Search results for: technological interventions

Authors: Hong Zhang, Runlian Miao, Min Zhang

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Coordinated development of Beijing-Tianjin-Hebei region is of great importance and has been emphasized by the government in recent years. Beijing-Tianjin-Hebei region accumulates a large part of S&T resources of the whole country and boasts the most influential achievements. In order to improve innovation capability of the region, universities, research institutions and enterprises from Beijing, Tianjin and Hebei have cooperated in many forms, but technological innovation is not so satisfactory due to unbalanced allocation, poor sharing and low utilization efficiency of S&T resources. Therefore, it’s very necessary to promote resources sharing, optimize their overall layout, and enhance their innovation performance, which can further deepen coordination development of the region. This study focuses on S&T resources with the methods of documents research plus field investigation and qualitative research combing plus quantitive research. It starts from the macro background of promoting coordinated development of Beijing-Tianjin-Hebei region and arrives at improving regional innovation capability. Firstly, the author makes a literature review on coordinated development of Beijing-Tianjin-Hebei region and summarizes that coordinated development has been carried forward in the major fields which lay foundation for regional innovation; secondly, analyzes current S&T resources distribution and coordinated innovation by taking key industries as the examples; based on analysis of the status quo of resources sharing and innovation in the region, the author points out problems and obstacles that holdbacks coordinated innovation of the region and at last raises some suggestions to resources sharing and regional innovation. It reaches the conclusion that an efficient management mechanism, market laws, favorable environment, model innovation and incentive measures can help to accelerate resources sharing and regional innovation in the region.

Keywords: Beijing-Tianjin-Hebei region, coordinated development, innovation, S&T resources

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Authors: Krishna Pal Singh, Shailendra Kumar Gupta, Olaf Wolkenhauer

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Background: Our study aimed to identify common genes and potential targets across the four diseases, which include rheumatoid arthritis, melanoma metastasis, ulcerative colitis, and Crohn’s disease. We used a network and systems biology approach to identify the hub gene, which can act as a potential target for all four disease conditions. The regulatory network was extracted from the PPI using the MCODE module present in Cytoscape. Our objective was to investigate the significance of hub genes in these diseases using gene ontology and KEGG pathway enrichment analysis. Methods: Our methodology involved collecting disease gene-related information from DisGeNET databases and performing protein-protein interaction (PPI) network and core genes screening. We then conducted gene ontology and KEGG pathway enrichment analysis. Results: We found that IL6 plays a critical role in all disease conditions and in different pathways that can be associated with the development of all four diseases. Conclusions: The theoretical importance of our research is that we employed various systems and structural biology techniques to identify a crucial protein that could serve as a promising target for treating multiple diseases. Our data collection and analysis procedures involved rigorous scrutiny, ensuring high-quality results. Our conclusion is that IL6 plays a significant role in all four diseases, and it can act as a potential target for treating them. Our findings may have important implications for the development of novel therapeutic interventions for these diseases.

Keywords: melanoma metastasis, rheumatoid arthritis, inflammatory bowel diseases, integrated bioinformatics analysis

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Authors: Xiangjun Kong, Dongning Yao, Yuanjia Hu

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Therapeutic antibodies have become the most valuable and successful class of biopharmaceutical drugs, with a huge market potential and therapeutic advantages. Antibody patents are, accordingly, extremely important. As the technological limitation of the early stage of this field, the U. S. Patent and Trademark Offices (USPTO) have issued guidelines that suggest an exception for patents claiming a genus of antibodies that bind to a novel antigen, even in the absence of any experimental antibody production. This 'antibody exception' allowed for a broad scope on antibody claims, and led a global trend to patent antibodies without antibodies. Disputes around the pertinent patentability and written description issues remain particularly intense. Yet the validity of such patents had not been overtly challenged until Centocor v. Abbott, which restricted the broad scope of antibody patents and hit the brakes on the 'antibody exception'. The courts tend to uphold the requirement for adequate description of antibodies in the patent specifications, to avoid overreaching antibody claims. Patents following the 'antibody exception' are at risk of being found invalid for inadequately describing what they have claimed. However, the relation between the court and USPTO guidelines remains obscure, and the waning of the 'antibody exception' has led to further disputes around antibody patents. This uncertainty clearly affects patent applications, antibody innovations, and even relevant business performance. This study will give an overview of the emergence, debate, and waning usage of the 'antibody exception' in a number of enlightening cases, attempting to understand the specific concerns and the potential influence of antibody patents. We will then provide some possible strategies for antibody patenting, under the current considerations on the 'antibody exception'.

