Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence, Distribution, and Genetic Diversity of Alfalfa (Medicago sativa L.) Viruses in Four Major Alfalfa-Producing Provinces of China

Alfalfa (Medicago sativa L.) is one of the most widely cultivated forage crops in the world. China is the second largest producer of alfalfa in terms of the planting area worldwide, with Gansu, Henan, Inner Mongolia, and Shaanxi provinces being the production hubs. Alfalfa viruses have been reported on a small-scale survey in some of these areas, but they have not been well characterized. In the present study, seven viruses were detected in 12 fields of 10 cities/counties of the four abovementioned provinces by high-throughput sequencing and assembly of small RNA. Their incidence, distribution, and genetic diversity were analyzed by enzyme-linked immunosorbent assay, polymerase chain reaction (PCR)/reverse transcription-PCR and clone sequencing. The results showed that alfalfa mosaic virus (AMV), pea streak virus (PeSV), lucerne transient streak virus (LTSV), alfalfa dwarf virus (ADV), Medicago sativa alphapartitivirus 1 (MsAPV1), MsAPV2, and alfalfa leaf curl virus (ALCV) were the main viruses infecting alfalfa in four examined provinces. AMV and MsAPV1 had the highest incidences in all 4 provinces. SDT analysis of the 7 viruses isolated in China revealed a highly conserved among AMV, LTSV, ADV, MsAPV1, MsAPV2, and ALCV, but the sequence was a high variation between China isolates to abroad isolates in PeSV, ADV, and ALCV. To our knowledge, this is the first report of ADV in Inner Mongolia and Gansu, ALCV in Inner Mongolia, MsAPV1 and MsAPV2 in all 4 provinces, and PeSV and LTSV in China. These findings provide a basis for future research on the genetic evolution of alfalfa viruses in China and on strategies to prevent diseases in alfalfa caused by these viruses.
Natural Shifts in Endosymbionts' Occurrence and Relative Frequency in Their Ciliate Host Population

The role of bacterial endosymbionts harbored by heterotrophic Paramecium species is complex. Obligate intracellular bacteria supposedly always inflict costs as the host is the only possible provider of resources. However, several experimental studies have shown that paramecia carrying bacterial endosymbionts can benefit from their infection. Here, we address the question which endosymbionts occur in natural paramecia populations isolated from a small lake over a period of 5 years and which factors might explain observed shifts and persistence in the symbionts occurrence. One hundred and nineteen monoclonal strains were investigated and approximately two-third harbored intracellular bacteria. The majority of infected paramecia carried the obligate endosymbiotic “Candidatus Megaira polyxenophila”, followed by Caedimonas varicaedens, and Holospora undulata. The latter was only detected in a single strain. While “Ca. M. polyxenophila” was observed in seven out of 13 samplings, C. varicaedens presence was limited to a single sampling occasion. After the appearance of C. varicaedens, “Ca. M. polyxenophila” prevalence dramatically dropped with some delay but recovered to original levels at the end of our study. Potential mechanisms explaining these observations include differences in infectivity, host range, and impact on host fitness as well as host competitive capacities. Growth experiments revealed fitness advantages for infected paramecia harboring “Ca. M. polyxenophila” as well as C. varicaedens. Furthermore, we showed that cells carrying C. varicaedens gain a competitive advantage from the symbiosis-derived killer trait. Other characteristics like infectivity and overlapping host range were taken into consideration, but the observed temporal persistence of “Ca. M. polyxenophila” is most likely explained by the positive effect this symbiont provides to its host.
Neuroprogenitor Cells From Patients With TBCK Encephalopathy Suggest Deregulation of Early Secretory Vesicle Transport

