Search results for: Wiener model

Authors: Lundqvist M., Alwin J., Levin L-A.

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Background: Assistance dogs are dogs trained to assist persons with functional impairment or chronic diseases. The assistance dog concept includes different types: guide dogs, hearing dogs, and service dogs. The service dog can further be divided into subgroups of physical services dogs, diabetes alert dogs, and seizure alert dogs. To examine the long-term effects of health care interventions, both in terms of resource use and health outcomes, cost-effectiveness analyses can be conducted. This analysis can provide important input to decision-makers when setting priorities. Little is known when it comes to the cost-effectiveness of assistance dogs. The study aimed to assess the cost-effectiveness of certified service or hearing dogs in comparison to regular companion dogs. Methods: The main data source for the analysis was the “service and hearing dog project”. It was a longitudinal interventional study with a pre-post design that incorporated fifty-five owners and their dogs. Data on all relevant costs affected by the use of a service dog such as; municipal services, health care costs, costs of sick leave, and costs of informal care were collected. Health-related quality of life was measured with the standardized instrument EQ-5D-3L. A decision-analytic Markov model was constructed to conduct the cost-effectiveness analysis. Outcomes were estimated over a 10-year time horizon. The incremental cost-effectiveness ratio expressed as cost per gained quality-adjusted life year was the primary outcome. The analysis employed a societal perspective. Results: The result of the cost-effectiveness analysis showed that compared to a regular companion dog, a certified dog is cost-effective with both lower total costs [-32,000 USD] and more quality-adjusted life-years [0.17]. Also, we will present subgroup results analyzing the cost-effectiveness of physicals service dogs and diabetes alert dogs. Conclusions: The study shows that a certified dog is cost-effective in comparison with a regular companion dog for individuals with functional impairments or chronic diseases. Analyses of uncertainty imply that further studies are needed.

Keywords: service dogs, hearing dogs, health economics, Markov model, quality-adjusted, life years

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Authors: Leah Li Echiverri, Haoyu Shang, Yue Li

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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.

Keywords: class participation, English immersion program, English language learning, learning efficiency

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Authors: Shigeyuki Haruyama, Oke Oktavianty, Zefry Darmawan, Tadayuki Kyoutani, Ken Kaminishi

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Cab’s frame strength is considered as an important factor in excavator’s operator safety, especially during roll-over. In this study, we use a model of cab frame with different thicknesses and perform elastoplastic numerical analysis by using Finite Element Method (FEM). Deformation mode and energy absorption's of cab’s frame part are investigated on two conditions, with wrinkle and without wrinkle. The occurrence of wrinkle when deforming cab frame can reduce energy absorption, and among 4 parts with wrinkle, the energy absorption significantly decreases in part C. Residual stress that generated upon the bending process of part C is analyzed to confirm it possibility in increasing the energy absorption.

Keywords: ROPS, FEM, hydraulic excavator, cab frame

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Authors: Mohammadreza DaqiqShirazi, Rouhollah Torabi, Alireza Riasi, Ahmad Nourbakhsh

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In this paper, the flow in a sidewall gap of an impeller which belongs to a centrifugal pump is studied using numerical method. The flow in sidewall gap forms internal leakage and is the source of “disk friction loss” which is the most important cause of reduced efficiency in low specific speed centrifugal pumps. Simulation is done using CFX software and a high quality mesh, therefore the modeling error has been reduced. Navier-Stokes equations have been solved for this domain. In order to predict the turbulence effects the SST model has been employed.

Keywords: numerical study, centrifugal pumps, disk friction loss, sidewall gap

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Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

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Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

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Authors: Gabriela D. Silva, Rodrigo L. O. R. Cunha, Mauricio D. Coutinho-Neto

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In the last four decades the biological activities of selenium compounds has received great attention, particularly for hypervalent derivates from selenium (IV) used as enzyme inhibitors. The unregulated activity of cysteine proteases are related to the development of several pathologies, such as neurological disorders, cardiovascular diseases, obesity, rheumatoid arthritis, cancer and parasitic infections. These enzymes are therefore a valuable target for designing new small molecule inhibitors such as selenuranes. Even tough there has been advances in the synthesis and design of new selenuranes based inhibitors, little is known about their mechanism of action. It is a given that inhibition occurs through the reaction between the thiol group of the enzyme and the chalcogen atom. However, several open questions remain about the nature of the mechanism (associative vs. dissociative) and about the nature of the reactive species in solution under physiological conditions. In this work we performed a theoretical investigation on model systems to study the possible routes of substitution reactions. Nucleophiles may be present in biological systems, our interest is centered in the thiol groups from the cysteine proteases and the hydroxyls from the aqueous environment. We therefore expect this study to clarify the possibility of a route reaction in two stages, the first consisting of the substitution of chloro atoms by hydroxyl groups and then replacing these hydroxyl groups per thiol groups in selenuranes. The structures of selenuranes and nucleophiles were optimized using density function theory along the B3LYP functional and a 6-311+G(d) basis set. Solvent was treated using the IEFPCM method as implemented in the Gaussian 09 code. Our results indicate that hydrolysis from water react preferably with selenuranes, and then, they are replaced by the thiol group. It show the energy values of -106,0730423 kcal/mol for dople substituition by hydroxyl group and 96,63078511 kcal/mol for thiol group. The solvatation and pH reduction promotes this route, increasing the energy value for reaction with hydroxil group to -50,75637672 kcal/mol and decreasing the energy value for thiol to 7,917767189 kcal/mol. Alternative ways were analyzed for monosubstitution (considering the competition between Cl, OH and SH groups) and they suggest the same route. Similar results were obtained for aliphatic and aromatic selenuranes studied.

