Miracle-dz/UniFAR-FTUs huggingface dataset:
Teacher's Motivation on the Use of Virtual Learning Environment (VLE): The Effect of Social Factors, Self-Efficacy and Technological Support

Vol. 11(2) 2022, Abstract Virtual learning environment or VLE has been introduced in educational institutions such as schools, colleges and universities to encourage a systematic online teaching and learning platform. The application of VLE is suggested as one of the mediators to vary the delivery process therefore teaching and learning process will be easier and more interesting. This paper aims to examine the effect of social factors, self-efficacy and technological support on the utilization of VLE in the educational process. A quantitative approach was employed and the data was collected through questionnaire administered to selected respondents. A total of 356 accounting teachers from secondary schools in Peninsular Malaysia were chosen as the samples. Reflective measurement model in Partial Least Square-Structural Equation Modelling was utilized to measure the effect of exogenous latent variable on the endogenous latent variable. Results indicated that social factor namely (colleague, administrators and school culture) significantly effect the use of VLE among teachers. The finding can be interpreted as teachers with higher value of social factors have higher intention to use VLE in his/her teaching and learning. Further, self-efficacy and technological support (facilities quali ty, internet access and technical support) positively influence teachers’ to apply VLE during teaching. This paper proposes that teachers need to be given ongoing support and appropriate training to develop their skills in using digital technology. Further, the quality of technological facilities in schools need to be developed to promote effective educational processes and motivate teachers to use digital technology.
Machine-Learning-Based Noninvasive In Vivo Estimation of HbA1c Using Photoplethysmography Signals

Glycated hemoglobin (HbA1c) is an important factor in monitoring diabetes. Since the glycated hemoglobin value reflects the average blood glucose level over 3 months, it is not affected by exercise or food intake immediately prior to measurement. Thus, it is used as the most basic measure of evaluating blood-glucose control over a certain period and predicting the occurrence of long-term complications due to diabetes. However, as the existing measurement methods are invasive, there is a burden on the measurement subject who has to endure increased blood gathering and exposure to the risk of secondary infections. To overcome this problem, we propose a machine-learning-based noninvasive estimation method in this study using photoplethysmography (PPG) signals. First, the development of the device used to acquire the PPG signals is described in detail. Thereafter, discriminative and effective features are extracted from the acquired PPG signals using the device, and a machine-learning algorithm is used to estimate the glycated hemoglobin value from the extracted features. Finally, the performance of the proposed method is evaluated by comparison with existing model-based methods.
Imaginaries of platform entrepreneurship in the creative industries: techno-optimism and subversion in Ghanaian filmmaking

ABSTRACT This article examines imaginaries of platform entrepreneurship in film industries in Ghana. To understand how these imaginaries are spatially shaped and locally defined, we carried out in-depth qualitative research with fifty filmmakers in four regions of Ghana. Digital and platform technologies have long been optimistically celebrated as a way for marginalized creative entrepreneurs, particularly in Africa, to break into global markets and reach unprecedented levels of business success. However, far from being universally adopted by African creative entrepreneurs, these global techno-optimistic imaginaries are continually reworked, contested and subverted in practice. In this article, we show how Ghanaian filmmakers mobilized, deployed and resisted imaginaries of platform entrepreneurship in their efforts to make sense of their situated entrepreneurial practices and to imagine the future of their creative businesses. We found that rather than naïvely adhering to techno-optimist imaginaries, through their practices, Ghanaian filmmaking entrepreneurs challenged the power geometry of the current platform ecosystem dominated by major Silicon Valley players. We contribute empirically rich data on how filmmaking entrepreneurs use and imagine platform technologies, as is necessary when African digital entrepreneurs are surrounded by hype but inadequate data. We also contribute to the literature about how individual platforms and platform types have unique affordances and how these affordances are shaped by the location and socio-economic position of the entrepreneur.
Resonance-induced growth of number entropy in strongly disordered systems

We study the growth of the number entropy SN in one-dimensional number-conserving interacting systems with strong disorder, which are believed to display many-body localization. Recently a slow and small growth of SN has been numerically reported, which, if holding at asymptotically long times in the thermodynamic limit, would imply ergodicity and therefore the absence of true localization. By numerically studying SN in the disordered isotropic Heisenberg model we first reconfirm that, indeed, there is a small growth of SN. However, we show that such growth is fully compatible with localization. To be specific, using a simple model that accounts for expected rare resonances we can analytically predict several main features of numerically obtained SN: trivial initial growth at short times, a slow power-law growth at intermediate times, and the scaling of the saturation value of SN with the disorder strength. Because resonances crucially depend on individual disorder realizations, the growth of SN also heavily varies depending on the initial state, and therefore SN and von Neumann entropy can behave rather differently.
Experimental investigation on the mechanical behaviour of AAC blocks for sustainable concrete masonry

