Miracle-dz/UniFAR-FTUs huggingface dataset:
Children’s Perspectives on Using Serious Games as a Complement to Promoting Their Social–Emotional Skills

The use of serious games may be an appealing and complementary way to motivate curriculum-based social and emotional learning (SEL); still, investigation into this potential usefulness is scarce. This study aims to address the usefulness of serious games within the program ‘Me and Us of Emotions’. Specifically, we analyzed the differences in children’s satisfaction in sessions that did or did not use serious games as a complement to the intervention, explored the contribution of using serious games to the global satisfaction with the program, and explored children’s qualitative feedback regarding the sessions. The participants were 232 children (122 boys and 110 girls) aged between 8 and 12 years old (M = 9.09, SD = 0.80). The measures were based on the subjective appraisals of the sessions made by the participating children, including quantitative and qualitative assessments of the degree of satisfaction of the participants. The results showed that there were similar levels of satisfaction with the sessions that did or did not use serious games as a complement to the program. However, only satisfaction with the sessions that used serious games (and not satisfaction with the sessions that did not use them) contributed significantly to explaining both the enjoyment of the activities and the interest in the subjects. Satisfaction with serious games was significantly and positively associated with fun, easiness, ability to understand the session, and ability to cope with emotions. Qualitative analysis showed three main themes, namely: positive aspects, negative aspects, and opportunities for improvement of the program. Overall, these results indicate that children’s satisfaction with the ‘Me and Us of Emotions’ program is related to serious games, suggesting the relevance of using this complementary tool more often when intervening with younger generations.
Interim Guidance for Prevention and Treatment of Monkeypox in Persons with HIV Infection — United States, August 2022

Monkeypox virus, an orthopoxvirus sharing clinical features with smallpox virus, is endemic in several countries in Central and West Africa. The last reported outbreak in the United States, in 2003, was linked to contact with infected prairie dogs that had been housed or transported with African rodents imported from Ghana (1). Since May 2022, the World Health Organization (WHO) has reported a multinational outbreak of monkeypox centered in Europe and North America, with approximately 25,000 cases reported worldwide; the current outbreak is disproportionately affecting gay, bisexual, and other men who have sex with men (MSM) (2). Monkeypox was declared a public health emergency in the United States on August 4, 2022. † Available summary surveillance data from the European Union, England, and the United States indicate that among MSM patients with monkeypox for whom HIV status is known, 28%-51% have HIV infection (3-10). Treatment of monkeypox with tecovirimat as a first-line agent is available through CDC for compassionate use through an investigational drug protocol. No identified drug interactions would preclude coadministration of tecovirimat with antiretroviral therapy (ART) for HIV infection. Pre- and postexposure prophylaxis can be considered with JYNNEOS vaccine, if indicated. Although data are limited for monkeypox in patients with HIV, prompt diagnosis, treatment, and prevention might reduce the risk for adverse outcomes and limit monkeypox spread. Prevention and treatment considerations will be updated as more information becomes available.
The Green Manure (Astragalus sinicus L.) Improved Rice Yield and Quality and Changed Soil Microbial Communities of Rice in the Karst Mountains Area