Keywords: chalcogenes, computational study, cysteine proteases, enzyme inhibitors

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

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Authors: Daniela Salih Khidir, Mohamed G. Al Kuwari, Mercia V. Walt, Izzeldin J. Ibrahim

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Background: University-based physical activity interventions aim to establish durable social patterns during the transition to adulthood. This study is a comprehensive evaluation of a 3-year intervention-based program to increase the culture of physical activity (PA) routine in Qatar campuses community, using a holistic approach. Methodology: General assessment methods: formative evaluation-SIH Campuses logic model design, stakeholders’ identification; process evaluation-members’ step counts analyze and qualitative Appreciative Inquiry session (4-D model); daily steps categorized as: ≤5,000, inactive; 5,000-7,499 low active; ≥7,500, physically active; outcome evaluation - records 3 years interventions. Holistic PA interventions methods: walking interventions - pedometers distributions and walking competitions for students and staff; educational interventions - in campuses implementation of bilingual educational materials, lectures, video related to PA in prevention of non-communicable diseases (NCD); articles published online; monthly emails and sms notifications for pedometer use; mass media campaign - radio advertising, yearly pre/post press releases; community stakeholders interventions-biyearly planning/reporting/achievements rewarding/ qualitative meetings; continuous follow-up communication, biweekly steps reports. Findings: Results formative evaluation - SIH in Campuses logic model identified the need of PA awareness and education within universities, resources, activities, health benefits, program continuity. Results process evaluation: walking interventions: Phase 1: 5 universities recruited, 2352 members, 3 months competition; Phase 2: 6 new universities recruited, 1328 members in addition, 4 months competition; Phase 3: 4 new universities recruited in addition, 1210 members, 6 months competition. Results phase 1 and 2: 1,299 members eligible for analyzes: 800 females (62%), 499 males (38%); 86% non-Qataris, 14% Qatari nationals, daily step count 5,681 steps, age groups 18–24 (n=841; 68%) students, 25–64; (n=458; 35.3%) staff; 38% - low active, 37% physically active and 25% inactive. The AI main themes engaging stakeholders: awareness/education - 5 points (100%); competition, multi levels of involvement in SIH, community-based program/motivation - 4 points each (80%). The AI points represent themes’ repetition within stakeholders’ discussions. Results education interventions: 2 videos implementation, 35 000 educational materials, 3 online articles, 11 walking benefits lectures, 40 emails and sms notifications. Results community stakeholders’ interventions: 6 stakeholders meetings, 3 rewarding gatherings, 1 focus meeting, 40 individual reports, 18 overall reports. Results mass media campaign: 1 radio campaign, 7 press releases, 52 campuses newsletters. Results outcome evaluation: overall 2013-2016, the study used: 1 logic model, 3 PA holistic interventions, partnerships 15 universities, registered 4890 students and staff (aged 18-64 years), engaged 30 campuses stakeholders and 14 internal stakeholders; Total registered population: 61.5% female (2999), 38.5% male (1891), 20.2% (988) Qatari nationals, 79.8% (3902) non-Qataris, 55.5% (2710) students aged 18 – 25 years, 44.5% (2180) staff aged 26 - 64 years. Overall campaign 1,558 members eligible for analyzes: daily step count 7,923; 37% - low active, 43% physically active and 20% inactive. Conclusion: The study outcomes confirm program effectiveness and engagement of young campuses community, specifically female, in PA. The authors recommend implementations of 'holistic PA intervention program approach in Qatar' aiming to impact the community at national level for PA guidelines achievement in support of NCD prevention.

Keywords: campuses, evaluation, Qatar, step-count

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Authors: Tanja Ecken, Laura Fricke, Anika Steger, Maren M. Michaelsen, Tobias Esch