To satisfy the increasing demand of energy efficient buildings, AAC manufacturers are nowadays encouraged to produce blocks with ever lower densities. However, a compromise between energy-saving requirements and mechanical performances is needed to ensure structural safety, as well as an adequate structural durability. This paper reports a comprehensive experimental study on AAC mechanical properties (compressive and tensile strengths, as well as fracture energy), and on their dependency from material density and moisture content. The collected data are compared with some well-known analytical relations taken from the literature, which are often used for the calibration of mechanical parameters required for mathematical and/or finite element modelling of AAC load-bearing masonry, as well as of AAC masonry-infilled framed structures. These comparisons highlight some critical issues in the formulation of analytical relations having a general applicability; however, it was found that RILEM suggestions are appropriate for the considered AAC productions, at least for densities greater than 400 kg/m3.
Optimal Growth Conditions for Azolla pinnata R. Brown: Impacts of Light Intensity, Nitrogen Addition, pH Control, and Humidity

Nitrogen pollution from agriculture is a major challenge facing our society today. Biological nitrogen fixation is key to combat the damage that is caused by synthetic nitrogen. Azolla spp. are ideal candidates for fast nitrogen fixation. This study aimed to investigate the optimal growth conditions for Azolla pinnata R. Brown. The growth conditions that were investigated included the growth medium type and strength, light intensity, the presence/absence of nitrogen in the medium, pH control, and humidity. Higher light intensities increased plant growth by 32%, on average. The highest humidity (90%) yielded higher growth rate values than lower humidity values (60% and 75%). The presence of nitrogen in the medium had no significant effect on the growth rate of the plants. pH control was critical under the fast growth conditions of high light intensity and high humidity, and it reduced algal growth (from visual observation). The optimal growth rate that was achieved was 0.321 day−1, with a doubling time of 2.16 days. This was achieved by using a 15% strength of the Hoagland solution, high light intensity (20,000 lx), nitrogen present in the medium, and pH control at 90% humidity. These optimised conditions could offer an improvement to the existing phytoremediation systems of Azolla pinnata and aid in the fight against synthetic nitrogen pollution.
Let AI Perform Better Next Time—A Systematic Review of Medical Imaging-Based Automated Diagnosis of COVID-19: 2020–2022

The pandemic of COVID-19 has caused millions of infections, which has led to a great loss all over the world, socially and economically. Due to the false-negative rate and the time-consuming characteristic of the Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, diagnosing based on X-ray images and Computed Tomography (CT) images has been widely adopted to confirm positive COVID-19 RT-PCR tests. Since the very beginning of the pandemic, researchers in the artificial intelligence area have proposed a large number of automatic diagnosing models, hoping to assist radiologists and improve the diagnosing accuracy. However, after two years of development, there are still few models that can actually be applied in real-world scenarios. Numerous problems have emerged in the research of the automated diagnosis of COVID-19. In this paper, we present a systematic review of these diagnosing models. A total of 179 proposed models are involved. First, we compare the medical image modalities (CT or X-ray) for COVID-19 diagnosis from both the clinical perspective and the artificial intelligence perspective. Then, we classify existing methods into two types—image-level diagnosis (i.e., classification-based methods) and pixel-level diagnosis (i.e., segmentation-based models). For both types of methods, we define universal model pipelines and analyze the techniques that have been applied in each step of the pipeline in detail. In addition, we also review some commonly adopted public COVID-19 datasets. More importantly, we present an in-depth discussion of the existing automated diagnosis models and note a total of three significant problems: biased model performance evaluation; inappropriate implementation details; and a low reproducibility, reliability and explainability. For each point, we give corresponding recommendations on how we can avoid making the same mistakes and let AI perform better in the next pandemic.
Internet Gaming Disorder (IGD) in Children: Clinical Treatment Insights

Introduction: The objective of this case series study was to provide an in-depth account of the profile, associated risk factors and impacts on development of Internet Gaming Disorder (IGD) and Gaming Disorder (GD) in cases aged between 11-13 years old, representing the youngest cohort to date in the IGD and GD case study literature. A further aim was to evaluate a multi-modal parent/child treatment approach. Methods: Case files from six children at the Screens & Gaming Disorder Clinic (Sydney) were analysed for evidence of a range of factors including: amount of daily screen use, risk factors for developing IGD and GD, impact on development, symptoms relevant to IGD and GD diagnostic criteria and treatment outcomes. This paper provides summary data from all cases and a detailed account of two cases. Results: Risk factors for developing IGD and GD were prominent, with both cases displaying evidence of at least four risk factors. The younger case (aged 11 years) displayed less impact on development than the 13-year-old case. The study found evidence that the multi-modal parent/child treatment approach used facilitated positive outcomes and reduced negative impacts on development and functioning. Conclusions: The multi-model parent/child treatment approach used may be an effective means to address risk factors and increase protective factors in the development of IGD/GD, forming a “circuit breaker” for developmental impacts and functioning and reducing symptoms of IGD in children. Future randomized controlled trials are needed in early intervention strategies for problematic screen use and IGD and should focus on primary school aged children before the pivotal transition to high school where developmental impacts can compound in a more chronic or comorbid course.
Examination of the Verifiable Details Provided by Liars in Their Alibis

