Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Effectiveness of in-situ Active Warming Combined With Open Top Chambers to Study Plant Responses to Climate Change

Temperature manipulation experiments are an effective way for testing plant responses to future climate conditions, especially for predicting shifts in plant phenological events. While passive warming techniques are widely used to elevate temperature in low stature plant communities, active warming has been applied less frequently due to the associated resource requirements. In forest ecosystems, however, active warming is crucial to simulate projected air temperature rises of 3–5 K, especially at the warm (i.e., southern and low elevation) range edges of tree species. Moreover, the warming treatment should be applied to the complete height of the experimental plants, e.g., regenerating trees in the understory. Here, we combined open top chambers (OTCs) with active heat sources, an electric heater (OTC-EH) and warming cables (OTC-WC), and tested the effectiveness of these set-ups to maintain constant temperature differences compared to ambient temperature across 18 m2 plots. This chamber size is needed to grow tree saplings in mixture in forest gaps for 3 to 10 years. With passive warming only, an average temperature increase of approx. 0.4 K as compared to ambient conditions was achieved depending on time of the day and weather conditions. In the actively warmed chambers, average warming exceeded ambient temperatures by 2.5 to 2.8 K and was less variable over time. However, active warming also reduced air humidity by about 15%. These results underline the need to complement passive warming with active warming in order to achieve constant temperature differences appropriate for climate change simulations under all weather conditions in large OTCs. Since we observed considerable horizontal and vertical temperature variation within OTCs with temperature differences of up to 16.9 K, it is essential to measure and report within-plot temperature distribution as well as temporal temperature variation. If temperature distributions within large OTCs are well characterized, they may be incorporated in the experimental design helping to identify non-linear or threshold responses to warming.
Review of the biology and ecology of a ragweed leaf beetle, Ophraella communa (Coleoptera: Chrysomelidae), which is a biological control agent of an invasive common ragweed, Ambrosia artemisiifolia (Asterales: Asteraceae)

ABSTRACT A ragweed leaf beetle, Ophraella communa (Coleoptera: Chrysomelidae), has been highlighted as a potential biological control agent of Ambrosia artemisiifolia. O. communa and A. artemisiifolia are native in North America and alien species in East Asia and Europe. As an invasive weed, A. artemisiifolia causes severe economic losses as reducing agricultural production as well as producing severe allergenic pollen. As an herbivore insect, O. communa has strong host preference on A. artemisiifolia. All the developmental stages of O. communa can be found on A. artemisiifolia and it attacks a single plant in repeated and extended manners. With few individuals on A. artemisiifolia, O. communa can completely defoliate before pollen production. Therefore, O. communa had been focused as a biological control of this invasive weed, but its introduction was denied because of possible damage on an important crop, Helianthus annuus. O. communa was accidentally introduced in East Asia and Europe in 1990s and 2010s, respectively. Fortunately, O. communa population was well established to suppress A. artemisiifolia in the introduced areas. Following detailed field surveys and host specificity tests of O. communa were conducted and proved a strong potential of O. communa as a biological control agent of A. artemisiifolia. Moreover, O. communa has been investigated in physiological and evolutionary studies. In this study, the potential of O. communa as a biological control agent and a study organism are reviewed.
GARPOS: Analysis Software for the GNSS‐A Seafloor Positioning With Simultaneous Estimation of Sound Speed Structure

Global Navigation Satellite System–Acoustic ranging combined seafloor geodetic technique (GNSS-A) has extended the geodetic observation network into the ocean. The key issue for analyzing the GNSS-A data is how to correct the effect of sound speed variation in the seawater. We constructed a generalized observation equation and developed a method to directly extract the gradient sound speed structure by introducing appropriate statistical properties in the observation equation, especially the data correlation term. In the proposed scheme, we calculate the posterior probability based on the empirical Bayes approach using the Akaike’s Bayesian Information Criterion for model selection. This approach enabled us to suppress the overfitting of sound speed variables and thus to extract simpler sound speed field and stable seafloor positions from the GNSS-A dataset. The proposed procedure is implemented in the Python-based software “GARPOS” (GNSS-Acoustic Ranging combined POsitioning Solver).
Evaluation of saliva as a source of accurate whole-genome and microbiome sequencing data

