Search results for: early childhood professionals

Authors: Seree Chadcham, Niphon Sukvilai

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This study is the research and development which is intended to: 1) design of the Intelligent Scaffolding Learning Management System (ISLMS) for vocational education, 2) assess the suitability of the Design of Intelligent Scaffolding Learning Management System for Vocational Education. Its methods are divided into 2 phases. Phase 1 is the design of the ISLMS for Vocational Education and phase 2 is the assessment of the suitability of the design. The samples used in this study are work done by 15 professionals in the field of Intelligent Scaffolding, Learning Management System, Vocational Education, and Information and Communication Technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ISLMS for vocational education consists of 2 main components which are: 1) the Intelligent Learning Management System for Vocational Education, 2) the Intelligent Scaffolding Management System. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: intelligent, scaffolding, learning management system, vocational education

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Authors: Nataša Šarlija, Sanja Pfeifer

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This study analyzes the innovative orientation of the Croatian entrepreneurs. Innovative orientation is represented by the perceived extent to which an entrepreneur’s product or service or technology is new, and no other businesses offer the same product. The sample is extracted from the GEM Croatia Adult Population Survey dataset for the years 2003-2013. We apply descriptive statistics, t-test, Chi-square test and logistic regression. Findings indicate that innovative orientations vary with personal, firm, meso and macro level variables, and between different stages in entrepreneurship process. Significant predictors are occupation of the entrepreneurs, size of the firm and export aspiration for both early stage and established entrepreneurs. In addition, fear of failure, expecting to start a new business and seeing an entrepreneurial career as a desirable choice are predictors of innovative orientation among early stage entrepreneurs.

Keywords: multilevel determinants of the innovative orientation, Croatian early stage entrepreneurs, established businesses, GEM evidence

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Authors: Pinhas Dannon, Aviv Weinstein

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Impulsivity is raising major interest clinically because it is associated with various clinical conditions such as delinquency, antisocial behavior, suicide attempts, aggression, and criminal activity. The evolutionary perspective argued that impulsivity relates to self-regulation and it has predicted that female individuals should have evolved a greater ability to inhibit pre-potent responses. There is supportive evidence showing that female individuals have better performance on cognitive tasks measuring impulsivity such as delay in gratification and delayed discounting mainly in childhood. During adolescence, brain imaging studies using diffusion tensor imaging on white matter architecture indicated contrary to the evolutionary perspective hypothesis, that young adolescent male individuals may be less vulnerable than age-matched female individuals to risk- and reward- related maladaptive behaviors. In adults, the results are mixed presumably owing to hormonal effects on neuro-biological mechanisms of reward. Consequently, female individuals were less impulsive than male individuals only during fertile stages of the menstrual cycle. Finally, there is evidence the serotonin (5-HT) system is more involved in the impulsivity of men than in that of women. Overall, there seem to be sex differences in impulsivity but these differences are more pronounced in childhood and they are later subject to maturational and hormonal changes during adolescence and adulthood and their effects on the brain, cognition, and behavior.

Keywords: impulse control, male population, female population, gender differences, reward, neurocognitive tests

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Authors: Rreze Gecaj, Corina Schanzenbach, Benedikt Kirchner, Michael Pfaffl, Bajram Berisha

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The maintenance of corpus lutem (CL) during early pregnancy in cattle is a critical and multifarious process. A luteotrophic mechanism originating from the embryo is widely accepted as the triggering signal for the CL maintenance. In the cattle, it is the interferon-tau (IFNT) secretion form conceptus that prevents CL regression and ensures progesterone production for the establishment of pregnancy. In addition to endocrine and paracrine signals, microRNA (miRNA) can also support CL sustainability during early pregnancy. MiRNA are small non-coding nucleic acids that regulate gene expression post-transcriptionally and are shown to be involved in the modulation of CL function. However, the examination of miRNAs in corpus luteum function at the early pregnancy still remains largely uncovered. This study aims at profiling the expression of miRNA in CL during the early pregnancy in cattle by comparing it with the CL form late cycle and with the regressed CL. Corpora lutea were assigned in two different groups during the cycle (C13 group, late CL: days 13-18 and C18, regressed CL group: day >18) and during the early pregnancy (group P: 1-2 month). The estrous cycle was determined by macroscopic examination and to age the fetus crown-rump length measurement was applied. A total of 9 corpora lutea from individual animals were included in the study, three corpora lutea for each group. MiRNAs population was profiled using small RNA next-generation sequencing and biologically significant miRNAs were evaluated for their differential expression using the DESeq2-methodology. We show that 6 differentially expressed miRNAs (bta-mir-2890, -2332, -2441-3p, -148b, -1248 and -29c) are common to both comparisons, P vs C13 and P vs C18. While for each stage individually we have identified unique miRNAs differentially expressed only for the given comparison. bta-miR-23a and -769 were unique miRNAs differentially expressed in P vs C13, whereas forty-four unique miRNAs were identified as differentially expressed in P vs C18. These data confirm that miRNAs are highly abundant in luteal tissue during early pregnancy and potentially regulate the CL maintenance at this stage of fetus development.