Keywords: antibody exception, antibody patent, USPTO (U. S. Patent and Trademark Offices) guidelines, written description requirement

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Authors: Andre F. A. Cyrino

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Knowing that the technological advance is the focus on the efficient extraction of energy from wind, and therefore in the design of wind turbine structures, this work aims the study of the fluid-structure interaction of an idealized wind turbine. The blade was studied as a beam attached to a cylindrical Hub with rotation axis pointing the air flow that passes through the rotor. Using the calculus of variations and the finite difference method the blade will be simulated by a discrete number of nodes and the aerodynamic forces were evaluated. The study presented here was written on Matlab and performs a numeric simulation of a simplified model of windmill containing a Hub and three blades modeled as Euler-Bernoulli beams for small strains and under the constant and uniform wind. The mathematical approach is done by Hamilton’s Extended Principle with the aerodynamic loads applied on the nodes considering the local relative wind speed, angle of attack and aerodynamic lift and drag coefficients. Due to the wide range of angles of attack, a wind turbine blade operates, the airfoil used on the model was NREL SERI S809 which allowed obtaining equations for Cl and Cd as functions of the angle of attack, based on a NASA study. Tridimensional flow effects were no taken in part, as well as torsion of the beam, which only bends. The results showed the dynamic response of the system in terms of displacement and rotational speed as the turbine reached the final speed. Although the results were not compared to real windmills or more complete models, the resulting values were consistent with the size of the system and wind speed.

Keywords: blade aerodynamics, fluid–structure interaction, wind turbine aerodynamics, wind turbine blade

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Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

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With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

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Authors: Garima Joshi, Pratap Sharan, V. Sreenivas, Nand Kumar, Kameshwar Prasad, Ashima N. Wadhawan

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Schizophrenia is a debilitating disorder and is marked by cognitive impairment, which deleteriously impacts the social and professional functioning along with the quality of life of the patients and the caregivers. Often the cognitive symptoms are in their prodromal state and worsen as the illness progresses; they have proven to have a good predictive value for the prognosis of the illness. It has been shown that intensive cognitive rehabilitation (CR) leads to improvements in the healthy as well as cognitively-impaired subjects. As the majority of population in India falls in the lower to middle socio-economic status and have low education levels, using the existing packages, a majority of which are developed in the West, for cognitive rehabilitation becomes difficult. The use of technology is also restricted due to the high costs involved and the limited availability and familiarity with computers and other devices, which pose as an impedance for continued therapy. Cognitive rehabilitation in India uses a plethora of retraining methods for the patients with schizophrenia targeting the functions of attention, information processing, executive functions, learning and memory, and comprehension along with Social Cognition. Psychologists often have to follow an integrative therapy approach involving social skills training, family therapy and psychoeducation in order to maintain the gains from the cognitive rehabilitation in the long run. This paper reviews the methodologies and cognitive retaining programs used in India. It attempts to elucidate the evolution and development of methodologies used, from traditional paper-pencil based retraining to more sophisticated neuroscience-informed techniques in cognitive rehabilitation of deficits in schizophrenia as home-based or supervised and guided programs for cognitive rehabilitation.

Keywords: schizophrenia, cognitive rehabilitation, neuropsychological interventions, integrated approached to rehabilitation

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Authors: Solmaz Jahed Shiran, John Hearne, Tayebeh Saghapour

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Daily travel behavior is strongly influenced by the location of the places of residence, education, and employment. Hence a change in those locations due to a move or changes in an occupation leads to a change in travel behavior. Given the interventions of housing mobility and travel behaviors, the hypothesis is that a mobile housing market allows households to move as a result of any change in their life course, allowing them to be closer to central services, public transport facilities and workplace and hence reducing the time spent by individuals on daily travel. Conversely, household’s immobility may lead to longer commutes of residents, for example, after a change of a job or a need for new services such as schools for children who have reached their school age. This paper aims to investigate the association between residential mobility and travel behavior. The Victorian Integrated Survey of Travel and Activity (VISTA) data is used for the empirical analysis. Car ownership and journey to work time and distance of employed people are used as indicators of travel behavior. Change of usual residence within the last five years used to identify movers and non-movers. Statistical analysis, including regression models, is used to compare the travel behavior of movers and non-movers. The results show travel time, and the distance does not differ for movers and non-movers. However, this is not the case when taking into account the residence tenure-type. In addition, car ownership rate and number found to be significantly higher for non-movers. It is hoped that the results from this study will contribute to a better understanding of factors other than common socioeconomic and built environment features influencing travel behavior.

