Miracle-dz/UniFAR-FTUs huggingface dataset:
Plastid phylogenomics provides novel insights into the infrafamilial relationship of Polypodiaceae

The polygrammoids (Polypodiaceae) are the most species‐rich and diversified epiphytic fern lineages, and hold an important role to understand the deep diverging events and rapid adaptation to changing environments in the plant tree of life. Despite progress in the phylogeny of this group of ferns in previous multilocus phylogenetic studies, uncertainty remains especially in backbone relationships among closely related clades, and the phylogenetic placement of recalcitrant species or lineages. Here, we investigated the deep phylogenetic relationships within Polypodiaceae by sampling all major lineages and using 81 plastid genomes (plastomes), of which 70 plastomes were newly sequenced with high‐throughput sequencing technology. Based on parsimony, maximum‐likelihood, Bayesian and multispecies coalescent analyses of genome skimming data, we achieved a better resolution of the backbone phylogeny of Polypodiaceae. Using simulated data matrices, we detected that potential phylogenetic artefacts, such as long‐branch attraction and insufficient taxonomic sampling, may have a confounding impact on the incongruence of phylogenetic inferences. Furthermore, our phylogenetic analyses offer greater resolution than previous multilocus studies, providing a robust framework for future phylogenetic implications on the subfamilial taxonomy of Polypodiaceae. Our phylogenomic study not only demonstrates the advantage of a character‐rich plastome dataset for resolving the recalcitrant lineages that have undergone rapid radiation, but also sheds new light on integrative explorations understanding the evolutionary history of large fern groups in the genomic era.
Paying the widening participation penalty: Racial and ethnic minority students and mental health in British universities

Racial and ethnic minority (REM) students are more likely to experience poor mental health than their White peers yet are less likely to seek help from university counseling services. In attempting to explain this puzzle, the role of environmental factors are rarely explored, despite evidence which suggests that the university environment is itself a major factor. Here, I take a qualitative paired comparison approach to examine the influence of the university environment on the mental health and help‐seeking attitudes of REM undergraduate students, evaluating their experiences at a Russell Group university (RGU) with low REM participation and a neighboring non‐Russell Group university with high REM participation. While both universities declared a commitment to widen participation and promote inclusion for REM individuals, semi‐structured interviews with 48 REM students reveal that feelings of isolation and the experience of discrimination were heightened at the RGU. However, students at both universities described having to navigate a “minefield” of racial microaggressions and “othering. ” Further, these environmental pressures are compounded by personal factors (i.e., prior help‐seeking experiences, cultural norms, and family pressures). Together, these factors largely influence both their mental health and their help‐seeking attitudes. I argue that these factors create a widening participation penalty for REM students and suggest that support for these students must go beyond initial acts of increasing diversity on campus (for example, through Widening Participation schemes). Rather, efforts should focus on addressing and reforming the institutional environments and behaviors that hinder university campuses from becoming truly inclusive and mentally healthy environments.
Hysteresis loss of ultra-large off-the-road tire rubber compounds based on operating conditions at mine sites

The objective of this study is to investigate the hysteresis loss of ultra-large off-the-road (OTR) tire rubber compounds based on typical operating conditions at mine sites. Cyclic tensile tests were conducted on tread and sidewall compounds at six strain levels ranging from 10% to 100%, eight strain rates from 10% to 500% s−1 and 14 rubber temperatures from −30°C to 100°C. The test results showed that a large strain level (e.g. 100%) increased the hysteresis loss of tire rubber compounds considerably. Hysteresis loss of tire rubber compounds increased with a rise of strain rates, and the increasing rates became greater at large strain levels (e.g. 100%). Moreover, a rise of rubber temperatures caused a decrease in hysteresis loss; however, the decrease became less significant when the rubber temperatures were above 10°C. Compared with tread compounds, sidewall compounds showed greater hysteresis loss values and more rapid increases in hysteresis loss with the rising strain rate.
Amidoxime-functionalized bead cellulose for the decomposition of highly toxic organophosphates

