Search results for: genome scale model

Authors: Rachel Cherner

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Introduction: The current study investigates several user characteristics that may predict the adoption of digital mental health supports. The extent to which individual characteristics predict preferences for functional elements of computer-mediated social support (CMSS) platforms and mental health (MH) apps is relatively unstudied. Aims: The present study seeks to illuminate the relationship between broad user characteristics and perceived attraction to CMSS platforms and MH apps. Methods: Participants (n=353) were recruited using convenience sampling methods (i.e., digital flyers, email distribution, and online survey forums). The sample was 68% male, and 32% female, with a mean age of 29. Participant racial and ethnic breakdown was 75% White, 7%, 5% Asian, and 5% Black or African American. Participants were asked to complete a 25-minute self-report questionnaire that included empirically validated measures assessing a battery of characteristics (i.e., subjective levels of anxiety/depression via PHQ-9 (Patient Health Questionnaire 9-item) and GAD-7 (Generalized Anxiety Disorder 7-item); attachment style via MAQ (Measure of Attachment Qualities); personality types via TIPI (The 10-Item Personality Inventory); growth mindset and mental health-seeking attitudes via GM (Growth Mindset Scale) and MHSAS (Mental Help Seeking Attitudes Scale)) and subsequent attitudes toward CMSS platforms and MH apps. Results: A stepwise linear regression was used to test if user characteristics significantly predicted attitudes towards key features of CMSS platforms and MH apps. The overall regression was statistically significant (R² =.20, F(1,344)=14.49, p<.000). Conclusion: This original study examines the clinical and sociocultural factors influencing decisions to use CMSS platforms and MH apps. Findings provide valuable insight for increasing adoption and engagement with digital mental health support. Fostering a growth mindset may be a method of increasing participant/patient engagement. In addition, CMSS platforms and MH apps may empower under-resourced and minority groups to gain basic access to mental health support. We do not assume this final model contains the best predictors of use; this is merely a preliminary step toward understanding the psychology and attitudes of CMSS platform/MH app users.

Keywords: computer-mediated social support platforms, digital mental health, growth mindset, health-seeking attitudes, mental health apps, user characteristics

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: Fatemeh Abdollahi, Mehran Zarghami, Jamshid Yazdani Jarati, Mun-Sunn Lye

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Fathers may be at risk of depression during the postpartum period. Some studies have been reported maternal depression is the key predictor of paternal postpartum depression (PPD). This study aimed to explore this association. Using a cross-sectional study design, 591 couples referring to primary health centers at 2-8 weeks postpartum (during 2017) were recruited. Couples screened for depression using Edinburgh Postnatal Depression Scale (EPDS). Data on socio-demographic characteristics and psychosocial factors was also gathered. Paternal PPD was analyzed in relation to maternal PPD and other related factors using multiple regressions. The prevalence of Paternal and maternal postpartum depression was 15.7% (93) and 31.8% (188), respectively. The regression model showed that there was increased risk of PPD in fathers whose wives experienced PPD [OR=1.15, (95%CI: 1.04-1.27)], who had a lower state of general health [OR=1.21, (95%CI: 1.11-1.33)], who experienced increased number of life events [OR=1.42, (95%CI: 1.01-1.2.00)], and who were at older age [OR=1.20, (95%CI: 1.05- 1.36)]. Also, there was a decreased risk of depression in fathers with more children compared with those with fewer children [OR=0.20, (95%CI: 0.07-0.53)]. Maternal PPD and psychosocial risk factors were the strong predictors of parental PPD. Being grown up in a family with two depressed parents are an important issue for children and needs futher research and attention.

Keywords: Father, Mother, Postpartum depression, Risk factors

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Authors: M. Ndaw, G. Mendy, S. Ouya

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Information system risk management helps to reduce or eliminate risk by implementing appropriate controls. In this paper, we propose a quantification model of controls impact on information system risks by automatizing the residual criticality estimation step of FMECA which is based on a inductive reasoning. For this, we defined three equations based on type and maturity of controls. For testing, the values obtained with the model were compared to estimated values given by interlocutors during different working sessions and the result is satisfactory. This model allows an optimal assessment of controls maturity and facilitates risk analysis of information system.