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Studies and applied experiences evidence severe and traumatic accidents to not only require physical rehabilitation and recovery but also to necessitate a psychological adaption and reorganization to the changed living conditions. Neurobiological models underpinning the experience of happiness and satisfaction postulate life shocks to potentially enhance the experience of happiness and life satisfaction, i.e., posttraumatic growth (PTG). This present study aims to provide an in-depth understanding of the underlying psychological processes of PTG and to outline its consequences on subjective happiness and life satisfaction. To explore the aforementioned, Esch’s (2022) ABC Model was used as guidance for the development of a questionnaire assessing changes in happiness and life satisfaction and for a schematic model postulating the development of PTG in the context of paraplegia. Two-stage qualitative interview procedures explored participants’ experiences of paraplegia. Specifically, narrative, semi-structured interviews (N=28) focused on the time before and after the accident, the availability of supportive resources, and potential changes in the perception of happiness and life satisfaction. Qualitative analysis (Grounded Theory) indicated an initial phase of reorganization was followed by a gradual psychological adaption to novel, albeit reduced, opportunities in life. Participants reportedly experienced a ‘compelled’ slowing down and elements of mindfulness, subsequently instilling a sense of gratitude and joy in relation to life’s presumed trivialities. Despite physical limitations and difficulties, participants reported an enhanced ability to relate to oneself and others and a reduction of perceived every day nuisances. Concluding, PTG can be experienced in response to severe, traumatic life events and has the potential to enrich the lives of affected persons in numerous, unexpected and yet challenging ways. PTG appears to be spectrum comprised of an interplay of internal and external resources underpinned by neurobiological processes. Participants experienced PTG irrelevant of age, gender, marital status, income or level of education.

Keywords: inhibition theory, posttraumatic growth, trauma, stress, life satisfaction, subjective happiness, traumatic life events, paraplegia

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Mrinal Gupta, Mohammad Rumman, Babita Singh Abbas Ali Mahdi, Shivani Pandey

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Introduction: Berberine (BBR), a bioactive compound isolated from Coptidis Rhizoma, possesses diverse pharmacological activities, including anti-bacterial, anti-inflammatory, antitumor, hypolipidemic, and anti-diabetic. However, its role as an anti-diabetic agent in animal models of dexamethasone (Dex)-induced diabetes remains unknown. Studies have shown that natural compounds, including aloe, caper, cinnamon, cocoa, green and black tea, and turmeric, can be used for treating Type 2 diabetes mellitus (DM). Compared to conventional drugs, natural compounds have fewer side effects and are easily available. Herein, we studied the anti-diabetic effects of BBR in a mice model of Dex-induced diabetes. Methods: HepG2 cell line was used for glucose release and glycogen synthesis studies. Cell proliferation was measured by methylthiotetrazole (MTT) assay. For animal studies, mice were treated with Dex (2 mg/kg, i.m.) for 30 days and the effect of BBR at the doses 100, 200, and 500 mg/kg (p.o.) was analyzed. Glucose, insulin, and pyruvate tests were performed to evaluate the development of the diabetic model. An echo MRI was performed to assess the fat mass. Further, to elucidate the mechanism of action of BBR, mRNA expression of genes regulating gluconeogenesis, glucose uptake, and glycolysis were analyzed. Results: In vitro BBR had no impact on cell viability up to a concentration of 50μM. Moreover, BBR suppressed the hepatic glucose release and improved glucose tolerance in HepG2 cells. In vivo, BBR improved glucose homeostasis in diabetic mice, as evidenced by enhanced glucose clearance, increased glycolysis, elevated glucose uptake, and decreased gluconeogenesis. Further, Dex treatment increased the total fat mass in mice, which was ameliorated by BBR treatment. Conclusion: BBR improves glucose tolerance by increasing glucose clearance, inhibiting hepatic glucose release, and decreasing obesity. Thus, BBR may become a potential therapeutic agent for treating glucocorticoid-induced diabetes and obesity in the future.

Keywords: glucocorticoid, hyperglycemia, berberine, HepG2 cells, insulin resistance, glucose

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Authors: Vasupradaa Manivannan, Santosh Maruthy

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Background/Aims: Preliminary evidence suggests that code-switching and code-mixing may act as one of the voluntary coping behavior to avoid the stuttering characteristics in children and adults; however, less is known about the types and patterns of code-mixing (CM) and code-switching (CS). Further, it is not known how it is different between children to adults who stutter. This study aimed to identify and compare the CM and CS patterns between Kannada-English bilingual children and adults who stutter. Method: A standard group comparison was made between five children who stutter (CWS) in the age range of 9-13 years and five adults who stutter (AWS) in the age range of 20-25 years. The participants who are proficient in Kannada (first language- L1) and English (second language- L2) were considered for the study. There were two tasks given to both the groups, a) General conversation (GC) with 10 random questions, b) Narration task (NAR) (Story / General Topic, for example., A Memorable Life Event) in three different conditions {Mono Kannada (MK), Mono English (ME), and Bilingual (BIL) Condition}. The children and adults were assessed online (via Zoom session) with a high-quality internet connection. The audio and video samples of the full assessment session were auto-recorded and manually transcribed. The recorded samples were analyzed for the percentage of dysfluencies using SSI-4 and CM, and CS exhibited in each participant using Matrix Language Frame (MLF) model parameters. The obtained data were analyzed using the Statistical Package for the Social Sciences (SPSS) software package (Version 20.0). Results: The mean, median, and standard deviation values were obtained for the percentage of dysfluencies (%SS) and frequency of CM and CS in Kannada-English bilingual children and adults who stutter for various parameters obtained through the MLF model. The inferential results indicated that %SS significantly varied between population (AWS vs CWS), languages (L1 vs L2), and tasks (GC vs NAR) but not across free (BIL) and bound (MK, ME) conditions. It was also found that the frequency of CM and CS patterns varies between CWS and AWS. The AWS had a lesser %SS but greater use of CS patterns than CWS, which is due to their excessive coping skills. The language mixing patterns were more observed in L1 than L2, and it was significant in most of the MLF parameters. However, there was a significantly higher (P<0.05) %SS in L2 than L1. The CS and CS patterns were more in conditions 1 and 3 than 2, which may be due to the higher proficiency of L2 than L1. Conclusion: The findings highlight the importance of assessing the CM and CS behaviors, their patterns, and the frequency of CM and CS between CWS and AWS on MLF parameters in two different tasks across three conditions. The results help us to understand CM and CS strategies in bilingual persons who stutter.

