Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid model for daily runoff interval predictions based on Bayesian inference

ABSTRACT The highly non-linear and nonstationary nature of runoff events in changing environments makes accurate and reliable runoff forecasting difficult. We propose a hybrid model by integrating an autoregressive (AR) model, Bayesian inference, a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm, Bayesian optimization, and support vector regression. Two Bayesian inference methods (the No-U-Turn Sampler (NUTS) and variational inference) were used to calculate the parameters of the AR model to obtain a Bayesian AR (BAR) model. Credible intervals were used to analyse the uncertainty of the parameters and model prediction results. The above model is applied to the daily runoff predictions of hydrological stations in the Yellow River basin of China. The results show that (1) the hybrid model can improve the prediction accuracy and (2) the NUTS algorithm-based model provides a narrower reliable interval and performs better in uncertainty analyses.
Detecting biased user-product ratings for online products using opinion mining

Abstract Collaborative filtering recommender system (CFRS) plays a vital role in today’s e-commerce industry. CFRSs collect ratings from the users and predict recommendations for the targeted product. Conventionally, CFRS uses the user-product ratings to make recommendations. Often these user-product ratings are biased. The higher ratings are called push ratings (PRs) and the lower ratings are called nuke ratings (NRs). PRs and NRs are injected by factitious users with an intention either to aggravate or degrade the recommendations of a product. Hence, it is necessary to investigate PRs or NRs and discard them. In this work, opinion mining approach is applied on textual reviews that are given by users for a product to detect the PRs and NRs. The work also examines the effect of PRs and NRs on the performance of CFRS by evaluating various measures such as precision, recall, F-measure and accuracy.
Ferroelectric phase transitions and dynamical behavior in KNbO3/KTaO3 superlattices by molecular-dynamics simulation

The phase transitions and dynamical behavior of superlattices consisting of equal-thickness layers of a perovskite ferroelectric (KNbO3) and a perovskite paraelectric (KTaO3) are explored using molecular-dynamics simulation. We find that the response in the plane and in the modulation direction are essentially decoupled. The Curie temperature for the transition from a polarized to unpolarized state in the modulation direction decreases approximately linearly with modulation length, Λ, for Λ>12; for smaller modulation lengths, it is essentially constant. The Curie temperature in the plane appears to be only weakly modulation-length dependent. We relate our results to experimental findings on the same system.The phase transitions and dynamical behavior of superlattices consisting of equal-thickness layers of a perovskite ferroelectric (KNbO3) and a perovskite paraelectric (KTaO3) are explored using molecular-dynamics simulation. We find that the response in the plane and in the modulation direction are essentially decoupled. The Curie temperature for the transition from a polarized to unpolarized state in the modulation direction decreases approximately linearly with modulation length, Λ, for Λ>12; for smaller modulation lengths, it is essentially constant. The Curie temperature in the plane appears to be only weakly modulation-length dependent. We relate our results to experimental findings on the same system.
The role of soil and plant cover as drivers of soil macrofauna of the Dnipro River floodplain ecosystems

Abstract Floodplain ecosystems are hotspots of biological diversity and perform important ecosystem functions in the landscape. The key to understanding the sustainability of ecosystem function is knowledge of the relationships between ecosystem components. The article reveals the role of morphological and physical properties of soil, as well as phytoindication of environmental factors as drivers of biological diversity of soil macrofauna of protected ecosystems of the Dnipro River floodplain. The studies were conducted in the forest floodplain ecosystems of the “Dnipro-Orilskiy” Nature Reserve. The studies of morphological properties of soils allowed us to identify the representatives of two reference groups: Fluvisol and Gleysol. The soil physical property data were subjected to principal component analysis, which extracted four principal components whose eigenvalues exceeded unity and described 79.9% of the variation in traits. The principal components of variation in soil physical properties and phytoindication assessments of environmental factors were used as predictors of the community structure of soil macrofauna. These predictors were able to explain 29.6% of the community variation. Physical soil properties are most important as a driver of soil macrofauna. The morphological properties of the soil and phytoindicator assessments are able to explain a much smaller part of the community variation. The pure influence of the predictors is small, indicating that they interact significantly in influencing soil animals. The results obtained have implications for the development of optimal strategies for floodplain ecosystem management and biodiversity conservation.
Microsaccades are directed towards the midpoint between targets in a variably cued attention task

