Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Comparison of Convolutional and Multiclass Neural Network for Learning Style Detection from Facial Images

Improving the accuracy of learning style detection models is a primary concern in the area of automatic detection of learning style, which can be achieved either through, attribute/feature selection or classification algorithm. However, the role of facial expression in improving accuracy has not been fully explored in the research domain. On the other hand, deep learning solutions have become a new approach for solving complex problems using Deep Neural networks (DNNs); these DNNs have deep architectures that are capable of decomposing problems into multiple processing layers, enabling and devising multiple mapping of complex problems functions. In this paper, we investigate and compare the performance of Convolutional Neural Network (CNN) and MultiClass Neural Network (MCNN) for classification of learners into VARK learning-style dimensions (i.e Visual, Aural, Reading Kinaesthetic, including Neutral class) based on facial images. The performances of the two networks were evaluated and compared using square mean error MSE for training and accuracy metric for testing. The results show that MCNN offers better and robust classification performance of VARK learning style based on facial images. Finally, this paper has demonstrated a potential of a new method for automatic classification of VARK LS based on Facial Expressions (FEs). Based on the experimental results of the models, this approach can benefit both researchers and users of adaptive e-learning systems to uncover the potential of using FEs as identifier learning styles for recommendations and personalization of learning environments.
A Tool Proposal for Recommending Design Thinking Techniques in Software Development

Design Thinking (DT) has been incorporated into software processes by teams from startups to large companies, used in problem exploration fostering innovative solutions, and integrated into agile methods to satisfy the real stakeholders’ needs. DT places the customer needs up-front and helps to empathize with users, examining their behaviors, and producing outcomes focused on users’ demand. A set of techniques, like personas and user journey, can be used to support this human-centered approach. Selecting which technique to use might be challenging since factors such as the application scenario, stakeholder engagement level and previous knowledge of the problem-to-be-solved may vary from case to case. In our previous work we presented a DT session conducted to better understand the need for a recommendation tool, followed by a requirements elicitation activity in which we defined how the tool should work, and an early evaluation of the initial tool low-fidelity prototypes. Inspired by the Design Science Research method, in this article we extend our previous work by furthering what we performed in the tool’s definition process. We included in this work a requirements refining activity through high-level fidelity prototypes, and a requirements validation activity through a questionnaire-based feedback collection with professionals who have experience on the use of DT in software development. Our results show that our proposal offers an useful and easy to use tool to recommend DT techniques with the potential to support those professionals who apply DT in requirements engineering by suggesting techniques that are the best fit to the declared context.
Snow depth drives habitat selection by overwintering birds in built‐up areas, farmlands and forests

Abundances of animals vary according to species‐specific habitat selection, but habitats are undergoing rapid change in response to anthropogenic alterations of land use and climate. The long‐term decline of snowfall is one of the most dramatic abiotic changes in boreal regions, with potential to alter species communities and shape future ecosystems. However, the effects of snow cover on habitat‐specific abundances remain unclear for many taxa. Here we explore whether long‐term declines in snow cover affect the abundances of overwintering birds.
Planning for Autonomous Operation of Unmanned Surface Vehicles

Title of dissertation: PLANNING FOR AUTONOMOUS OPERATION OF UNMANNED SURFACE VEHICLES Brual Shah, Doctor of Philosophy, 2016 Dissertation directed by: Professor Satyandra K. Gupta Department of Mechanical Engineering The growing variety and complexity of marine research and application oriented tasks requires unmanned surface vehicles (USVs) to operate fully autonomously over long time horizons even in environments with significant civilian traffic. The autonomous operations of the USV over long time horizons requires a path planner to compute paths over long distances in complex marine environments consisting of hundreds of islands of complex shapes. The available free space in marine environment changes over time as a result of tides, environmental restrictions, and weather. Secondly, the maximum velocity and energy consumption of the USV is significantly influenced by the fluid medium flows such as strong currents. Finally, the USV have to operate in an unfamiliar, unstructured marine environment with obstacles of variable dimensions, shapes, and motion dynamics such as other unmanned surface vehicles, civilian boats, shorelines, or docks poses numerous planning challenges. The proposed Ph.D. dissertation explores the above mentioned problems by developing computationally efficient path and trajectory planning algorithms that enables the long term autonomous operation of the USVs. We have developed a lattice-based 5D trajectory planner for the USVs operating in the environment with the congested civilian traffic. The planner estimates collision risk and reasons about the availability of contingency maneuvers to counteract unpredictable behaviors of civilian vessels. Secondly, we present a computationally efficient and optimal algorithm for long distance path planning in complex marine environments using A* search on visibility graphs defined over quad trees. Finally, we present an A* based path planning algorithm with newly developed admissible heuristics for computing energy efficient paths in environment with significant fluid flows. The effectiveness of the planning algorithms is demonstrated in the simulation environments by using systems identified dynamics model of the wave amplitude modular vessel (WAM-V) USV14. Planning for Autonomous Operation of Unmanned Surface Vehicles
Can the Right Composition and Diversity of Farmed Species Improve Food Security Among Smallholder Farmers?