This study sets out to establish the suitability of saliva-based whole-genome sequencing (WGS) through a comparison against blood-based WGS. To fully appraise the observed differences, we developed a novel technique of pseudo-replicates. We also investigated the potential of characterising individual salivary microbiomes from non-human DNA fragments found in saliva. We observed the majority of discordant genotype calls between blood and saliva calls fell into known regions of the human genome that are typically sequenced with low confidence; and could be identified by quality control measures. Pseudo-replication demonstrated that the levels of discordance between blood- and saliva-derived WGS data were entirely similar to what one would expect between technical replicates if an individual’s blood or saliva had been sequenced twice. Finally, we successfully sequenced salivary microbiomes in parallel to human genomes as demonstrated by a comparison against the Human Microbiome Project. Author Summary DNA is usually collected from blood for the analysis of human genomes. In France, a new and very large genetic dataset will be created where selected participants will be sent saliva-collection kits in the post as this data collection method presents numerous logistical benefits. It has been previously shown that good quality genetic data can be created from saliva, though existing studies have often not considered the latest technologies or have only analysed a very small number of individuals. In this study, we have analysed genetic data derived from saliva for 39 individuals to give a firm conclusion that the proposed genome sequencing approach of the new French dataset will be capable of provided high quality data by making a comparison to pre-existing genetic data derived from blood for these 39 individuals. In order to do so, we developed a novel method (presented here) to establish the similarity between two sets of genetic data for the same individual that are generated from separate DNA samples. Finally, we have also demonstrated an added bonus of colleting saliva samples: that it is possible to gather both human genetic data and potentially interesting salivary microbiome data at the same time by separating and analysing in parallel human and non-human DNA fragments.
Moving in on human motor cortex. Characterizing the relationship between body parts with non-rigid population response fields

For cortical motor activity, the relationships between different body part representations is unknown. Through reciprocal body part relationships, functionality of cortical motor areas with respect to whole body motor control can be characterized. In the current study, we investigate the relationship between body part representations within individual neuronal populations in motor cortices, following a 7 Tesla fMRI 18-body-part motor experiment in combination with our newly developed non-rigid population Response Field (pRF) model and graph theory. The non-rigid pRF metrics reveal somatotopic structures in all included motor cortices covering frontal, parietal, medial and insular cortices and that neuronal populations in primary sensorimotor cortex respond to fewer body parts than secondary motor cortices. Reciprocal body part relationships are estimated in terms of uniqueness, clique-formation, and importance. We report unique response profiles for the knee, a clique of body parts surrounding the ring finger, and a central role for the shoulder and wrist. These results reveal associations among body parts from the perspective of the central nervous system, while being in agreement with intuitive notions of body part usage.
Identification of covalent modifications regulating immune signaling complex composition and phenotype

Cells signal through rearrangements of protein communities governed by covalent modifications and reversible interactions of distinct sets of proteins. A method that identifies those post-transcriptional modifications regulating signaling complex composition and functional phenotypes in one experimental setup would facilitate an efficient identification of novel molecular signaling checkpoints. Here we devised Modifications, Interactions and Phenotypes by Affinity Purification Mass Spectrometry (MIP-APMS), comprising the streamlined cloning and transduction of tagged proteins into functionalized reporter cells as well as affinity chromatography, followed by MS-based quantification. We report the time-resolved interplay of more than 50 previously undescribed modification and hundreds of protein-protein interactions of 19 immune protein complexes in monocytes. Validation of interdependecies between covalent, reversible and functional protein complex regulations by knock-out or site-specific mutation, revealed isgylation and phosphorylation of TRAF2 as well as ARHGEF18 interaction in Toll-like receptor 2 signaling. Moreover, we identify distinct mechanisms of action for small molecule inhibitors of p-38 (MAPK14). Our method provides a fast and cost-effective pipeline for the molecular interrogation of protein communities in diverse biological systems and primary cells. Highlights Experimental framework to reveal dynamic signaling checkpoints in primary cells Identification of crosstalk between protein modifications and interactions in signaling complexes Discovery of TRAF2 isgylation, phosphorylation and ARHGEF18 interaction in monocytes Differential drug mode of action for p-38 (MAPK14) kinase inhibitors Graphical abstract
Methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data

Differential DNA methylation and chromatin accessibility are associated with disease development, particularly cancer. Methods that allow profiling of these epigenetic mechanisms in the same reaction and at the single-molecule or single-cell level continue to emerge. However, a challenge lies in jointly visualizing and analyzing the heterogeneous nature of the data and extracting regulatory insight. Here, we developed methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin landscapes. Methylscaper implements a weighted principle component analysis that orders sequencing reads, each providing a record of the chromatin state of one epiallele, and reveals patterns of nucleosome positioning, transcription factor occupancy, and DNA methylation. We demonstrate methylscaper’s utility on a long-read, single-molecule methyltransferase accessibility protocol for individual templates (MAPit) dataset and a single-cell nucleosome, methylation, and transcription sequencing (scNMT-seq) dataset. In comparison to other procedures, methylscaper is able to readily identify chromatin features that are biologically relevant to transcriptional status while scaling to larger datasets. Availability and implementation Methylscaper, is available on GitHub at https://github.com/rhondabacher/methylscaper. Contact rbacher@ufl.edu
Combinatorial active contour bilateral filter for ultrasound image segmentation