Keywords: information system, risk, control, FMECA method

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Authors: Essam Gooda, Chadi Abdallah, Hamdi Seif, Safaa Baydoun, Rouya Hdeib, Hilal Obeid

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Floods are common natural disaster occurring in semi-arid regions in Lebanon. This results in damage to human life and deterioration of environment. Despite their destructive nature and their immense impact on the socio-economy of the region, flash floods have not received adequate attention from policy and decision makers. This is mainly because of poor understanding of the processes involved and measures needed to manage the problem. The current understanding of flash floods remains at the level of general concepts; most policy makers have yet to recognize that flash floods are distinctly different from normal riverine floods in term of causes, propagation, intensity, impacts, predictability, and management. Flash floods are generally not investigated as a separate class of event but are rather reported as part of the overall seasonal flood situation. As a result, Lebanon generally lacks policies, strategies, and plans relating specifically to flash floods. Main objective of this research is to improve flash flood prediction by providing new knowledge and better understanding of the hydrological processes governing flash floods in the East Catchments of El Assi River. This includes developing rainstorm time distribution curves that are unique for this type of study region; analyzing, investigating, and developing a relationship between arid watershed characteristics (including urbanization) and nearby villages flow flood frequency in Ras Baalbeck and Fekha. This paper discusses different levels of integration approach¬es between GIS and hydrological models (HEC-HMS & HEC-RAS) and presents a case study, in which all the tasks of creating model input, editing data, running the model, and displaying output results. The study area corresponds to the East Basin (Ras Baalbeck & Fakeha), comprising nearly 350 km2 and situated in the Bekaa Valley of Lebanon. The case study presented in this paper has a database which is derived from Lebanese Army topographic maps for this region. Using ArcMap to digitizing the contour lines, streams & other features from the topographic maps. The digital elevation model grid (DEM) is derived for the study area. The next steps in this research are to incorporate rainfall time series data from Arseal, Fekha and Deir El Ahmar stations to build a hydrologic data model within a GIS environment and to combine ArcGIS/ArcMap, HEC-HMS & HEC-RAS models, in order to produce a spatial-temporal model for floodplain analysis at a regional scale. In this study, HEC-HMS and SCS methods were chosen to build the hydrologic model of the watershed. The model then calibrated using flood event that occurred between 7th & 9th of May 2014 which considered exceptionally extreme because of the length of time the flows lasted (15 hours) and the fact that it covered both the watershed of Aarsal and Ras Baalbeck. The strongest reported flood in recent times lasted for only 7 hours covering only one watershed. The calibrated hydrologic model is then used to build the hydraulic model & assessing of flood hazards maps for the region. HEC-RAS Model is used in this issue & field trips were done for the catchments in order to calibrated both Hydrologic and Hydraulic models. The presented models are a kind of flexible procedures for an ungaged watershed. For some storm events it delivers good results, while for others, no parameter vectors can be found. In order to have a general methodology based on these ideas, further calibration and compromising of results on the dependence of many flood events parameters and catchment properties is required.

Keywords: flood risk management, flash flood, semi arid region, El Assi River, hazard maps

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Authors: Jae Won Shin, Chang Ho Hyun

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A disintegration of deuterons by photons (dγ → np) reaction model for GEANT4 is developed in this work. An effective field theory with dibaryon fields Introducing a dibaryon field, we can take into account the effective range contribution to the propagator up to infinite order, and it consequently makes the convergence of the theory better than the pionless effective field theory without dibaryon fields. We develop a hadronic model for GEANT4 which is specialized for the disintegration of the deuteron by photons, dγ → np. For the description of two-nucleon interactions, we employ an effective field theory so called pionless theory with dibaryon fields (dEFT). In spite of its simplicity, the theory has proven very effective and useful in the applications to various two-nucleon systems and processes at low energies. We apply the new model of GEANT4 (G4dEFT) to the calculation of total and differential cross sections in dγ → np, and obtain good agreements to experimental data for a wide range of incoming photon energies.