Keywords: bovine, corpus luteum, microRNA, pregnancy, RNA-Seq

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Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

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Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: Matthew Cruickshank, Chaaruchandra Korde, Roger P. West, John Reddy

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Precast concrete element exports are growing in importance in Ireland’s concrete industry and with the increased global focus on reducing carbon emissions, the industry is exploring more sustainable alternatives such as using ground granulated blast-furnace slag (GGBS) as a partial replacement of Portland cement. It is well established that GGBS, with low early age strength development, has limited use in precast manufacturing due to the need for early de-moulding, cutting of pre-stressed strands and lifting. In this dichotomy, the effects of temperature, admixture, are explored to try to achieve the required very early age strength. Testing of the strength of mortars is mandated in the European cement standard, so here with 50% GGBS and Super Fine GGBS, with three admixture conditions (none, conventional accelerator, novel accelerator) and two early age curing temperature conditions (20°C and 35°C), standard mortar strengths are measured at six ages (16 hours, 1, 2, 3, 7, 28 days). The present paper will describe the effort towards developing maturity curves to aid in understanding the effect of these accelerating admixtures and GGBS fineness on slag cement mortars, allowing prediction of their strength with time and temperature. This study is of particular importance to the precast industry where concrete temperature can be controlled. For the climatic conditions in Ireland, heating of precast beds for long hours will amount to an additional cost and also contribute to the carbon footprint of the products. When transitioned from mortar to concrete, these maturity curves are expected to play a vital role in predicting the strength of the GGBS concrete at a very early age prior to demoulding.

Keywords: accelerating admixture, early age strength, ground granulated blast-furnace slag, GGBS, maturity, precast concrete

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Authors: Coline Bretz, Andrea Vaccaro, Dario Leumann

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The food, personal care, and cosmetic industries are seeing increased consumer demand for more sustainable and innovative ingredients. When developing new formulations incorporating such ingredients, stability is one of the first criteria that must be assessed, and it is thus of great importance to have a method that can detect instabilities early and quickly. Diffusing Wave Spectroscopy (DWS) is a light scattering technique that probes the motion,i.e., the mean square displacement (MSD), of colloids, such as nanoparticles in a suspension or droplets in emulsions. From the MSD, the rheological properties of the surrounding medium can be determined via the so-called microrheology approach. In the case of purely viscous media, it is also possible to obtain information about particle size. DWS can thus be used to monitor the size evolution of particles, droplets, or bubbles in aging dispersions, emulsions, or foams. In the context of early instability detection in emulsions, DWS offers considerable advantages, as the samples are measured in a contact-free manner, using only small quantities of samples loaded in a sealable cuvette. The sensitivity and rapidity of the technique are key to detecting and following the ageing of emulsions reliably. We present applications of DWS focused on the characterization of emulsions. In particular, we demonstrate the ability to record very subtle changes in the structural properties early on. We also discuss the various mechanisms at play in the destabilization of emulsions, such as coalescence or Ostwald ripening, and how to identify them through this technique.