Reliable, non-invasive biomarkers that reveal the internal state of a subject are an invaluable tool for neurological diagnoses. Small fixational eye movements, called microsaccades, are a candidate biomarker thought to reflect a subject’s focus of attention (1, 2). The linkage between the direction of microsaccades and attention has mainly been demonstrated using explicit and unambiguous attentional cues. However, the natural world is seldom predictable and rarely provides unambiguous information. Thus, a useful biomarker must be robust to such changes in environmental statistics. To determine how well microsaccades reveal visual-spatial attention across behavioral contexts, we analyzed these fixational eye movements in monkeys performing a conventional change detection task. The task included two stimulus locations and variable cue validities across blocks of trials. Subjects were adept at the task, showing precise and graded modulations of visual attention for subtle target changes and performing better and faster when the cue was more reliable (3). However, over tens of thousands of microsaccades, we found no difference in microsaccade direction between cued locations when cue variability was high nor between hit and miss trials. Instead, microsaccades were made towards the midpoint of the two target locations, not towards individual targets. Our results suggest that the direction of microsaccades should be interpreted with caution and may not be a reliable measure of covert spatial attention in more complex viewing conditions. Significance Statement Small fixational eye movements called microsaccades are thought to “point” towards a location that is being attended in the visual periphery. This phenomenon has largely been studied using visual cues that unambiguously indicate the location of the upcoming stimulus change. Because the natural world is rarely unambiguous, we studied the relationship between microsaccade direction and spatial attention using less reliable cues. We found that monkeys’ microsaccade directions in a standard visuospatial attention task did not indicate the animals’ focus of attention, despite behavioral and neuronal evidence of spatial attention. Instead, microsaccades were made towards the midpoint between the target locations in both animals, suggesting a more complex relationship between microsaccades and attention in naturalistic settings.
Membrane-dependent actin polymerization mediated by the Legionella pneumophila effector protein MavH

L. pneumophila propagates in eukaryotic cells within a specialized niche, the Legionella-containing vacuole (LCV). The infection process is controlled by over 330 effector proteins delivered through the type IV secretion system. In this study, we report that the Legionella MavH effector harbors a lipid-binding domain that specifically recognizes PI(3)P (phosphatidylinositol 3-phosphate) and localizes to endosomes when ectopically expressed. We show that MavH recruits host actin capping proteins (CP) and actin to the endosome via its CP interacting (CPI) motif and WH2-like actin-binding domain, respectively. In vitro assays revealed that MavH stimulates robust actin polymerization only in the presence of PI(3)P-containing liposomes and the recruitment of CP by MavH negatively regulates F-actin density at the membrane. Furthermore, in L. pneumophila-infected cells, MavH can be detected around the LCV at the very early stage of infection. Together, our results reveal a novel mechanism of membrane-dependent actin polymerization catalyzed by MavH that may play a role at the early stage of L. pneumophila infection by regulating host actin dynamics.
Path analysis reveals that corticosterone mediates gluconeogenesis from fat-derived substrates during acute stress in songbirds

Glucocorticoids (e.g., corticosterone or CORT in birds) mobilize energy reserves during stress to aid survival. Stress liberates glucose (GLU) by glycogenolysis, but with glycogen depletion, gluconeogenesis of fat and protein sources predominates. Songbirds have higher metabolic rates and GLU concentrations than mammals and likely rely more on fat and protein stores during stress. We tested this hypothesis in four songbird species using path analysis to model the interrelationships between CORT and energy metabolites both at baseline and after acute stress. Individuals in better condition had higher triglyceride and CORT levels at baseline than individuals in poor body condition, and these differences became more pronounced with stress. Free CORT (the fraction unbound to circulating proteins) was associated with more GLU and free glycerol at baseline, but the former relationship was lost after acute stress. This suggests a shift from a combination of glycogenolysis and gluconeogenesis to solely the latter with acute stress. Glucose levels were also associated with uric acid indicating that birds obtain GLU during stress from gluconeogenesis of mostly fat-derived substrates. This provides a previously elusive functional link between body condition and the stress response, and suggests songbirds are more susceptible to stress challenges during energy-limiting conditions than mammals.
Building a genome-based understanding of bacterial pH preferences