Keywords: dγ → np, dibaryon fields, effective field theory, GEANT4

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Authors: Muhammad Tayyab Afzal, Muhammad Arslan, Mirza Muhammad Waqar

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One of the key components of the water cycle is evapotranspiration (ET), which represents water consumption by vegetated and non-vegetated surfaces. Conventional techniques for measurements of ET are point based and representative of the local scale only. Satellite remote sensing data with large area coverage and high temporal frequency provide representative measurements of several relevant biophysical parameters required for estimation of ET at regional scales. The objective is of this research is to exploit satellite data in order to estimate evapotranspiration. This study uses Surface Energy Balance System (SEBS) model to calculate daily actual evapotranspiration (ETa) in Larkana District, Sindh Pakistan using Landsat TM data for clouds-free days. As there is no flux tower in the study area for direct measurement of latent heat flux or evapotranspiration and sensible heat flux, therefore, the model estimated values of ET were compared with reference evapotranspiration (ETo) computed by FAO-56 Penman Monteith Method using meteorological data. For a country like Pakistan, agriculture by irrigation in the river basins is the largest user of fresh water. For the better assessment and management of irrigation water requirement, the estimation of consumptive use of water for agriculture is very important because it is the main consumer of water. ET is yet an essential issue of water imbalance due to major loss of irrigation water and precipitation on cropland. As large amount of irrigated water is lost through ET, therefore its accurate estimation can be helpful for efficient management of irrigation water. Results of this study can be used to analyse surface conditions, i.e. temperature, energy budgets and relevant characteristics. Through this information we can monitor vegetation health and suitable agricultural conditions and can take controlling steps to increase agriculture production.

Keywords: SEBS, remote sensing, evapotranspiration, ETa

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Authors: H. Pegram, R. Stevens, L. De Girolamo

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Aligned electrospun nanofibres act as effective neuronal and glial cell scaffolds that can be layered to contain multiple sheets harboring different cell populations. This allows personalised biofunctional prostheses to be manufactured with both acellular and cellularised layers for the treatment of spinal cord injury. Additionally, the manufacturing route may be configured to produce in-vitro 3D cell based model of spinal cord injury to aid drug development and enhance prosthesis performance. The goal of this investigation was to optimise the multi-layer scaffold design parameters for prosthesis manufacture, to enable the development of multi-layer patient specific implant therapies. The work has also focused on the fabricating aligned nanofibre scaffolds that promote in-vitro neuronal and glial cell population growth, cell-to-cell interaction and long-term survival following trauma to mimic an in-vivo spinal cord lesion. The approach has established reproducible lesions and has identified markers of trauma and regeneration marked by effective neuronal migration across the lesion with glial support. The investigation has advanced the development of an in-vitro model of traumatic spinal cord injury and has identified a route to manufacture prostheses which target the repair spinal cord injury. Evidence collated to investigate the multi-layer concept suggests that physical cues provided by nanofibres provide both a natural extra-cellular matrix (ECM) like environment and controls cell proliferation and migration. Specifically, aligned nanofibre layers act as a guidance system for migrating and elongating neurons. On a larger scale, material type in multi-layer systems also has an influence in inter-layer migration as cell types favour different material types. Results have shown that layering nanofibre membranes create a multi-level scaffold system which can enhance or prohibit cell migration between layers. It is hypothesised that modifying nanofibre layer material permits control over neuronal/glial cell migration. Using this concept, layering of neuronal and glial cells has become possible, in the context of tissue engineering and also modelling in-vitro induced lesions.

Keywords: electrospinning, layering, lesion, modeling, nanofibre

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Authors: Kodo Sektani, Apostolos Tsouvalas, Andrei Metrikine

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The reassessment of existing movable bridges in The Netherlands has created the need for acceptance/rejection criteria to assess whether the machineries are meet certain design demands. However, the existing design code defines a different limit state design, meant for new machineries which is based on a simple linear spring-mass model. Observations show that existing bridges do not confirm the model predictions. In fact, movable bridges are nonlinear systems consisting of mechanical components, such as, gears, electric motors and brakes. Next to that, each movable bridge is characterized by a unique set of parameters. However, in the existing code various variables that describe the physical characteristics of the bridge are neglected or replaced by partial factors. For instance, the damping ratio ζ, which is different for drawbridges compared to bascule bridges, is taken as a constant for all bridge types. In this paper, a model is developed that overcomes some of the limitations of existing modelling approaches to capture the dynamics of the powertrain of a class of bridge machineries First, a semidefinite dynamic model is proposed, which accounts for stiffness, damping, and some additional variables of the physical system, which are neglected by the code, such as nonlinear braking torques. The model gives an upper bound of the peak forces/torques occurring in the powertrain during emergency braking. Second, a discrete nonlinear dynamic model is discussed, with realistic motor torque characteristics during normal operation. This model succeeds to accurately predict the full time history of the occurred stress state of the opening and closing cycle for fatigue purposes.