Keywords: instrumentation, emulsions, stability, DWS

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Authors: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

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Authors: Saman Naqvi

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Introduction: Telemedicine is the practise of providing remote healthcare to patients via the utilisation of communication technologies. Its application has become increasingly important since the Coronavirus Disease 2019 (COVID-19) pandemic. It is essential to determine the knowledge and attitudes of healthcare professionals concerning its use in order to maximise its application. Purpose: We aim to examine and evaluate the current understanding and perceptions of medical staff toward the use of telemedicine. Methods: In this cross-sectional study, we surveyed 1091 healthcare professionals worldwide. Following an extensive review of the literature, data were gathered using a questionnaire. To depict the participant profile, frequency, percentages, and cumulative percentages were determined. Results: The majority of respondents had either heard of (90.9%), seen (65.3%), or were familiar with (74.6%) how telemedicine is implemented in practice. 72.2% of people were familiar with the tools that could be applied to this technology. Those with a medical degree and experience of under five years were found to be more familiar with telemedicine. Additionally, opinions on providing healthcare remotely were largely favorable, with 80% of respondents stating that it reduced staff burden and 80.6% thinking that it eliminated unnecessary transportation costs. Furthermore, 83% expressed that it saves clinicians' time. However, 20% of participants believed telemedicine adds to staff workload and 40% of healthcare professionals felt it compromises patient privacy and information confidentiality. Conclusion: Despite being a new and developing practice in many countries, telemedicine appears to have a bright future. This is crucial during a pandemic as it provides effective healthcare while maintaining social isolation measures. Moreover, the majority of the participants in this study demonstrated a good understanding and a favorable attitude toward telemedicine.

Keywords: healthcare system, global survey, knowledge, attitude, covid 19, telemedicine

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Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

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In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

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Authors: Wisit Wichitkosoom

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Objectives: To find out the more effect of early cardiologist consultation using a simple technology on the diagnosis and early proper management of patients with Non-STEMI at emergency department of district hospitals without cardiologist on site before transferred. Methods: A cohort study was performed in Udonthani general hospital at Udonthani province. From 1 October 2012–30 September 2013 with 892 patients diagnosed with Non-STEMI. All patients mean aged 46.8 years of age who had been transferred because of Non-STEMI diagnosed, over a 12 week period of studied. Patients whose transferred, in addition to receiving proper care, were offered a cardiologist consultation with average time to Udonthani hospital 1.5 hour. The main outcome measure was length of hospital stay, mortality at 3 months, inpatient investigation, and transfer rate to the higher facilitated hospital were also studied. Results: Hospital stay was significantly shorter for those didn’t consult cardiologist (hazard ratio 1.19; approximate 95% CI 1.001 to 1.251; p = 0.039). The 136 cases were transferred to higher facilitated hospital. No statistically significant in overall mortality between the groups (p=0.068). Conclusions: Early cardiologist consultant can reduce length of hospital stay for patients with cardiovascular conditions outside of cardiac center. The new basic technology can apply for the safety patient.

Keywords: critical, telemedicine, safety, non STEMI

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Authors: Katherine Karayianis

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Children with Attention Deficit Hyperactivity Disorder (ADHD) have trouble learning in traditional classrooms. These children miss out on important developmental opportunities in school, which leads to challenges starting in early childhood, and these problems persist throughout their adult lives. Despite receiving supplemental support in school, children with ADHD still perform below their non-ADHD peers. Thus, there is a great need to find better ways of facilitating learning in children with ADHD. Evidence has shown that children with ADHD learn best through interactive engagement, but this is not always possible in schools, given classroom restraints and the large student-to-teacher ratio. Redesigning classrooms may not be feasible, so informal learning opportunities provide a possible alternative. One popular informal learning opportunity is educational TV shows like Sesame Street. These types of educational shows can teach children foundational skills taught in pre-K and early elementary school. One downside to these shows is the lack of interactive dialogue between the TV characters and the child viewers. Pseudo-interaction is often deployed, but the benefits are limited if the characters can neither understand nor contingently respond to the child. AI technology has become extremely advanced and is now popular in many electronic devices that both children and adults have access to. AI has been successfully used to create interactive dialogue in children’s educational TV shows, and results show that this enhances children’s learning and engagement, especially when children perceive the character as a reliable teacher. It is likely that children with ADHD, whose minds may otherwise wander, may especially benefit from this type of interactive technology, possibly to a greater extent depending on their perception of the animated dialogic agent. To investigate this issue, I have begun examining the moderating role of inattention among children’s learning from an educational TV show with different types of dialogic interactions. Preliminary results have shown that when character interactions are neither immediate nor accurate, children who are more easily distracted will have greater difficulty learning from the show, but contingent interactions with a TV character seem to buffer these negative effects of distractibility by keeping the child engaged. To extend this line of work, the moderating role of the child’s perception of the dialogic agent as a reliable teacher will be examined in the association between children’s attention and the type of dialogic interaction in the TV show. As such, the current study will investigate this moderated moderation.

