Miracle-dz/UniFAR-FTUs huggingface dataset:
Teachers’ and Students’ Perceptions of the Socio-Scientific Issues (SSI)-based Electronic Student Worksheets for Improving Scientific Literacy and Collaboration Skills

Abstract. The purpose of this study was to analyze and explain Teacher and Student Perceptions in Learning Using SSI-based electronic student worksheets in improving scientific literacy and collaboration skills. The research method is descriptive method. The population in this study were ten junior high school teachers and one hundred junior high school students from ten different schools. Data collection using questionnaires and data analysis techniques using percentages. The results showed that the teacher's perception of learning using SSI-based electronic student worksheets in the implementation aspect was in the very low category, because teachers still used conventional worksheets and books. Teachers' perceptions of aspects of scientific literacy are still low, but teachers have tried to apply them in learning. Furthermore, teachers' perceptions about student collaboration are in the "low" category. Students' perceptions of aspects of the SSI-based electronic Student Worksheet learning science literacy and collaboration skills are still very low. Then the percentage of student needs in using SSI-based electronic Student Worksheets in learning is in the "high" category. It can be concluded that the use of SSI-based electronic Student Worksheets can improve scientific literacy and student collaboration skills.
Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects

Although interaction effects can be exploited to improve predictions and allow for valuable insights into covariate interplay, they are given little attention in analysis. We introduce interaction forests, which are a variant of random forests for categorical, continuous, and survival outcomes, explicitly considering quantitative and qualitative interaction effects in bivariable splits performed by the trees constituting the forests. The new effect importance measure (EIM) associated with interaction forests allows ranking of the covariate pairs with respect to their interaction effects' importance for prediction. Using EIM, separate importance value lists for univariable effects, quantitative interaction effects, and qualitative interaction effects are obtained. In the spirit of interpretable machine learning, the bivariable split types of interaction forests target well interpretable interaction effects that are easy to communicate. To learn about the nature of the interplay between identified interacting covariate pairs it is convenient to visualise their estimated bivariable influence. We provide functions that perform this task in the R package diversityForest that implements interaction forests. In a large-scale empirical study using 220 data sets, the prediction performance of interaction forest was statistically significantly better than that of conventional random forests and competing random forest variants that use multivariable splitting. In a simulation study, EIM delivered considerably better rankings for the relevant quantitative and qualitative interaction effects than competing approaches. These results indicate that interaction forests are suitable tools for identifying and making use of well interpretable interaction effects in predictive modelling.
PA-GAN: Graph Attention Network for Preference-Aware Social Recommendation

Social recommendation has been recently proposed by incorporating trust relationship to alleviate data-sparsity and cold-start problems. However, most of existing works only focus on friends different contribution to model user representation. They ignore users have different preference on items, and share different preference with friends. To address these problems, in this paper, we propose a novel Preference-Aware Graph Attention Network (PA-GAN) for trust recommendation. And we design three modules: item aggregation for user, friend-preference aggregation for user and user aggregation for item to model users’ local and global preference. Experiments on two publicly available datasets shows the proposed model PA-GAN outperforms the state-of-the-art recommendation models, and improves performance greatly.
Development of Genomic Resources From Crossostephium Chinense (Asteraceae) Based on Genome Skimming Data

Crossostephium chinense is a traditional Chinese medicinal herb and it is often cultivated as an ornamental plant. Previous studies on this species mainly focused on its chemical composition and it was represented rarely and marginally in genetic studies, which limited knowledge about its genetic background, and thus genomic resources remain scarce. To develop both chloroplast and nuclear polymorphic microsatellites for C. chinense, potential microsatellites were screened from genome skimming data of two individuals of C. chinense. Sixty-four and 63 cpSSR markers were identified from two chloroplast genomes of C. chinense. This study performed for the first-ever study on employment of genome skimming data and CandiSSR, consequently a total of 133 polymorphic nSSRs were developed. Ten nSSRs were randomly selected to test their transferability across 35 individuals from three populations of C. chinense, and 20 individuals each of Artemisia stolonifera and A. argyi. Cross-amplifications were successful done for C. chinense, and were partially successful amplified for both Artemisia species. The number of alleles varied from two to nine. The observed heterozygosity and expected heterozygosity per locus ranged from 0.000 to 0.286 and from 0.029 to 0.755, respectively. These genomic resources will be valuable for population genetics and conservation studies in C. chinense and Artemisia.
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow

Abstract Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO3) and iodine (I2). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m2 kg−1) and densities (135–463 kg m−3) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m−1 per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters.
“Brave New World” of Fake News: How It Works

The spread of fake news poses a serious threat to democracy and journalism. Fake news has found the ideal tools to thrive in the digital world. Therefore, it is urgent to understand this phenomenon. The purpose of this review is to analyse the various stages of the fake news circuit, in order to clarify the phenomenon, its causes and processes, identifying the various routes for spreading fake news, the reasons behind its manufacture and the factors that contribute to its rapid proliferation and success. Our results showed that the problem is not just social media, but the entire digital and technological universe, as well as user behaviour. On the one hand, programmatic web advertising, coupled with ideological motivations, remains an incentive for the creation of fake news. On the other hand, malicious bots and bad algorithms (initially created with good intentions) are being the great allies of fake news, promoting the creation of filter bubbles and echo chambers. In addition, literature has shown that filter bubbles are created not only by bad algorithms, but also by users who are unaware of how the algorithms work and prefer to consume information according to their beliefs, limiting themselves to a closed view.
Mapping incentives for sustainable water use: global potential, local pathways

Competition for freshwater resources is intensifying water scarcity and its impacts on people, economies, and the environment, posing a growing challenge for sustainable development. Meeting these challenges will require incentives to encourage sustainable water use. Prior calls to shift from supply-driven solutions to a soft path of demand management (pricing, markets, behavioral changes) have encountered stubborn obstacles. We undertake a multi-scale assessment of water reallocation and investment in water conservation technologies to understand their potential and limits for addressing different drivers of water scarcity. Our model identifies what drives water scarcity at the subbasin scale, and examines two prominent responses to these drivers. Our analysis distinguishes different types of water scarcity based on the demands for water and their timing, creating nine (9) categories of water competition, which can overlap. Water demand within agriculture contributes to scarcity in 94% of the basins experiencing scarcity, concentrated in central USA, Spain, and India. Urbanization has led to competition between cities and agriculture in 1,596 of 3,057 subbasins (52%). We examine how different institutional mechanisms (incentive-based water reallocation) and technologies (investment in water conservation technologies) can address these different types of water scarcity. This study builds on several local and high-resolution models demonstrating the potential to increase the economic efficiency (and marginal productivity) of water use. The gap between potential and implementation is high, however. Efforts to bridge this gap in priority geographies can link modelling advances with the design of pathways that combine incentives with robust water accounting, caps on water extraction, and enforcement capacity at multiple scales.
Pregnancy complicated by neurological and neurosurgical conditions – The evidence regarding mode of delivery

Neurological and neurosurgical conditions complicating pregnancy may precipitate considerable concern regarding the risk of complications, and uncertainty regarding the preferred mode of delivery and anaesthesia. Caesarean section is known to be associated with significantly increased risk of adverse maternal outcomes compared with vaginal delivery in healthy pregnancy. Nevertheless, a common perception exists among the general population and some health professionals that caesarean section is safer for the mother and baby in high-risk pregnancies. This manuscript examines the literature regarding the risks and outcomes related to mode of delivery in pregnancy complicated by disorders of the central nervous system. With the exception of women with raised intracranial pressure, and some women with Von Hippel-Lindau syndrome, the available evidence suggests that the mode of delivery should be based upon obstetric indications.
THE EFFECT OF DHIKR ON ANXIETY AND DEPRESSION LEVEL IN HEMODIALYSIS PATIENTS AT PURWOKERTO ISLAMIC HOSPITAL