Food security and livelihoods among smallholder farmers in sub-Saharan Africa are often constrained by limited farm resource endowment. It can be difficult to improve resource endowment given barriers such as low land availability and the unaffordability of agricultural inputs, so here we ask whether farmers can gain a better return on their resources through optimizing their farm strategy in terms of the composition and/or diversity of crop and livestock species raised. Our survey of 1,133 smallholder farmers in western Kenya and northern Nigeria, using a modified version of RHoMIS, indicated that different farm strategies were related to differences in food security and farm incomes. In particular, we found that it was possible for farms with a high species richness but low resource endowment to achieve similar or better food security and income outcomes than farms with low species richness and high resource endowment. This indicates strong potential for diversification to improve food security and livelihoods among smallholder farmers. However, further research will be required to prove a causal relationship. We also noted some exceptions to this trend that require investigation: increasing species richness was not beneficial for low-resourced, livestock-focused farmers in western Kenya, and increasing species richness was associated with a decline in dietary diversity in northern Nigeria (due to declines in purchased dietary diversity that outweighed increases in on-farm and other sources of dietary diversity). Similar analyses could be applied to a wider RHoMIS dataset covering a greater diversity of countries and agro-ecological zones to help identify where, and why, different farm strategies result in better or worse outcomes for smallholder farmers.
Inline surface topography measurements of ultrashort laser pulsed manufactured micro structures based on low coherence interferometry

Abstract In view of ever-increasing demands on process accuracies and increasingly narrow tolerance windows in laser micro structuring, the monitoring of laser processes and the subsequent quality assurance of the laser-structured products are becoming more and more important. Functional surface structures to be manufactured by laser micro structuring are nowadays in the range of 50 μm down to 10 μm regarding their surface geometries. To cover this demand, this paper deals with the development of a holistic approach to scanner-based, coaxial topography measurement by the integration of a highly accurate inline measuring system into the existing optics of a laser micro machining system. The combination and implementation of the laser processing beam and the measuring beam by the same optics is intended to open up the possibilities of real-time process feedback of the measurement data for the realization of an adaptively controlled laser micro structuring process. Therefore, the influence of the individual system components of the laser beam path on the measurement beam and induced optical aberrations gets evaluated and explained. Resulting from this, solutions for improving the system against these aberrations are developed and evaluated in a demonstrator setup, implementing the measurement system coaxially into a laser micro machining beam path.
The Brain Is Adaptive Not Triune: How the Brain Responds to Threat, Challenge, and Change

Theory impacts how research is conducted. A popular theory used to conceptualize brain functioning is the triune brain theory. The triune brain theory is an evolutionary theory of brain development that emphasizes three key brain regions consisting of the brainstem, the limbic system, and the cortex that function relatively independently in coping with stress via fight or flight, emotion, and cognition, respectively. However, modern neuroscience research demonstrates that the triune brain theory does not accurately explain how the brain functions in everyday life or during the stress response. Specifically, emotion and cognition are interdependent and work together, the limbic system is not a purely emotional center nor are there purely emotional circuits in the brain, and the cortex is not a purely cognitive center nor are there purely cognitive circuits in the brain. We propose a new evolutionarily based model, the adaptive brain, that is founded on adaptive prediction resulting from interdependent brain networks using interoception and exteroception to balance current needs, and the interconnections among homeostasis, allostasis, emotion, cognition, and strong social bonds in accomplishing adaptive goals.
Differential Responses of Eelgrass and Macroalgae in Pacific Northwest Estuaries Following an Unprecedented NE Pacific Ocean Marine Heatwave