Keywords: bilinguals, code mixing, code switching, stuttering

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Authors: Jianming Cai

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Exposure to ionizing radiation causes severe damage to human body and an safe and effective radioprotector is urgently required for alleviating radiation damage. In 2008, flagellin, an agonist of TLR5, was found to exert radioprotective effects on radiation injury through activating NF-kB signaling pathway. From then, the radioprotective effects of TLR ligands has shed new lights on radiation protection. CpG-ODN is an unmethylated oligonucleotide which activates TLR9 signaling pathway. In this study, we demonstrated that CpG-ODN has therapeutic effects on radiation injuries induced by γ ray and 12C6+ heavy ion particles. Our data showed that CpG-ODN increased the survival rate of mice after whole body irradiation and increased the number of leukocytes as well as the bone marrow cells. CpG-ODN also alleviated radiation damage on intestinal crypt through regulating apoptosis signaling pathway including bcl2, bax, and caspase 3 etc. By using a radiation-induced pulmonary fibrosis model, we found that CpG-ODN could alleviate structural damage, within 20 week after whole–thorax 15Gy irradiation. In this model, Th1/Th2 imbalance induced by irradiation was also reversed by CpG-ODN. We also found that TGFβ-Smad signaling pathway was regulated by CpG-ODN, which accounts for the therapeutic effects of CpG-ODN in radiation-induced pulmonary injury. On another hand, for high LET radiation protection, we investigated protective effects of CpG-ODN against 12C6+ heavy ion irradiation and found that after CpG-ODN treatment, the apoptosis and cell cycle arrest induced by 12C6+ irradiation was reduced. CpG-ODN also reduced the expression of Bax and caspase 3, while increased the level of bcl2. Then we detected the effect of CpG-ODN on heavy ion induced immune dysfunction. Our data showed that CpG-ODN increased the survival rate of mice and also the leukocytes after 12C6+ irradiation. Besides, the structural damage of immune organ such as thymus and spleen was also alleviated by CpG-ODN treatment. In conclusion, we found that TLR9 ligand, CpG-ODN reduced radiation injuries in response to γ ray and 12C6+ heavy ion irradiation. On one hand, CpG-ODN inhibited the activation of apoptosis induced by radiation through regulating bcl2, bax and caspase 3. On another hand, through activating TLR9, CpG-ODN recruit MyD88-IRAK-TRAF6 complex, activating TAK1, IRF5 and NF-kB pathway, and thus alleviates radiation damage. This study provides novel insights into protection and therapy of radiation damages.

Keywords: TLR9, CpG-ODN, radiation injury, high LET radiation

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Authors: M. H. Ahmadi, A. Mortazavi, H. Zarei

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Several authors have described the main mechanism of formation of cracks in the segment lining during the construction of tunnels with tunnel boring machines. A comprehensive analysis of segmental lining joints may help to guarantee a safe construction during Tunneling and serviceable stages. The most frequent types of segment damage are caused by a condition of uneven segment matching due to contact deficiencies. This paper investigated the interaction mechanism of precast concrete lining joints in tunnels. The Discrete Element Method (DEM) was used to analyze a typical segmental lining model consisting of six segment rings. In the analyses, typical segmental lining design parameters of the Ghomrood water conveyance tunnel, Iran were employed in the study. In the conducted analysis, the worst-case scenario of loading faced during the boring of Ghomrood tunnel was considered. This was associated with the existence of a crushed zone dipping at 75 degree at the location of the key segment. In the analysis, moreover, the effect of changes in horizontal stress ratio on the loads on the segment was assessed. The boundary condition associated with K (ratio of the horizontal to the vertical stress) values of 0.5, 1, 1.5 and 2 were applied to the model and separate analysis was conducted for each case. Important parameters such as stress, moments, and displacements were measured at joint locations and the surrounding rock. Accordingly, the segment joint interactions were assessed and analyzed. Moreover, rock mass properties of the Ghomrood in Ghom were adopted. In this study, the load acting on segments joints are included a crushed zone stratum force that intersect tunnel with 75 slopes in the location of the key segment, gravity force of segments and earth pressures. A numerical investigation was used for different coefficients of stress concentration of 0.5, 1, 1.5, 2 and different geological conditions of saturated crushed zone under the critical scenario. The numerical results also demonstrate that maximum bending moments in longitudinal joints occurred for crushed zone with the weaken strengths (Sandstone). Besides that, increasing the load in segment-stratum interfaces affected radial stress in longitudinal joints and finally the opening of joints occurred.