The “cognitive approach” to detecting deception assumes that deception is a cognitively taxing experience, so interpersonal questioning techniques that make the task even more cognitively difficult will make liars easier to detect. The present experiment asked participants to imagine they were involved in either a high-stakes or low-stakes deceptive theft scenario and compared these conditions to a no-theft truthful condition. They were interviewed by a researcher who asked for an alibi of their whereabouts during the theft. Results indicated participants used few verifiable details overall, despite being prompted that they would improve the believability of the alibi. Consistent with the cognitive approach, truth-tellers named identifiable witnesses more in their alibis than deceivers. Participants in the high-stakes condition who wrote their alibis first used significantly more references to identifiable people than any other group. Writing the alibi prior to the interview reduced feelings of guilt and increased both motivation and perceptions of success.
Comparison of Cardiovascular Risk and Events among Spanish Patients with and without Ocular Pseudoexfoliation

The purpose of this study was to calculate and compare individual cardiovascular risk (CVR) and the development of cardiovascular events and mortality in patients with and without ocular pseudoexfoliation (PEX). A cohort study was carried out to compare two groups of patients who underwent cataract surgery: patients with (n = 99) and without PEX (n = 239). The CVR factors were recorded for all the subjects, and CVR was calculated for each individual using ERICE risk assessment charts. After a six-year follow-up, the cardiovascular events and mortality rates were compared between the two groups. The mean CVR was 36.41% in the PEX group and 33.72% in the non-PEX group (p = 0.13). High blood pressure was detected in significantly more PEX patients (71.4%) than non-PEX patients (58.6%, p = 0.035), yet no differences were found in the other CVR factors. The prevalence of cardiovascular events in the PEX and non-PEX patients was 17.1% and 12.5%, respectively (p = 0.26), with 5% of patients in the PEX group and 5% in the non-PEX group suffering an acute coronary event (p = 0.9). Moreover, 12% of the PEX patients and 7.5% of the non-PEX patients experienced a stroke (p = 0.17), and the six-year mortality rate was 29.3% in the PEX group and 25.9% in the non-PEX group (p = 0.52). PEX was associated with high blood pressure in our cohort of patients, although cardiovascular risk was not shown to be higher in this group. In addition, patients with PEX did not experience more cardiovascular events or have a higher mortality rate than patients without PEX during the period studied.
Transcriptional profile of TB antigen-specific T cells reveals novel multifunctional features1

In latent tuberculosis infection (LTBI) spread of the bacteria is contained by a persistent immune response, which includes CD4 + T cells as important contributors. Here we show that TB-specific CD4 + T cells have a characteristic chemokine expression signature (CCR6 + CXCR3 + CCR4 − ), and that the overall number of these cells is significantly increased in LTBI donors compared to healthy subjects. We have comprehensively characterized the transcriptional signature of CCR6 + CXCR3 + CCR4 − cells and find significant differences to conventional Th1, Th17 and Th2 cells, but no major changes between healthy and LTBI donors. CCR6 + CXCR3 + CCR4 − cells display linage-specific signatures of both Th1 and Th17 cells, but also have a unique gene expression program including genes associated with susceptibility to TB, enhanced T cell activation, enhanced cell survival, and induction of a cytotoxic program akin to CTL cells. Overall, the gene expression signature of CCR6 + CXCR3 + CCR4 − cells reveals characteristics important for controlling latent TB infections. transcriptome PCR amplification adaptors, shearing of amplified cDNA, fragment size selection, efficiency of ligation of sequencing adaptors and to determine library complexity.
Improving Medication Adherence in Community-Dwelling Patients with Schizophrenia Through Therapeutic Alliance and Medication Attitude: A Serial Multiple Mediation Model