The 2013-2016 northeast Pacific Ocean marine heatwave (MHW) had myriad impacts on marine communities, but little is known about how this event affected coastal estuaries. We examined the extent to which elevated temperatures associated with the offshore MHW were observed in four estuaries (Willapa Bay, Washington and Netarts Bay, Yaquina Bay, and Coos Bay, Oregon) and the responses of macrophytes at marine dominated sites within these estuaries. Records of eelgrass (Zostera marina), ulvoid macroalgae (Ulva and Enteromorpha spp.), and environmental characteristics, including water temperature, were analyzed over three periods: before (2006-2010), during (2015-2016), and after (2017-2019) the MHW. During the MHW, all four estuaries experienced “estuarine heatwaves” (anomalous warm water events) at monitoring stations and there was an associated decline in macroalgae biomass. In northern estuaries (Willapa and Netarts bays) where water temperatures are normally higher and estuaries are shallower, aboveground eelgrass biomass declined and did not recover for at least three years after the MHW. In southern estuaries (Yaquina and Coos bays), where water temperatures are normally colder and estuaries are deeper, the MHW was associated with a neutral, or temporarily positive, change in aboveground eelgrass biomass. Our analysis supports the hypothesis that upwelling intensity and estuarine depth determined the severity of MHW impacts on macrophytes at marine dominated sites, and that the colder and deeper estuaries in the south may serve as refuges for eelgrass but not macroalgae. We suggest that estuary-specific responses were predictable given the drivers of macrophyte abundance at marine dominated sites, and that baseline ocean upwelling and estuarine temperature can be used to anticipate macrophyte responses at marine dominated sites to MHWs in the future.
Salient Findings on Host Range, Resistance Screening, and Molecular Studies on Sterility Mosaic Disease of Pigeonpea Induced by Pigeonpea sterility mosaic viruses (PPSMV-I and PPSMV-II)

Two distinct emaraviruses, Pigeonpea sterility mosaic virus-I (PPSMV-I) and Pigeonpea sterility mosaic virus-II (PPSMV-II) were found to be associated with sterility mosaic disease (SMD) of pigeonpea [Cajanus cajan (L.) Millsp. ]. The host range of both these viruses and their vector are narrow, confined to Nicotiana benthamiana identified through mechanical transmission, and to Phaseolus vulgaris cvs. Top Crop, Kintoki, and Bountiful (F: Fabaceae) through mite transmission. A weed host Chrozophora rottleri (F: Euphorbiaceae) was also infected and tested positive for both the viruses in RT-PCR. Among the wild Cajanus species tested, Cajanus platycarpus accessions 15661, 15668, and 15671, and Cajanus scarabaeoides accessions 15683, 15686, and 15922 were infected by both the viruses and mite vector suggesting possible sources of SMD inoculum. Though accession 15666 of C. platycarpus, 15696 of C. scarabaeoides, and 15639 of Cajanus lanceolatus were infected by both the viruses, no mite infestation was observed on them. Phylogenetic analysis of nucleotide sequences of RNA-1 and RNA-2 of PPSMV-I and PPSMV-II isolates in southern India revealed significant divergence especially PPSMV-II, which is closely related to the Fig mosaic virus (FMV) than PPSMV-I. In multilocation testing of pigeonpea genotypes for their broad-based resistance to SMD for two consecutive years, genotypes ICPL-16086 and ICPL-16087 showed resistance reaction (<10% incidence) in all three locations studied. Overall, the present study gives a clear idea about the host range of PPSMV-I and PPSMV-II, their molecular relationship, and sources of resistance. This information is critical for the development of reliable diagnostic tools and improved disease management strategies.
Differences in Sleep Patterns and Mental Health Problems During Different Periods of COVID-19 Outbreak Among Community-Dwelling Older Men in Hong Kong

Objectives: To determine the association of sleep with mental health among Hong Kong community-dwelling older men in the context of the COVID-19 pandemic. Methods: This additional analysis was derived from the community-dwelling men aged >60 recruited during three COVID-19 outbreaks (i.e., pre-outbreak, between the second and third wave, and during the third wave) in Hong Kong from July 2019 to September 2020. Sleep and mental health were measured by Pittsburgh Sleep Quality Index questionnaire and Hospital Anxiety and Depression Scale, respectively. Multivariate logistic regression models were performed for the associations between sleep and mental health after considering the outbreaks’ impact. Results: Subjects enrolled between the second and third wave tended to have better sleep but worse mental health. Positive associations between poor sleep and depression (AOR = 3.27, 95% CI: 1.60–7.03) and anxiety (AOR = 2.40, 95% CI: 1.07–5.76) were observed. The period “between second and third wave” was positively associated with depression (AOR = 2.65, 95% CI: 1.22–5.83), showing an additive interaction with poor sleep. Conclusion: The positive association between poor sleep and depression was aggravated by the period “between the second and third wave” among community-dwelling older males in Hong Kong.
The Influence of Orthographic Units Across Korean Children of Different Ages in Hangul Reading