Keywords: Dynamics of movable bridges, Bridge machinery, Powertrains, Torque measurements

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Authors: Hossein Pourbashash

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Recent experimental studies have shown that HIV can be transmitted directly from cell to cell when structures called virological synapses form during interactions between T cells. In this article, we describe a new within-host model of HIV infection that incorporates two mechanisms: infection by free virions and the direct cell-to-cell transmission. We conduct the local and global stability analysis of the model. We show that if the basic reproduction number R0 1, the virus is cleared and the disease dies out; if R0 > 1, the virus persists in the host. We also prove that the unique positive equilibrium attracts all positive solutions under additional assumptions on the parameters.

Keywords: HIV virus model, cell-to-cell transmission, global stability, Lyapunov function, second compound matrices

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Authors: Mohammed Darwish

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Workplace injuries cost organizations significant amount of money. Causes of injuries at workplace are very well documented in the literature and attributed to variety of reasons. One important reason is the long working-hours. The purpose of this paper is to develop a mathematical model that finds the optimal working-hours at workplace. The developed model minimizes the expected total cost which consists of the expected cost incurred due to unsafe conditions of workplace, the other cost is related to the lost production due to work incidents, and the production cost.

Keywords: 8-hour workday, mathematical model, optimal working hours, workplace injuries

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Authors: Sang-Woo Han, Jong-Shik Shin

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w-Transaminase (w-TA) is broadly used for synthesizing chiral amines with a high enantiopurity. However, the reaction mechanism of w-TA has been not well studied, contrary to a-transaminase (a-TA) such as AspTA. Here, we propose in silico model on the reaction mechanism of w-TA. Based on the modeling results which showed large free energy gaps between external aldimine and quinonoid on deamination (or ketimine and quinonoid on amination), withdrawal of Ca-H seemed as a critical step which determines the reaction rate on both amination and deamination reactions, which is consistent with previous researches. Hyperconjugation was also observed in both external aldimine and ketimine which weakens Ca-H bond to elevate Ca-H abstraction.

Keywords: computational modeling, reaction intermediates, w-transaminase, in silico model

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Authors: Manar Aslan, Selver Gokdemir, Chatitze Chousein

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This research was conducted to evaluate the factors affecting the working environment of nurses working in three state hospitals. A favorable working environment contributes to increased job satisfaction of nurses and improved working conditions that affects the quality of the work done in a positive way. The population of the study was composed the three largest state hospitals in the region of Thrace in Turkey and 931 nurses working in there. In this research was not used any sampling method. The sampling was composed of nurses who accepted to take part in this research from three hospitals. It was used nursing work index-the practice work environment scale (Turkish version) for data collection (Cronbach alpha: 0.94).When the total scale scores of the nurses in the research were examined, it was determined that they evaluated the working environment below the average. It was also determined that the adequacy of human and other resources, dimensions of the physician-nurse communication scores were low. As in every profession group, the working environment in nursing has an importance to provide quality health and nursing care. A favorable working environment will increase nurses' performance and satisfaction with their work. Identifying the factors affecting the working environment and carrying out the remedial work for them will increase the quality of the health service.

Keywords: work environment, work index, nursing, hospitals

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Authors: Syahruddin Sumardi Samindjaya, Indra Fajar Alamsyah, Junaidah Hashim

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Purpose: This study attempts to explore and presents a proposed recruitment model in Islamic university which aligned with holistic role. Design/methodology/approach: It is a conceptual paper in nature. In turn, this study is designed to utilize exploratory approach. Literature and document review that related to this topic are used as the methods to analyse the content found. Findings: Recruitment for any organization is fundamental to achieve its goal effectively. Staffing in universities is vital due to the important role of lecturers. Currently, Islamic universities still adopt the common process of recruitment for their academic staffs. Whereas, they have own characteristics which are embedded in their institutions. Furthermore, the FCWC (Foundation, Capability, Worldview and Commitment) model of recruitment proposes to suit the holistic character of Islamic university. Research limitation/implications: Further studies are required to empirically validate the concept through systematic investigations. Additionally, measuring this model by a designed means is appreciated. Practical implications: The model provides the map and alternative tool of recruitment for Islamic universities to determine the process of recruitment which can appropriate their institutions. In addition, it also allows stakeholders and policy makers to consider regarding Islamic values that should inculcate in the Islamic higher learning institutions. Originality/value: This study initiates a foundational contribution for an early sequence of research.