Keywords: joint, interface, segment, contact

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Authors: Arega Shumetie Ademe, Belay Kassa, Degye Goshu, Majaliwa Mwanjalolo

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Currently the world economy is suffering from one critical problem, climate change. Some studies done before identified that impact of the problem is region specific means in some part of the world (temperate zone) there is improvement in agricultural performance but in some others like in the tropics there is drastic reduction in crop production and crop income. Climate variability is becoming dominant cause of short-term fluctuation in rain-fed agricultural production and income of developing countries. The purely rain-fed Ethiopian agriculture is the most vulnerable sector to the risks and impacts of climate variability. Thus, this study tried to identify impact of climate variability on crop income of smallholders in Ethiopia. The research used eight rounded unbalanced panel data from 1994- 2014 collected from six villages in the study area. After having all diagnostic tests the research used fixed effect method of regression. Based on the regression result rainfall and temperature deviation from their respective long term averages have negative and significant effect on crop income. Other extreme devastating shocks like flood, storm and frost, which are sourced from climate variability, have significant and negative effect on crop income of households’. Parameters that notify rainfall inconsistency like late start, variation in availability at growing season, and early cessation are critical problems for crop income of smallholder households as to the model result. Given this, impact of climate variability is not consistent in different agro-ecologies of the country. Rainfall variability has similar impact on crop income in different agro-ecology, but variation in temperature affects cold agro-ecology villages negatively and significantly, while it has positive effect in warm villages. Parameters that represent rainfall inconsistency have similar impact in both agro-ecologies and the aggregate model regression. This implies climate variability sourced from rainfall inconsistency is the main problem of Ethiopian agriculture especially the crop production sub-sector of smallholder households.

Keywords: climate variability, crop income, household, rainfall, temperature

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Authors: Fernanda M. Bastos, Teógenes A. da Silva

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Extrapolation chambers were designed to be used as primary standard dosimeter for measuring absorbed dose in a medium in beta radiation and low energy x-rays. The International Organization for Standardization established series of reference x-radiation for calibrating and determining the energy dependence of dosimeters that are to be reproduced in metrology laboratories. Standardization of the low energy x-ray beams with tube potential lower than 30 kV may be affected by the instrument used for dosimetry. In this work, parameters of a 23392 model PTW extrapolation chamber were determined aiming its use in low energy x-ray beams as a reference instrument.

Keywords: extrapolation chamber, low energy x-rays, x-ray dosimetry, X-ray metrology

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Authors: Eli Avraham

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The Arab Spring was widely covered in the global media and the number of Western tourists traveling to the area began to fall. The goal of this study was to analyze which media strategies marketers in Middle Eastern countries chose to employ in their attempts to repair the negative image of the area in the wake of the Arab Spring. Several studies were published concerning image-restoration strategies of destinations during crises around the globe; however, these strategies were not part of an overarching theory, conceptual framework or model from the fields of crisis communication and image repair. The conceptual framework used in the current study was the ‘multi-step model for altering place image’, which offers three types of strategies: source, message and audience. Three research questions were used: 1.What public relations crisis techniques and advertising campaign components were used? 2. What media policies and relationships with the international media were adopted by Arab officials? 3. Which marketing initiatives (such as cultural and sports events) were promoted? This study is based on qualitative content analysis of four types of data: 1) advertising components (slogans, visuals and text); (2) press interviews with Middle Eastern officials and marketers; (3) official media policy adopted by government decision-maker (e.g. boycotting or arresting newspeople); and (4) marketing initiatives (e.g. organizing heritage festivals and cultural events). The data was located in three channels from December 2010, when the events started, to September 31, 2013: (1) Internet and video-sharing websites: YouTube and Middle Eastern countries' national tourism board websites; (2) News reports from two international media outlets, The New York Times and Ha’aretz; these are considered quality newspapers that focus on foreign news and tend to criticize institutions; (3) Global tourism news websites: eTurbo news and ‘Cities and countries branding’. Using the ‘multi-step model for altering place image,’ the analysis reveals that Middle Eastern marketers and officials used three kinds of strategies to repair their countries' negative image: 1. Source (cooperation and media relations; complying, threatening and blocking the media; and finding alternatives to the traditional media) 2. Message (ignoring, limiting, narrowing or reducing the scale of the crisis; acknowledging the negative effect of an event’s coverage and assuring a better future; promotion of multiple facets, exhibitions and softening the ‘hard’ image; hosting spotlight sporting and cultural events; spinning liabilities into assets; geographic dissociation from the Middle East region; ridicule the existing stereotype) and 3. Audience (changing the target audience by addressing others; emphasizing similarities and relevance to specific target audience). It appears that dealing with their image problems will continue to be a challenge for officials and marketers of Middle Eastern countries until the region stabilizes and its regional conflicts are resolved.