Using the dual-route reading model as a framework, this study investigated the following research questions on Hangul reading: Which orthographic units (e.g., letters, syllable blocks, and words) influence the reading performance of Korean-speaking children? In addition, do the influential units change as the children grow up? To answer these questions, we tested the effects of age, frequency, lexicality, and two types of length—the numbers of letters (letter length) and syllable blocks (syllable block length)—and the interactions of these factors in the reading performance of Korean-speaking preschool and primary school children from first to third grade. Regarding reading latencies, there was a significant three-way interaction of age × lexicality × length regardless of the type of length. This interaction indicated that, for words only, the interaction between age and length was significant. Accordingly, the length effect decreased as children’s age increased. When reading latencies for words were analyzed with a mixed-effect model consisting of three factors—age, frequency, and length—neither a main effect of syllable block length nor an interaction of syllable block length with age was significant. In contrast, the interaction of age × letter length in word reading latencies remained significant. The length effect was smaller as children’s age increased. In addition, the frequency effect was significant and interacted significantly with age. The frequency effect increased as children’s age increased. In conclusion, significant frequency effects indicate that Korean-speaking children use the lexical process in addition to the non-lexical process when reading Hangul words. Importantly, as children grow up, a larger orthographic unit, that is, words, is more strongly related to reading performance, whereas the influence of the smaller orthographic unit, that is, letters, decreases.
Mindfulness as a Protective Factor Against Depression, Anxiety and Psychological Distress During the COVID-19 Pandemic: Emotion Regulation and Insomnia Symptoms as Mediators

Objectives Research has linked mindfulness to improved mental health, yet the mechanisms underlying this relationship are not well understood. This study explored the mediating role of emotion regulation strategies and sleep in the relationship between mindfulness and symptoms of depression, anxiety and psychological distress during the COVID-19 pandemic. Methods As detailed in this study’s pre-registration (osf.io/k9qtw), a cross-sectional research design was used to investigate the impact of mindfulness on mental health and the mediating role of emotion regulation strategies (i.e., cognitive reappraisal, rumination and suppression) and insomnia. A total of 493 participants from the general population answered an online survey and were included in the final analysis. The online survey consisted of the short form of the Five-Facets Mindfulness Questionnaire (FFMQ-SF), the Impact of Event Scale-revised (IES-R), the Generalised Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire (PHQ-8), the Emotion Regulation Questionnaire (ERQ), the short form of the Rumination Response Scale (RSS-SF), and the Insomnia Severity Index (ISI). Results Structural equation modelling revealed that mindfulness was related to lower symptoms of depression, anxiety and psychological distress, both directly and indirectly. Mindfulness was negatively associated with rumination and insomnia. As hypothesised, models revealed that the associations between mindfulness and depression, anxiety and psychological distress were significantly mediated by its negative associations with rumination and insomnia. Our findings also demonstrated that rumination was related to increased insomnia symptoms, which in turn was associated with increased mental health problems, indicating a mediated mediation. Mindfulness was also positively associated with cognitive reappraisal and negatively associated with suppression, which were, respectively, negatively and positively associated with depressive symptoms, and thus functioned as specific mediators of the association between mindfulness and depression. Conclusion Our findings suggest that rumination and insomnia operate transdiagnostically as interrelated mediators of the effects of mindfulness on mental health, whereas cognitive reappraisal and suppression function as specific mediators for depression. These insights emphasise the importance of targeting emotion regulation and sleep in mindfulness interventions for improving mental health. Limitations and implications for practice are discussed.
Development and Psychometric Evaluation of Family Caregivers’ Hardiness Scale: A Sequential-Exploratory Mixed-Method Study

Objective Caring for patients with Alzheimer’s disease (AD) is a stressful situation and an overwhelming task for family caregivers. Therefore, these caregivers need to have their hardiness empowered to provide proper and appropriate care to these older adults. From the introduction of the concept of hardiness, few studies have been conducted to assess the hardiness of caregivers of patients with AD. Presumably, one reason for this knowledge gap is the lack of a proper scale to evaluate hardiness in this group. This study was conducted to develop a reliable and valid Family Caregivers’ Hardiness Scale (FCHS) to measure this concept accurately among Iranian family caregivers sample. Methods This study is a cross-sectional study with a sequential-exploratory mixed-method approach. The concept of family caregivers’ hardiness was clarified using deductive content analysis, and item pools were generated. In the psychometric step, the samples were 435 family caregivers with a mean age of 50.26 (SD ± 13.24), and the data were gathered via an online form questionnaire. In this step, the items of the FCHS were evaluated using face and content validity. Then, the factor structure was determined and confirmed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) followed by convergent and divergent validity, respectively. Finally, scale reliability, including stability, and internal consistency were evaluated. Results The finding revealed that FCHS consists of five factors, namely, “Religious Coping” (5 items), “Self-Management” (6 items), “Empathic Communication” (3 items), “Family Affective Commitment” (3 items), and “Purposeful Interaction” (4 items) that explained 58.72% of the total variance. The results of CFA showed a good model fit. Reliability showed acceptable internal consistency and stability. Conclusion Based on the results of the psychometric evaluation of the FCHS, turned out that the concept of hardiness in Iranian family caregivers is a multidimensional concept that is most focused on individual-cultural values, emotional family relationships, and social relationships. The designed scale also has acceptable validity and reliability features that can be used in future studies to measure this concept in family caregivers.