Keywords: attention, dialogic TV, informal learning, educational TV, perception of teacher

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Authors: Chau-Kuang Chen, Juanita Buford, Colette Davis, Raisha Allen, John Hughes, James Tyus, Dexter Samuels

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During the post-Civil War era, the city of Nashville, Tennessee, had the highest mortality rate in the country. The elevated death and disease among ex-slaves were attributable to the unavailability of healthcare. To address the paucity of healthcare services, the College, an institution with the mission of educating minority professionals and serving the under served population, was established in 1876. This study was designed to assess if the College has accomplished its mission of serving under served communities and contributed to the elimination of health disparities in the United States. The study objective was to quantify the impact of socioeconomic status and adverse health outcomes on primary care professionals serving disadvantaged communities, which, in turn, was significantly associated with a health professional shortage score partly designated by the U.S. Department of Health and Human Services. Various statistical methods were used to analyze the alumni data in years 1975 – 2013. K-means cluster analysis was utilized to identify individual medical and dental graduates into the cluster groups of the practice communities (Disadvantaged or Non-disadvantaged Communities). Discriminant analysis was implemented to verify the classification accuracy of cluster analysis. The independent t test was performed to detect the significant mean differences for clustering and criterion variables between Disadvantaged and Non-disadvantaged Communities, which confirms the “content” validity of cluster analysis model. Chi-square test was used to assess if the proportion of cluster groups (Disadvantaged vs Non-disadvantaged Communities) were consistent with that of practicing specialties (primary care vs. non-primary care). Finally, the partial least squares (PLS) path model was constructed to explore the “construct” validity of analytics model by providing the magnitude effects of socioeconomic status and adverse health outcome on primary care professionals serving disadvantaged community. The social ecological theory along with statistical models mentioned was used to establish the relationship between medical and dental graduates (primary care professionals serving disadvantaged communities) and their social environments (socioeconomic status, adverse health outcome, health professional shortage score). Based on social ecological framework, it was hypothesized that the impact of socioeconomic status and adverse health outcomes on primary care professionals serving disadvantaged communities could be quantified. Also, primary care professionals serving disadvantaged communities related to a health professional shortage score can be measured. Adverse health outcome (adult obesity rate, age-adjusted premature mortality rate, and percent of people diagnosed with diabetes) could be affected by the latent variable, namely socioeconomic status (unemployment rate, poverty rate, percent of children who were in free lunch programs, and percent of uninsured adults). The study results indicated that approximately 83% (3,192/3,864) of the College’s medical and dental graduates from 1975 to 2013 were practicing in disadvantaged communities. In addition, the PLS path modeling demonstrated that primary care professionals serving disadvantaged community was significantly associated with socioeconomic status and adverse health outcome (p < .001). In summary, the majority of medical and dental graduates from the College provide primary care services to disadvantaged communities with low socioeconomic status and high adverse health outcomes, which demonstrate that the College has fulfilled its mission.

Keywords: disadvantaged community, K-means cluster analysis, PLS path modeling, primary care

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Authors: Sisira Edirippulige