The use of green manure plants for soil restoration is a viable agricultural practice that can mitigate soil degradation and biodiversity loss caused by the long-term application of inorganic fertilizers. However, the effects of green manure on soil microbial communities, rice yield, and quality in the karst mountains are largely unknown. The effects of no chemical fertilizer, chemical fertilizer, chemical fertilizer + different Astragalus sinicus L. (Chinese milk vetch, CMV) treatments on the microbial community, soil enzyme activities, soil nutrient content, and crop yield were investigated through field experiments. A moderate application of chemical fertilizer with green manure can increase chlorophyll content, increase effective rice spikes, positive impact on rice yield, and increase crude protein, etc. Additional application of the moderate amount of CMV can increase alkali-hydrolyzable nitrogen and available phosphorus (a significant increase of 54.87–72.65%), improve microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) (CFMV2 significantly increased by 22.16%), improve soil urease and phosphatase activities, and the urease activity increased by 43.43–69.24% with CMV application compared to CK. Moreover, all bacterial communities were dominated by three major phyla (Proteobacteria, Chloroflexi, and Acidobacteria), where the application of chemical fertilizer with CMV increased the ratio of abundance of Proteobacteria and Acidobacteria in rice soils, and the effect of chemical fertilizer application on the dominant bacteria was regulated to some extent by additional green manure application, which may have a beneficial effect on rice yield. Therefore, we conclude that the rational use of chemical fertilizers with CMV (22,500 kg ha−1) in karst landscapes is one of the effective measures to achieve efficient and sustainable use of rice fields.
Enclosure in Combination with Mowing Simultaneously Promoted Grassland Biodiversity and Biomass Productivity

Grassland is the primary land use in China, which has experienced extensive degradation in recent decades due to overexploitation. Here, we conducted field experiments to quantify the degraded grassland’s recovery rate in Northeast Inner Mongolia in response to restoration measures, including fallow + enclosure (FE) and mowing + enclosure (ME) in comparison to livestock grazing (LG), since 2005. Plant community properties were surveyed and aboveground biomass (AGB) sampled in summer 2013. Our results showed that the regional dominant species Leymus chinensis retained its dominance under FE, whereas a range of forb species gained dominance under LG. Vegetative cover was maximal under FE and minimal under LG. The least amount of vegetation development and AGB were observed under LG. However, plant diversity showed an opposite pattern, with maximal diversity under LG and minimal under FE. Statistical analysis revealed that AGB was negatively associated with plant diversity for all treatments except ME. For ME, a positive AGB-diversity relationship was characterized, suggesting that mowing intensity was a controlling factor for the AGB-diversity relationship. Overall, these results demonstrated that enclosure plus mowing represented an effective conservation measure that provided fair support to forage production and a progressive pathway to a more resilient grassland system.
The Preparation of Packaging Films from Ramie Based Carboxymethyl Cellulose

ABSTRACT In this study, ramie fiber was used as the biomass material to prepare carboxymethyl cellulose (CMC). Additionally, the films were prepared by casting method using the ramie-based CMC, and the glycol was added as a plasticizer to overcome the fragility of the films. The films were extensively characterized using FT-IR, XRD, and TG&DSC. Moreover, the physicochemical characteristics and tensile properties of the CMC films were also evaluated. It was demonstrated that the CMC films prepared from ramie fiber with good film performances and better tensile properties which are suitable for packaging applications. This study provides a new way for value-added ramie fiber.
An Attention-Based Multimodal Siamese Architecture for Tweet-User Verification

With the advent of internet technologies, it has created different ways of writing anonymously, which has lead to criminal and malicious activities over social media platforms. Thus, the automatic authentication checking of the available contents is the need of the hour. Social media sites, such as Facebook, Twitter, and so on, are used heavily by the users for sharing of information about their day-to-day activities. The identity of the suspect user is matched against tweets written by the specific user in tweet-user verification process. Writing styles of different users differ from each other, due to unique word choices, emoji selection, sentence formation, and punctuation usage. We have developed a multimodal Siamese-based architecture, which uses attention between the text and emoji parts of the tweet for generating a combined representation for the tweet. Attention helps in selecting the relevant information from different modalities. Modality attention is used for fusing the two modalities (text and emoji). We have used a newly developed multimodal Twitter dataset for evaluating the performance of the proposed model. We achieved an average accuracy, precision, recall, and $F$ -measure values of 68.50%, 78.52%, 69.47%, and 67.05%, respectively. The results show an increase of 2.14% in $F$ -measure in comparison with the current state-of-the-art (SOTA) models for this dataset.
Past and Future Land Use/Land Cover Changes in the Ethiopian Fincha Sub-Basin