Keywords: academic staff, Islamic values, recruitment model, university

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Authors: Aghasadeghi MR., Bahramali G., Sadat SM., Sadeghi SA., Yousefi M., Khodaei K., Ghorbani M., Sadat Larijani M.

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Background:The emerging COVID-19 pandemic is a serious concernfor the public health worldwide. Despite the many mutations in the virus genome, it is important to find an effective vaccine against viral mutations. Therefore, in current study, we aimed at immunoinformatic evaluation of the virus proteins immunogenicity to design a preventive vaccine candidate, which could elicit humoral and cellular immune responses as well. Methods:Three antigenic regions are included;Spike, Membrane, and Nucleocapsid amino acid sequences were obtained, and possible fusion proteins were assessed andcompared by immunogenicity, structural features, and population coverage. The best fusion protein was also evaluated for MHC-I and MHC-II T-cell epitopes and the linear and conformational B-cell epitopes. Results: Among the four predicted models, the truncated Spike protein in fusion with M and N proteins is composed of 24 highly immunogenic human MHC class I and 29 MHC class II, along with 14 B-cell linear and 61 discontinues epitopes. Also, the selected protein has high antigenicity and acceptable population coverage of 82.95% in Iran and 92.51% in Europe. Conclusion: The data indicate that the truncated Spike-M-N SARS-CoV-2form which could be potential targets of neutralizing antibodies. The protein also has the ability to stimulate humoral and cellular immunity. The in silico study provided the fusion protein as a potential preventive vaccine candidate for further in vivo evaluation.

Keywords: SARS-CoV-2, immunoinformatic, protein, vaccine

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Authors: A. Durgadevi, S. Pushpavanam

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In this work, absorption studies are done by conducting experiments of 99.9 (v/v%) pure CO₂ with various concentrations of sodium hydroxide solutions in a T-junction glass circular milli-channel. The gas gets absorbed in the aqueous phase resulting in the shrinking of slugs. This phenomenon is used to develop a lumped parameter model. Using this model, the chemical dissolution dynamics and the mass transfer characteristics of the CO₂-NaOH system is analysed. The liquid side mass transfer coefficient is determined with the help of the experimental data.

Keywords: absorption, dissolution dynamics, lumped parameter model, milli-channel, mass transfer coefficient

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

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Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

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Authors: Peng Guo

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Objective: This study investigates the clinical characteristics of sleep disorders (SD) in patients with Alzheimer's disease (AD) and their relationship with cognitive impairment. Methods: According to the inclusion and exclusion criteria of AD, 460 AD patients were consecutively included in Beijing Tiantan Hospital from January 2016 to April 2022. Demographic data, including gender, age, age of onset, course of disease, years of education and body mass index, were collected. The Pittsburgh sleep quality index (PSQI) scale was used to evaluate the overall sleep status. AD patients with PSQI ≥7 was divided into AD with SD (AD-SD) group, and those with PSQI < 7 were divided into AD with no SD (AD-nSD) group. The overall cognitive function of AD patients was evaluated by the scales of Mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA), memory was evaluated by the AVLT-immediate recall, AVLT-delayed recall and CFT-delayed memory scales, the language was evaluated by BNT scale, visuospatial ability was evaluated by CFT-imitation, executive function was evaluated by Stroop-A, Stroop-B and Stroop-C scales, attention was evaluated by TMT-A, TMT-B, and SDMT scales. The correlation between cognitive function and PSQI score in AD-SD group was analyzed. Results: Among the 460 AD patients, 173 cases (37.61%) had SD. There was no significant difference in gender, age, age of onset, course of disease, years of education and body mass index between AD-SD and AD-nSD groups (P>0.05). The factors with significant difference in PSQI scale between AD-SD and AD-nSD groups include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleeping medication and daytime dysfunction (P<0.05). Compared with AD-nSD group, the total scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales in AD-SD group were significantly lower（P＜0.01，P＜0.01，P＜0.01，P＜0.05）. In AD-SD group, subjective sleep quality was significantly and negatively correlated with the scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales (r=-0.277，P=0.000; r=-0.216，P=0.004; r=-0.253，P=0.001; r=-0.239, P=0.004), daytime dysfunction was significantly and negatively correlated with the score of AVLT-immediate recall scale (r=-0.160，P=0.043). Conclusion The incidence of AD-SD is 37.61%. AD-SD patients have worse subjective sleep quality, longer time to fall asleep, shorter sleep time, lower sleep efficiency, severer nighttime SD, more use of sleep medicine, and severer daytime dysfunction. The overall cognitive function, immediate recall and visuospatial ability of AD-SD patients are significantly impaired and are closely correlated with the decline of subjective sleep quality. The impairment of immediate recall is highly correlated with daytime dysfunction in AD-SD patients.

