Search results for: daily probability model

Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: Tianyu Chen

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China's school district education policy has encouraged parents to purchase properties in school districts with high-quality education resources. Shanghai has implemented "Simultaneous Admission to Public and Private Schools" (SAPPS) since 2018, which has covered all nine-year compulsory education by 2020. This study examines the impact of SAPPS on the housing market, specifically the premium effect of houses located in dual-school districts. Based on the Hedonic Pricing Model and the Signaling Theory, data is collected from 585 second-hand house transactions in Pudong New Area, Shanghai, and it is analyzed with the Difference-in-Differences (DID) model. The results indicate that the implementation of SAPPS has exacerbated the premium of dual school district housing and weakened the effect of the policy to a certain degree. To ensure equal access to education for all students, the government should work both on the supply and demand sides of the education resource equation.

Keywords: simultaneous admission to public and private schools, housing prices, education policy, education equity

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Authors: Ekta Yadav, Sukanta Bhattacharya, Brijesh Yadav, Ariel Hus, Jagjit Yadav

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Background and Significance: Respiratory exposure to toxicants (chemicals or particulates) causes disruption of lung homeostasis leading to lung toxicity/injury manifested as pulmonary inflammation, edema, and/or other effects depending on the type and extent of exposure. This emphasizes the need for investigating toxicant type-specific mechanisms to understand therapeutic targets. Aquaporins, aka water channels, are known to play a role in lung homeostasis. Particularly, the two major lung aquaporins AQP5 and AQP1 expressed in alveolar epithelial and vasculature endothelia respectively allow for movement of the fluid between the alveolar air space and the associated vasculature. In view of this, the current study is focused on understanding the regulation of lung aquaporins and other targets during inhalation exposure to toxic chemicals (Cigarette smoke chemicals) versus toxic particles (Carbon nanoparticles) or co-exposures to understand their relevance as markers of injury and intervention. Methodologies: C57BL/6 mice (5-7 weeks old) were used in this study following an approved protocol by the University of Cincinnati Institutional Animal Care and Use Committee (IACUC). The mice were exposed via oropharyngeal aspiration to multiwall carbon nanotube (MWCNT) particles suspension once (33 ugs/mouse) followed by housing for four weeks or to Cigarette smoke Extract (CSE) using a daily dose of 30µl/mouse for four weeks, or to co-exposure using the combined regime. Control groups received vehicles following the same dosing schedule. Lung toxicity/injury was assessed in terms of homeostasis changes in the lung tissue and lumen. Exposed lungs were analyzed for transcriptional expression of specific targets (AQPs, surfactant protein A, Mucin 5b) in relation to tissue homeostasis. Total RNA from lungs extracted using TRIreagent kit was analyzed using qRT-PCR based on gene-specific primers. Total protein in bronchoalveolar lavage (BAL) fluid was determined by the DC protein estimation kit (BioRad). GraphPad Prism 5.0 (La Jolla, CA, USA) was used for all analyses. Major findings: CNT exposure alone or as co-exposure with CSE increased the total protein content in the BAL fluid (lung lumen rinse), implying compromised membrane integrity and cellular infiltration in the lung alveoli. In contrast, CSE showed no significant effect. AQP1, required for water transport across membranes of endothelial cells in lungs, was significantly upregulated in CNT exposure but downregulated in CSE exposure and showed an intermediate level of expression for the co-exposure group. Both CNT and CSE exposures had significant downregulating effects on Muc5b, and SP-A expression and the co-exposure showed either no significant effect (Muc5b) or significant downregulating effect (SP-A), suggesting an increased propensity for infection in the exposed lungs. Conclusions: The current study based on the lung toxicity mouse model showed that both toxicant types, particles (CNT) versus chemicals (CSE), cause similar downregulation of lung innate defense targets (SP-A, Muc5b) and mostly a summative effect when presented as co-exposure. However, the two toxicant types show differential induction of aquaporin-1 coinciding with the corresponding differential damage to alveolar integrity (vascular permeability). Interestingly, this implies the potential of AQP1 as a differential marker of toxicant type-specific lung injury.

Keywords: aquaporin, gene expression, lung injury, toxicant exposure

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Authors: Sudik S. D., Raymon J. B., Maidala A., Lawan A., Bagudu I. A.