The increasing human pressure on African regions is recognizable when looking at Land Use Land Cover (LULC) change maps, generally derived from satellite imagery. Using the Ethiopian Fincha watershed as a case study, the present work focuses on (i) identifying historical LULC change in the period 1989–2019; (ii) estimating LULC in the next thirty years, combining Geographical Information Systems (GIS) with Land Change Modelling (LCM). Landsat 5/8 images were combined with field evidence to map LULC in three reference years (1989, 2004, 2019), while the Multi-Layer Markov Chain (MPL-MC) model of LCM was applied to forecast LULC in 2030, 2040, and 2050. The watershed was classified into six classes: waterbody, grass/swamp, built-up, agriculture; forest; and shrub. The results have shown that, in the past 30 years, the Fincha watershed experienced a reduction in forest and shrubs of about −40% and −13%, respectively, mainly due to ever-increasing agricultural activities, and such a trend is also expected in the future. In fact, for the period 2019–2050, LCM simulated a significant decrease in both forest and shrubs (around −70% and −20%, respectively), in favor of more areas covered by grass (19%) and built-up (20%). It is worth noting that a decrease in natural forests can drive an increase in soil erosion, fostering siltation in the water reservoirs located in the sub-basin. The study pointed out the urgency of taking actions in the sub-basin to counteract such changes, which can eventually lead to a less sustainable environment.
Experimental Methodologies for the Obtainment of Momordica charantia L. Extracts with Anthelminth Activity: A Review

Currently, the therapeutic alternatives available for the treatment of helminthiases are restricted to a low number of synthetic drugs that are classically used on a large scale, thus causing the resistance of several parasites. Seeking to optimize this problem, and often because it is the only option in low-income populations, the use of medicinal plants against parasites is the subject of several studies. Momordica charantia L. is a plant species with notorious pharmacological activities described in the literature, among which the anthelmintic activity stands out, which is mainly associated with the presence of saponins, tannins, flavonoids and alkaloids. The optimization of extractive processes through the most suitable choice of solvents and also the best methodology helps directly in obtaining rich fractions of the compounds of interest, as well as in a better yield of the extract to be used in pharmaceutical forms. Techniques that employ speed in execution, and even those that result in longer contact time between drug: solvent are reported here, as well as the use of solvents ranging from water to the most nonpolar organic compounds. The designation of a specific marker for quality control purposes is also an important factor and, as much as the plant species have a variety of constituents, the selection of a standard such as quercetin has been observed as the most common in the use of techniques such as chromatography and mass spectrometry.
Distribution and Morphological Characteristics of Oligodendrocytes in Selected Areas of the Brain of Male and Female Red Kangaroos (Macropus rufus)

This study was carried out on six adult red kangaroos of both sexes. To determine the location of the oligodendrocytes (OLGs) of the hippocampus (Hip) and corpus callosum (CC), the method of impregnation of the neuroglia with silver salts was applied. The iron distribution in the OLGs was determined by the histochemical method. The Nissl method was used to determine the location of the brain structure and to analyze the number of OLGs. In the Hip, these cells are located one beside another, mainly in blood vessels and neurons; in the neocortex (NC), they are located in layers I–VI; and in the CC, they are arranged in characteristic rows and accompany both nerve fibers and blood vessels. The analysis of the results obtained by the chosen methods in the Hip, NC, and CC in males and females did not show statistically significant differences in the distribution and location of the red kangaroo OLGs. The involvement of these cells is a physiological process that proceeds in a similar manner throughout the life of individuals and actively influences the metabolism of neurons and myelin.
Effect of Feature Engineering Technique for Determining Vegetation Density

