Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Facial Expressions using Machine Learning

Recognition of facial expressions is one of the most powerful and challenging tasks in Non-verbal communication. Normally major part of communication involves verbal Channels. But Non-verbal gestures are majorly expressed through facial expressions. Our project is based on classification of various human expressions using various types of Face Expression Recognition (FER) techniques which include the three major stages such as preprocessing, feature extraction and classification. We have carried out all these techniques using Convolutional Neural Networks (CNN). Our project is inspired by VGG and Xception model. Datasets used are FER 2013 (for emotion classification), IMDB (for gender classification), FEC (Google facial expression comparison). Using CNN, we classify 7 different expressions like Happy, Sad, Anger, Disgust, Fear, Surprise and Neutral.
Developing Intercultural Competence Through Design Thinking

Cultural competence, as the ability to interact effectively with the culturally diverse others, is a key component to your success in the globalized world. Developing cultural competence gives us an insight how to benefit from the diversity within intercultural interactions. Everyone may misinterpret the cultural differences due to the low level of cultural competence. That can influence further cooperation with different cultures. Therefore, it is very important to foster students’ intercultural skills, in particular by using different learning techniques and implementing new ideas into the traditional teaching methods. One of them is design thinking as a practice that encourages collaboration and can help students to manage intercultural challenges. Hence, the research problem for this study is to reveal the correlation between the development of students’ intercultural competence and design thinking method application. The purpose of the study is to summarize and synthesize the research on cross-cultural interactions and design thinking to build a framework that shows how the implementation of the design thinking method into the learning process facilitates the development of students’ intercultural competence. The tasks of the research are:a) to review the main contributions to the field of design thinking by analysing multidisciplinary studies on how design thinking fosters development of variety competences including intercultural competence;b) to design the framework to reveal the correlation between the components of intercultural competence and the stages of design thinking process;c) to observe the changes in the students’ intercultural competence level by analysing learners’ responses to the case of intercultural misunderstanding at the beginning of studying the cross-cultural communication classes and after finishing the course.d) The study uses mixed approaches such as quantitative and qualitative methods, scientific literature studies, intercultural competence assessment, grouping, comparative analysis, synthesis, inductive and deductive methods.The key results are presented in the framework that demonstrates the ways how design thinking method supports the development of intercultural competence. This framework can be used by educators to teach intercultural competence and everyone involved in cross-cultural interactions, and who would like to benefit from the diversity.
Ecology and genomic background shape the probability of parallel adaptation to climate

Evolution can repeat itself, resulting in parallel adaptations in independent lineages occupying similar environments. Moreover, parallel evolution sometimes, but not always, uses the same genes. Two main hypotheses have been put forth to explain the probability and extent of parallel evolution. First, parallel evolution is more likely when shared ecologies result in similar patterns of natural selection in different taxa. Second, parallelism is more likely when genomes are similar, because of shared standing variation and similar mutational effects in closely related genomes. Here we combine ecological, genomic, experimental, and phenotypic data with randomization tests and Bayesian modeling to quantify the degree of parallelism and study its relationship with ecology and genetics. Our results show that the probability of parallel adaptation to climate among species of Timema stick insects is shaped collectively by shared ecology and genomic background. Specifically, the probability of genetic parallelism decays with divergence in climatic (i.e., ecological) conditions and genomic similarity. Moreover, we find that climate-associated loci are likely subject to selection in a field experiment, overlap with genetic regions associated with cuticular hydrocarbon traits, and are not strongly shaped by introgression between species. Our findings shed light on when evolution is most expected to repeat itself.
Environmental Pressures on Top-Down and Bottom-Up Forces in Coastal Ecosystems