Abstract. Purpose: Utilization of computer-aided diagnosis (CAD) on radiological ultrasound (US) imaging has increased tremendously. The prominent CAD applications are found in breast and thyroid cancer investigation. To make appropriate clinical recommendations, it is important to accurately segment the cancerous object called a lesion. Segmentation is a crucial step but undoubtedly a challenging problem due to various perturbations, e.g., speckle noise, intensity inhomogeneity, and low contrast. Approach: We present a combinatorial framework for US image segmentation using a bilateral filter (BF) and hybrid region-edge-based active contour (AC) model. The BF is adopted to smooth images while preserving edges. Then the hybrid model of region and edge-based AC is applied along the scales in a global-to-local manner to capture the lesion areas. The framework was tested in segmenting 258 US images of breast and thyroid, which were validated by manual ground truths. Results: The proposed framework is accessed quantitatively based on the overlapping values of the Dice coefficient, which reaches 90.05 ± 5.81 % . The evaluation with and without the BF shows that the enhancement procedure improves the framework well. Conclusions: The high performance of the proposed method in our experimental results indicates its potential for practical implementations in CAD radiological US systems.
Characteristics and Drive Design Analysis of SiC

In this paper, a new model is established ,which aimed at the physical model and analytical model structure,and ombined with the nonlinear capacitance and parasitic parameters of SiC. The accuracy and rapidity of the model are preserved as much as possible. This paper firstly compares and analyzes the established models through theoretical analysis of new models and SIMetrix/SIMPLIS platforms. Then the paper analyzes the switching characteristics of the SiC and verify the accuracy of the verification results by setting up a double pulse platform experiment. Finally, by analyzing the physical, high temperature, static and dynamic characteristics of SiC and Si, the reference values of driving voltage design of SiC and the comparative data of SiC and Si losses are obtained by means of the double pulse experimental platform, which is used to analyze the physical characteristics, high temperature resistance, static characteristics and dynamic characteristics of SiC. Thus better play the superior performance of SiC.
SiC Trenched Schottky Diode with Step-Shaped Junction Barrier for Superior Static Performance and Large Design Window

A novel silicon carbide (SiC) trenched schottky diode with step-shaped junction barrier is proposed for superior static performance and large design window. In the proposed diode, to improve tradeoff between specific on-resistance and surface peak electric field, the shape of the trenched-junction is modified to stair-step, without extra fabrication process. To investigate the performances of the SiC step-shaped trenched junction barrier schottky (SSTJBS) diode, numerical simulations are carried out through Silvaco TCAD. The results indicate that the proposed diode can accommodate highly doped drift region with no degradation of its reverse blocking characteristic. In comparison with the conventional SiC trenched junction barrier schottky (TJBS) diode, the proposed SiC SSTJBS diode shows a larger design window of drift region doping concentration from 7.9×1015cm-3 to 9.5×1015cm-3. In the design window, the specific on-resistance and surface peak electric field can be reduced by 12.9% and 11%, respectively.
SnO2 Nano/Microfibers for Gas Sensors

SnO2 is an n-type semiconductor with the band gap energy of 3.6 eV. It has been widely studied for gas sensing applications, the sensitivity of which can be easily tuned by the operating temperature. The presented paper is focused on the preparation and detailed characterization of the hollow SnO2 nano/microfibers suitable for gas detection sensors. Ceramic SnO2 fibers were produced by needleless electrospinning and followed by the calcination process. The characterization was performed by SEM, TEM, XRD, and Raman spectroscopy. The precursor PVP/SnO2 fibers had amorphous nature. The calcination of the electro spun precursor resulted in the formation of hollow crystalline fibrous structures. The formation mechanism of hollow fibers has been described. Subsequently, a homogeneous fibrous layer was created by the spin coating method for gas sensing applications.
Drought tolerance in cork oak is associated with low leaf stomatal and hydraulic conductances