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An experiment was conducted with 240 Abor Acre broilers to determine the effect of replacing maize with acha offal (Digitaria exilis) on performance, haematology, and serum biochemical. Chicks were allotted to six diets (T1, T2, T3, T4, T5, and T6) with acha offal (AO) at 0.0%, 5.0%, 7.5%, 10.0%, 12.5% and 15.0% respectively as replacement of maize with 4 replicates consisting of 10 birds per replicate in a completely randomized design. They were allowed ad libitum accessed to feed and water throughout a 42 days experiment. The results showed that at the starter phase, only feed conversion ratio (FCR) was significantly affected (p < 0.05). Chicks fed T5 had best FCR more than those fed T1 while those fed T2, T3, T4, and T6 had similar FCR comparable with T1. At the finisher stage, final weight (FW), total weight change (TWC), average daily gain (ADG), and FCR were significantly affected (p < 0.05). Chickens fed T3, T4, T5, and T6 had similar FW, TWC, and ADG and higher than those fed T1; those fed T2 had similar FW, TWG, and DWG with T1. Chickens fed T6 had best FCR, followed by those fed T3, T4, and T5, while those T2 had worse FCR similar with those fed T1. Eviscerated weight was significantly affected (p < 0.05) by treatment. Birds fed T4, T5, and T6 had higher eviscerated weight followed by T3 while those fed T2 had least eviscerated weight comparable with those fed T1. The entire organs (Gizzard, heart, kidneys, liver, lungs, pancreas, and proventriculus) were not significantly affected (p > 0.05) by treatments. Packed cell volume (PCV) and red blood cell (RBC) were significantly (p < 0.05) affected by treatment. Birds fed T4, T5, and T6 had higher and similar PCV and RBC with those fed T1 while those fed T2 and T3 had lower PCV and RBC. The entire serum metabolites were not significantly affected (p > 0.05) by treatments. In conclusion, acha offal can replace maize in starter and finisher broilers’ diets at 12.5% and 15.0%, respectively, without an adverse effect.

Keywords: broiler, acha offal, maize, performance, eviscerated, haematology, serum

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Authors: Magda Cepeda, Frances Hodgson, Ann Jopson

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There are different barriers people face when choosing to cycle for commuting purposes. This study examined the role of psycho-social factors predicting the intention to cycle to commute in Mexico City. An extended version of the theory of planned behaviour was developed and utilized with a simple random sample of 401 road users. We applied exploratory and confirmatory factor analysis and after identifying five factors, a structural equation model was estimated to find the relationships among the variables. The results indicated that cycling attributes, attitudes to cycling, social comparison and social image and prestige were the most important factors influencing intention to cycle. Although the results from this study are specific to Mexico City, they indicate areas of interest to transportation planners in other regions especially in those cities where intention to cycle its linked to its perceived image and there is political ambition to instigate positive cycling cultures. Moreover, this study contributes to the current literature developing applications of the Theory of Planned Behaviour.

Keywords: cycling, latent variable model, perception, theory of planned behaviour

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Azlinda Saadon

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This paper provides detail review on river bank erosion studies with respect to their processes, methods of measurements and factors governing river bank erosion. Bank erosion processes are commonly associated with river changes initiation and development, through width adjustment and planform evolution. It consists of two main types of erosion processes; basal erosion due to fluvial hydraulic force and bank failure under the influence of gravity. Most studies had only focused on one factor rather than integrating both factors. Evidences of previous works have shown integration between both processes of fluvial hydraulic force and bank failure. Bank failure is often treated as probabilistic phenomenon without having physical characteristics and the geotechnical aspects of the bank. This review summarizes the findings of previous investigators with respect to measurement techniques and prediction rates of river bank erosion through field investigation, physical model and numerical model approaches. Factors governing river bank erosion considering physical characteristics of fluvial erosion are defined.