Regenerated bead cellulose is a promising material with excellent mechanical and rheological properties, ideally suited for advanced environmental applications. By introducing the amidoxime functional group into the glucose unit at the C-6 position, highly effective reactive sorbent was prepared and used to destroy priority hazardous substances such as organophosphate pesticides or nerve-paralytic chemical warfare agents (CWAs). Quantum mechanical (QM) calculations were performed to study the interactions of organophosphates with amidoxime functional groups at the molecular level. It was found that the energetic reaction barrier of the rate-limiting step is markedly reduced (from 31.40 to 11.37 kcal mol−1) in the case of the amidoxime-catalysed degradation of parathion methyl, which resulted in a dramatic increase in the degradation rate; this was fully confirmed by experiments, in which the pesticide degradation proceeded at the time scale of several hours (t1/2 = 20–30 hours at pH 7.22).
Teacher Technology Uptake in Indonesian EFL Classes

Technology is becoming increasingly integrated into teaching environments in terms of enhancing students' engagement and facilitating teaching. Technology as one of the important tools in helping the success of 21st-century learning requires students to use it appropriately in accessing information. Equally important is that teachers are expected to be more adept at empowering technology in classroom learning. This paper reveals the results of a study investigating EFL teachers’ computer and internet use as an aid to teaching and their reasons for integrating or ignoring technology use when teaching. This study involved 50 English teachers who teach in Junior (JHS) and senior high schools (SHS) in one province in Indonesia. The data were collected through questionnaires containing statements related to the teachers’ computer and the internet use in teaching and follow-up Focus Group Interviews (FGI) to explore their reasons for integrating or ignoring the technology use when teaching. Conclusions and suggestions are then presented for EFL teaching using technology and further research as well.
YOUNG GENERATION AND ENVIRONMENTAL FRIENDLY AWARENESS: DOES IT THE IMPACT OF GREEN ADVERTISING?

The environmental issues nowadays have make consumers becoming more selective in selecting products and brands going to use. The purpose of this study is to investigate the effect of green advertising on green purchase intentions mediated by green attitude awareness in the young generation. Young generation has strong curiosity and has easier access on getting products information, so this research focuses deeper on examining how much green advertising, green knowledge, and eco-label information affect the awareness on green attitude which later influences green intention to purchase. This research used primary data obtained from questionnaires distributed directly to 150 undergraduate students of universities in Indonesia. We used Structural Equation Modeling (SEM) for verifying hypothesis and AMOS 20 software for getting empirical results of 16 items questions representing indicator of 4 variables. The result showed that green advertising and green knowledge were able to form the awareness on environmental friendly. Although eco-label information did not influence the awareness on green attitude, it influenced the green purchase intention directly.
User Behavior Analysis Based on Stacked Autoencoder and Clustering in Complex Power Grid Environment

Analyzing user behavior characteristics in a complex power grid environment is essential for user behavior planning and resource coordination optimization. Traditional user behavior analysis methods based on model-driven and causal analysis have the disadvantages of strong subjectivity and physical models that are difficult to deal with the randomness and uncertainty of user behavior in complex grid environments. In this paper, we use unsupervised learning methods to analyze user behavior in complex power grid environments, and propose user behavior analysis methods based on stacked autoencoder and clustering. We first reduce the complexity of user behavior data by proposing adaptive feature selection algorithm of user behavior based on stacked autoencoder and unsupervised learning (AFS-SAEUL). Finally, we build a user behavior analysis model based on adaptive feature selection and improved clustering (UBA-AFSIC). The model improved the performance of unsupervised classification of user behavior by fusing the adaptive generation strategy of the initial cluster centers. The simulation experiment results on two real electricity datasets and one public electric vehicle charging dataset show that compared with the existing feature selection algorithm and clustering algorithm, the algorithms proposed in this paper have higher feature selection rate and better clustering performance.
Regeneration of submediterranean species Euonymus latifolius (L.) Mill. at its southernmost limit in Europe

Due to the ongoing effects of climate change in the Mediterranean (increasing temperature and decreasing rainfall), conditions for Submediterranean species are disappearing as their habitats are dwindling. We have focused on Euonymus latifolius (L.) Mill. , a nemoral-Submediterranean species, at its southernmost populations of Europe. The aim was to evaluate the population structure and regeneration niche of the species at microhabitat scale. We selected five larger populations among the 13 existing ones, marking 25-30 individuals per population. We measured twice: height, width, vegetation cover, survival, soil moisture and temperature.As result, we provided data of the 13 existing populations, containing 93 adults and 350 juveniles. Moreover, we have obtained a very skew population structure with a low number of recruits for five selected populations, especially at smaller populations. Most E. latifolius juveniles were encountered under dense tree canopy (more than 80 % in cover) formed by a mixture of Submediterranean and Mediterranean species. Biovolume per population showed significant differences among the main populations CP and CV, presenting this last a higher recruitment, while recruitment was very low in general. For soil parameters, we found a critical role of canopy, which showed a positive effect on juvenile microhabitat (higher moisture and lower soil temperature). The results showed us the critical situation of the species, with very fragmented populations, low number of individuals, and scattered spatial patterns of individuals within the populations. Also, survival problems, a non-balance demographic structure, and regeneration problems were detected. Finally, we propose a sere of conservation measures, from monitoring to active measures (key tree species plantation, reintroduction, reinforcements), combined with threat control (herbivory, pests, and impact from outdoor activities). All combined may help to preserve this species at its southernmost populations.
Precipitation over southern Africa: Is there consensus among GCMs, RCMs and observational data?

