitation as well as food preparation and consumption practice of community people in study area. The major focus of this study is to assess the state of sanitation and food hygiene condition of rural people. It is found that most of the villagers have lack of knowledge about food safety. Open defecation rate is high which lead threat to ensure food security.

Keywords: food safety, challenges, hygiene, Bangladesh

Procedia PDF Downloads 335

Authors: Valentin Nickolai, Florian Pfeffel, Christian Louis Kühner

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In many industrialized nations, the demand for skilled workers rises, causing the current market for employees to be more candidate-driven than employer-driven. Therefore, losing highly skilled and experienced employees due to early or partial retirement negatively impacts firms. Therefore, finding new ways to incentivize older employees (Silver Workers) to stay longer with the company and in their job can be crucial for the success of a firm. This study analyzes how working remotely can be a valid incentive for experienced Silver Workers to stay in their job and instead work from home with more flexible working hours. An online survey with n = 684 respondents, who are employed in the service sector, has been conducted based on 13 constructs that influence job satisfaction. These have been further categorized into three groups “classic influencing factors,” “influencing factors changed by remote working,” and new remote working influencing factors,” and were analyzed using structural equation modeling (SEM). Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). It was shown in the SEM-analysis that the influencing factor on job satisfaction, “identification with the work,” is the most significant with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis also shows that the identification with the work is the most significant factor in all three work models mentioned above and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees between the ages of 56 and 65 years have the highest job satisfaction when working entirely from home or remotely. Furthermore, their job satisfaction score of 5.4 on a scale from 1 (very dissatisfied) to 7 (very satisfied) is the highest amongst all age groups in any of the three work models. Due to the significantly higher job satisfaction, it can be argued that giving Silver Workers the offer to work from home or remotely can incentivize them not to opt for early retirement or partial retirement but to stay in their job full-time Furthermore, these findings can indicate that employees in the Silver Worker age are much more inclined to leave their job for early retirement if they have to entirely work in the office.

Keywords: home office, remote work instead of early or partial retirement, silver worker, structural equation modeling

Procedia PDF Downloads 75

Authors: Marina Wagdy Nageeb Eskander

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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 60

Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Daniele Traversaro

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Problem: Senior citizens have been facing a challenging reality as a result of strict public health measures designed to protect people from the COVID-19 outbreak. These include the risk of social isolation due to the inability of the elderly to integrate with technology. Never before have information and communication technology (ICT) skills become essential for their everyday life. Although third-age ICT education and lifelong learning are widely supported by universities and governments, there is a lack of literature on which teaching strategy/methodology to adopt in an entirely online ICT course aimed at third-age learners. This contribution aims to present an application of the Think-Pair-Share (TPS) learning method in an ICT third-age virtual classroom with an intergenerational approach to conducting online group labs and review activities. This collaborative strategy can help increase student engagement, promote active learning and online social interaction. Research Question: Is collaborative learning applicable and effective, in terms of student engagement and learning outcomes, for an entirely online third-age ICT introductory course? Methods: In the TPS strategy, a problem is posed by the teacher, students have time to think about it individually, and then they work in pairs (or small groups) to solve the problem and share their ideas with the entire class. We performed four experiments in the ICT course of the University of the Third Age of Genova (University of Genova, Italy) on the Microsoft Teams platform. The study cohort consisted of 26 students over the age of 45. Data were collected through online questionnaires. Two have been proposed, one at the end of the first activity and another at the end of the course. They consisted of five and three close-ended questions, respectively. The answers were on a Likert scale (from 1 to 4) except two questions (which asked the number of correct answers given individually and in groups) and the field for free comments/suggestions. Results: Results show that groups perform better than individual students (with scores greater than one order of magnitude) and that most students found it helpful to work in groups and interact with their peers. Insights: From these early results, it appears that TPS is applicable to an online third-age ICT classroom and useful for promoting discussion and active learning. Despite this, our experimentation has a number of limitations. First of all, the results highlight the need for more data to be able to perform a statistical analysis in order to determine the effectiveness of this methodology in terms of student engagement and learning outcomes as a future direction.