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Background: Digital health education and training (DHET) is imperative for preparing current and future clinicians to work competently in digitally enabled environments. Despite rapid integration of digital health in modern health services, systematic education and training opportunities for health workers is still lacking. Objectives: This study aimed to investigate healthcare professionals’ perspectives and expectations regarding the knowledge, skills and competency needs in digital health for current and future healthcare workforce. Methods: A qualitative study design with semi-structured individual interviews was employed. A purposive sample method was adopted to collect relevant information from the health workers. Inductive thematic analysis was used to analyse data. Interviews were audio-recorded and transcribed verbatim. Consolidated Criteria for Reporting Qualitative Research (COREQ) was followed when we reported this study. Results: Two themes emerged while analysing the data: (1) what to teach in DHET and (2) how to teach DHET. Overall, healthcare professionals agreed that DHET is important for preparing current and future clinicians for working competently in digitally enabled environments. Knowledge relating to what is digital health, types of digital health, use of technology and human factors in digital health were considered as important to be taught in DHET. Skills relating to digital health consultations, clinical information system management and remote monitoring were considered important to be taught. Blended learning which combined e-learning and classroom-based teaching, simulation sessions and clinical rotations were suggested by healthcare professionals as optimal approaches to deliver the above-mentioned content. Conclusions: This study is the first of its kind to investigate health professionals’ perspectives and expectations relating to the knowledge, skills and competency needs in digital health for current and future healthcare workforce. Healthcare workers are keen to acquire relevant knowledge, skills and competencies related to digital health. Different modes of education delivery is of interest to fit in with busy schedule of health workers.

Keywords: digital health, telehealth, telemedicine, education, curriculum

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Authors: Mohd Abdullah

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This review describes some of the effects of repetitive strain/stress injury (RSI) on the human body especially among computer professionals today that spend extended hours of prolonged sitting in front of a computer day in and day out. The review briefly introduces the main factors that contribute to an increase of RSI among such computer professionals. The review briefly discusses how the human spinal column and knees are mainly affected by the onset of RSI resulting in poor posture. The root and secondary causes and effects of RSI are reviewed. The importance and value of the various breathing techniques are reviewed in an attempt to alleviate some of the effects of RSI. The review concludes with a small sample of suggested office stretches and poses geared towards at reducing RSI follows in this review. Readers will learn about the effects of RSI, as well as ways to cope with it. A better understanding of coping strategies may lead to well-being and a healthier overall lifestyle. Ultimately, the investment of time to connect with oneself with the poses and the power of the breath would promote a well-being that is overall healthier thus resulting in a better ability to cope/manage life stresses.

Keywords: health, wellness, repetitive, chairs

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Authors: Natalie Thorburn

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New Zealand legalised and regulated prostitution 13 years ago with the hope of eradicating unsafe or exploitative practices in the sex trade, but the extent to which this has been successful has been hotly contested, with the New Zealand Government denying any existence of sex trafficking and evidence generally indicating the success of the 2004 reform. The aim of the research was therefore to establish the circumstances in which sex trafficking may be occurring without using any previously instrumental gatekeepers of the New Zealand sex industry. 14 survivors of gang, family, or intimate partner trafficking (all of whom had first been trafficked prior to the age of 16) were interviewed, as well as several key informants. It was found that there was a perceived lack of commitment by Police to investigate instances of trafficking, and this was considered to be linked to the legal status of prostitution. The lack of recognition at both community and political levels of the existence and prevalence of trafficking also meant that medical and social service practitioners were unaware trafficking was occurring, and would not know who to refer to if it was disclosed. Participants commonly normalised coercion into sex, seeing this as a continuation of prior sexually abusive experiences that were prevalent in their childhood and early adolescent environments. Their experiences with the helping services were typically either negative or non-existent, and they expressed frustration regarding the absence of justice, the lack of awareness, and health and outcomes they suffered in relation to their experiences of having been trafficked. Barriers to engagement and strategies to facilitate meaningful and sustainable engagement with this population group are therefore presented.

Keywords: legalisation, regulation, service access, socio-political context

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Authors: Sanjeev Sharma, Suman Lata