Global change is manifesting new and potent pressures that may determine the relative influence of top-down and bottom-up forces on the productivity of plants that undergird coastal ecosystems. Here, I present a meta-analysis conducted to assess how herbivory, nitrogen enrichment, and elevated salinity influence plant productivity according to the salinity regimes of coastal ecosystems. An examination of 99 studies representing 288 effect sizes across 76 different plant species revealed that elevated salinity negatively affected productivity across all environments, but particularly in freshwater ecosystems. Nitrogen enrichment, on the other hand, positively affected productivity. In agreement with the plant stress hypothesis, herbivory had the greatest negative impact in saline habitats. This trend, however, appears to reverse with nitrogen enrichment, with maximum losses to herbivory occurring in brackish habitats. These findings demonstrate that multiple stressors can yield complex, and sometimes opposite outcomes to those arising from individual stressors. This study also suggests that trophic interactions will likely shift as coastal ecosystems continue to experience nutrient enrichment and sea level rise.
Urban-nesting mountain chickadees have a reduced response to a simulated predator

Anti-predator behaviour is common among birds, but little research exists on whether differences in the predator landscape between urban and rural habitats results in differential anti-predator behaviour. We compared nest-defence behaviour of mountain chickadees (Poecile gambeli) in urban and rural habitats in Kamloops, BC, Canada to a simulated predator model (snake) on top of nest boxes while incubating females were away from nests on foraging bouts. Upon their return, we recorded proximity to the predator model, latency to contact the nest box and enter the nest, and number of gargle and chick-a-dee calls as measures of anti-predator behaviour and compared multivariate “predator aversion scores” across birds occupying either rural or urban landscapes. Rural-nesting birds had more aversive reactions to the predator model than the urban-nesting birds, which may suggest differences in perceived threat of the model, in combination with increased boldness associated with urban-nesting birds.
Future Temperature and Salinity in Puget Sound, Washington State, Under CMIP6 Climate Change Scenarios

In Washington State, climate change will reshape the Puget Sound marine ecosystem through bottom-up and top-down processes, directly affecting species at all trophic levels. To better understand future climate change effects on sea surface temperature and salinity in Puget Sound, we used empirical downscaling to derive high-resolution time series of future sea surface temperature and salinity. Downscaling was based on scenario outputs of two coarse-resolution General Circulation Models, GFDL-CM4 and CNRM-CM6-1-HR, developed as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). We calculated 30-year climatologies for historical and future simulations, calculated the anomalies between historical and future projections, interpolated to a high resolution, and applied the resulting downscaled anomalies to a Regional Ocean Modeling System (ROMS) time series, yielding short-term (2020–2050) and long-term (2070–2100) delta-downscaled forecasts. Downscaled output for Puget Sound showed temperature and salinity variability between scenarios and models, but overall, there was strong model agreement. Model variability and uncertainty was higher for long-term projections. Spatially, we found regional differences for both temperature and salinity, including higher temperatures in the South Basin of Puget Sound and higher salinity in the North Basin. This study is a first step to translating CMIP6 outputs to higher resolution predictions of future conditions in Puget Sound. Interpreting downscaled projections of temperature and salinity in Puget Sound will help inform future ecosystem-based management decisions, such as supporting end-to-end ecosystem modeling simulations and assessing local-scale exposure risk to climate change.
A Framework to Assess the Potential Uncertainties of Three FPAR Products

The remote sensing products of the fraction of photosynthetically active radiation (FPAR) are widely used in large‐scale terrestrial vegetation condition monitoring and ecological modeling. However, the validation and evaluation of these products are still insufficient due to limited ground measurements. A framework is proposed in this study that does not rely on ground FPAR observations to evaluate the potential uncertainties of three FPAR data sets over a large scale. Two independent methods, including a statistical method named extended triple colocation (ETC) and FPAR‐based gross primary production (GPP) comparative evaluation at the site level, are integrated. The framework was applied to three widely used FPAR products, including GLASS (Global Land Surface Satellite), GEOV2 (version 2 of the COPERNICUS 1‐km product), and MODIS (Moderate Resolution Imaging Spectroradiometer), in China from 2001–2015. The root‐mean‐square error (RMSE) and correlation coefficient (R) based on the ETC method showed that at the national spatial scale, GEOV2‐FPAR had the highest precision (RMSEFPAR = 0.0367, RFPAR = 0.9012), followed by MODIS‐FPAR (RMSEFPAR = 0.0482, RFPAR = 0.8392) and GLASS‐FPAR (RMSEFPAR = 0.0536, RFPAR = 0.736). In particular, each FPAR data set was locally optimal over some regions. Using a light use efficiency model, GPP was calculated using these three FPAR data sets and other identical variables and parameters at 22 eddy flux sites. General coherent results were found in both GPP evaluation and site‐level ETC analysis of these three FPAR data sets. Therefore, we conclude that this framework is reliable and applicable in evaluating the potential uncertainties of FPAR.
Development of prosocial competencies in PETE and Sport Science students. Social justice, Service-Learning and Physical Activity in cultural diversity contexts