The environmental preferences of many microbes remain undetermined. This is the case for bacterial pH preferences, which can be difficult to predict a priori despite the importance of pH as a factor structuring bacterial communities in many systems. We compiled data on bacterial distributions from five datasets spanning pH gradients in soil and freshwater systems (1470 samples in total), quantified the pH preferences of bacterial taxa across these datasets, and compiled genomic data from representative bacterial taxa. While taxonomic and phylogenetic information were generally poor predictors of bacterial pH preferences, we identified genes consistently associated with pH preference across environments. We then developed and validated a machine learning model to estimate bacterial pH preferences from genomic information alone, a model which could aid in the selection of microbial inoculants, improve species distribution models, or help design effective cultivation strategies. More generally, we demonstrate the value of combining biogeographic and genomic data to infer and predict the environmental preferences of diverse bacterial taxa.
Image identification and restoration based on equal power spectrum

The most challenging question in image restoration nowadays is how to obtain blur information from the degraded image. Specifically, the identification of PSF has been a subject of great interest. However, many early identification methods are, in general, more expensive computationally, and have some limitations, more or less. In this paper, a new identification and restoration method based on the power spectrum filter was proposed by means of equivalent power spectrum assumption. Specifically, a recognition method, for the power spectrum of the original image in the filter transfer function expression, was suggested through exploring spectra of the degraded image. The major merits of this method are it is simpler, more practicable, and more economical computationally than the others, such as identifying PSF parameters.
Delineation of complex gene expression patterns in single cell RNA-seq data with ICARUS v2.0

Complex biological traits and disease often involve patterns of gene expression that can be characterised and examined. Here we present ICARUS v2.0, an update to our single cell RNA-seq analysis web server with additional tools to investigate gene networks and understand core patterns of gene regulation in relation to biological traits. ICARUS v2.0 enables gene co-expression analysis with MEGENA, transcription factor regulated network identification with SCENIC, trajectory analysis with Monocle3, and characterisation of cell-cell communication with CellChat. Cell cluster gene expression profiles may be examined against Genome Wide Association Studies with MAGMA to find significant associations with GWAS traits. Additionally, differentially expressed genes may be compared against the Drug-Gene Interaction database (DGIdb 4.0) to facilitate drug discovery. ICARUS v2.0 offers a comprehensive toolbox of the latest single cell RNA-seq analysis methodologies packed into an efficient, user friendly, tutorial style web server application (accessible at https://launch.icarus-scrnaseq.cloud.edu.au/) that enables single cell RNA-seq analysis tailored to the user’s dataset.
Delineating genotypes and phenotypes of individual cells from long-read single cell transcriptomes

Single-cell nanopore sequencing of full-length mRNAs (scNanoRNAseq) is transforming singlecell multi-omics studies. However, challenges include computational complexity and dependence on short-read curation. To address this, we developed a comprehensive toolkit, scNanoGPS to calculate same-cell genotypes-phenotypes without short-read guidance. We applied scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell lines. Standalone, scNanoGPS accurately deconvoluted error-prone long-reads into single-cells and single-molecules. Further, scNanoGPS simultaneously accessed both phenotypes (expressions/isoforms) and genotypes (mutations) of individual cells. Our analyses revealed that tumor and stroma/immune cells often expressed significantly distinct combinations of isoforms (DCIs). In a kidney tumor, we identified 924 genes with DCIs involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Moreover, transcriptome-wide mutation analyses identified many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting critical roles of different populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing.
Soybean and Cotton Spermosphere Soil Microbiome Shows Dominance of Soilborne Copiotrophs

The central hypothesis of this research was that plant species and seed exudate release would alter the assembly of microbes in the spermosphere soil. Our research investigated the response of microbes to the initial burst of nutrients into the spermosphere soil, filling knowledge gaps from previous studies that pregerminated seeds under sterile conditions. ABSTRACT The spermosphere is the transient, immediate zone of soil around imbibing and germinating seeds. It represents a habitat where there is contact between seed-associated microbes and soil microbes, but it is studied less than other plant habitats. Previous studies on spermosphere microbiology were primarily culture based or did not sample the spermosphere soil as initially defined in space and time. Thus, the objectives of this study were to develop an efficient strategy to collect spermosphere soils around imbibing soybean and cotton in nonsterile soil and investigate changes in microbial communities. The method employed sufficiently collected spermosphere soil as initially defined in space by constraining the soil sampled with a cork borer and confining the soil to a 12-well microtiter plate. Spermosphere prokaryote composition changed over time and depended on the crop within 6 h after seeds were sown. By 12 to 18 h, crops had unique microbial communities in spermosphere soils. Prokaryote evenness dropped following seed imbibition, with the proliferation of copiotrophic soil bacteria. Due to their long history of plant growth promotion, prokaryote operational taxonomic units (OTUs) in Bacillus, Paenibacillus, Burkholderia, Massilia, Azospirillum, and Pseudomonas were notable organisms enriched. Fungi and prokaryotes were hub taxa in cotton and soybean spermosphere networks. Additionally, the enriched taxa were not hubs in networks, suggesting that other taxa besides those enriched may be important for spermosphere communities. Overall, this study advances knowledge in the assembly of the plant microbiome early in a plant’s life, which may have plant health implications in more mature plant growth stages. IMPORTANCE The central hypothesis of this research was that plant species and seed exudate release would alter the assembly of microbes in the spermosphere soil. Our research investigated the response of microbes to the initial burst of nutrients into the spermosphere soil, filling knowledge gaps from previous studies that pregerminated seeds under sterile conditions. We identified several copiotrophic bacterial lineages with a long history of plant growth promotion proliferating in response to the initial exudate release. With a comparative network approach, we show that these copiotrophic bacteria are not central to networks, demonstrating that other microbes (including fungi) may be important for community structure. This study improves knowledge on microbial dynamics in the understudied spermosphere and helps inform solutions for biologically or ecologically motivated solutions to spermosphere pathogens.
CELL INSTANCE SEGMENTATION VIA MULTI-SCALE NON-LOCAL CORRELATION