—Vegetation density is one type of information collected from vegetation cover. Vegetation density influences evapotranspiration in terrain, which is essential in assessing how vulnerable peatlands are to fire. The Keetch and Byram Drought Index model, which evaluates peatland fire vulnerability, divides vegetation density into heavily grazed, softly grazed, and un-grazed. Manual approaches for analyzing vegetation density in the field, on the other hand, need a significant amount of resources. Image data acquisition, pre-processing, feature extraction, classification, feature selection, classification, and validation are all computer vision approaches used to solve these problems. Artificial intelligence algorithms and machine learning approaches promise outstanding accuracy in modern computer vision research. However, in the classification process, the impact of feature extraction is critical. Pattern identification at Back Propagation Neural Network (BPNN) is problematic because the feature extraction dimension is excessively complicated. The solution to this problem is using the feature engineering technique to choose the characteristics. This research aims to explore how feature engineering influences the accuracy of results. According to the statistics, implementing the recommended strategy can increase accuracy by 1% and increase kappa by 1.5%. This increase in vegetation density classification accuracy might help detect peatland vulnerability sooner. The novel aspect of this paper is that, after feature extraction, a feature engineering strategy is used in the machine learning classification stage to reduce the number of complex dimensions.
Academic development through a collective approach – introducing peer observation of teaching in a multidisciplinary faculty

Peer observation of teaching is seen as a significant feature of professional development in higher education, aiming to improve teaching and learning. This qualitative case study explores how peer observation can be introduced at a multidisciplinary faculty with STEM and business educations, identifying opportunities and challenges experienced when colleagues participate in peer observation. A peer observation project was launched as part of implementing the faculty strategy to enhance educational quality and led by the vice-dean of education at the faculty. A stepwise protocol focusing on planning, classroom management and self-reflection was used to help organize the cooperation. Twelve academics participated, all were observed during teaching, and all acted as an observer. Semi-structured interviews with four participants and a summary from the closing meeting of the project, showed that peer observation enhanced the educational discourse with their significant colleagues and enabled to accentuate teaching as a collective approach. The findings of this study indicate the potential of peer observation of teaching. Experience was gained on how education leaders can approach the task of introducing peer observation of teaching as a practice in a multidisciplinary faculty, overcoming barriers to participation such as lack of time and fear of being observed, and enabling a real step away from teaching as a private enterprise towards teaching as acollective approach for faculty development.
Dyeing of Silk through Iron Ion-Induced Formation of Hydrophobic Lignin Coatings

ABSTRACT There is a continuous demand for a specific type of Chinese silk fabric, which is one of China’s national intangible cultural heritage items called Xiang-Yun-Sha. Xiang-Yun-Sha is silk fabric dyed using the vegetable dyes from a yam and the mud from the Pearl Delta River. The ingenious and sophisticated dyeing process inspires us to explore new dyes for silk. Through learning from the traditional mud dyeing process of Xiang-Yun-Sha, especially the contents of the mud, lignin and iron species are recognized as key factors. Yet little attention has been dedicated to lignin as a dye despite its wide applications. In this study, the feasibility of using lignin to dye silk is investigated using sodium lignosulfonate and alkaline lignin as model systems. Thanks to their advantageous polyphenolic features, such as stacking tendency and ability to form stable complexes with iron ions, lignin-related compounds show excellent performance in serving as dyes by themselves, as well as protective coatings for other dyes; the dyed silk fabric could inherit anti-ultraviolet property from lignin. Considering that iron is inexpensive and that leftover lignin is a vastly underutilized biomass resource, this study offers a promising strategy to exploit the enormous potential of these naturally occurring materials by developing high value-added products.
Arabic Image Captioning: The Effect of Text Pre-processing on the Attention Weights and the BLEU-N Scores