ABSTRACT Background The development of prosocial competencies in university students can be attained through the implementation of Service-Learning (S-L) methodology by carrying out a community service to groups of foreign unaccompanied minors (FUM). Physical Education Teacher Education (PETE) and Sport Science (SS) students involved in an S-L experience normally develop a critical way of thinking as they face social conflicts. Besides, social justice education and S-L attempt to help in favour of social inclusion of vulnerable groups. Purpose This study aims to assess the development of prosocial competencies in PETE and SS students taking a Dual Degree Program in Physical Activity (PA) and SS and Primary Education. This is done through S-L methodology, by carrying out a community service to groups of FUM. Method A total of 21 male and 9 female PETE and SS students participated in this study. The methodology used is of a qualitative nature. Reflective diary is used as an instrument for data collection, and content analysis as an information analysis technique. Results It has been observed an improvement in the prosocial competencies of the PETE and SS students involved in the S-L experience. The competencies with the greatest number of references and, therefore, those with a greater presence in their testimonies, include organisation, proactivity and optimism, self-esteem, and tolerance and respect. Conclusion The S-L is capable of undertaking a transformative role which enables PETE and SS students to acquire prosocial competencies in contexts relating to cultural diversity and social justice.
Experimental Study on Abstract Expression of Human-Robot Emotional Communication

With the continuous development of intelligent product interaction technology, the facial expression design of virtual images on the interactive interface of intelligent products has become an important research topic. Based on the current research on facial expression design of existing intelligent products, we symmetrically mapped the PAD (pleasure–arousal–dominance) emotion value to the image design, explored the characteristics of abstract expressions and the principles of expression design, and evaluated them experimentally. In this study, the experiment of PAD scores was conducted on the emotion expression design of abstract expressions, and the data results were analyzed to iterate the expression design. The experimental results show that PAD values can effectively guide designers in expression design. Meanwhile, the efficiency and recognition accuracy of human communication with abstract expression design can be improved by facial auxiliary elements and eyebrows.
SARS-CoV-2 NSP-12 mutations survey during the pandemic in the world

Background SARS-CoV-2 belongs to the beta coronavirus family responsible for coronavirus disease 2019 (COVID-19), a novel severe acute respiratory syndrome pandemic. The infection first emerged in Wuhan, China, and rapidly spread worldwide. The ongoing outbreak has posed an urgent worldwide health threat due to the rapid transmittable potential and high mortality rate. Due to the critical role of none structural protein − 12 (NSP-12) in COVID-19. This study tries to investigate the link between genotype-phenotype NSP-12 variation and the prevalence of this disease. Methods We analyzed approximately 2 million Nsp12 of SARS-CoV-2 protein sequence from January 2020 until June 2021. Python programming language was utilized to preprocess and apply inclusion criteria on FASTA files to prepare a list of suitable samples for clustering samples. NSP-12 regions were aligned to the reference sequence to compare and identify mutation patterns, categorized based on frequency and continent. Results The rate of ‌NSP-12 mutation in divided geographical areas was different. Based on continental studies, the P227L and G671S mutations have multiplied over time and in European and Asian societies in recent months. According to biochemical studies, the occurrence of G671S mutation increases the stability of the protein. Conclusion We concluded that NSP-12 P227L and G671S mutations in SARS-CoV-2 are increased in recent months. Further studies will be required to investigate whether these mutations impact the severity of the disease.
Keys to the flesh flies of Sarawak, East Malaysia, with descriptions of two new genera and eight new species (Diptera: Sarcophagidae)