Keywords: Arab spring, cultural events, image repair, Middle East, tourism marketing

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Authors: Mahdy ‎Esmailian, Mahdi ‎Doostparast, Ahmad ‎Parsian

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‎In this article‎, ‎sequential order statistics (SOS) censoring type II samples coming from the generalized Pareto distribution are considered‎. ‎Maximum likelihood (ML) estimators of the unknown parameters are derived on the basis of the available multiple SOS data‎. ‎Necessary conditions for existence and uniqueness of the derived ML estimates are given‎. Due to complexity in the proposed likelihood function‎, ‎a useful re-parametrization is suggested‎. ‎For illustrative purposes‎, ‎a Monte Carlo simulation study is conducted and an illustrative example is analysed‎.

Keywords: bayesian estimation‎, generalized pareto distribution‎, ‎maximum likelihood estimation‎, sequential order statistics

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Authors: Alexander David Natanson

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This paper focuses on the effect of Sanctuary and Immigration and Customs Enforcement (ICE) policies on local economies. "Sanctuary cities" refers to municipal jurisdictions that limit their cooperation with the federal government's efforts to enforce immigration. Using county-level data from the American Community Survey and ICE data on economic indicators from 2006 to 2018, this study isolates the effects of local immigration policies on U.S. counties. The investigation is accomplished by simultaneously studying the policies' effects in counties where immigrants' families are persecuted via collaboration with Immigration and Customs Enforcement (ICE), in contrast to counties that provide protections. The analysis includes a difference-in-difference & two-way fixed effect model. Results are robust to nearest-neighbor matching, after the random assignment of treatment, after running estimations using different cutoffs for immigration policies, and with a regression discontinuity model comparing bordering counties with opposite policies. Results are also robust after restricting the data to a single-year policy adoption, using the Sun and Abraham estimator, and with event-study estimation to deal with the staggered treatment issue. In addition, the study reverses the estimation to understand what drives the decision to choose policies to detect the presence of reverse causality biases in the estimated policy impact on economic factors. The evidence demonstrates that providing protections to undocumented immigrants increases economic activity. The estimates show gains in per capita income ranging from 3.1 to 7.2, median wages between 1.7 to 2.6, and GDP between 2.4 to 4.1 percent. Regarding labor, sanctuary counties saw increases in total employment between 2.3 to 4 percent, and the unemployment rate declined from 12 to 17 percent. The data further shows that ICE policies have no statistically significant effects on income, median wages, or GDP but adverse effects on total employment, with declines from 1 to 2 percent, mostly in rural counties, and an increase in unemployment of around 7 percent in urban counties. In addition, results show a decline in the foreign-born population in ICE counties but no changes in sanctuary counties. The study also finds similar results for sanctuary counties when separating the data between urban, rural, educational attainment, gender, ethnic groups, economic quintiles, and the number of business establishments. The takeaway from this study is that institutional inclusion creates the dynamic nature of an economy, as inclusion allows for economic expansion due to the extension of fundamental freedoms to newcomers. Inclusive policies show positive effects on economic outcomes with no evident increase in population. To make sense of these results, the hypothesis and theoretical model propose that inclusive immigration policies play an essential role in conditioning the effect of immigration by decreasing uncertainties and constraints for immigrants' interaction in their communities, decreasing the cost from fear of deportation or the constant fear of criminalization and optimize their human capital.

Keywords: inclusive and exclusive institutions, post matching, fixed effect, time trend, regression discontinuity, difference-in-difference, randomization inference and sun, Abraham estimator

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Authors: C. P. Autry, A.W. Roscoe

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Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: authentication, enterprise IoT cybersecurity, PKI/TTP, IoT space

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Authors: Nada Mohamed, Abdel Aziz Mohamed

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Climate change in coastal areas is a global issue that can be felt on local scale and will be around for decades and centuries to come to an end; it also has critical risks on the city’s economy, communities, and the natural environment. One of these changes that cause a huge risk on coastal cities is the sea level rise (SLR). SLR is a result of scarcity and reduction in global environmental system. The main cause of climate change and global warming is the countries with high development index (HDI) as Japan and Germany while the medium and low HDI countries as Egypt does not have enough awareness and advanced tactics to adapt with this changes that destroy urban areas and cause loss in land and economy. This is why Climate Resilience is one of the UN sustainable development goals 2030, which is calling for actions to strengthen climate change resilience through mitigation and adaptation. For many reasons, adaptation has received less attention than mitigation and it is only recently that adaptation has become a focal global point of attention. This adaption can be achieved through some actions such as upgrading the use and the design of the land, adjusting business and activities of people, and increasing community understanding of climate risks. To reach the adaption goals, and we have to apply a strategic pathway to Climate Resilience, which is the Urban Bioregionalism Paradigm. Resiliency has been framed as persistence, adaptation, and transformation. Climate Resilience decision support system includes a visualization platform where ecological, social, and economic information can be viewed alongside with specific geographies that's why Urban Bioregionalism is a socio-ecological system which is defined as a paradigm that has potential to help move social attitudes toward environmental understanding and deepen human-environment connections within ecological development. The research aim is to achieve an adaptive integrated urban development model throughout the analyses of tactics and strategies that can be used to adapt urban areas and coastal communities to the challenges of climate changes especially SLR and also simulation model using advanced technological software for a coastal city corridor to elaborates the suitable strategy to apply.