For cell instance segmentation on Electron Microscopy (EM) images, state-of-the-art methods either conduct pixel-wise classification or follow a detection and segmentation manner. However, both approaches suffer from the enormous cell instances of EM images where cells are tightly close to each other and show inconsistent morphological properties and/or homogeneous appearances. This fact can easily lead to over-segmentation and under-segmentation problems for model prediction, i.e., falsely splitting and merging adjacent instances. In this paper, we propose a novel approach incorporating non-local correlation in the embedding space to make pixel features distinct or similar to their neighbors and thus address the over- and under-segmentation problems. We perform experiments on five different EM datasets where our proposed method yields better results than several strong baselines. More importantly, by using non-local correlation, we observe fewer false separations within one cell and fewer false fusions between cells.
Circadian oscillation in primary cilium length by clock genes regulates fibroblast cell migration

Various mammalian cells have autonomous cellular clocks that are produced by the transcriptional cycle of clock genes. Cellular clocks provide circadian rhythms for cellular functions via transcriptional and cytoskeletal regulation. The vast majority of mammalian cells possess a primary cilium, an organelle protruding from the cell surface. Here, we investigated the little-known relationship between circadian rhythm and primary cilia. The length and number of primary cilia showed circadian dynamics both in vitro and in vivo. The circadian rhythm of primary cilium length was abolished by SR9011 and Bmal1 knockout. A centrosomal protein, pericentrin, transiently accumulates in centriolar satellites, the base of primary cilia at the shortest cilia phase, and induces elongation of primary cilia at the longest cilia phase in the circadian rhythm of primary cilia. In addition, rhythmic cell migration during wound healing depends on the length of primary cilia and affects the rate of wound healing. Our findings demonstrate that the circadian dynamics of primary cilia length by clock genes control fibroblast migration and could provide new insights into chronobiology.
Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into “motif groups,” diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.
Nashi dust storm over the United Arab Emirates

An exceptional winter dust storm affected the eastern parts of the United Arab Emirates (UAE) and the Sultanate of Oman on 12 and 13 December 2003. It was caused by a cold and dry northeasterly wind known locally as a Nashi wind (UAE Climate, 1996). Visibility was very poor, particularly along the Gulf of Oman coast on the 12th when it fell to below 100m at Fujairah and Muscat (Figure 1). On the west coast of the UAE visibility decreased to 1000m at Ras Al Khaimah and 500m at Dubai late in the day. The dust reached Abu Dhabi early the following morning, and reduced visibility there to 1500m. Although somewhat dated, this Nashi dust storm is of considerable interest, because of the source region of the dust over Iran. The authors have not found any other articles describing such a storm. De Villiers and van Heerden (2007), in a study of 173 dust events (i.e. visibility seriously reduced by dust in the atmosphere) over the UAE from 1994 to 2003 when the visibility was 5000m or less, found that 55% of the dust events occurred in a southeast to southwesterly wind from the Empty Quarter, 24% in a northwesterly from northern Saudi Arabia via the Arabian Gulf, and 21% in an east to northeasterly. Of this last group, however, 31% deteriorated into dust storms (with the visibility below 1000m). By way of comparison, only 13% of the more frequent events with southerly winds worsened into dust storms.