Keywords: journey to work, regression models, residential mobility, commute mode, car ownership

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Authors: Hamed Azad, Azadeh M. Ardakani

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Visual content, as an integral part of social media marketing, is growing dramatically. They are, in different technological usage categories (i.e., photos, graphics, animation IGTV, Stories, Livestreams, and Reels), associated with improving customer engagement behaviours (CEBs) in social commerce (SC). However, few researchers have explored the impact of specific and occasional contents that respect green products, gender equality, religious freedom, and LGBTs' rights. This study aims to compare and analyse how the ten best global brands (Interbrand's) in different categories communicate with customers on Instagram. Netnography approach and method used to conduct the data collection and data analysis of 1072 Instagram posts and 10494 comments. The results show that brands in fashion, sport, and homeware categories (H&M, Nike, and Ikea) emerge to use more effective content with the above global values elements than other brand categories. Findings also indicate that some different themes such as celebrities, models, pets, kids, aged and disabled people are part of visual management strategies on Instagram brands' pages. This research aims to inform researchers to consider all aspects of visual elements in content quality and marketing managers to increase brand optimisation, awareness, and authenticity by promoting contemporary world values on Instagram.

Keywords: green products, gender equality, religious freedom, LGBTs, Instagram, netnography

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Authors: B. El Fadil, R. Najar

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STEM education is promoted by many scholars and curricula around the world, but it is not yet well established in the province of Quebec in Canada. In addition, effective instructional STEM activities and design methods are required to ensure that students and teachers' needs are being met. One potential method is the Engineering Design Process (EDP), a methodology that emphasizes the importance of creativity and collaboration in problem-solving strategies. This article reports on a case study that focused on using the EDP to develop instructional materials by means of making a technological artifact to teach mathematical variables and functions at the secondary level. The five iterative stages of the EDP (design, make, test, infer, and iterate) were integrated into the development of the course materials. Data was collected from different sources: pre- and post-questionnaires, as well as a working document dealing with pupils' understanding based on designing, making, testing, and simulating. Twenty-four grade seven (13 years old) students in Northern Quebec participated in the study. The findings of this study indicate that STEM activities have a positive impact not only on students' engagement in classroom activities but also on learning new mathematical concepts. Furthermore, STEM-focused activities have a significant effect on problem-solving skills development in an interdisciplinary approach. Based on the study's results, we can conclude, inter alia, that teachers should integrate STEM activities into their teaching practices to increase learning outcomes and attach more importance to STEM-focused activities to develop students' reflective thinking and hands-on skills.

Keywords: engineering design process, motivation, stem, integration, variables, functions

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Authors: Yi-Ning Chang

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With the rapid advancement of technology, it has become crucial for educators to adeptly integrate technology into their teaching and develop a robust Computer-Assisted Language Learning (CALL) competency. Addressing this need, the present study adopted a technology-based Lesson Study approach to assess its impact on the CALL competency and professional capabilities of EFL teachers. Additionally, the study delved into teachers' perceptions of the benefits derived from participating in the creation of technologically integrated lesson plans. The iterative process of technology-based Lesson Study facilitated ample peer discussion, enabling teachers to flexibly design and implement lesson plans that incorporate various technological tools. This 15-week study included 10 in- service teachers from a university of science and technology in the central of Taiwan. The collected data included pre- and post- lesson planning scores, pre- and post- TPACK survey scores, classroom observation forms, designed lesson plans, and reflective essays. The pre- and post- lesson planning and TPACK survey scores were analyzed employing a pair-sampled t test; students’ reflective essays were respectively analyzed applying content analysis. The findings revealed that the teachers’ lesson planning ability and CALL competencies were improved. Teachers perceived a better understanding of integrating technology with teaching subjects, more effective teaching skills, and a deeper understanding of technology. Pedagogical implications and future studies are also discussed.

Keywords: CALL, language learning, lesson study, lesson plan

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Authors: K. M. Wong

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Engineering education is crucial to technological innovation and advancement worldwide by generating young talents who are able to integrate scientific principles and design practical solutions for real-world problems. Graduates of engineering curriculums are expected to demonstrate an extensive set of learning outcomes as required in international accreditation agreements for engineering academic qualifications, such as the Washington Accord and the Sydney Accord. On the other hand, students have different learning preferences of receiving, processing and internalizing knowledge and skills. If the learning environment is advantageous to the learning styles of the students, there is a higher chance that the students can achieve the intended learning outcomes. With proper identification of the learning styles of the students, corresponding teaching strategies can then be developed for more effective learning. This research was an investigation of learning styles of tertiary students studying higher diploma programmes in Hong Kong. Data from over 200 students in engineering programmes were collected and analysed to identify the learning characteristics of students. A small-scale longitudinal study was then started to gather academic results of the students throughout their two-year engineering studies. Preliminary results suggested that the sample students were reflective, sensing, visual, and sequential learners. Observations from the analysed data not only provided valuable information for teachers to design more effective teaching strategies, but also provided data for further analysis with the students’ academic results. The results generated from the longitudinal study shed light on areas of improvement for more effective engineering curriculum design for better teaching and learning.