e present revisional work is based on very large collections made by the rst and second authors during the course of studies. Most specimens of sarcophagid esh ies were made by the authors during the eld surveys programmed by the Sarawak Museum Department, Kuching, Malaysia from 2005 to 2019. A total of 24 genera and 59 species is recorded. Two new genera, Omarisca gen. nov. and Zulisca gen. nov. are established for two peculiar species found in mangroves. Also eight new species are described: Myorhina miyagii sp. nov., M. tomae sp. nov., Burmanomyia barioensis sp. nov., B. pseudoborneensis sp. nov., Sarcorohdendor a kerohi sp. nov., S. okazawai sp. nov., Hosarcophaga palustris sp. nov., and H. puteri sp. nov. e following seven species are newly recorded from Malaysia: Senotainia albifrons (Rondani, 1859), Burmanomyia aureomarginata (Shinonaga & Tumrasvin, 1979), Hosarcophaga auricauda (Ho, 1938), H. serrata (Ho, 1938), Parasarcophaga idmais (Séguy, 1934), P. montiblensis (Sugiyama, 1990) and P. walshi (Ho, 1938), Revised identi cation keys to the Malaysian species are provided.
WHAT’S ‘UP NEXT’? INVESTIGATING ALGORITHMIC RECOMMENDATIONS ON YOUTUBE
 ACROSS ISSUES AND OVER TIME

YouTube’s ‘up next’ feature algorithmically suggests videos to watch after a video that is currently playing. This feature has been criticised for limiting users’ exposure to diverse media content and information sources; meanwhile, YouTube has reported that they have implemented technical and policy changes to address these concerns. Yet, there is limited data to support either the existing concerns or YouTube’s claims. Drawing on the concept of platform observability, this paper combines computational and qualitative methods to investigate the types of content YouTube’s ‘up next’ feature amplifies over time, using three search terms associated with sociocultural issues where concerns have been raised about YouTube’s role: ‘coronavirus’, ‘feminism’ and ‘beauty’. Over six weeks, we collected the videos (and their metadata) that were highly ranked in the search results for each keyword, as well as the top-ranked recommendations associated with each video, repeating the exercise for three steps in the recommendation chain. We then examined patterns in the recommended videos (and channels) for each query and their variation over time. We found evidence of YouTube's stated efforts to boost ‘authoritative’ media outlets, but at the same time, misleading and controversial content continues to be recommended. We also found that while algorithmic recommendations offer diversity in videos over time, there are clear ‘winners’ at the channel level that are given a visibility boost in YouTube’s 'up next' feature. These impacts were attenuated differently depending on the nature of the search topic.
sp2–sp3 Hybrid Porous Carbon Materials Applied for Supercapacitors

Carbon materials have gained considerable attention in recent years due to their superior properties. Activated carbon has been used in supercapacitors due to its density and rapid adsorption capability. The sp2–sp3 hybrid porous carbon materials are synthesized using herringbone-type carbon nanofibers (CNFs) and carbonized spherical phenol resins, with KOH as the activating agent. The morphology of the hybrid porous carbon facilitates the formation of ribbon-like nanosheets from highly activated CNFs wrapped around spherical resin-based activated carbon. The etching and separation of the CNFs produce a thin ribbon-like nanosheet structure; these CNFs simultaneously form new bonds with activated carbon, forming the sp2–sp3 hybrid porous structure. The relatively poor electrical conductivity of amorphous carbon is improved by the 3D conductive network that interconnects the CNF and amorphous carbon without requiring additional conductive material. The composite electrode has high electron conductivity and a large surface area with a specific capacitance of 120 F g−1. Thus, the strategy substantially simplifies the hybrid materials of sp2-hybridized CNFs and sp3-hybridized amorphous spherical carbon and significantly improves the comprehensive electrochemical performance of supercapacitors. The developed synthesis strategy provides important insights into the design and fabrication of carbon nanostructures that can be potentially applied as electrode materials for supercapacitors.
Relating Field Moduli of Asphalt Mixture Layer Under Vehicular Loading and its Dynamic Moduli Under Laboratory Loading