Background Increased medication adherence improves patient outcomes and lowers the overall cost of care by preventing disease relapse and hospital readmission. Several systematic reviews have identified that insight, therapeutic alliance, and attitude towards medication affect medication adherence in patients with schizophrenia; however, no study has examined all the aforementioned variables together nor has discussed the chains of these mediators. Purpose To examine the insight–medication adherence relationship among community-dwelling schizophrenia patients through a serial multiple mediation model of therapeutic alliance and medication attitude. Patients and Methods This study with a cross-sectional correlational design included a convenience sample of community-dwelling schizophrenia patients from Taiwan (n = 229). From January 2017 to January 2018, data were collected by trained nurses using questionnaires. The PROCESS tool was used to analyse fine-grained chains. Results In serial multiple mediation, the indirect effect of insight on medication adherence through therapeutic alliance and, subsequently, alteration of medication attitude was significant. However, the direct effect changed from significant to non-significant, indicating a complete mediating effect. Conclusion In community-dwelling schizophrenia patients, the effects of therapeutic alliance and medication attitude on medication adherence are greater than that of insight. We recommend revising the strategy of community home visits by different psychiatrists or nurses in alternating shifts. Therapeutic alliance is the first step required to promote medication adherence. Based on this alliance, altering the patients’ medication attitude may be more effective in improving medication adherence than merely enhancing insight.
The study of the effectiveness of Particles in radiation therapy using GEANT4 simulation

This thesis describes a Monte-Carlo based simulation study in order to investigate the impact of radiation quality especially linear energy transfer (LET) on the damage of living cell induced by radiation. In this study, the simplified target is used for determining the pattern of the energy deposition of charged particles at different energies in macroscopic level by using Geant4 toolkit. This study highlights the factor that may cause the erroneous LET calculation when using small target in the model. It is shown that although LET is used as a universal term to describes radiation quality, its stochastic nature causes uncertainty when incorporating with biological outcome. In addition, the structural DNA model is used to quantify a number of radiation-induced DNA damage in microscopic level by incorporating with spatial distribution of energy deposition. It is important to note that the number of DNA damage is significantly dependent on adjustable parameters in the simulation including energy threshold for inducing the damage. Finally, the experimental database, PIDE, of various cell types and particles allows investigating the factors including type of cell and particle that influence biological effect.
Advancing a Democratic Pedagogy and Supervision Framework: An Illustrative Case of Teacher Questioning in Secondary Mathematics Instruction

This article pushes back against the evalu-centric view of improvement (Hazi, 2018; 2020) in the supervision literature by advocating for a democratic pedagogy and supervision framework developed to support instructional supervision and evaluation dialogue between teachers and leaders. This democratized approach honors and centers the teacher’s expertise and learning as well as the leader’s in the observation, debrief, and reflection process. Through this decentering of expertise in the instructional supervision cycle, our goal is to build leaders’ and teachers’ mutual capacity to develop, implement, and sustain democratic instructional supervision cultures in classrooms and schools. Additionally, we illustrate our framework through a subject/discipline-specific case of instructional supervision in secondary mathematics instruction. Through this illustrative case, we demonstrate how the framework provides school leaders and teachers with specific, shared pedagogical language to engage in standards-based mathematical dialogue during the instructional supervision process. Finally, we discuss the implications of our questioning framework for democratic school leadership, supervisors’ leadership content knowledge, teachers’ discipline-specific work of teaching, and instructional supervision practices, which are often stifled by accountability-driven teacher evaluation education policies that suppress schools’ leadership capacity to apply democratic instructional supervision standards and principles.
DESIGN OF USER-CENTRED WIRELESS SENSOR TECHNOLOGY IN SPORTS: AN EMPIRICAL STUDY ON HOW ELITE KAYAK ATHLETES CAN CONTRIBUTE TO UNIVERSITY RESEARCH

University research is demanded to be more need-driven and user-centred in order to address and solve problems and needs of the market. In the present study a group of athletes and coaches has been analysed on their lead user characteristics. Some of the lead users have contributed with advanced user insights and aid in trend foresight in this sport. In a combined qualitative and quantitative approach the value of lead users in sports technology was examined and four users were identified as lead users. In consistence with previous research the results indicate that involving lead users will foster superior insight and research.
Impacts of Competitive Uncertainty on Supply Chain Competence Impacts of Competitive Uncertainty on Supply Chain Competence and Big Data Analytics Utilization: An Information Processing and Big Data Analytics Utilization: An Information Processing View View

Research advancements in big data analytics have invoked tremendous attention from both academics and industries. Many researchers refer that the adoption and application of big data analytics could lead to performance impact to organizations, and therefore further affect organizational adoption intention of this technology. However, few studies discuss the association between business strategy and big data analytics adoption under uncertainty such as pandemics or disasters. Furthermore, the role of firms’ functional activities such as supply chain operations has seldom been addressed in the adoption considerations of big data analytics under abnormal situations. In this research, empirical data from enterprises were collected and analyzed to assess the impact of competitive strategy uncertainty on big data analytics adoption and the possible effect of supply chain competence in the linkage. The results supported positive effects of strategy practices and supply chain competence on big data analytics utilization. The implications for management decisions are then elaborated.