Keywords: learning styles, learning characteristics, engineering education, vocational education, Hong Kong

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Authors: Jamshed Ahmad, Abdul Wahid Khan, Javed Ali Khan

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Managing software quality requirements change management is a difficult task in the field of software engineering. Avoiding incoming changes result in user dissatisfaction while accommodating to many requirement changes may delay product delivery. Poor requirements management is solely considered the primary cause of the software failure. It becomes more challenging in global software outsourcing. Addressing success factors in quality requirement change management is desired today due to the frequent change requests from the end-users. In this research study, success factors are recognized and scrutinized with the help of a systematic literature review (SLR). In total, 16 success factors were identified, which significantly impacted software quality requirement change management. The findings show that Proper Requirement Change Management, Rapid Delivery, Quality Software Product, Access to Market, Project Management, Skills and Methodologies, Low Cost/Effort Estimation, Clear Plan and Road Map, Agile Processes, Low Labor Cost, User Satisfaction, Communication/Close Coordination, Proper Scheduling and Time Constraints, Frequent Technological Changes, Robust Model, Geographical distribution/Cultural differences are the key factors that influence software quality requirement change. The recognized success factors and validated with the help of various research methods, i.e., case studies, interviews, surveys and experiments. These factors are then scrutinized in continents, database, company size and period of time. Based on these findings, requirement change will be implemented in a better way.

Keywords: global software development, requirement engineering, systematic literature review, success factors

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Authors: Bisola Olumegbon

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Globally, there were about 229 million cases of malaria in 2022. The sub-Saharan African region accounted for 92% of the reported cases and 94% of deaths. Nigeria had the highest number of malaria cases and deaths, representing 27% of global cases. This scholarly project was a case study guided by the political determinants of health. Triangulation of data using thematic analysis was used to identify the political determinants of malaria in Nigeria and to understand how the concept of interaction contributes to the persistence of the disease. The analysis involved a deductive and inductive approach based on the literature review and the evidence of political determinants gathered in the data. Participants’ in-depth interviews were used to collect data from frontline personnel. Data triangulation was done using thematic analysis, a method used to identify patterns and themes in qualitative data. The study findings revealed a correlation between political determinants of health and malaria management efforts in Nigeria. Some influencing factors included voting challenges, inadequate funding, lack of health priority from the government, noncompliance among patients, and hurdles to effective communication. The findings suggest a need to deliberately increase dedication to the political agenda, provide sufficient financial resources, enhance communication, and active community involvement to address the persistent malaria endemic effectively. Further study is recommended to identify interventions to address identified factors of political determinants of health to reduce malaria in Nigeria. Such intervention must involve collaboration with diverse stakeholders such as policymakers, healthcare professionals, community leaders, and researchers.

Keywords: malaria, malaria management, health worker, stakeholders, political determinant of health

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Authors: M. Z. Bin Mohd Ghazali, N. C. Wilson, A. F. Bin Ahmad Fuad, M. A. H. B. Musa, M. U. Mohamad Sani, F. Zulkifli, M. S. Zainal Abidin

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Physical activity levels are low in Malaysia and this study was undertaken to determine if a four week work-based intervention program would be effective in changing physical activity levels. The study was conducted in a Malaysian Government Department and had three stages: baseline data collection, four-week intervention and two-month post intervention data collection. During the intervention and two-month post intervention phases, physical activity levels (determined by a pedometer) and basic health profiles (BMI, abdominal obesity, blood pressure) were measured. Staff (58 males, 47 females) with an average age of 33 years completed baseline data collection. Pedometer steps averaged 7,102 steps/day at baseline, although male step counts were significantly higher than females (7,861 vs. 6114). Health profiles were poor: over 50% were overweight/obese (males 66%, females 40%); hypertension (males 23%, females 6%); excess waist circumference (males 52%, females 17%). While 86 staff participated in the intervention, only 49 regularly reported their steps. There was a significant increase (17%) in average daily steps from 8,965 (week 1) to 10,436 (week 4). Unfortunately, participation in the intervention program was avoided by the less healthy staff. Two months after the intervention there was no significant difference in average steps/day, despite the fact that 89% of staff reporting they planned to make long-term changes to their lifestyle. An unexpected average increase of 2kg in body weight occurred in participants, although this was less than the 5.6kg in non-participants. A number of recommendations are made for future interventions, including the conclusion that pedometers were a useful tool and popular with participants.