—Image captioning using deep neural networks has recently gained increasing attention, mostly for English langue, with only few studies in other languages. Good image captioning model is required to automatically generate sensible, syntactically and semantically correct captions, which in turn requires good models for both computer vision and natural language processing. The process is more challenging in case of data scarcity, and languages with complex morphological structures like the Arabic language. This was the reason why only limited number of studies have been published for Arabic image captioning, compared to those of English language. In this paper, an efficient deep learning model for Arabic image captioning has been proposed. In addition, the effect of using different text pre-processing methods on the obtained BLEU-N scores and the quality of generated images, as well as the attention mechanism behavior were investigated. Furthermore, the “THUMB” framework to assess the quality of the generated captions is used -for the first time- for Arabic captions’ evaluation. As shown in the results, a BLEU-4 score of 27.12, has been achieved, which is the highest obtained results so far, for Arabic image captioning. In addition, the best THUMB scores were obtained, compared to previously published results on common images.
Coherent control and manipulation of classical or quantum light via nonlocal effects

The thesis is devoted to the theoretical studies of coherent control and manipulation of classical or quantum light via nonlocal effects. At the classical level, controllable light propagation dynamics in the paraxial regime is investigated. The specific type of nonlocal linear effects induced in thermal atomic vapor is explored to achieve diffraction-less and lossless propagation, uniform phase modulation, and frequency conversion with diffractionless image duplication for laser beams with arbitrarily encoded spatial profiles. Next, the study is extended to investigate propagation dynamics in the presence of nonlocal nonlinear effects generated in thermal interacting Rydberg atoms, which mainly reveals simultaneous competition between the nonlocal nonlinear absorption and the modulational instability for each wave component. Moreover, parity-time (PT) sym- metric dynamics in cold Rydberg atoms are exploited, and it is shown that a phase transition from unbroken to broken PT symmetry can be induced by nonlocal nonlinear effects. At the quantum level, it is further proposed to test the quantum nonlocality of single x-ray photons in a system where very weak x-ray pulses interact with 57 Fe nuclei in a thin cavity, such that a Bell-like inequality in the single-photon version is violated. All these proposals are feasible in current experimental settings.
Trends in the interest in COVID-19 news of the local media and their readers: The case of Spain

The COVID-19 has caused not just an unprecedented sanitary crisis but a social crisis, which has affected, among many other fields, the local journalism, which had to adapt to meet the public’s information needs about coronavirus. In this study we analyzed the evolution of local news about COVID-19 in Spain throughout the pandemic by examining local news articles in social media. Using a unique dataset of over 230k Facebook posts published by Spanish local media organizations during 2020 and 2021, we found evidence that the interest of local media in COVID-19, measured as the proportion of the news related to COVID-19, changed as the pandemic evolved. Our results also show that the interest that local media readers had in COVID-19, measured as the proportion Facebook interactions related to COVID-19, was even higher, and also evolved during the pandemic. Although the interest in COVID-19 of local media and their readers essentially progressed in parallel, we also identified some periods in which they behaved differently. While a fatigue with COVID-19 related news would be expected after 2 years of pandemic, a clear decrease of interest was not observed neither in journalists nor in readers.
Fabric wrinkle rating model based on ResNet18 and optimized random vector functional-link network

To improve the accuracy and efficiency of the objective evaluation of the fabric wrinkle model, the R18-COTSA-RVFL model is proposed in this paper. The fabric wrinkle rating model is based on the combination of ResNet18 (R18) and the enhanced random vector functional-link network, in which the enhanced random vector functional-link network replaces the Softmax layer of ResNet18. This model uses ResNet18 (R18) to extract features from wrinkled images. In addition, a random vector functional-link network model improved by the tunicate swarm algorithm was proposed for wrinkle-level classification. First, we used chaotic-logistic maps and opposition-based learning to optimize the initial population of the tunicate swarm algorithm. The proposed search agent fragment mapping method enables the tunicate swarm algorithm simultaneously to optimize the hidden layer node parameters and bias, input layer weight, and activation function of the random vector functional-link network, thus avoiding the inaccurate classification result caused by random parameter selection in the random vector functional-link network. From comparative experiments, the proposed R18-COTSA-RVFL has the highest average classification accuracy and stability.