Hemodialysis is a routinely performed therapy on chronic kidney patients, leading to psychological problems among subjects who undergo hemodialysis, such as anxiety and depression. One of the efforts to overcome anxiety and depression is with the dhikr intervention. Dhikr presents hearts to remember and be obedient to Allah followed by the words and actions in various conditions. Discover dhikr's influence on the level of anxiety and depression in patients on hemodialysis in Purwokerto Islamic Hospital. It was a quantitative study using quasi experiment with a non-quivalent control group design. The number of samples was 12 subjects consisting of 6 subjects in the control group and six subjects in the intervention group with the purposive sampling technique. Instruments were used to measure anxiety and depression are the HADS ( Hospital Anxiety and Depression Scale ) before and after dhikr intervention as much as 12 times. Research is carried out in Hemodialysis Unit of Purwokerto Islamic Hospital. Test statistics on research are used paired t-test and independent t-tests. This study showed a decrease in the mean level of anxiety from 5, 83 to 1.67 in the experimental group ( p = 0.003). The mean level of depression experienced a decline of 9, 67 becomes 4.67 on a group experiment ( p = 0.003). Dhikr reduces the level of anxiety and depression in hemodialysis patients at the Purwokerto Islamic Hospital.
Interpretable Deep Learning for the Earth System with Fractal Nets

Our confidence in the projections made by Earth System Models (ESMs) depends on understanding them to be, in some important respects, faithful representations of the Earth system. Here we present an “explainable Artificial Intelligence (AI)” method that allows us to uncover the dynamical structure of the observed and modeled Earth system, discover hidden links across wide spatiotemporal scales, target model development efforts at poorly-represented dynamics
A Pathway to Technology Integration: Eliciting Consumer’s Behavioural Intention to Use Paytm Services

The present study integrates the technology acceptance model (TAM) and the innovation diffusion theory (IDT) for analysing consumers’ intention to make use of Paytm services. It is a cross-sectional study; the data was gathered from 259 Internet consumers. The statistical tools, including structural equation modelling (SEM), are applied to understand the inter-construct relationships. The intention to use Paytm is positively influenced by a perceived ease of use, perceived usefulness and social influence. Moreover, the moderating effects of perceived risk (PR) are found to be significant on the associations among social influence, perceived ease of use and Paytm usage intentions. This study will help digital wallet service providers (DWSP), who focus on identifying the important factors for accelerating the use of mobile wallets. The findings will also facilitate the government to devise ways for augmenting cashless fund movement in the economy. Besides explaining the phenomenon of Paytm usage intentions, the study reveals the moderating role of PR with respect to various antecedents, thereby filling the gap in the existing literature.
Removal and recovery of organic solvents from aqueous waste mixtures by extractive and pressure swing distillation

Different scenarios for handling wastewaters of different concentrations containing acetone and methanol (in equimolar quantities) in order to remove and/or recover organic components are investigated by rigorous simulation. The extractive and pressure swing distillation processes are optimized by genetic algorithm (GA). The different alternatives including incineration of the whole amount of waste are compared on the basis of the capital, operation, and total annual costs. The influence of the water content of the waste mixture is also investigated. The best results are obtained with the separation of the whole quantity of the waste mixture into specified purity products by extractive distillation. The results obtained for pressure swing distillation with heat integration remained only slightly under those of the extractive distillation.
Understanding the psychological aspects of the radicalisation process: a sociocognitive approach

Abstract Understanding the psychological dimensions underlying the radicalisation process is a considerable challenge in the context of the legal judicial treatment of perpetrators of acts of radical violence. This clinical and qualitative study is based on an analysis of legal expert interviews of people at different stages of the radicalisation process. It highlights common psychological characteristics in personality, mechanisms of moral neutralisation and sociocognitive and interpretive treatment during radicalisation. These observations suggest the applicability of a model of cognitive–emotional transformation of self and meaning-building in radical violent engagement.
Beyond refueling: Investigating the diversity of functions of migratory stopover events

ABSTRACT Stopovers comprise a significant proportion of the time that many birds spend migrating, and researchers have long relied on these events to define and classify broader migratory strategies. Analyses of stopovers often assume that individuals stop primarily or exclusively in order to replenish energy stores, but other non-fueling behaviors have also been described during stopover events and can influence stopover incidence and duration. Here, we discuss the growing demand for understanding these non-fueling behaviors and for restoring the inherent behavioral complexity to stopover events. We begin by describing how light-weight tracking technologies allow researchers to follow individuals along their entire migratory journeys, capturing stopovers that controvert the traditional stop–refuel–resume paradigm. We then discuss 5 well-identified non-fueling behaviors—recovering, sleeping, waiting, information gathering, and social interactions—and examine how including these behaviors can alter interpretations of individual movement paths. Finally, we outline emerging directions for identifying these behaviors and look to larger implications for population management and site conservation along migratory flyways. LAY SUMMARY Many birds make stops during their migratory journeys, and they may have various reasons for stopping. In the past, researchers have investigated the role of energy stores in stopping decisions, but birds may also need to stop or prolong their time at a stopping site in order to recover from bodily stress, catch up on lost sleep, wait for travel conditions to improve, or reconvene with other migrants. Non-fueling behaviors have been more difficult to study, but novel approaches that combine individual movement data with information about ecological and physiological conditions along the way are offering insights into when and where they occur. Investigating non-fueling stopping behaviors can reveal a more complex story about how birds navigate the challenges of seasonal migration.
Chaos control of small-scale UAV helicopter based on high order differential feedback controller