Biallelic pathogenic variants in TBCK cause encephaloneuropathy, infantile hypotonia with psychomotor retardation, and characteristic facies 3 (IHPRF3). The molecular mechanisms underlying its neuronal phenotype are largely unexplored. In this study, we reported two sisters, who harbored biallelic variants in TBCK and met diagnostic criteria for IHPRF3. We provided evidence that TBCK may play an important role in the early secretory pathway in neuroprogenitor cells (iNPC) differentiated from induced pluripotent stem cells (iPSC). Lack of functional TBCK protein in iNPC is associated with impaired endoplasmic reticulum-to-Golgi vesicle transport and autophagosome biogenesis, as well as altered cell cycle progression and severe impairment in the capacity of migration. Alteration in these processes, which are crucial for neurogenesis, neuronal migration, and cytoarchitecture organization, may represent an important causative mechanism of both neurodevelopmental and neurodegenerative phenotypes observed in IHPRF3. Whether reduced mechanistic target of rapamycin (mTOR) signaling is secondary to impaired TBCK function over other secretory transport regulators still needs further investigation.
Curriculum fidelity of Turkish preschool teachers in school-based practices

ABSTRACT This study aims to determine the level of fidelity of preschool teachers to the curriculum within the framework of school-based practices (SBPs) and evaluated in terms of participant responsiveness. In this case study, interview and document analysis methods were used to collect the data from eight preschool teachers working in a university kindergarten. Results indicate that the teachers were attempting to implement the school-based curriculum development (SBCD) approach, but with a limited understanding. The findings reveal that teachers who adopt the adaptation approach structurally adhere to the curriculum, and their process fidelity is extended in SBPs. It is also concluded that the supportive educational environment, participatory institutional culture, teacher qualifications and the curriculum structure promoting flexibility in practice contribute to fidelity.
Transient Two-Phase Flow in Porous Media: A Literature Review and Engineering Application in Geotechnics

This work reviews the transient two-phase flow in porous media with engineering applications in Geotechnics. It initially overviews constitutive relationships, conventional theories, and experiments. Then, corresponding limitations are discussed according to conflicting observations and multiphase interfacial dynamics. Based on those findings, the dynamic nonequilibrium effects were so defined, which could also be abbreviated as dynamic/transient effects. Four advanced theories have already been developed to resolve these effects. This review collects them and discusses their pros and cons. In addition, this work further reviews the state-of-art in terms of experimental methods, influential factors in dynamic/transient effects, and modelling performance, as well as micromodel and numerical methods at pore-scale. Last, the corresponding geotechnical applications are reviewed, discussing their applicability in effective stress, shear strength, and deformation. Finally, the entire review is briefed to identify research gaps in Geotechnics.
Moiré patterns and carbon nanotube sorting

Moiré patterns (MPs), arising from the superposition of two lattices with close periods, are tightly related to the physicochemical properties of bilayer nanostructures. Here, we develop the theory of complex MPs emerging in twisted bilayer graphene and planar nets of double-walled nanotubes at significant relative twist and/or deformation of layers. The proposed theory clarifies the physicochemical regularities arising at sorting of single-walled carbon nanotubes (SWCNTs) by organic molecules, which self-assemble in regular coatings on both the tubes and planar graphene. We introduce and consider an outer tubular virtual lattice that is a parent structure for the deposited coating and due to this fact, its existence is crucial for the coating formation. As we show, such outer lattices exist only for successfully sorted SWCNTs and the superposition between the outer lattice and SWCNT forms a specific long-period MP. We explain known experimental results of SWCNT sorting by molecules of flavin group, poly(9,9-dioctylfluorene-2,7-diyl), and poly [(m-phenylenevinylene)-alt-(p-phenylenevinylene)]. Also, our approach points out other organic molecules and polymers suitable for effective carbon nanotube sorting.
A New Species of Acoela Possessing a Middorsal Appendage with a Possible Sensory Function