Keywords: river bank erosion, bank erosion, dimensional analysis, geotechnical aspects

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Authors: Rubina Shakya, Srijana Dangol, Dil Islam Mansur

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The exposure of constant stress stimuli in our daily lives is causing deterioration of neural connectivity in the brain. Interestingly, the improvement in larger-scale neural communication has been argued to rely on brain rhythms, which might be sensitive to binaural beats of particular frequency bands. The theoretical idea behind neural entrainment is that the rhythmic oscillatory activity within and between different brain regions can enhance cognitive function and mood state. So, we aimed to investigate whether the binaural beats of 40 Hz could enhance the cognition and the mood stability of the medical students at Kathmandu University of age 18-25 years old, which possibly, in the long run, might help to enhance their work productivity. The participants were asked to focus on the auditory stimuli of binaural beats with 200 Hz on the right side and 240 Hz on the left side of the headset for 15 minutes, every alternative day of three consecutive weeks. The Stroop’s test and the Brunel Mood Scale (BRUMS) were applied to assess the cognitive function and the mood state, respectively. The binaural beats significantly decreased the reaction time for the incoherent component of Stroop’s test in both male and female participants. For the mood state, scores of all positive emotions except ‘Calmness’ were significantly increased in the case of males. Whereas, scores of all positive emotions except ‘Vigor’ were significantly increased in the case of females. The results suggested that the meditation aided by binaural beats of 40 Hz helps in improving cognition and mood states to some extent.

Keywords: binaural beats, cognitive function, gamma neural oscillation, mood states

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Authors: Maryam Bordbar, Yaser Mokhayeri, Sajjad Roosta, Fatemeh Ghasemi, Saeed Choobkar, Hamidreza Nikbakht, Ebrahim Falahi

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Objective: Diabetes mellitus type 2 is the most common metabolic disorder that is growing exponentially worldwide. Satureja Khuzestanica Jamzad is a native plant of Iran that grows widely in the south of Iran. Its antimicrobial, antioxidant, anti-inflammatory and pain-relieving effects have been documented in animal studies. The purpose of this study is to investigate the effect of consumption daily S. khuzestanica on inflammatory and antioxidant indicators in type 2 diabetic patients. Methods and Materials: In a double-blind, placebo-controlled clinical trial, 67 patients with type 2 diabetes were included and divided into two groups. One group received S. khuzestanica (capsule containing 500 mg) and the other group received placebo (500 mg talcum powder) once a day for 12 weeks. After the intervention, the inflammatory and antioxidant indicators of the two groups were compared. Results: In comparison to placebo groups, there was a significant difference in levels of total antioxidant capacity, superoxide dismutase, catalase, glutathione reductase, and glutathione peroxidase; these antioxidant indicators were higher in the intervention group (P<0.05). Moreover, a considerable decrease in weight, CRP and IL-6 levels were observed in patients in the S.Khuzestanica group. Conclusion: Our findings may provide novel complementary treatments without adverse effects for diabetes complications.

Keywords: Satureja khuzestanica Jamzad, diabetes mellitus, antioxidant indicators, IL-6, C-reactive protein

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Authors: Chinazo Onyeka Eziuzo

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This work presents the simulation and control of the flywheel system in the rotor of a wind turbine using Simulink and OpenFAST for assessing the effect on the mechanical loads. This concept allows the flywheel system to serve two main tasks: supporting the power system and mitigating the mechanical loads in the wind turbine. These tasks are grouped into four control scenarios; scenario 1 represents steadying the power infeed in the Flywheel, scenario 2 represents steadying power with FW and grid loss, scenario 3 represents mitigating excitations from gravity, and scenario 4 represents damping in-plane blade vibrations. The s-function of the OpenFAST model was used to substitute the given 1st Eigen mode model of the WT. After that, the simulations were run for the above-listed scenarios. Additionally, the effects of the control options on the mechanical loads were assessed, and it was established that the FW system assists in steadying infeed power and mechanical load mitigation.

Keywords: simulation, control, wind turbine, OpenFAST

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Authors: Alireza Derambakhsh

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The objective of this examination is to explore the capability of utilizing Google Earth for Internet GIS applications. The study particularly analyzes the utilization of vector and characteristic information and the capability of showing and preparing this information in new ways utilizing the Google Earth stage. It has progressively been perceived that future improvements in GIS will fixate on Internet GIS, and in three noteworthy territories: GIS information access, spatial data scattering and GIS displaying/preparing. Google Earth is one of the group of geobrowsers that offer a free and simple to utilize administration that empower information with a spatial part to be overlain on top of a 3-D model of the Earth. This examination makes a methodological structure to accomplish its objective that comprises of three noteworthy parts: A database level, an application level and a customer level. As verification of idea a web model has been produced, which incorporates a differing scope of datasets and lets clients direst inquiries and make perceptions of this custom information. The outcomes uncovered that both vector and property information can be successfully spoken to and imagined utilizing Google Earth. In addition, the usefulness to question custom information and envision results has been added to the Google Earth stage.