Keywords: pedometers, walking, health, intervention

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Authors: Omkar More, Isha Saini, Gracy Mathai

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To study whether there is any clinical correlation between pterygium and dry eye and to evaluate the status of the tear film in patients with pterygium. Methods: 100 eyes with pterygium were compared with 100 control eyes without pterygium. Patients between 20 – 70 years were included in the study. A detailed history was taken and Schirmer’s test and TBUT were performed on all to evaluate the status of dry eye. Schirmer’s test ˂ 10 mm and TBUT ˂10 seconds was considered abnormal. Results: Maximum number (52) of patients affected by dry eye in both the groups were in the age group 31-40 years which statistically showed age as a significant factor of association for both pterygium and dry eye (P < 0.01).Schirmer’s test was slightly reduced in patients with pterygium(18.73±5.69 mm). TBUT was significantly reduced in the case group (12.26±2.24sec).TBUT decreased maximally in 51-60 yrs age group (13.00±2.77sec) with pterygium showing a tear film instability. On comparison of pterygia and controls with normal and abnormal tear film, Odd’s Ratio was 1.14 showing a risk of dry eye in pterygia patients to be 1.14 times higher than controls. Conclusion: Whether tear dysfunction is a precursor to pterygium growth or pterygium causes tear dysfunction is still not clear. Research and clinical evidence, however, suggest that there is a relationship between the two. This study is, therefore, undertaken to investigate the correlation between pterygium and dry eye. The patients with pterygia were compared with normals to evaluate their status regarding dryness. A close relationship exists between ocular irritation symptoms and functional evidence of tear instability. Schirmer’s test and TBUT should routinely be used in the outpatient department to diagnose dry eye in patients with pterygium and these patients should be promptly treated to prevent any sight-threatening complications.

Keywords: footfall, nursing assessment, quality improvement, six sigma

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Authors: Dušica Kovačević

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This study explores the influence of destructive groups on the mental health and social integration of high school students in Loznica, Serbia. Despite increasing concerns, there is a significant lack of research on the impact of these groups on adolescents in this region. This qualitative study aims to fill this gap by examining the prevalence of destructive groups, their psychological effects on students, and their broader social implications. Data were collected through surveys and in-depth interviews with high school students, educators, and mental health professionals. The study focuses on key mental health indicators, such as anxiety, depression, and identity formation, alongside social factors, including peer relationships and community engagement. Additionally, it defines coping mechanisms and supporting strategies employed by students affected by these groups. The findings reveal substantial psychological and social challenges faced by students exposed to destructive groups, including increased levels of anxiety and depression, disrupted identity development, and impaired social integration. Insights into the personal experiences of these students provide a detailed understanding of the groups’ impact, underscoring the need for targeted interventions. This research offers evidence-based recommendations for educators, mental health practitioners, and policymakers. It emphasizes the importance of developing effective educational programs and support services to enhance the well-being of high school advocates for proactive measures to protect adolescent mental health and promote healthy social values within educational and community settings.

Keywords: adolescents, mental health, destructive groups, social integration, qualitative study, high school students, Serbia

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Authors: Si Yin Tee

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Bimetallic nanostructures have received tremendous interests as a new class of nanomaterials which may have better technological usefulness with distinct properties from those of individual atoms and molecules or bulk matter. They excelled over the monometallic counterparts because of their improved electronic, optical and catalytic performances. The properties and the applicability of these bimetallic nanostructures not only depend on their size and shape, but also on the composition and their fine structure. These bimetallic nanostructures are potential candidates for bio-applications such as biosensing, bioimaging, biodiagnostics, drug delivery, targeted therapeutics, and tissue engineering. Herein, gold-incorporated copper (Cu/Au) nanostructures were synthesized through the controlled disproportionation of Cu⁺-oleylamine complex at 220 ºC to form copper nanowires and the subsequent reaction with Au³⁺ at different temperatures of 140, 220 and 300 ºC. This is to achieve their synergistic effect through the combined use of the merits of low-cost transition and high-stability noble metals. Of these Cu/Au nanostructures, Cu/Au nanotubes display the best performance towards electrochemical non-enzymatic glucose sensing, originating from the high conductivity of gold and the high aspect ratio copper nanotubes with high surface area so as to optimise the electroactive sites and facilitate mass transport. In addition to high sensitivity and fast response, the Cu/Au nanotubes possess high selectivity against interferences from other potential interfering species and excellent reproducibility with long-term stability. By introducing gold into copper nanostructures at a low level of 3, 1 and 0.1 mol% relative to initial copper precursor, a significant electrocatalytic enhancement of the resulting bimetallic Cu/Au nanostructures starts to occur at 1 mol%. Overall, the present fabrication of stable Cu/Au nanostructures offers a promising low-cost platform for sensitive, selective, reproducible and reusable electrochemical sensing of glucose.