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With the availability of diverse printed, electronic literature and web sites on medical and health related information, it is impossible for the medical professional to get the information he seeks in the shortest possible time. For all these problems information literacy is the only solution. Thus, information literacy is recognized as an important aspect of medical education. In the present study, an attempt has been made to know the information literacy skills of the faculty and students at medical colleges of Haryana, Punjab and Chandigarh. The scope of the study was confined to the 12 selected medical colleges of three States (Haryana, Punjab, and Chandigarh). The findings of the study were based on the data collected through 1018 questionnaires filled by the respondents of the medical colleges. It was found that Online Medical Websites (such as WebMD, eMedicine and Mayo Clinic etc.) were frequently used by 63.43% of the respondents of Chandigarh which is slightly more than Haryana (61%) and Punjab (55.65%). As well, 30.86% of the respondents of Chandigarh, 27.41% of Haryana and 27.05% of Punjab were familiar with the controlled vocabulary tool; 25.14% respondents of Chandigarh, 23.80% of Punjab, 23.17% of Haryana were familiar with the Boolean operators; 33.05% of the respondents of Punjab, 28.19% of Haryana and 25.14% of Chandigarh were familiar with the use and importance of the keywords while searching an electronic database; and 51.43% of the respondents of Chandigarh, 44.52% of Punjab and 36.29% of Haryana were able to make effective use of the retrieved information. For accessing information in electronic format, 47.74% of the respondents rated their skills high, while the majority of respondents (76.13%) were unfamiliar with the basic search technique i.e. Boolean operator used for searching information in an online database. On the basis of the findings, it was suggested that a comprehensive training program based on medical professionals information needs should be organized frequently. Furthermore, it was also suggested that information literacy may be included as a subject in the health science curriculum so as to make the medical professionals information literate and independent lifelong learners.

Keywords: information, information literacy, medical professionals, medical colleges

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Aikaterini Tavoulari

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This research aims to address the types of repetitive behaviours (RBs) observed by adults in children with vision impairment (VI) or autism spectrum disorder (ASD), the explanations the adults employ to interpret these behaviours, and the impact RBs have on the child, the caregiver, the professional and society. The underlying reason for this is an attempt to discover any potential differences between two different disabilities in a comparative fashion. The study is based on the interpretivism paradigm and follows a qualitative approach. A comparative case study design based on the ecological systems theory (EST) is adopted. Thirty-five caregivers and accredited professionals were recruited (17 for the VI group, out of whom 8 were caregivers and 9 were professionals, and 18 for the ASD group, out of whom 9 were caregivers and 9 were professionals). Following the completion of a pilot study, all participants were interviewed regarding one specific child – their own child/student – via semi-structured interviews. During the interviews, the researcher used a research diary as a methodological tool and video elicitation as a facilitation tool. A cross-case analysis was conducted, and data were analysed according to the method of thematic analysis. A link has been indicated between VI and ASD, which concerns perceptions about the socially constructed manner in which an RB is perceived. ASD is perceived by the participants as a disability with challenging characteristics, such as an RB. The ASD group perceived RB as linked to ableism, social stigmatisation, and taboo, in contrast to VI, where the existence of RB seems to be a consequence of sensory loss. Bi-directionality of EST seems to have been lost completely, and the macrosystem seems to drive the interactions between the ecological systems.

Keywords: ableism, social stigma, disability, repetitive behaviour, vision impairment, autism spectrum disorder, perceptions

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Authors: Sreelekha Prakash, Yulong Gu

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Background: About 61% of adults surveyed across 25 states reported they had experienced at least one type of Adverse Childhood Experience (ACE) before 18 years of age. Relationships between ACEs and a variety of substance-related behaviors and behavioral health have been reported in previous studies. ACEs can have lasting, negative effects on health, well-being, as well as life opportunities such as education and job potential. Objectives: For the current research, the aim was to assess the factors affecting substance use behavior in young adults. The further onset of drug use and its association was analyzed with ACEs and mental health. Method: The young adults from a county in the north-eastern United States were invited to participate in an online questionnaire survey with prior consent through an IRB approved study. The Survey included questions related to social determinants of health, 10 item ACE questionnaire, and substance use related to Alcohol, Marijuana, Opioids, Stimulants, and other drugs. PHQ-9 questionnaire was used to assess cognitive health. Results: Data was analyzed for the 244 completed surveys {68% (165) were females, and 78% (190) were Whites}. The average age of the participants was 26.7 years, and approximately 80% were lifelong residents of the county or year-round residents. Of the respondents, 50% (122) were high school graduates with some college education, and 56% (136) had a full-time jobs. Past 30-day usage for alcohol was 76% (72), and marijuana was 28.4% (27). The data showed that the higher the ACE scores, the younger they start using any substance (p < 0.0001). The data for PHQ-9 and ACE scores showed that the higher the ACE score, the higher the PHQ-9 score, with a significant p-value (p 0.0001). The current data also showed a significant association with other drugs; marijuana use showed significance for 30 days of use (p 0.0001), stimulant use (0.0008), prescription drug misuse (0.01), and opioids (0.01). Conclusion: These findings further support the association between ACEs and initiation of drug use and its correlation with mental health symptoms. Promoting a safe and supportive environment for children and youth in their earlier ages can prevent the youth and young adults from the effects of drug use and create healthy living habits for young adults.