Keywords: Google earth, internet GIS, vector, characteristic information

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Authors: Mehravar Javid, James Sexton, Farzaneh Amani, Kainaz Patravala

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Self-expansion is a procedure through which people expand the dimensions of their self-concept by incorporating novel content into their sense and experience of identity. Greater self-expansion predicts positive consequences for individuals and romantic relationships. The self-expansion questionnaire (SEQ) originally developed by Lewandowski & Aron (2002) assumes that self-expansion is constituted of key components from the self-expansion model. This study aimed to confirm the factor structure of SEQ and adapt the questions of the scale to the Iranian culture. The sample included 190 participants who responded to 14 items and were selected by simple random sampling. Using Amos-21 and SPSS-21, descriptive statistics, Pearson correlation and Confirmatory Factor Analysis (CFA) were calculated. Cronbach’s alpha coefficient for total SEQ items was 0.92. Results of CFA supported the factor structure SEQ [RMSEA=0.08, GFI=0.88 and CFI=0.92] that showed the model has a good fit and also all the items of SEQ, have a high correlation and have a direct and significant relationship. So, the SEQ demonstrated acceptable psychometric properties in Tehran University students. Looking forward, it would be interesting and exciting to see the implications of the scale as applied to romantic relationships.

Keywords: validity, reliability, confirmatory factor analysis, self-expansion questionnaire

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, A. Abu-Siada

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Dissolved Gas Analysis is one of impressive technique to detect and predict internal fault of transformers by using gas generated by transformer oil sample. A number of methods are used to interpret the dissolved gas from transformer oil sample: Doernenberg Ratio Method, IEC (International Electrotechnical Commission) Ratio Method, and Duval Triangle Method. While the assessment of dissolved gas within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straight forward as it depends on personnel expertise more than mathematical formulas. To get over this limitation, this paper is aimed at improving the interpretation of Doernenberg Ratio Method, IEC Ratio Method, and Duval Triangle Method using Two Stages Adaptive Neuro-Fuzzy Inference System (ANFIS). Dissolved gas analysis data from 520 faulty transformers was analyzed to establish the proposed ANFIS model. Results show that the developed ANFIS model is accurate and can standardize the dissolved gas interpretation process with accuracy higher than 90%.

Keywords: ANFIS, dissolved gas analysis, Doernenberg ratio method, Duval triangular method, IEC ratio method, transformer

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Authors: Asif Khaliq, Sayeeda A. Sayed

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The drug information centers provide drug related information to the requesters that include physicians, pharmacist, nurses and other allied health care professionals. The International Pharmacist Federation (FIP) describes basic functions of a drug and poison information centers as drug evaluation, therapeutic counseling, pharmaceutical advice, research, pharmaco-vigilence and toxicology. Continuous advancement in the field of medicine has expanded the medical literature, which has increased demand of a drug and poison information center for the guidance, support and facilitation of physicians. The objective of the study is to determine the need of drug and poison information centers in public and private hospitals of Karachi, Pakistan. A cross sectional study was conducted during July 2013 to April 2014 using a self-administered, multi-itemed questionnaire. Non Probability Convenient sampling was used to select the study participants. A total of 307 physicians from public and private hospitals of Karachi participated in the study. The need for 24/7 Drug and poison information center was highlighted by 92 % of physicians and 67% physicians suggested opening a drug information center at the hospital. It was reported that 70% physicians take at least 15 minutes for searching the information about the drug while managing a case. Regarding the poisoning case management, 52% physicians complaint about the unavailability of medicines in hospitals; and mentioned the importance of medicines for safe and timely management of patients. Although 73% physicians attended continued medical education (CME) sessions, 92 % physicians insisted on the need of 24/7 Drug and poison information center. The scarcity of organized channel for obtaining the information about drug and poisons is one of the most crucial problems for healthcare workers in Pakistan. The drug and poison information center is an advisory body that assists health care professional and patients in provision of appropriate drug and hazardous substance information. Drug and poison information center is one of the integral needs for running an effective health care system. Provision of a 24 /7 drug information centers with specialized staff offer multiple benefits to the hospitals while reducing treatment delays, addressing awareness gaps of all stakeholders and ensuring provision of quality health care.