Keywords: collaborative learning, information technology education, lifelong learning, older adult education, think-pair-share

Procedia PDF Downloads 190

Authors: Rajendra Chetty

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The paper aims to address two aspects of postgraduate studies: interdisciplinary research and creative models of supervision. Interdisciplinary research can be viewed as a key imperative to solve complex problems. While excellent research requires a context of disciplinary strength, the cutting edge is often found at the intersection between disciplines. Interdisciplinary research foregrounds a team approach and information, methodologies, designs, and theories from different disciplines are integrated to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline. Our aim should also be to generate research that transcends the original disciplines i.e. transdisciplinary research. Complexity is characteristic of the knowledge economy, hence, postgraduate research and engaged scholarship should be viewed by universities as primary vehicles through which knowledge can be generated to have a meaningful impact on society. There are far too many ‘ordinary’ studies that fall into the realm of credentialism and certification as opposed to significant studies that generate new knowledge and provide a trajectory for further academic discourse. Secondly, the paper will look at models of supervision that are different to the dominant ‘apprentice’ or individual approach. A reflective practitioner approach would be used to discuss a range of supervision models that resonate well with the principles of interdisciplinarity, growth in the postgraduate sector and a commitment to engaged scholarship. The global demand for postgraduate education has resulted in increased intake and new demands to limited supervision capacity at institutions. Team supervision lodged within large-scale research projects, working with a cohort of students within a research theme, the journal article route of doctoral studies and the professional PhD are some of the models that provide an alternative to the traditional approach. International cooperation should be encouraged in the production of high-impact research and institutions should be committed to stimulating international linkages which would result in co-supervision and mobility of postgraduate students and global significance of postgraduate research. International linkages are also valuable in increasing the capacity for supervision at new and developing universities. Innovative co-supervision and joint-degree options with global partners should be explored within strategic planning for innovative postgraduate programmes. Co-supervision of PhD students is probably the strongest driver (besides funding) for collaborative research as it provides the glue of shared interest, advantage and commitment between supervisors. The students’ field serves and informs the co-supervisors own research agendas and helps to shape over-arching research themes through shared research findings.

Keywords: interdisciplinarity, internationalisation, postgraduate, supervision

Procedia PDF Downloads 238

Authors: Ardita Malaj, Ahmad R. Alsaber, Bedour Alboloushi, Anwaar Alkandari

Abstract:

Organizations worldwide, particularly in Kuwait, are concerned with implementing a progressive workplace culture and fostering social innovation behaviours. The main aim of this research is to examine and establish a thorough comprehension of the relationship between an inventive organizational culture, employee intrapreneurial behaviour, authentic leadership, employee job satisfaction, and employee job commitment in the manufacturing sector of Kuwait, which is a developed economy. Literature reviews analyse the core concepts and their related areas by scrutinizing their definitions, dimensions, and importance to uncover any deficiencies in existing research. The examination of relevant research uncovered major gaps in understanding. This study examines the reliability and validity of a newly developed questionnaire designed to identify the appropriate applications for a large-scale investigation. A preliminary investigation was carried out, determining a sample size of 36 respondents selected randomly from a pool of 223 samples. SPSS was utilized to calculate the percentages of the demographic characteristics for the participants, assess the credibility of the measurements, evaluate the internal consistency, validate all agreements, and determine Pearson's correlation. The study's results indicated that the majority of participants were male (66.7%), aged between 35 and 44 (38.9%), and possessed a bachelor's degree (58.3%). Approximately 94.4% of the participants were employed full-time. 72.2% of the participants are employed in the electrical, computer, and ICT sector, whilst 8.3% work in the metal industry. Out of all the departments, the human resource department had the highest level of engagement, making up 13.9% of the total. Most participants (36.1%) possessed intermediate or advanced levels of experience, whilst 21% were classified as entry-level. Furthermore, 8.3% of individuals were categorized as first-level management, 22.2% were categorized as middle management, and 16.7% were categorized as executive or senior management. Around 19.4% of the participants have over a decade of professional experience. The Pearson's correlation coefficient for all 5 components varies between 0.4009 to 0.7183. The results indicate that all elements of the questionnaire were effectively verified, with a Cronbach alpha factor predominantly exceeding 0.6, which is the criterion commonly accepted by researchers. Therefore, the work on the larger scope of testing and analysis could continue.

Keywords: pilot study, ESIB, innovative organizational culture, Kuwait, validation

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