Acoels, belonging to Xenacoelomorpha, are small worms with a relatively simple body plan and are considered a critical clade for understanding the evolution of bilaterians. Despite acoels' importance, however, many undiscovered species are predicted to be present worldwide. Here, we describe a new marine acoel species, Amphiscolops oni sp. nov., based on materials collected from the intertidal and subtidal zones of rocky shores at several localities along the Japanese Pacific coast. The new species is approximately 3 mm long and shows typical characteristics of the family Convolutidae, such as the presence of eyespots, symbiosis with algae, position of the gonopores, morphology of the bursal nozzles, lack of central singlet microtubules in the axonemes of spermatozoa, and funnel-like posture of the anterior end. Based on morphology and the results of molecular phylogenetic analyses, we assign this species to the genus Amphiscolops. Interestingly, these worms show unique behaviors such as swimming by flapping the lateral sides and actively capturing prey by swinging the anterior funnel. Furthermore, they possess a dorsal appendage—a characteristic previously unreported in Xenacoelomorpha—representing an evolutionary novelty acquired by this species.
Structural and Magnetic Properties of Nanosized Half-Doped Rare-Earth Ho0.5Ca0.5MnO3 Manganite

We investigated the structural and magnetic properties of 20 nm-sized nanoparticles of the half-doped manganite Ho0.5Ca0. 5MnO3 prepared by sol-gel approach. Neutron powder diffraction patterns show Pbnm orthorhombic symmetry for 10 K < T < 290 K, with lattice parameters a, b, and c in the relationship c/√2 < a < b, indicating a cooperative Jahn–Teller effect, i.e., orbital ordering OO, from below room temperature. In contrast with the bulk samples, in the interval 250 < T < 300 K, the fingerprint of charge ordering (CO) does not manifest itself in the temperature dependence of lattice parameters. However, there are signs of CO in the temperature dependence of magnetization. Accordingly, below 100 K superlattice magnetic Bragg reflections arise, which are consistent with an antiferromagnetic phase strictly related to the bulk Mn ordering of a charge exchange-type (CE-type), but characterized by an increased fraction of ferromagnetic couplings between manganese species themselves. Our results show that in this narrow band half-doped manganite, size reduction only modifies the balance between the Anderson superexchange and Zener double exchange interactions, without destabilizing an overall very robust antiferromagnetic state.
Fear might motivate secure password choices in the short term, but at what cost?

Fear has been used to convince people to behave securely in a variety of cybersecurity domains. In this study, we tested the use of fear appeals, together with threat and coping appraisal components separately and together, on password hygiene behaviors. Fear did indeed elicit the anticipated response: people had higher levels of behavioral intention to engage in better password hygiene. Unfortunately, we also detected a largely negative affective response to the appeals. Fear, as a short-lived emotion, can indeed be effective in the short term. Snapshot-like studies, like the one reported here, might lead us to conclude that fear is indeed indicated and efﬁcacious. Yet, it may backﬁre in the long term due to the negative long term affects it can trigger.
The Effect of Number of Factors and Data on Monthly Weather Classification Performance Using Artificial Neural Networks

Current weather-related research only focuses on weather prediction based on raw data and the factors used are generally 4 factors: average temperature, solar radiation, air pressure, and wind. In this research, monthly weather prediction is done using 5 factors where the additional factor used is rainfall in the previous time. In contrast to previous prediction research, the prediction process carried out in this study emphasizes the modeling of training data according to the desired prediction model. These two things distinguish this research from previous studies. The prediction model used in this study is a classification-based prediction model that is the Artificial Neural Network (ANN) method combined with the backpropagation algorithm for calculating the weight of the ANN network. The data used are meteorological data from 2010 to 2018 in the Bogor area, where data from 2010 to 2016 are used as training data, and data from 2017 to 2018 are used as test data. The results of this study indicate that the design of the model with the use of data for 6 years with feature data of 5 factors has an accuracy rate of 83.33%.
High Throughput Identification of the Potential Antioxidant Peptides in Ophiocordyceps sinensis