Keywords: drug and poison information centers, Pakistan, physicians, public and private hospitals

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

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Despite the appropriate characteristics of ¹⁷⁷Lu and DOTATOC, to our best knowledge, the therapeutic benefit of ¹⁷⁷Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of ¹⁷⁷Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.¹⁷⁷Lu was prepared with the specific activity of 2.6-3 GBq.mg^-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with ¹⁷⁷Lu-DOTATOC as an ideal therapeutic agent.

Keywords: ¹⁷⁷Lu, adenocarcinoma breast cancer, DOTATOC, BALB/c mice

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Authors: Yi-Fung Lin, Pei-Chen Tsai

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Background: The hospital healthcare team provides 24-hour patient care, and therefore shift-work is inevitable in the nursing field. There is an increased awareness that shift-work affecting circadian rhythms may cause various health problems, especially in poor sleep quality, which may harm the quality of life. Purposes: The purpose of this study was to investigate the influences of demographic characteristics on nurses’ sleep quality and quality of life and the relationship between these predictors of nurses’ quality of life. Methods: A cross-sectional, descriptive correlational study was conducted with purposive sampling of 520 female nurses in a medical center in north Taiwan from July to September 2014. Data were collected with structured questionnaires using Psychometric Evaluation of the Chinese version of the Pittsburgh Sleep Quality Index (PSQI) and the World Health Organization Quality of Life (WHOQOL-BREF). Outcomes: The main results include: 1) Irregular menstruation, non-regular exercisers, and more daily caffeine consumption have negative impacts on sleep quality. 2) Younger age, fewer children, low education level, low annual income, irregular menstruation, pain during menstrual cycles, non-regular exercisers, constipation, and poor sleep quality all contribute negative impacts on the quality of life. 3) The odds ratio of sleep disturbance between 12-hour shifts and 8-hour shifts was 2.26, but there was no significant difference regarding their quality of life scores. Conclusion: This study showed that there is a strong correlation between oncology nurses’ sleep quality and quality of life. Sleep quality is a significant predictor of quality of life in oncology nurses.

Keywords: oncology nurses, sleep quality, quality of life, shift-work

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Authors: O. Berriche, R. Ben Othmen, H. Sfar, H. Abdesslam, S. Bou Meftah, S. Bhouri, F. Mahjoub, C. Amrouche, H. Jamoussi

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Introduction: Although current evidence emphasizes a high prevalence of vitamin D deficiency and an inverse association between serum 25-hydroxyvitamin D (25-OHD) concentration and obesity, no studies have been conducted in Tunisian obese. The objectives of our study were to estimate the vitamin D deficiency in obese, identify risk factors for vitamin D deficiency, demonstrating a possible association between vitamin D levels and metabolic parameters. Methods: This was a descriptive study of 100 obese 18-65 year-old. Anthropometric measurements were determined. Fasting blood samples were assessed for the following essays : serum calcium, 25 OH vitamin D, inorganic phosphorus, fasting glucose, HDL, LDL cholesterol and triglyceride. Insulin resistance was evaluated by fasting insulin, HOMA-IR and HOMA-ß. Consumption of foods riche in vitamin D, sunscreen use, wearing protective clothes and exposed surface were assessed through applied questionnaires. Results: The deficit of vitamin D (< 30 ng/ml) among obese was 98,8%. Half of them had a rate < 10ng/ml. Environmental factors involved in vitamin D deficiency are : the veil (p = 0,001), wearing protective clothes (p = 0,04) and the exposed surface (p = 0,011) and dietary factors are represented by the daily caloric intake (p = 0,0001). The percent of fat mass was negatively related to vitamin D levels (p = 0,01) but not with BMI (p = 0,11) or waist circumference (p = 0,88). Similarly, lipid and glucose profile had no link with vitamin D. We found no relationship between Insulin resistance and vitamin D levels. Conclusion: At the end of our study, we have identified a very important vitamin D deficiency among obese. Dosage and systematic supplementation should be applied and for that physician awareness is needed.