Keywords: Alzheimer's disease, sleep disorders, cognitive impairment, correlation

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Authors: Raouf Mbarki, Fadi Al Khatib, Malek Adouni

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Knee collateral ligaments play a significant role in restraining excessive frontal motion (varus/valgus rotations). In this investigation, a multiscale frame was developed based on structural hierarchies of the collateral ligaments starting from the bottom (tropocollagen molecule) to up where the fibred reinforced structure established. Experimental data of failure tensile test were considered as the principal driver of the developed model. This model was calibrated statistically using Bayesian calibration due to the high number of unknown parameters. Then the model is scaled up to fit the real structure of the collateral ligaments and simulated under realistic boundary conditions. Predications have been successful in describing the observed transient response of the collateral ligaments during tensile test under pre- and post-damage loading conditions. Collateral ligaments maximum stresses and strengths were observed near to the femoral insertions, a results that is in good agreement with experimental investigations. Also for the first time, damage initiation and propagation were documented with this model as a function of the cross-link density between tropocollagen molecules.

Keywords: multiscale model, tropocollagen, fibrils, ligaments commas

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Authors: RuiJin Zhang, HengJiang Cai, JinSong Gui

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It takes Patinopecten yessoensis larvae more than 20 days from spawning to settlement. Due to the natural environmental factors such as current, Patinopecten yessoensis larvae are transported to a distance more than hundreds of kilometers, leading to a high instability of their spatial and temporal distribution and great difficulties in the natural spat collection. Therefore predicting the distribution is of great significance to improve the operating efficiency of the collecting. Hydrodynamic model of Northern China Yellow Sea was established and the motions equations of physical oceanography and verified by the tidal harmonic constants and the measured data velocities of Dalian Bay. According to the passivity drift characteristics of the larvae, combined with the hydrodynamic model and the particle tracking model, the spatial and temporal distribution prediction model was established and the spatial and temporal distribution of the larvae under the influence of flow and wind were simulated. It can be concluded from the model results: ocean currents have greatest impacts on the passive drift path and diffusion of Patinopecten yessoensis larvae; the impact of wind is also important, which changed the direction and speed of the drift. Patinopecten yessoensis larvae were generated in the sea along Zhangzi Island and Guanglu-Dachangshan Island, but after two months, with the impact of wind and currents, the larvae appeared in the west of Dalian and the southern of Lvshun, and even in Bohai Bay. The model results are consistent with the relevant literature on qualitative analysis, and this conclusion explains where the larvae come from in the perspective of numerical simulation.

Keywords: numerical simulation, Patinopecten yessoensis larvae, predicting model, spatial and temporal distribution

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Authors: Sousan Arafeh

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Educational systems and schools worldwide are increasingly reliant on information and communication technology (ICT). Unfortunately, most educational leadership development programs do not offer formal curricular and/or field experiences that prepare students for managing ICT resources, personnel, and processes. The result is a steep learning curve for the leader and his/her staff and dissipated organizational energy that compromises desired outcomes. To address this gap in education leaders’ development, Arafeh’s Integrated Technology Leadership Model (AITLM) was created. It is a conceptual model and tool that educational leadership students can use to better understand the ICT ecology that exists within their schools. The AITL Model consists of six 'infrastructure types' where ICT activity takes place: technical infrastructure, communications infrastructure, core business infrastructure, context infrastructure, resources infrastructure, and human infrastructure. These six infrastructures are further divided into 16 key areas that need management attention. The AITL Model was created by critically analyzing existing technology/ICT leadership models and working to make something more authentic and comprehensive regarding school leaders’ purview and experience. The AITL Model then served as a tool when it was distributed to over 150 educational leadership students who were asked to review it and qualitatively share their reactions. Students said the model presented crucial areas of consideration that they had not been exposed to before and that the exercise of reviewing and discussing the AITL Model as a group was useful for identifying areas of growth that they could pursue in the leadership development program and in their professional settings. While development in all infrastructures and key areas was important for students’ understanding of ICT, they noted that they were least aware of the importance of the intangible area of the resources infrastructure. The AITL Model will be presented and session participants will have an opportunity to review and reflect on its impact and utility. Ultimately, the AITL Model is one that could have significant policy and practice implications. At the very least, it might help shape ICT content in educational leadership development programs through curricular and pedagogical updates.