Keywords: subtance use, young adults, adverse childhood experience, PHQ-9

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Authors: Salwa Hagag Abdelaziz, Dorria Salem, Hoda Zaki, Suzan Atteya

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Early detection of breast cancer saves many thousands of lives each year via application of mammography and genetic screening and many more lives could be saved if nurses are involved in breast care screening practices. So, the aim of the study was to identify nurse's role in early detection of breast cancer through mammography and genetic screening and its impact on patient's outcome. In order to achieve this aim, 400 women above 40 years, asymptomatic were recruited for mammography and genetic screening. In addition, 50 nurses and 6 technologists were involved in the study. A descriptive analytical design was used. Five tools were utilized: sociodemographic, mammographic examination and risk factors, women's before, during and after mammography, items relaying to technologists, and items related to nurses were also obtained. The study finding revealed that 3% of women detected for malignancy and 7.25% for fibroadenoma. Statistically, significant differences were found between mammography results and age, family history, genetic screening, exposure to smoke, and using contraceptive pills. Nurses have insufficient knowledge about screening tests. Based on these findings the present study recommended involvement of nurses in breast care which is very important to in force population about screening practices.

Keywords: mammography, early detection, genetic screening, breast cancer

Procedia PDF Downloads 557

Authors: Pui-Lai To, Chechen Liao, Ming-Chi Sung

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Work and family life are the most important areas for men and women today. Every professional is required to meet and fulfill the responsibilities of work and family roles. Although the development and popularity of communication technology bring a lot of benefits, including effective and efficient communication, may also generate conflicts between work and family life. Since mobile devices and the applications of mobile devices, such as instant messages, are ubiquitous, the boundaries of work and family roles are increasingly blurred. Professionals may be in the risk of work over-loading and work-family conflict. This study examines the impact of work stress on professionals’ life and health in the context of instant messaging application of smart phone. This study uses a web-based questionnaire to collect samples. The questionnaires are sent via virtual community sites, instant messaging applications, and e-mail. The study develops and empirically validates a work-family conflict model by integrating the pressure theory and technostress factors. The causal relationship between variables in the research model is tested. In terms of data analysis, Partial Least Square (PLS) in Structural Equation Modeling (SEM) is used for sample analysis and research model testing. The results of this study are as follows. First, both the variables of work-related stress and technological violations positively affect the work-family conflict. Second, both the variables of work-loading and technology-overloading have no effect on work-family conflict. Third, work-family conflict has negative effect on job satisfaction, family satisfaction, physical health, and mental health.

Keywords: mental health, physical health, technostress, work-family conflict, work-related stress

Procedia PDF Downloads 286

Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

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Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

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Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

Abstract:

Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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Authors: Mahdi Alshamasin, Riad Al-Kasasbeh, Nikolay Korenevskiy

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We apply mathematical models for the interaction of the internal and biologically active points of meridian structures. Amongst the diseases for which reflex diagnostics are effective are those of the stomach disease. It is shown that use of fuzzy logic decision-making yields good results for the prediction and early diagnosis of gastrointestinal tract diseases, depending on the reaction energy of biologically active points (acupuncture points). It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained by using fuzzy logic decision-making.

Keywords: acupuncture points, fuzzy logic, diagnostically important points (DIP), confidence factors, membership functions, stomach diseases

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Authors: Theresa Robinson Harris

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Small businesses are important to the United States economy, yet the majority struggle to remain relevant and close before their fifth year. This qualitative study explored small business failure by comparing the experiences of small-business owners to understand their involvement with leadership during the early stages of the business, and the impact of this on the firms’ ability to survive. Participants’ experiences from two groups were compared to glean an understanding of the leadership process, how leadership differs between the groups, and to see what themes or constructs emerged that could help to explain the high failure rate. Leadership was perceived to be important when envisioning a path for the future and when providing a platform for employees to succeed. Those who embraced leadership as a skillset were more likely to get through the challenges of the early developmental years while those ignoring the importance of leadership were more likely to close prematurely. These findings suggest a disconnect with regards to the understanding, role, and benefits of leadership in small organizations, particularly young organizations in the early stages of development.