ABSTRACT The small-scale unmanned aerial vehicle (UAV) helicopter has a complex structure, strong nonlinearity, coupling and open-loop instability, making it shake violently and even produce chaotic oscillation under wind disturbances and improper configuration. The chaotic angular velocity dynamic model of the UAV helicopter is analysed via two cases. The sliding mode controller (SMC) relying on the linearised model, the PID controller, and the high order differential feedback controller (HODFC) not relying on the model are designed. The closed-loop system stability under both SMC and HODFC are analysed. The HODFC with a control filtering can actively reject the disturbance and uncertainty. The control performance of HODFC is superior to SMC and PID controllers. The SMC and HODFC can stabilise the chaotic oscillations of UAV helicopter’s angular velocity, whereas the PID controller fails, and the HODFC control effect is superior to the SMC for disturbance rejection, uncertainty and linearisation bias in steady-state errors.
Ecological specialization promotes diversity and diversification in the East Mediterranean genus Ricotia (Brassicaceae)

Despite its amazing biodiversity, the Eastern Mediterranean remains a highly understudied region especially when compared to the Western Mediterranean. Scarcity of such studies restrict our understanding of the processes shaping diversity across the entire Mediterranean. To this end we used a combination of molecular markers and presence/absence data from all species of the Eastern Mediterrranean genus Ricotia collected across its full geographic range to determine historical, ecological and evolutionary factors responsible for lineage-specific diversification in this genus. Network analysis based on nuclear ribosomal and chloroplast DNA revealed high genetic structure within all lineages and phylogenetic reconstructions based on the multispecies coalescent showed that within lineage diversification corresponded to the onset of the Mediterranean climate. Reconstruction of ancestral histories indicate the genus originated within Anatolia and slowly spread across the Eastern Mediterranean and Levant using the Taurus mountains. Ecological niche models based on climatic and environmental variables suggest local populations did not go through any major distributional shifts and have persisted in present day habitats since the LGM. Furthermore, niche differentiation tests revealed significant niche differences between closely related species and showed the main variables predicting species limits to be different for each species. Our results give crucial information on the patterns and processes shaping diversity in the Eastern Mediterranean and show the main factor promoting diversification to be local environmental dynamics and ecological specialization and not large scale latitudinal movements as often reported for southern Europe. By determining regional and global patterns of diversification in an eastern Mediterranean genus we further our understanding of the major trends influencing plant diversity in the Mediterranean basin as a whole.
Watching television in a home environment: effects on children’s attention, problem solving and comprehension

ABSTRACT Correlational studies have suggested some harmful effects of television viewing in early childhood, especially for the viewing of fast-paced entertainment programs. However, this has not been consistently supported by experimental studies, many of which have lacked ecological validity. The current study explores the effects of pace of program on the attention, problem solving and comprehension of 41 3- and 4-year-olds using an ecologically valid experimental design. Children were visited twice at home; on each visit they were shown an episode of a popular animated entertainment program which differed in pace: one faster paced, one slower paced. Children’s behavior was coded for attention and arousal during viewing, attention, and effort on a problem-solving task after viewing, and performance on unrelated (problem-solving) and related (program comprehension) tasks. The faster-paced program was attended to more, while 3-year-olds showed more attention and effort on the problem-solving task after watching the slower program, but there were no significant differences in performance on unrelated or related tasks depending on pace. The lack of differences observed in this naturalistic setting together with the high levels of comprehension of the programs watched provides some evidence to counter the “harm” perceived in young children watching fast-paced entertainment programs.