Abstract. The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modelling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behaviour of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (Oct–Mar), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP5 ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensemble exhibited improved performance compared to its forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher resolution regional climate simulations. The CMIP6 ensemble displayed a similar behaviour to CMIP5, however reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angolan Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic process that take place. Improvements in observational networks (both in-situ and satellite), as well as continued advancements in high-resolution modelling will be critical, in order to develop a robust assessment of climate change for southern Africa.
Couple resilience predicted marital satisfaction but not well-being and health for married couples in Bali, Indonesia

Throughout their marriage, couples face numerous adversities, with marital dissolution the ultimate threat. Couple resilience is defined as the process undertaken by couples to manage adversity through positive relationship behaviors. Previous studies on couple resilience have focused on negative relationship behaviors, but have not explored the interaction effect between the dyads. Three hundred couples living in Bali, Indonesia participated in this study by reporting their positive and negative relationship behaviors, and the expected outcomes of these (marital satisfaction, emotional wellbeing, and general health status). Model fit analysis showed that the relationship behaviors did not predict the outcomes and that there was no interaction effect between couples. Positive behaviors, however, showed a higher probability of predicting marital satisfaction, especially amongst wives. The implication of this finding leads to the practical suggestion for future couple resilience studies to conduct a multiphase longitudinal study with repeated measures of the outcomes.
Information Content Carried by Brain Signals Reduces Differentially in MCS and UWS Patients

Objective: Human consciousness is thought to depend on information integration in the brain. How brain injuries affect the information content carried by signals of brain imaging modalities in patients with consciousness disorders has received little attention. Here we propose a novel approach to quantify changes of regional information content in the brain by assessing the entropy delineated by the principal components of regional voxel-based functional imaging signals in clinical MCS and UWS patients.Method: Resting-state functional imaging was performed in 23 MCS patients, 31 UWS patients, and 20 age-matched healthy individuals. Results: We show that, as the symptoms of DOC deepen from MCS to UWS, regional information content also was significantly reduced in that order in the sensory and memory systems of the brain. In contrast, with few exceptions, regional information content in high-order cognitive systems remained statistically at a level similar to those in healthy individuals in MCS patients and only showed a significant reduction in UWS patients. Conclusions and Significance: These findings provide, in the theoretical context of consciousness, novel evidence for a reduction of regional information content as a potential systems-level mechanism of consciousness disorder in MCS and UWS. Further, the findings reveal, for the first time, differential patterns of the reduction of information content in the sensory and memory compared with cognitive systems in MCS and UWS patients, consistent with the manifestations of clinical symptoms in the two DOC patient populations.
Cerous Fluoride Dopant‐Free Electron‐Selective Contact for Crystalline Silicon Solar Cells

Dopant‐free carrier‐selective contacts have drawn intensive attention for efficient crystalline silicon (c‐Si) photovoltaics due to the low‐temperature simple process and better carrier selectivity. By incorporating a thermally evaporated dielectric film cerium fluoride (CeF3) as the electron transport layer (ETL) between a c‐Si(n) and aluminum (Al) electrode, higher conversion efficiency of the crystalline silicon solar cell is obtained, which is 21.27% compared to 16.89% of a reference cell without CeF3. The insertion of an ultrathin CeF3 ETL helps in alleviating the strong Fermi‐level pinning at the interface, leading to better electron transport with a low contact resistivity of 10.96 mΩ cm2. The morphology and element distribution of the interface are also investigated by high‐resolution transmission electron microscopy (HRTEM). The primary results demonstrate that the utilization of kinds of lanthanide fluorides, including CeF3, offers a good choice for efficient and cost‐effective electron‐selective contacts for optical–electrical devices.
A LoRa-Based Multisensor IoT Platform for Agriculture Monitoring and Submersible Pump Control in a Water Bamboo Field