Keywords: bimetallic, electrochemical sensing, glucose oxidation, gold-incorporated copper nanostructures

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Authors: Limor Gadot, Orly Sarid

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Integration of young adults with disabilities (YAWD) into workplaces provides an opportunity for social and occupational mobility, enabling them to financial independence. To enhance integration, it is important to understand their occupational preferences as well as the factors that influencing it such as demographic variables, self-assessed health, beliefs about work, subjective norms, and self-efficacy. Planned behavior theory was chosen as a basis for this study. A cross-sectional study, based on preliminary sample of 37 YAWD who have been recognized by the National Insurance Institute and are engaged in a year of national service. The finding shows that most of the participants were single (97%) women (60%); average age was 22(+ 2) years, approximately half were secular. Most of the participants had disabilities resulting from CP (96%). Self-assessed health was correlated positively and significantly with behavioral intentions to work in the free market (r = .33, p = .05), and significant negative correlation with behavioral intentions to work in supported settings (r =.-40, p = .01), and sheltered settings (r =-.36, p = .03): individuals who perceived themselves as having more severe disabilities showed a greater tendency to choose a workplace with more rehabilitative inputs. Furthermore, women showed a greater tendency than men to perceive their disability as impairing their future intention to work: t (36) = 2.23, p < .05. Beliefs about work were positively associated with normative beliefs (r = .308, p = .06). The findings indicate that, especially with women, perceptions of health are related to occupational preferences. Moreover, the findings indicate that the relationship between subjective norms about work and normative beliefs about integrating in a workplace that prevail in the individual's environment affects occupational preferences. The contribution of the study lies in the development of new responses and interventions to encourage adults with disabilities to work.

Keywords: young adults, disabilities, work preferences, occupational preferences

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Authors: Maha Alhussain, Moira A Taylor, Ian A. Macdonald

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Background: It is well established that dietary composition has effects on metabolism and therefore impacts on health; however other aspects of diet, such as meal pattern, could also be important in both obesity management and promoting health. The present study investigated the effect of irregular meal frequency on anthropometric measurements and energy expenditure (EE) in healthy women. Design: 11 healthy weight women (18–40 years) were studied in a randomized crossover trial with two phases of 2 weeks each. In Phase 1, participants consumed either a regular meal pattern (6 meals/day) or an irregular meal pattern (varying from 3 to 9 meals/day). In Phase 2, participants followed the alternative meal pattern to that followed in Phase 1, after a 2-weeks washout period. In the two phases, identical foods were provided to a participant in amounts designed to keep body weight constant. Participants came to the laboratory after an overnight fast at the start and end of each phase. EE was measured in fasting state by indirect calorimetry. Postprandial EE was measured during the 3 h period after consumption of a milkshake, test drink. Results: There were no significant changes in body weight and anthropometric measurements after both meal pattern interventions. There was also no significant difference in mean daily energy intake between the regular and irregular meal pattern (2043 ±31 and 2099 ±33 respectively). EE in the fasting state showed no significant differences cross the experiment visits. There was a significant difference in Postprandial EE (measured for 3 h) by visit (P=0.04). Postprandial EE after the regular meal pattern was significantly higher than at baseline (P=0.002) or than after the irregular meal pattern (P= 0.04). Conclusion: Eating regularly for 14-day period significantly increases Postprandial EE which may contribute to weight loss and obesity management.

Keywords: energy expenditure, energy intake, meal pattern, weight loss

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Authors: Nabil Ahmed Kamal Badawy, Ali Falah Alhajraf, Mawaheb Falah Alsamdan