Keywords: insulinresistance, risk factors, obesity, vitamin D

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Authors: Ralph Adaimy, Wassim El-Hajj, Ghassen Ben Brahim, Hazem Hajj, Haidar Safa

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Huge amounts of data and personal information are being sent to and retrieved from web applications on daily basis. Every application has its own confidentiality and integrity policies. Violating these policies can have broad negative impact on the involved company’s financial status, while enforcing them is very hard even for the developers with good security background. In this paper, we propose a framework that enforces security-by-construction in web applications. Minimal developer effort is required, in a sense that the developer only needs to annotate database attributes by a security class. The web application code is then converted into an intermediary representation, called Extended Program Dependence Graph (EPDG). Using the EPDG, the provided annotations are propagated to the application code and run against generic security enforcement rules that were carefully designed to detect insecure information flows as early as they occur. As a result, any violation in the data’s confidentiality or integrity policies is reported. As a proof of concept, two PHP web applications, Hotel Reservation and Auction, were used for testing and validation. The proposed system was able to catch all the existing insecure information flows at their source. Moreover and to highlight the simplicity of the suggested approaches vs. existing approaches, two professional web developers assessed the annotation tasks needed in the presented case studies and provided a very positive feedback on the simplicity of the annotation task.

Keywords: web applications security, secure information flow, program dependence graph, database annotation

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Hongyan Chen, Megan Jobson, Andrew J. Masters, Maria Gonzalez-Miquel, Simon Halstead, Mayri Diaz de Rienzo

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Ionic liquids offer excellent advantages over conventional solvents for industrial extraction of metals from aqueous solutions, where such extraction processes bring opportunities for recovery, reuse, and recycling of valuable resources and more sustainable production pathways. Recent research on the use of ionic liquids for extraction confirms their high selectivity and low volatility, but there is relatively little focus on how their properties can be best exploited in practice. This work addresses gaps in research on process modelling and simulation, to support development, design, and optimisation of these processes, focusing on the separation of the highly similar transition metals, cobalt, and nickel. The study exploits published experimental results, as well as new experimental results, relating to the separation of Co and Ni using trihexyl (tetradecyl) phosphonium chloride. This extraction agent is attractive because it is cheaper, more stable and less toxic than fluorinated hydrophobic ionic liquids. This process modelling work concerns selection and/or development of suitable models for the physical properties, distribution coefficients, for mass transfer phenomena, of the extractor unit and of the multi-stage extraction flowsheet. The distribution coefficient model for cobalt and HCl represents an anion exchange mechanism, supported by the literature and COSMO-RS calculations. Parameters of the distribution coefficient models are estimated by fitting the model to published experimental extraction equilibrium results. The mass transfer model applies Newman’s hard sphere model. Diffusion coefficients in the aqueous phase are obtained from the literature, while diffusion coefficients in the ionic liquid phase are fitted to dynamic experimental results. The mass transfer area is calculated from the surface to mean diameter of liquid droplets of the dispersed phase, estimated from the Weber number inside the extractor. New experiments measure the interfacial tension between the aqueous and ionic phases. The empirical models for predicting the density and viscosity of solutions under different metal loadings are also fitted to new experimental data. The extractor is modelled as a continuous stirred tank reactor with mass transfer between the two phases and perfect phase separation of the outlet flows. A multistage separation flowsheet simulation is set up to replicate a published experiment and compare model predictions with the experimental results. This simulation model is implemented in gPROMS software for dynamic process simulation. The results of single stage and multi-stage flowsheet simulations are shown to be in good agreement with the published experimental results. The estimated diffusion coefficient of cobalt in the ionic liquid phase is in reasonable agreement with published data for the diffusion coefficients of various metals in this ionic liquid. A sensitivity study with this simulation model demonstrates the usefulness of the models for process design. The simulation approach has potential to be extended to account for other metals, acids, and solvents for process development, design, and optimisation of extraction processes applying ionic liquids for metals separations, although a lack of experimental data is currently limiting the accuracy of models within the whole framework. Future work will focus on process development more generally and on extractive separation of rare earths using ionic liquids.