Ophiocordyceps sinensis, an ascomycete caterpillar fungus, has been used as a Traditional Chinese Medicine owing to its bioactive properties. However, until now the bio-active peptides have not been identified in this fungus. Here, the raw RNA sequences of three crucial growth stages of the artificially cultivated O. sinensis and the wild-grown mature fruit-body were aligned to the genome of O. sinensis. Both homology-based prediction and de novo-based prediction methods were used to identify 8541 putative antioxidant peptides (pAOPs). The expression profiles of the cultivated mature fruiting body were similar to those found in the wild specimens. The differential expression of 1008 pAOPs matched genes had the highest difference between ST and MF, suggesting that the pAOPs were primarily induced and play important roles in the process of the fruit-body maturation. Gene ontology analysis showed that most of pAOPs matched genes were enriched in terms of ‘cell redox homeostasis’, ‘response to oxidative stresses’, ‘catalase activity’, and ‘ integral component of cell membrane’. A total of 1655 pAOPs was identified in our protein-seqs, and some crucial pAOPs were selected, including catalase, peroxiredoxin, and SOD [Cu–Zn]. Our findings offer the first identification of the active peptide ingredients in O. sinensis, facilitating the discovery of anti-infectious bio-activity and the understanding of the roles of AOPs in fungal pathogenicity and the high-altitude adaptation in this medicinal fungus.
Predicting relapse or recurrence of depression: systematic review of prognostic models

Background Relapse and recurrence of depression are common, contributing to the overall burden of depression globally. Accurate prediction of relapse or recurrence while patients are well would allow the identification of high-risk individuals and may effectively guide the allocation of interventions to prevent relapse and recurrence. Aims To review prognostic models developed to predict the risk of relapse, recurrence, sustained remission, or recovery in adults with remitted major depressive disorder. Method We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2021. We included development and external validation studies of multivariable prognostic models. We assessed risk of bias of included studies using the Prediction model risk of bias assessment tool (PROBAST). Results We identified 12 eligible prognostic model studies (11 unique prognostic models): 8 model development-only studies, 3 model development and external validation studies and 1 external validation-only study. Multiple estimates of performance measures were not available and meta-analysis was therefore not necessary. Eleven out of the 12 included studies were assessed as being at high overall risk of bias and none examined clinical utility. Conclusions Due to high risk of bias of the included studies, poor predictive performance and limited external validation of the models identified, presently available clinical prediction models for relapse and recurrence of depression are not yet sufficiently developed for deploying in clinical settings. There is a need for improved prognosis research in this clinical area and future studies should conform to best practice methodological and reporting guidelines.
A Pricing Model for Urban Rental Housing Based on Convolutional Neural Networks and Spatial Density: A Case Study of Wuhan, China

With the development of urbanization and the expansion of floating populations, rental housing has become an increasingly common living choice for many people, and housing rental prices have attracted great attention from individuals, enterprises and the government. The housing rental prices are principally estimated based on structural, locational and neighborhood variables, among which the relationships are complicated and can hardly be captured entirely by simple one-dimensional models; in addition, the influence of the geographic objects on the price may vary with the increase in their quantities. However, existing pricing models usually take those structural, locational and neighborhood variables as one-dimensional inputs into neural networks, and often neglect the aggregated effects of geographical objects, which may lead to fluctuating rental price estimations. Therefore, this paper proposes a rental housing price model based on the convolutional neural network (CNN) and the synthetic spatial density of points of interest (POIs). The CNN can efficiently extract the complex characteristics among the relevant variables of housing, and the two-dimensional locational and neighborhood variables, based on the synthetic spatial density, effectively reflect the aggregated effects of the urban facilities on rental housing prices, thereby improving the accuracy of the model. Taking Wuhan, China, as the study area, the proposed method achieves satisfactory and accurate rental price estimations (coefficient of determination (R2) = 0.9097, root mean square error (RMSE) = 3.5126) in comparison with other commonly used pricing models.
A pleiotropic chemoreceptor facilitates the functional coupling of pheromone production and perception