Keywords: leadership, small business, entrepreneurship, success, failure

Procedia PDF Downloads 246

Authors: T. Borja-Alvarez, V. Jiménez-Borja, M. Jiménez Borja, C. J. Jiménez-Mosquera

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Research on child sexual abuse has predominantly focused on female survivors. This has resulted in less research looking at the particular context in which this abuse takes place for boys and the impact this abuse may have on male survivors. The aim of this study is to examine the sex and age of the perpetrators of child sexual abuse and explore gender differences in the impact along with the subjective interpretation that survivors attribute to these experiences. The data for this study was obtained from Ecuadorian university students (M = 230, F = 293) who reported sexual abuse using the ISPCAN Child Abuse Screening Tool Retrospective version (ICAST-R). Participants completed Horowitz's Impact of Event Scale (IES) and were also requested to choose among neutral, positive, and negative adjectives to describe these experiences. The results indicate that in the case of males, perpetrators were both males (adults =27%, peers =20%, relatives =10.3%, cousins =7.4%) and young females (girlfriends or ex-girlfriends =25.6%, neighborhood =20.7%, school =16.7%, cousins =15.3%, strangers =12.8%). In contrast, almost all females reported that adult males were the perpetrators (relatives =29.6%, neighborhood =11.9%, strangers =19.9%, family friends =9.7%). Regarding the impact of these events, significant gender differences emerged. More females (50%) than males (20%) presented symptoms of post-traumatic stress disorder (PTSD). Gender differences also surfaced in the way survivors interpret their experiences. Almost half of the male participants selected the word “consensual” followed by the words “normal”, “helped me to mature”, “shameful”, “confusing”, and “traumatic”. In contrast, almost all females chose the word “non-consensual” followed by the words “shameful”, “traumatic”, “scary”, and “confusing”. In conclusion, the findings of this study suggest that young females and adult males were the most common perpetrators of sexually abused boys whereas adult males were the most common perpetrators of sexually abused girls. The impact and the subjective interpretation of these experiences were more negative for girls than for boys. The factors that account for the gender differences in the impact and the interpretation of these experiences need further exploration. It is likely that the cultural expectations of sexual behaviors for boys and girls in Latin American societies may partially explain the differential impact in the way these childhood sexual abuse experiences are interpreted in adulthood. In Ecuador, as is the case in other Latin American countries, the machismo culture not only accepts but encourages early sexual behaviors in boys and negatively judges premature sexual behavior in females. The result of these different sexual expectations may be that sexually abused boys may re-define these experiences as “consensual” and “normal” in adulthood, even though these were not consensual at the time of occurrence. Future studies are needed to more deeply understand the different contexts of sexual abuse for boys and girls in order to analyze the long-term impact of these experiences.

Keywords: abuse, child, gender differences, sexual

Procedia PDF Downloads 93

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 351

Authors: Ya-Ting Carolyn Yang, Ping-Han Cheng, Shi-Hui Gilbert Chang, Terry Yuan-Fang Chen, Chih-Chieh Li

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Nanotechnology is widely applied in various areas so professionals in the related fields have to know more than nano knowledge. In the study, we focus on adopting ICT-assisted PBL in college general education to foster professionals who possess multiple abilities. The research adopted a pretest and posttest quasi-experimental design. The control group received traditional instruction, and the experimental group received ICT-assisted PBL instruction. Descriptive statistics will be used to describe the means, standard deviations, and adjusted means for the tests between the two groups. Next, analysis of covariance (ANCOVA) will be used to compare the final results of the two research groups after 6 weeks of instruction. Statistics gathered in the end of the research can be used to make contrasts. Therefore, we will see how different teaching strategies can improve students’ understanding about nanotechnology and learning skills.

Keywords: nanotechnology, science education, project-based learning, information and communication technology

Procedia PDF Downloads 371