This paper presents a long-range (LoRa)-based Internet of Things (IoT) system that consists of a series of IoT units in the field, as well as several servers for agriculture monitoring and pump control in water bamboo fields. Four types of IoT units were developed in accordance with the application’s need based on LoRa technology. Front- and back-end servers were constructed for data delivery, storage, and visualization, forming a complete solution. Another key feature is making a traditional submersible pump programmable with one IoT unit attached to the magnetic contactor in the electricity distribution box. Moreover, this paper presents design details of the proposed system and field experiment results for function validation. This IoT system is the first step in our project of revealing the relationship between farming and environmental reaction. This makes proposing a new farming procedure possible in the future.
Cascaded model‐free predictive control for single‐phase boost power factor correction converters

Conventionally, the dual‐loop PI controllers are designed for the single‐phase boost power factor correction (PFC) converters operating under continuous conduction mode (CCM), which is not available to perform rapid adaptations to plant uncertainties caused by the different operation modes and the parameter variations. In order to improve the control performance and robustness, a cascaded model‐free predictive control (MFPC) scheme is proposed based on the unified ultra‐local model under CCM and discontinuous conduction mode (DCM) for the single‐phase boost power factor correctors. Different from the traditional sluggish PI controllers, the proposed control law is adaptive to the operation mode and sudden variations with the algebraic identification technique, thus providing high‐quality line current and fast dynamic characteristic for the full power operating range. Comparative simulations and experiments with PI control scheme are provided to certificate the effectiveness of the proposed control scheme.
Extensible, Extendable, Expandable, Extractable: The 4E Design Approach for Reconfigurable Displays

ABSTRACT We introduce “4E,” a new design approach of reconfigurable displays that can change their form factors by capitalizing on four quality properties inspired by applied material: extensibility, extendability, expandability, and extractability. This approach is applicable to both fixed and portable displays. We define and exemplify each property, highlighting the key differences in how reconfigurable displays can change their form factors to accommodate more screen real estate for more users, applications, and functionality. To demonstrate the 4E approach, we conduct a targeted literature review and introduce E3Screen, a prototype that enhances any flat screen (e.g., of a tablet, laptop, monitor) with two slidable, rotatable, and foldable lateral displays. We report results from a controlled experiment with participants, conducted to collect, analyze, and understand end users’ preferences for display configurations permitted by the extendability, expandability, and extractability of E3Screen. Our results structure future research and development in reconfigurable displays and multi-display collaborative workspaces.
A Deep Reinforcement Learning Approach for the Energy-Aimed Train Timetable Rescheduling Problem Under Disturbances

At metro stations with very large passenger volumes and severe congestion, random disturbances often occur, resulting in the original offline optimal timetable no longer applicable. Deep reinforcement learning has the advantages of self-learning and online learning, making it possible to solve the energy-aimed train timetable rescheduling (ETTR) problem under random disturbances. In this article, a deep reinforcement learning approach (DRLA) has been proposed and applied to the ETTR problem to reschedule the train timetable in order to achieve the online optimal timetable for the minimum energy usage under disturbances. The proposed DRLA has the advantages of a real-time performance, high learning efficiency, and better energy-saving effect compared with the traditional heuristic algorithms such as genetic algorithm (GA), deep learning methods such as the combination of improved GA and long short-term memory (IGSA-LSTM), or other reinforcement learning algorithms such as deep deterministic policy gradient (DDPG) algorithm. Various experiments are conducted to compare the performance of DRLA and other algorithms. The experimental results indicate that in the two-train metro system and the five-train metro system, DRLA can save an average of energy by 5.11% and 7.29% with an average reaction time of only 0.0013 and 0.0019 s against disturbances, respectively.
Global dynamics for a non-smooth Filippov system with the threshold strategy

In this study, the Leslie-Gower model with functional response is extended into a non-smooth Filippov system by applying IPM strategies. Once the number of pests reaches or surpasses the given economic threshold(ET), spraying pesticides and releasing the natural enemy are implemented simultaneously. In order to maintain the pest population at or below ET, global dynamics of the proposed model are investigated completely, including the existence of sliding mode and various equilibria, sliding dynamics and global stability of equilibria. The result shows that real equilibrium cannot coexist with the unique pseudo-equilibrium. In particular, after excluding the existence of any possible limit cycle, the global stability of equilibria is obtained by employing qualitative and numerical techniques. In the end, the effect of our work on pest control are discussed.