Abstract: To investigate the role of seeds origin in drought tolerance, the response to water deprivation of cork oak seedlings differing in climatic conditions at their geographical origin was compared. Gafour is the provenance from the driest site and Feija is the provenance from the wettest site. Net photosynthesis (An), stomatal conductance (gs) and leaf water potential were measured during dehydration. A delayed decrease in leaf water potential is observed after water withholding in Gafour as compared to Feija leaves. At the onset of dehydration, An and gs were higher in Feija. After withholding watering, Gafour leaves were able to maintain a higher An and gs than Feija leaves. Most likely, drought tolerance in Gafour leaves is associated to their lower gs under well-hydrated conditions. The stomatal density (Ds) and specific leaf area (SLA) were not different in well-watered leaves but, leaf hydraulic conductance was lower in Gafour leaves when compared to Feija leaves. Our results suggested that lower stomatal and hydraulic conductances of Gafour leaves could be involved in bringing about the better resistance to dehydration.
Gray Matter Segmentation of Brain MRI Using Hybrid Enhanced Independent Component Analysis in Noisy and Noise Free Environment

Medical segmentation is the primary task performed to diagnosis the abnormalities in the human body. The brain is the complex organ and anatomical segmentation of brain tissues is a challenging task. In this paper, we used Enhanced Independent component analysis to perform the segmentation of gray matter. We used modified K means, Expected Maximization and Hidden Markov random field to provide better spatial correlation that overcomes in-homogeneity, noise and low contrast. Our objective is achieved in two steps (i) initially unwanted tissues are clipped from the MRI image using skull stripped Algorithm (ii) Enhanced Independent Component analysis is used to perform the segmentation of gray matter. We apply the proposed method on both T1w and T2w MRI to perform segmentation of gray matter at different noisy environments. We evaluate the the performance of our proposed system with Jaccard Index, Dice Coefficient and Accuracy. We further compared the proposed system performance with the existing frameworks. Our proposed method gives better segmentation of gray matter useful for diagnosis neurodegenerative disorders.
Control of long-distance motion of single molecules on a surface

Telegraphing molecules Scanning tunneling microscope (STM) tips have long been used to manipulate atoms and molecules through direct interactions. Civita et al. now show that at cryogenic temperatures, the bias voltage from an STM tip can propel a large organic molecule, dibromoterfluorene, long distances—tens of nanometers along straight tracks on the flat silver (111) surface (see the Perspective by Esch and Lechner). This electrostatic effect requires the molecule to be oriented along the track, and derivatives lacking bromide groups would change direction. In a dual-tip setup, changing the bias voltage sent and received molecules between two specific points about 60 nanometers apart. Science, this issue p. 957; see also p. 912 Single molecules are sent and received over relatively large distances on precisely defined tracks across a flat metal surface. Spatial control over molecular movement is typically limited because motion at the atomic scale follows stochastic processes. We used scanning tunneling microscopy to bring single molecules into a stable orientation of high translational mobility where they moved along precisely defined tracks. Single dibromoterfluorene molecules moved over large distances of 150 nanometers with extremely high spatial precision of 0.1 angstrom across a silver (111) surface. The electrostatic nature of the effect enabled the selective application of repulsive and attractive forces to send or receive single molecules. The high control allows us to precisely move an individual and specific molecular entity between two separate probes, opening avenues for velocity measurements and thus energy dissipation studies of single molecules in real time during diffusion and collision.
Adding software to package management systems can increase their citation by 280%

A growing number of biomedical methods and protocols are being disseminated as open-source software packages. When put in concert with other packages, they can execute in-depth and comprehensive computational pipelines. Therefore, their integration with other software packages plays a prominent role in their adoption in addition to their availability. Accordingly, package management systems are developed to standardize the discovery and integration of software packages. Here we study the impact of package management systems on software dissemination and their scholarly recognition. We study the citation pattern of more than 18,000 scholarly papers referenced by more than 23,000 software packages hosted by Bioconda, Bioconductor, BioTools, and ToolShed—the package management systems primarily used by the Bioinformatics community. Our results suggest that there is significant evidence that the scholarly papers’ citation count increases after their respective software was published to package management systems. Additionally, our results show that the impact of different package management systems on the scholarly papers’ recognition is of the same magnitude. These results may motivate scientists to distribute their software via package management systems, facilitating the composition of computational pipelines and helping reduce redundancy in package development. Significance Statement Software packages are the building blocks of computational pipelines. A myriad of packages are developed; however, the lack of integration and discovery standards hinders their adoption, leaving most scientists’ scholarly contributions unrecognized. Package management systems are developed to facilitate software dissemination and integration. However, developing software to meet their code and packaging standards is an involved process. Therefore, our study results on the significant impact of the package management systems on scholarly paper’s recognition can motivate scientists to invest in disseminating their software via package management systems. Dissemination of more software via package management systems will lead to a more straightforward composition of computational pipelines and less redundancy in software packages.