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Objectives: To estimate the prevalence of self-medication with over-the-counter pain relievers (acetaminophen, ibuprofen, and aspirin) among Kuwaiti citizens above the age of 16 years old and describe their patterns of use, perceived awareness of, and concerns about the drugs’ potential side effects. Design: A descriptive cross-sectional questionnaire-based survey. Setting: Samples were selected from the six Kuwaiti governorates. Subjects: The data were collected over a four-month period in 2012, from 850 subjects who identified as Kuwaiti citizens. These subjects were recruited using stratified random sampling. Results: Overall, a 67% response rate was obtained. In total, 68% (573) of the respondents reported the use of over-the-counter pain relievers. Women, middle-aged or single individuals, and those who had completed higher education used these drugs more than any other subgroup (p<0.05). We found evidence of inappropriate use of these drugs, with 15% (88) of the consumers using them almost daily. Further, 19% (111) of the consumers exceeded the recommended dosage at least once. Not only were 81% of the consumers unaware of the potential side effects, but also more than 61% were not concerned about them. Women were more knowledgeable than men regarding the maximum dose (p=0.036, OR 1.49, CI 1.03–2.17). Consumers with higher levels of education did not show distinct knowledge regarding the maximum allowed dose of the drugs (p=0.252, OR 1.71, CI 0.68-4.25). Conclusion: The results showed a high prevalence of self-medication with over-the-counter pain relievers among Kuwaiti citizens. The subjects showed marked unawareness and a lack of concern regarding the potential complications resulting from the inappropriate use of these analgesics. This demonstrates the need for educational interventions directed toward both patients and health care workers.

Keywords: awareness of side effects, concern, patterns of use, prevalence

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Authors: Sandhya Rao

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Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

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Authors: Á. L. Bendes

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By the end of the second decade of the 21st century, artificial intelligence (AI) has become an unavoidable part of everyday life and has necessarily aroused the interest of researchers in almost every field of science. This is no different in the case of jurisprudence, whose main task is not only to create its own theoretical paradigm related to AI. Perhaps the biggest impact on digital crime is artificial intelligence. In addition, the need to create legal frameworks suitable for the future application of the law has a similar importance. The prognosis according to which AI can reshape the practical application of law and, ultimately, the entire legal life is also of considerable importance. In the past, criminal law was basically created to sanction the criminal acts of a person, so the application of its concepts with original content to AI-related violations is not expected to be sufficient in the future. Taking this into account, it is necessary to rethink the basic elements of criminal law, such as the act and factuality, but also, in connection with criminality barriers and criminal sanctions, several new aspects have appeared that challenge both the criminal law researcher and the legislator. It is recommended to continuously monitor technological changes in the field of criminal law as well since it will be timely to re-create both the legal and scientific frameworks to correctly assess the events related to them, which may require a criminal law response. Artificial intelligence has completely reformed the world of digital crime. New crimes have appeared, which the legal systems of many countries do not or do not adequately regulate. It is considered important to investigate and sanction these digital crimes. The primary goal is prevention, for which we need a comprehensive picture of the intertwining of artificial intelligence and digital crimes. The goal is to explore these problems, present them, and create comprehensive proposals that support legal certainty.

Keywords: artificial intelligence, chat forums, defamation, international criminal cooperation, social networking, virtual sites

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Authors: Ruttana Phetsitong, Patama Vapattanawong, Malee Sunpuwan, Marc Voelker

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The majority of care for older people at home in Thai society falls upon caregivers resulting in caregiver’s mental health problem. Beyond individual characteristics, household factors might have a profound effect on the caregiver’s mental health. But reliable data capturing this at the household level have been limited to date. The objectives of the present study were to explore the levels of Thai caregiver’s mental health and to investigate the factors affecting the mental health at household level. Data were obtained from the 2011 National Survey of Thai Older Persons conducted by the National Statistical Office of Thailand. Caregiver’s mental health was measured by using the 15- items-short version of the Thai Mental Health Indicator (TMHI-15) developed by the Department of Mental Health, the Ministry of Public Health. Multivariate logistic regression models were used to explore the impact of potential factors on caregiver’s mental health. The THMI-15 produced an overall average caregiver mental health score of 30.9 out of 45 (SD 5.3). The score can be categorized into good (34.02-45), fair (27.01-34), and poor (0-27). Duration of care for older people, household wealth, and functional dependency of the older people significantly predicted total caregiver’s mental health. Household economic factor was key in predicting better mental health. Compared to those poorest households, the adjusted effect of the fifth quintile household wealth was high (OR=2.34; 95%CI=1.47-3.73). The findings of this study provide a fuller picture to a better understanding of the level and factors that cause the mental health of Thai caregivers. Health care providers and policymakers should consider these factors when designing interventions aimed at alleviating caregiver’s psychological burden when provided care for older people at home.