Optimal mating decisions depend on the robust coupling of signal production and perception because independent changes in either could carry a fitness cost. However, since the perception and production of mating signals are often mediated by different tissues and cell types, the mechanisms that drive and maintain their coupling remain unknown for most animal species. Here, we show that in Drosophila, sensory perception and production of an inhibitory mating pheromone are co-regulated by Gr8a, a member of the Gustatory receptor gene family. Specifically, we found that the pleiotropic action of Gr8a independently regulates the perception of pheromones by the chemosensory systems of males and females, as well as their production in the fat body and oenocytes of males. These findings provide a relatively simple molecular explanation for how pleiotropic receptors maintain robust mating signaling systems at the population and species levels.
Isolation and Characterization of Extracellular Vesicles from the Fungal Phytopathogen Colletotrichum higginsianum

Fungal phytopathogens secrete extracellular vesicles (EVs) associated with enzymes and phytotoxic metabolites. While these vesicles are thought to promote infection, defining the true contents and functions of fungal EVs, as well as suitable protein markers, is an ongoing process. To expand our understanding of fungal EVs and their possible roles during infection, we purified EVs from the hemibiotrophic phytopathogen Colletotrichum higginsianum, the causative agent of anthracnose disease in multiple plant species, including Arabidopsis thaliana. EVs were purified in large numbers from the supernatant of protoplasts but not the supernatant of intact mycelial cultures. We purified two separate populations of EVs, each associated with over 700 detected proteins, including proteins involved in vesicle transport, cell wall biogenesis and the synthesis of secondary metabolites. We selected two SNARE proteins (Snc1 and Sso2) and one 14-3-3 protein (Bmh1) as potential EV markers and generated transgenic lines expressing fluorescent fusions. Each marker was confirmed to be protected inside EVs. Fluorescence microscopy was used to examine the localization of each marker during infection on Arabidopsis leaves. These findings further our understanding of EVs in fungal phytopathogens and will help build an experimental system to study EV inter-kingdom communication between plants and fungi.
Accountability during Performance Appraisals: The Development and Validation of the Rater Accountability Scale

ABSTRACT The purpose of the current study was to create and validate a new measure of rater accountability (RA) for use in performance appraisal (PA) contexts. Previous research has identified the accountability audience as an important moderator of the effects of RA that existing measures do not consider. This new measure of RA, the Rater Accountability Scale (RAS), was developed to capture accountability pressures from different audiences. Across two studies that sampled current managers, the RAS scores achieved adequate fit and acceptable reliability. Initial construct-related validity evidence was collected by exploring relationships with convergent measures, rater characteristics, and appraisal outcomes. Overall, these findings provide support for the use of the RAS in research and applied settings while also helping to build the nomological network of RA.
Revisiting SLIC: Fast Superpixel Segmentation of Marine SAR Images Using Density Features

The simple linear iterative clustering (SLIC) has been shown as an efficient and widely used superpixel-based algorithm for segmenting marine synthetic aperture radar (SAR) images. However, SLIC does not consider the fact that the density of ship target pixels is significantly lower than that of sea clutter pixels, leading to a waste of computational cost and memory resources on lots of pure clutter areas and to the degradation of the compactness of superpixels. To address the aforementioned issues, we develop a new density-based SLIC (DSLIC) method for the superpixel-based segmentation of marine SAR images. In the initialization stage of our DSLIC, all the subimages in a large marine SAR image are rapidly prescreened via a new density-driven classifier, where most of the subimages only occupied by clutter pixels with comparatively high density are discarded and do not need to be segmented in the subsequent local clustering stage. The retained subimages contain both the clutter and potential target areas. This prescreening operation results in higher computation efficiency and memory savings. In the local clustering stage of DSLIC, besides the intensity proximity and the spatiality proximity (used in SLIC), the sparsity proximity (measured by density distances) is considered to reduce the coexistence of sparse target pixels with low density and nonsparse clutter pixels with high density within superpixels. Our theoretical and experimental results show that the proposed DSLIC method is faster and requires less memory than SLIC and other state-of-the-art superpixel-based segmentation methods for marine SAR images with similar or better segmentation accuracy.