The modulus of the asphalt layer is an essential input parameter in asphalt pavement design. For design purposes, the relationship between field and laboratory moduli of the asphalt mixture layer needs to be identified. In this research, the field modulus of the asphalt layer is predicted via a developed field modulus master curve. The laboratory modulus of asphalt mixture is measured using three different loading modes, namely uniaxial compressive (UC), indirect tensile (IDT), and four-point bending (4PB) modes. The loading mode is observed to affect the mixture’s laboratory modulus. The asphalt mixture moduli measured from UC mode are generally the highest, following by those from IDT mode, whereas the 4PB mode generates the lowest asphalt mixture moduli. By comparing field and laboratory moduli of asphalt mixture, it is found that the laboratory modulus from 4PB mode yields satisfactory predictions for the mixture’s field modulus in a wide range of loading frequencies. The UC and IDT modes, which tend to overpredict the field modulus of the asphalt layer, need to be modified. The modification factor ranges between 0.3 and 0.7 for UC mode, and varies from 0.2 to 1.0 for IDT mode. For both modes, the modification factors grow closer to 1.0 with increasing frequencies and decreasing temperatures, implying that UC and IDT modes become increasingly suitable for simulating field conditions at high frequencies and low temperatures.
Experimental Validation of Flow Uniformity Improvement by a Perforated Plate in the Heat Exchanger of SFR Steam Generator

The steam generator in a nuclear power plant is a type of heat exchanger in which heat transfer occurs from the hot fluid in multiple channels to the cold fluid. Therefore, a uniform flow over multiple channels is necessary to improve heat exchanger efficiency. The study aims at experimentally investigating the improvement of flow uniformity by the perforated plate in the heat exchanger used for a sodium-cooled fast reactor stream generator. A 1/4-scale experimental model for one heat exchanger unit with 33 × 66 channels was manufactured. The working fluid was water. A perforated plate was systematically designed using numerical simulations to improve the flow uniformity over the 33 × 66 channels. As a result, the flow uniformity greatly improved at a slight cost of pressure drop. To validate the numerical results, planar particle image velocimetry measurements were performed on the selected planes in the inlet and outlet headers. The experimental velocity profiles near the exits of the channels were compared with numerical simulation data. The experimental profiles agreed with the numerical data well. Both the numerical simulation and the experimental results showed a slight increase in pressure drop, despite significant improvement in the flow uniformity.
Initial teacher educators’ integrating iPads into their physical education teaching

Teachers today must not only be prepared to use technology but must also know how to use it (Butler, D., K. Marshall, and M. Leahy. 2015. Shaping the Future: How Technology Can Lead to Educational Transformation, 1st ed. Dublin: Liffey Press). The purpose of this study was to explore two primary physical education initial teacher educator’s (PEITE’s) professional learning experiences while introducing iPads into a physical education module. The module’s focus was to promote quality teaching, learning and assessment of fundamental movement skills in physical education with pre-service generalist primary teachers. It was a qualitative study utilising lesson study methodology. Data included audio files, video recordings and field notes. Following analysis, three themes were developed: learning the technology, managing the technology and integrating the technology. The findings showed that for the PEITEs, time was a valuable commodity while grappling with technological knowledge, technological pedagogical knowledge and pre-service teachers’ physical education knowledge. Self-directed learning was an enabler to facilitate technological and pedagogical competence for the PEITEs. Although managing aspects of the technology, such as limited Wi-Fi access and technical support, was a challenge, the PEITEs continued to integrate iPads into their teaching.