Keywords: education leadership, information and communications technology, ICT, leadership capacity building, leadership development

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Authors: Gultekin Gurcay

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In this paper, effects and responses of stock were analyzed. This analysis was done periodically. The dimensions of the financial crisis impact on the stock market were investigated by GARCH model. In this context, S&P 500 stock market is modeled with DAX, NIKKEI and BIST100. In this way, The effects of the changing in S&P 500 stock market were examined on European and Asian stock markets. Conditional variance coefficient will be calculated through garch model. The scope of the crisis period, the conditional covariance coefficient will be analyzed comparatively.

Keywords: conditional variance coefficient, financial crisis, garch model, stock market

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Authors: Noe Brice Nkoumbou Kaptchouang, Pierre-Guy Vincent, Yann Monerie

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The present work addresses the modelling and the simulation of crack initiation and propagation in ductile materials which failed by void nucleation, growth, and coalescence. One of the current research frameworks on crack propagation is the use of cohesive-volumetric approach where the crack growth is modelled as a decohesion of two surfaces in a continuum material. In this framework, the material behavior is characterized by two constitutive relations, the volumetric constitutive law relating stress and strain, and a traction-separation law across a two-dimensional surface embedded in the three-dimensional continuum. Several cohesive models have been proposed for the simulation of crack growth in brittle materials. On the other hand, the application of cohesive models in modelling crack growth in ductile material is still a relatively open field. One idea developed in the literature is to identify the traction separation for ductile material based on the behavior of a continuously-deforming unit cell failing by void growth and coalescence. Following this method, the present study proposed a semi-analytical cohesive model for ductile material based on a micromechanical approach. The strain localization band prior to ductile failure is modelled as a cohesive band, and the Gurson-Tvergaard-Needleman plasticity model (GTN) is used to model the behavior of the cohesive band and derived a corresponding traction separation law. The numerical implementation of the model is realized using the non-smooth contact method (NSCD) where cohesive models are introduced as mixed boundary conditions between each volumetric finite element. The present approach is applied to the simulation of crack growth in nuclear ferritic steel. The model provides an alternative way to simulate crack propagation using the numerical efficiency of cohesive model with a traction separation law directly derived from porous continuous model.

Keywords: ductile failure, cohesive model, GTN model, numerical simulation

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Authors: Neeti Sharma, Harshika Pareek, Prerna Puri, Manika Mohan

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The present study is aimed at studying the significant relationship between anxiety and depression in chronic headache patients. Chronic Headache patients coming to the Neurology Unit-1 Outpatient Department of the Sawai Mansingh Hospital (SMS) Jaipur, Rajasthan, were included in this study. The sample consisted of 100 patients (N=100). Initially patients were examined by a physician and then they were assessed for Anxiety and Depression using the Hamilton Anxiety Rating Scale (HAM-A) and the Hamilton Rating Scale for Depression. The relevant information was recorded on a Performa designed for this purpose comprising of socio-demographic variables like age, gender and triggering factors. The correlation-coefficient indicated a significant positive relationship between the anxiety and depression in chronic headache patients. These findings implicate high prevalence of anxiety and depression in the general population, and also indicate an association between headache and psychological disorders. Many evidences support the anxiety-headache-depression syndrome as a distinct disorder, and the association of co-morbid psychiatric illness with headache intractability. This study highlights the importance of prospective research for studying the developmental course and consequences of headache syndromes. Also, various psychotherapies should be applied to the headache patients so as to treat them, at the onset level of anxiety and depression, with the help of medication.

Keywords: anxiety, chronic headaches, depression, HAM-A, HAM

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Zahra Okba, Hassan El Ouizgani

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Anticipating an individual’s behavior to the environmental factors allows for having relevant ecological forecasts. The Dynamic Energy Budget model facilitates prediction, and it is mechanically dependent on biology to abiotic factors but is generally field verified under relatively stable physical conditions. Dynamic Energy Budget Theory (DEB) is a robust framework that can link the individual state to environmental factors, and in our work, we have tested its ability to account for variability by looking at model predictions in the Agadir Bay, which is characterized by a semi-arid climate and temperature is strongly influenced by the trade winds front and nutritional availability. From previous works in our laboratory, we have collected different biological DEB model parameters of Mytilus galloprovincialis mussel in Agadir Bay. We mathematically formulated the equations that make up the DEB model and then adjusted our analytical functions with the observed biological data of our local species. We also assumed the condition of constant immersion, and then we integrated the details of the tidal cycles to calculate the metabolic depression at low tide. Our results are quite satisfactory concerning the length and shape of the shell in one part and the gonadosomatic index in another part.