Keywords: climate resilience, sea level rise, SLR, coastal resilience, adaptive development simulation

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Authors: Nadia Allouache, Mohamed Belmedani

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—It is imperative today to further explore alternatives to fossil fuels by promoting in particular renewable sources such as solar energy to produce cold. It is also important to carefully examine its current state as well as its future prospects in order to identify the best conditions to support its optimal development. Technologies linked to this alternative source fascinate their users because they seem magical in their ability to directly transform solar energy into cooling without resorting to polluting fuels such as those derived from hydrocarbons or other toxic substances. In addition, these not only allow significant savings in electricity, but can also help reduce the costs of electrical energy production when applied on a large scale. In this context, our study aims to analyze the performance of solar adsorption cooling systems by selecting the appropriate pair Adsorbent/Adsorbat. This paper presents a model describing the heat and mass transfer in tubular finned adsorber of solar adsorption refrigerating machine. The modelisation of the solar reactor take into account the heat and mass transfers phenomena. The reactor pressure is assumed to be uniform, the reactive reactor is characterized by an equivalent thermal conductivity and assumed to be at chemical and thermodynamic equilibrium. The numerical model is controlled by heat, mass and sorption equilibrium equations. Under the action of solar radiation, the mixture of adsorbent–adsorbate has a transitory behavior. Effect of key parameters on the adsorbed quantity and on the thermal and solar performances are analyzed and discussed. The results show that, The performances of the system that depends on the incident global irradiance during a whole day depends on the weather conditions. For the used working pairs, the increase of the fins number corresponds to the decreasing of the heat losses towards environmental and the increasing of heat transfer inside the adsorber. The system performances are sensitive to the evaporator and condenser temperatures. For the considered data measured for clear type days of may and july 2023 in Algeria and Tunisia, the performances of the cooling system are very significant in Algeria compared to Tunisia.

Keywords: adsorption, adsorbent-adsorbate pair, finned reactor, numerical modeling, solar energy

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Authors: Ashutosh Saxena, Kumar Pallav, Ramji Dwivedi

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The present study estimates the seismicity parameter 'b' and maximum possible magnitude of an earthquake (Mmax) for Gujarat region with three well-established methods viz. Kijiko parametric model (KP), Kijiko-Sellevol-Bayern (KSB) and Tapered Gutenberg-Richter (TGR), as a combined seismic source regime. The earthquake catalogue is prepared for a period of 1330 to 2013 in the region Latitudes 20o N to 250 N and Longitudinally extending from 680 to 750 E for earthquake moment magnitude (Mw) ≥4.0. The ’a’ and 'b' value estimated for the region as 4.68 and 0.58. Further, Mmax estimated as 8.54 (± 0.29), 8.69 (± 0.48), and 8.12 with KP, KSB, and TGR, respectively.

Keywords: Mmax, seismicity parameter, Gujarat, Tapered Gutenberg-Richter

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Authors: Shuang Chen, Zongqian Shi, Jiajia Sun, Mingjia Li

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Microfluidics is a technology that small amounts of fluids are manipulated using channels with dimensions of tens to hundreds of micrometers. At present, this significant technology is required for several applications in some fields, including disease diagnostics, genetic engineering, and environmental monitoring, etc. Among these fields, manipulation of microparticles and cells in microfluidic device, especially separation, have aroused general concern. In magnetic field, the separation methods include positive and negative magnetophoresis. By comparison, negative magnetophoresis is a label-free technology. It has many advantages, e.g., easy operation, low cost, and simple design. Before the separation of particles or cells, focusing them into a single tight stream is usually a necessary upstream operation. In this work, the focusing of diamagnetic particles in ferrofluid microflows with a single set of overhead permanent magnets is investigated numerically. The geometric model of the simulation is based on the configuration of previous experiments. The straight microchannel is 24mm long and has a rectangular cross-section of 100μm in width and 50μm in depth. The spherical diamagnetic particles of 10μm in diameter are suspended into ferrofluid. The initial concentration of the ferrofluid c₀ is 0.096%, and the flow rate of the ferrofluid is 1.8mL/h. The magnetic field is induced by five identical rectangular neodymium−iron− boron permanent magnets (1/8 × 1/8 × 1/8 in.), and it is calculated by equivalent charge source (ECS) method. The flow of the ferrofluid is governed by the Navier–Stokes equations. The trajectories of particles are solved by the discrete phase model (DPM) in the ANSYS FLUENT program. The positions of diamagnetic particles are recorded by transient simulation. Compared with the results of the mentioned experiments, our simulation shows consistent results that diamagnetic particles are gradually focused in ferrofluid under magnetic field. Besides, the diamagnetic particle focusing is studied by varying the flow rate of the ferrofluid. It is in agreement with the experiment that the diamagnetic particle focusing is better with the increase of the flow rate. Furthermore, it is investigated that the diamagnetic particle focusing is affected by other factors, e.g., the width and depth of the microchannel, the concentration of the ferrofluid and the diameter of diamagnetic particles.