Keywords: caregiver’s mental health, household, older people, Thailand

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

Procedia PDF Downloads 79

Authors: Pouira Askary

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Indeed, in our globalized world which is facing with various international crises, the transnational corporations and other business enterprises have the capacity to foster economic well-being, development, technological improvement and wealth, as well as causing adverse impacts on human rights. The UN Human Rights Council declared that although the primary responsibility to protect human rights lie with the State but the transnational corporations and other business enterprises have also a responsibility to respect and protect human rights in the framework of corporate social responsibility. In 2011, the Human Rights Council endorsed the Guiding Principles on Business and Human Rights, a set of guidelines that define the key duties and responsibilities of States and business enterprises with regard to business-related human rights abuses. In UN’s view, the Guiding Principles do not create new legal obligations but constitute a clarification of the implications of existing standards, including under international human rights law. In 2014 the UN Human Rights Council decided to establish a working group on transnational corporations and other business enterprises whose mandate shall be to elaborate an international legally binding instrument to regulate, in international human rights law, the activities of transnational corporations and other business enterprises. Extremely difficult task for the working group to codify a legally binding document to regulate the behavior of corporations on the basis of the norms of international law! Concentration of this paper is on the origins of those human rights applicable on business enterprises. The research will discuss that the social and ethical roots of the CSR are much more institutionalized and elaborated than the legal roots. Therefore, the first step is to determine whether and to what extent corporations, do have an ethical responsibility to respect human rights and if so, by which means this ethical and social responsibility is convertible to legal commitments.

Keywords: CSR, ethics, international law, human rights, development, sustainable business

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Authors: Lovemore Motsi

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The rapid pace of technological innovation, along with a global fascination with the internet, continues to result in a dominating call to integrate internet technologies in institutions of learning. However, the pressing question remains – how can online in-service training for teachers, support quality and success in professional development programmers. The aim of this study was to examine an integrated model that extended the Unified Theory of Acceptance and Use of Technology (UTAUT) with additional constructs – including attitude and behaviour intention – adopted from the Theory of Planned Behaviour (TPB) to answer the question. Data was collected from secondary school teachers at 10 selected schools in the Tshwane South district by means of the Statistical Package for Social Scientists (SPSS v 23.0), and the collected data was analysed quantitatively. The findings are congruent with model testing under conditions of volitional usage behaviour. In this regard, the role of facilitating condition variables is insignificant as a determinant of usage behaviour. Social norm variables also proved to be a weak determinant of behavioural intentions. Findings demonstrate that effort expectancy is the key determinant of online INSET usage. Based on these findings, the variable social influence and facilitating conditions are important factors in ensuring the acceptance of online INSET among teachers in selected secondary schools in the Tshwane South district.

Keywords: unified theory of acceptance and use of technology (UTAUT), teacher professional development, secondary schools, online INSET

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Hameed Ullah, Karim Elakabawi, Han KE, Najeeb Ullah, Habib Ullah, Sardar Ali Shah, Hamad Haider Khan, Muhammad Asad Khan, Ning Guo, Zuyi Yuan

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Background: Predictors of decreased fractional flow reserve at left circumflex coronary artery after left main (LM) crossover stenting are still lacking. The objectives of the present study were to provide the predictors for low Fractional flow reserve (FFR) at coronary artery (LCx) and the possible treatment strategies for the compromised LCx-together with their long term outcomes. Methods: A total of 563 included patients out of 1974 patients admitted to our hospital from February 2015 to November 2020 with significant distal LM-bifurcation lesions. The enrolled patients underwent single-stent cross-over PCI under IVUS guidance with further LCx intervention as indicated by measured FFR. Results: The included patients showed angiographic significant LCx ostial affection after LM-stenting, but only 116 (20.6%) patients had FFR <0.8. The 3-year composite MACE rates were comparable between the high and low FFR groups (16.8% vs. 15.5%, respectively; P=0.744). In a multivariable analysis, a low FFR in the LCx was associated with post-stenting MLA of the LCx (OR: 0.032, P <0.001), post-stenting LCx-plaque burden (OR: 1.166, P <0.001), post-stenting LM-MLA (OR: 0.821, P =0.038) and pre-stenting LCx-MLA (OR: 0.371, P =0.044). In patients with low FFR, management of compromised LCx with DEB had the lowest 3-year MACE rate (8.1%) as compared to either KBI (17.5%) or stenting group (20.5%), P =0.299. Conclusion: FFR-guided LCx intervention can avoid unnecessary LCx intervention. The post-stenting predictors of low FFR include post-stenting MLA and plaque burden of the LCx and MV stent length. The 3-year MACE rates were comparable between high FFR patients and patients who had low FFR and were adequately managed.

Keywords: fractional flow reserve, left main stem, percutaneous coronary interventions, intravascular ultrasound

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

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Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: climate, reanalysis, renewable energy, solar radiation

Procedia PDF Downloads 195

Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

Procedia PDF Downloads 80