Keywords: dynamic energy budget, mussels, mytilus galloprovincialis, agadir bay, DEB model

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Authors: Yi Sun, George Ed Rainger, Steve P. Watson

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Background: Beyond the classical roles in haemostasis and thrombosis, platelets are important in the initiation and development of various thrombo-inflammatory diseases. In atherosclerosis and deep vein thrombosis, for example, platelets bridge monocytes with endothelium and form heterotypic aggregates with monocytes in the circulation. This can alter monocyte phenotype by inducing their activation, stimulating adhesion and migration. These interactions involve cell surface receptor-ligand pairs on both cells. This list is likely incomplete as new interactions of importance to platelet biology are continuing to be discovered as illustrated by our discovery of PEAR-1 binding to FcεR1α. Results: We have developed a highly sensitive avidity-based assay to identify novel extracellular interactions among 126 recombinantly-expressed platelet cell surface and secreted proteins involved in platelet aggregation. In this study, we will use this method to identify novel platelet-monocyte interactions. We aim to identify ligands for orphan receptors and novel partners of well-known proteins. Identified interactions will be studied in preliminary functional assays to demonstrate relevance to the inflammatory processes supporting atherogenesis. Conclusions: Platelet-monocyte interactions are essential for the development of thromboinflammatory disease. Up until relatively recently, technologies only allow us to limit our studies on each individual protein interaction at a single time. These studies propose for the first time to study the cell surface platelet-monocyte interactions in a systematic large-scale approach using a reliable screening method we have developed. If successful, this will likely to identify previously unknown ligands for important receptors that will be investigated in details and also provide a list of novel interactions for the field. This should stimulate studies on developing alternative therapeutic strategies to treat vascular inflammatory disorders such as atherosclerosis, DVT and sepsis and other clinically important inflammatory conditions.

Keywords: membrane proteins, large-scale screening, platelets, recombinant expression

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Authors: M. Ekiert, T. Uhl, A. Mlyniec

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Tendons are the biological soft tissue structures composed of collagen, proteoglycan, glycoproteins, water and cells of extracellular matrix (ECM). Tendons, which primary function is to transfer force generated by the muscles to the bones causing joints movement, are exposed to many micro and macro damages. In fact, tendons and ligaments trauma are one of the most numerous injuries of human musculoskeletal system, causing for many people (particularly for athletes and physically active people), recurring disorders, chronic pain or even inability of movement. The number of tendons reconstruction and transplantation procedures is increasing every year. Therefore, studies on soft tissues storage conditions (influencing i.e. tissue aging) seem to be an extremely important issue. In this study, an atomic-scale investigation on the kinetics of decomposition of two selected tendon components – collagen type I (which forms a 60-85% of a tendon dry mass) and elastin protein (which combine with ECM creates elastic fibers of connective tissues) is presented. A molecular model of collagen and elastin was developed based on crystal structure of triple-helical collagen-like 1QSU peptide and P15502 human elastin protein, respectively. Each model employed 4 linear strands collagen/elastin strands per unit cell, distributed in 2x2 matrix arrangement, placed in simulation box filled with water molecules. A decomposition phenomena was simulated with molecular dynamics (MD) method using ReaxFF force field and periodic boundary conditions. A set of NVT-MD runs was performed for 1000K temperature range in order to obtained temperature-depended rate of production of decomposition by-products. Based on calculated reaction rates activation energies and pre-exponential factors, required to formulate Arrhenius equations describing kinetics of decomposition of tested soft tissue components, were calculated. Moreover, by adjusting a model developed for collagen, system scalability and correct implementation of the periodic boundary conditions were evaluated. An obtained results provide a deeper insight into decomposition of selected tendon components. A developed methodology may also be easily transferred to other connective tissue elements and therefore might be used for further studies on soft tissues aging.

Keywords: decomposition, molecular dynamics, soft tissue, tendons

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Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

Abstract:

Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

Procedia PDF Downloads 526