Keywords: distribution coefficient, mass transfer, COSMO-RS, flowsheet simulation, phosphonium

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Authors: Li Yan Hei, Au Wing Tung

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Knowledge sharing is a process in which individuals mutually exchange existing knowledge and co-create new knowledge. Previous research has confirmed that trust is positively associated with knowledge sharing. However, only few studies systematically examined the antecedents of trust and these antecedents’ impacts on knowledge sharing. In order to explore and understand the relationships between trust and knowledge sharing in depth, this study proposed a relationship maintenance-based model to examine the antecedents of trust in knowledge sharing in project teams. Three critical elements within a project team were measured, including the environment, project team partner and interaction. It was hypothesized that the trust would lead to knowledge sharing and in turn result in perceived good team performance. With a sample of 200 Hong Kong employees, the proposed model was evaluated with structural equation modeling. Expected findings are trust will contribute to knowledge sharing, resulting in better team performance. The results will also offer insights into antecedents of trust that play a heavy role in the focal relationship. The present study contributes to a more holistic understanding of relationship between trust and knowledge sharing by linking the antecedents and outcomes. The findings will raise the awareness of project managers on ways to promote knowledge sharing.

Keywords: knowledge sharing, project management, team, trust

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Authors: Stefaan Carpentier, Aya Al Masri, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis, and ulceration to appear. In order to prevent these deterministic effects, a prediction of the peak skin-dose for the patient is important in order to improve the post-operative care to be given to the patient. The objective of this study is to estimate, before the intervention, the patient dose for ‘Chronic Total Occlusion (CTO)’ procedures by selecting relevant clinical indicators. Materials and methods: 103 procedures were performed in the ‘Interventional Cardiology (IC)’ department using a Siemens Artis Zee image intensifier that provides the Air Kerma of each IC exam. Peak Skin Dose (PSD) was measured for each procedure using radiochromic films. Patient parameters such as sex, age, weight, and height were recorded. The complexity index J-CTO score, specific to each intervention, was determined by the cardiologist. A correlation method applied to these indicators allowed to specify their influence on the dose. A predictive model of the dose was created using multiple linear regressions. Results: Out of 103 patients involved in the study, 5 were excluded for clinical reasons and 2 for placement of radiochromic films outside the exposure field. 96 2D-dose maps were finally used. The influencing factors having the highest correlation with the PSD are the patient's diameter and the J-CTO score. The predictive model is based on these parameters. The comparison between estimated and measured skin doses shows an average difference of 0.85 ± 0.55 Gy for doses of less than 6 Gy. The mean difference between air-Kerma and PSD is 1.66 Gy ± 1.16 Gy. Conclusion: Using our developed method, a first estimate of the dose to the skin of the patient is available before the start of the procedure, which helps the cardiologist in carrying out its intervention. This estimation is more accurate than that provided by the Air-Kerma.

Keywords: chronic total occlusion procedures, clinical experimentation, interventional radiology, patient's peak skin dose

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Authors: Mohamed Mousa

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Sacristies in the supply of freshwater, strict regulations on discharging wastewater and the support to encourage sustainable development by water minimization techniques leads to raise the interest of water reusing, regeneration, and recycling. Water is considered a vital element in chemical industries. In this study, an optimization model will be developed to determine the optimal design of refinery’s water network system via source interceptor sink that involves several network alternatives, then a Mixed-Integer Non-Linear programming (MINLP) was used to obtain the optimal network superstructure based on flowrates, the concentration of contaminants, etc. The main objective of the model is to reduce the fixed cost of piping installation interconnections, reducing the operating cots of all streams within the refiner’s water network, and minimize the concentration of pollutants to comply with the environmental regulations. A real case study for one of the Egyptian refineries was studied by GAMS / BARON global optimization platform, and the water network had been retrofitted and optimized, leading to saving around 195 m³/ hr. of freshwater with a total reduction reaches to 26 %.

Keywords: freshwater minimization, modelling, GAMS, BARON, water network design, wastewater reudction

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Authors: Ali Abd El-Aty, Ahmed Tauseef, Ahmad Farooq

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This research aims at analyzing and optimizing the hydroforming process parameters to achieve a sound bulged tube without failure. Theoretical constitutive model is formulated to develop a working diagram including process window, which represents the optimize region to carry out the hydroforming process and predict the type of tube failure during the process accurately. The model is applied into different bulging ratios for low carbon steel (C1010). From this study, it is concluded that the tubes with bulging ratios up to 50% and 70% are successfully formed without defects. The tubes with bulging ratio of 90% are successfully formed by hydroforming with optimized the loading path (axial feed versus internal pressure) within the process window. The working diagram is modified due to different types of formation of wrinkling during the hydroforming process. The formation of wrinkles with increasing axial feed can be useful in terms of the achievement of higher bulging ratio and/or less thinning and this type of wrinkles can be overcome through the internal pressure in the later stage of the hydroforming process. On the other hand, the formation of wrinkles may be harmful, if it cannot be reversed.