Keywords: diamagnetic particle, focusing, microfluidics, permanent magnet

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Authors: Yang Xinyu, Gong Cong, Hu Changjuan

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Stairway spaces are a crucial component of the pathway systems and vertical transportation networks in mountain city parks. These spaces are closely integrated with the undulating terrain of mountain environments, resulting in continuously changing spatial conditions that can significantly influence participants' behavioral characteristics, thereby affecting their perception. EEG signals, which have been proven to reflect various non-attentive physiological activities in the brain, are widely used in studies related to stress recovery effects and emotional perception. Existing research predominantly examines the impact of spatial characteristics and landscape elements of trails and greenways in plain cities on participants' perception, utilizing EEG signals in laboratory-simulated environments. These studies have preliminarily revealed the relationship between spatial environments and perception preferences. However, on-site ergonomics research in mountain environments remains relatively underdeveloped. To address this gap, the Stairway spaces in Pipashan Park, Chongqing, were selected as the research object. Wearable hydrogel EEG devices were employed to monitor participants' EEG data in real environments, and a Generalized Linear Mixed Model (GLMM) was constructed to explore differences in participants' perception under different paths and modes of movement, as well as the impact of visual and auditory environmental elements within each path on their perception. The model analysis results indicate significant differences in EEG data across different paths and movement modes. Additionally, typical mountainous spatial characteristics, such as openness, green view index, and elevation difference, are identified as key factors influencing participants' EEG data. Higher levels of natural sound and green view index were shown to effectively alleviate participants' stress perception in mountain stairway spaces. The findings reveal the intrinsic connections between environment, behavior, and perception in stairway spaces of mountain city parks, providing a theoretical basis for optimizing the design of stairway spaces in mountain cities.

Keywords: audio-visual perception, EEG monitoring, mountain city park, real environment, stairway space

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Authors: Safdar Muhammad Usman, Youji Kohda, Katsuhiro Umemoto

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Electronic market place plays an important intermediary role for connecting dealers and retail customers. The main aim of this paper is to design a value co-creation model in used-car auctions. More specifically, the study has been designed in order to describe the process of value co-creation in used-car auctions, to explore the co-created values in used-car auctions, and finally conclude the paper indicating the future research directions. Our analysis shows that economic values as well as non-economic values are co-created in used-car auctions. In addition, this paper contributes to the academic society broadening the view of value co-creation in service science.

Keywords: value co-creation, used-car auctions, non-financial values, service science

Procedia PDF Downloads 366

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 279

Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Feleke Tsegaye

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The work in this thesis mainly focuses on trajectory tracking of fixed wing unmanned aerial vehicle (FWUAV) by using fuzzy based sliding mode controller(FSMC) for surveillance applications. Unmanned Aerial Vehicles (UAVs) are general-purpose aircraft built to fly autonomously. This technology is applied in a variety of sectors, including the military, to improve defense, surveillance, and logistics. The model of FWUAV is complex due to its high non-linearity and coupling effect. In this thesis, input decoupling is done through extracting the dominant inputs during the design of the controller and considering the remaining inputs as uncertainty. The proper and steady flight maneuvering of UAVs under uncertain and unstable circumstances is the most critical problem for researchers studying UAVs. A FSMC technique was suggested to tackle the complexity of FWUAV systems. The trajectory tracking control algorithm primarily uses the sliding-mode (SM) variable structure control method to address the system’s control issue. In the SM control, a fuzzy logic control(FLC) algorithm is utilized in place of the discontinuous phase of the SM controller to reduce the chattering impact. In the reaching and sliding stages of SM control, Lyapunov theory is used to assure finite-time convergence. A comparison between the conventional SM controller and the suggested controller is done in relation to the chattering effect as well as tracking performance. It is evident that the chattering is effectively reduced, the suggested controller provides a quick response with a minimum steady-state error, and the controller is robust in the face of unknown disturbances. The designed control strategy is simulated with the nonlinear model of FWUAV using the MATLAB® / Simulink® environments. The simulation result shows the suggested controller operates effectively, maintains an aircraft’s stability, and will hold the aircraft’s targeted flight path despite the presence of uncertainty and disturbances.

Keywords: fixed-wing UAVs, sliding mode controller, fuzzy logic controller, chattering, coupling effect, surveillance, finite-time convergence, Lyapunov theory, flight path

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 63