Keywords: finite element, hydroforming, process window, wrinkling

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

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Researchers in the fields of AI and Robotics frequently encounter ethical dilemmas throughout their research endeavors. Various ethical challenges have been pinpointed in the existing literature, including biases and discriminatory outcomes, diffusion of responsibility, and a deficit in transparency within AI operations. This research aims to pinpoint these ethical quandaries faced by researchers and shed light on the mechanisms behind ethical decision-making in the research process. By synthesizing insights from existing literature and acknowledging prevalent shortcomings, such as overlooking the heterogeneous nature of decision-making, non-accumulative results, and a lack of consensus on numerous factors due to limited empirical research, the objective is to conceptualize and validate a model. This model will incorporate influences from individual perspectives and situational contexts, considering potential moderating factors in the ethical decision-making process. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focusing on collaborative robotics for several months. Subsequently, semi-structured interviews with 16 team members were conducted. The entire process took place during the first semester of 2023. Observations were analyzed using an analysis grid, and the interviews underwent thematic analysis using Nvivo software. An initial finding involves identifying the ethical challenges that AI/robotics researchers confront, underlining a disparity between practical applications and theoretical considerations regarding ethical dilemmas in the realm of AI. Notably, researchers in AI prioritize the publication and recognition of their work, sparking the genesis of these ethical inquiries. Furthermore, this article illustrated that researchers tend to embrace a consequentialist ethical framework concerning safety (for humans engaging with robots/AI), worker autonomy in relation to robots, and the societal implications of labor (can robots displace jobs?). A second significant contribution entails proposing a model for ethical decision-making within the AI/Robotics research sphere. The model proposed adopts a process-oriented approach, delineating various research stages (topic proposal, hypothesis formulation, experimentation, conclusion, and valorization). Across these stages and the ethical queries, they entail, a comprehensive four-point comprehension of ethical decision-making is presented: recognition of the moral quandary; moral judgment, signifying the decision-maker's aptitude to discern the morally righteous course of action; moral intention, reflecting the ability to prioritize moral values above others; and moral behavior, denoting the application of moral intention to the situation. Variables such as political inclinations ((anti)-capitalism, environmentalism, veganism) seem to wield significant influence. Moreover, age emerges as a noteworthy moderating factor. AI and robotics researchers are continually confronted with ethical dilemmas during their research endeavors, necessitating thoughtful decision-making. The contribution involves introducing a contextually tailored model, derived from meticulous observations and insightful interviews, enabling the identification of factors that shape ethical decision-making at different stages of the research process.

Keywords: ethical decision making, artificial intelligence, robotics, research

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Authors: Senda Trabelsi, Sébastien Poncet, Michel Poirier

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Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.

Keywords: ice slurry, propylene-glycol, ethylene-glycol, rheology

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Authors: Kimia Khoshdel Vajari, Saber Saffar

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Reducing the residual stresses caused by welding is desirable for the industry. The effect of welding sequence, as well as the effect of yield stress on the number of residual stresses generated in Inconel X750 superalloy sheets and beams, have been investigated. The finite element model used in this research is a three-dimensional thermal and mechanical model, and the type of analysis is indirect coupling. This analysis is done in two stages. First, thermal analysis is performed, and then the thermal changes of the first analysis are used as the applied load in the second analysis. ABAQUS has been used for modeling, and the Dflux subroutine has been used in the Fortran programming environment to move the arc and the molten pool. The results of this study show that the amount of tensile residual stress in symmetric, discontinuous, and symmetric-discontinuous welds is reduced to a maximum of 27%, 54%, and 37% compared to direct welding, respectively. The results also show that the amount of residual stresses created by welding increases linearly with increasing yield stress with a slope of 40%.

Keywords: residual stress, X750 superalloy, finite element, welding, thermal analysis

Procedia PDF Downloads 108