Miracle-dz/UniFAR-FTUs huggingface dataset:
Osteogenic Enhancement Between Icariin and Bone Morphogenetic Protein 2: A Potential Osteogenic Compound for Bone Tissue Engineering

Icariin, a typical flavonol glycoside, is the main active component of Herba Epimedii, which was used to cure bone-related diseases in China for centuries. It has been reported that Icariin can be delivered locally by biomaterials and it has an osteogenic potential for bone tissue engineering. Biomimetic calcium phosphate (BioCaP) bone substitute is a novel drug delivery carrier system. Our study aimed to evaluate the osteogenic potential when Icariin was internally incorporated into the BioCaP granules. The BioCaP combined with Icariin and bone morphogenetic protein 2 (BMP-2) was investigated in vitro using an MC3T3-E1 cell line. We also investigated its efficacy to repair 8 mm diameter critical size bone defects in the skull of SD male rats. BioCaP was fabricated according to a well-established biomimetic mineralization process. In vitro, the effects of BioCaP alone or BioCaP with Icariin and/or BMP-2 on cell proliferation and osteogenic differentiation of MC3T3-E1 cells were systematically evaluated. In vivo, BioCaP alone or BioCaP with Icariin and/or BMP-2 were used to study the bone formation in a critical-sized bone defect created in a rat skull. Samples were retrieved for Micro-CT and histological analysis 12 weeks after surgery. The results indicated that BioCaP with or without the incorporation of Icariin had a positive effect on the osteogenic differentiation of MC3T3-E1. BioCaP with Icariin had better osteogenic efficiency, but had no influence on cell proliferation. BioCap + Icariin + BMP-2 showed better osteogenic potential compared with BioCaP with BMP-2 alone. The protein and mRNA expression of alkaline phosphatase and osteocalcin and mineralization were higher as well. In vivo, BioCaP incorporate internally with both Icariin and BMP-2 induced significantly more newly formed bone than the control group and BioCaP with either Icariin or BMP-2 did. Micro-CT analysis revealed that no significant differences were found between the bone mineral density induced by BioCaP with icariin and that induced by BioCaP with BMP-2. Therefore, co-administration of Icariin and BMP-2 was helpful for bone tissue engineering.
Agrobacterium-Mediated Transformation of Russian Commercial Plum cv. “Startovaya” (Prunus domestica L.) With Virus-Derived Hairpin RNA Construct Confers Durable Resistance to PPV Infection in Mature Plants

In modern horticulture Plum pox virus (PPV) imposes serious threats to commercial plantations of a wide range of fruit species belonging to genera Prunus. Given the lack of natural genetic resources, which display reliable resistance to PPV infection, there has been considerable interest in using genetic engineering methods for targeted genome modification of stone fruit trees to control Sharka disease caused by PPV. Among the many virus defense mechanisms, RNA interference is shown to be the most promising transgenic disease-control strategy in plant biotechnology. The present study describes the production of transgenic PPV resistant European plum “Startovaya” (P. domestica L.) through the Agrobacterium-mediated transformation of in vitro leaf explants. Due to organogenesis from leaves, the established protocol allows the genetic engineering of the plum genome without losing clonal fidelity of original cultivar. Seven independent transgenic plum lines containing the self-complementary fragments of PPV-CP gene sequence separated by a PDK intron were generated using hpt as a selective gene and uidA as a reporter gene. The transformation was verified through the histochemical staining for β-glucuronidase activity, PCR amplification of appropriate vector products from isolated genomic DNA and Southern blot analysis of hairpin PPV-CP gene fragments. To clarify the virus resistance, plum buds infected by PPV-M strain were grafted onto 1-year-old transgenic plants, which further were grown into mature trees in the greenhouse. As evaluated by RT-PCR, DAS-ELISA, Western blot, ImmunoStrip test, and visual observations, GM plum trees remained uninfected over 9 years. Infected branches that developed from grafted buds displayed obvious symptoms of Sharka disease over the years and maintained the high level of virus accumulation, whereby host transgenic trees had been constantly challenged with the pathogen. Since the virus was unable to spread to transgenic tissues, the stable expression of PPV-derived gene construct encoding intron-spliced hairpin RNAs provided a highly effective protection of plum trees against permanent viral infection. At the same time, this observation indicates the lack of the systemic spread of resistance from GM tissues to an infected plum graft even after years of joint growth.
A Lumped-Mass Model for Large Deformation Continuum Surfaces Actuated by Continuum Robotic Arms

Currently, flexible surfaces enabled to be actuated by robotic arms are experiencing high interest and demand for robotic applications in various areas such as healthcare, automotive, aerospace, and manufacturing. However, their design and control thus far has largely been based on “trial and error” methods requiring multiple trials and/or high levels of user specialization. Robust methods to realize flexible surfaces with the ability to deform into large curvatures therefore require a reliable, validated model that takes into account many physical and mechanical properties including elasticity, material characteristics, gravity, external forces, and thickness shear effects. The derivation of such a model would then enable the further development of predictive-based control methods for flexible robotic surfaces. This paper presents a lumped-mass model for flexible surfaces undergoing large deformation due to actuation by continuum robotic arms. The resulting model includes mechanical and physical properties for both the surface and actuation elements to predict deformation in multiple curvature directions and actuation configurations. The model is validated against an experimental system where measured displacements between the experimental and modeling results showed considerable agreement with a mean error magnitude of about 1% of the length of the surface at the final deformed shapes.
Thinking Against Burnout? An Individual’s Tendency to Engage in and Enjoy Thinking as a Potential Resilience Factor of Burnout Symptoms and Burnout-Related Impairment in Executive Functioning

The personality trait need for cognition (NFC) refers to individual differences in the tendency to engage in and enjoy cognitive endeavors. In today’s working world, which is characterized by increasing cognitive demands, NFC may contribute to resilience against work-related stress and burnout symptoms. We investigated this question in a large population-wide sample of 4,134 individuals (Study 1) and in a sample of 125 students (Study 2). NFC was consistently negatively related to the burnout facets emotional exhaustion and reduced personal efficacy of the Maslach burnout inventory and explained up to 10% additional variance in burnout symptoms over and above the five-factor model of personality. In the student sample, where stress factors are mainly cognitive in nature, NFC was the most relevant predictor. In this sample, we additionally investigated whether NFC might be a relevant moderator of the inconsistently found associations between burnout and impairments in cognitive functioning. The participants conducted three cognitive tasks (number–letter task, two-back task, and Go/NoGo task) that measure the executive functions switching, updating, and response inhibition, respectively. While burnout was slightly negatively related to working memory performance, NFC did not moderate the relationship between burnout and executive control which could be traced back to the young and healthy sample used to examine this research question. All in all, our results clearly suggest that NFC may be an important individual difference factor contributing to the resilience against burnout, especially if stress factors are cognitive in nature.
Comparative spatial lipidomics analysis reveals cellular lipid remodelling in different developmental zones of barley roots in response to salinity

Abstract Salinity‐induced metabolic, ionic, and transcript modifications in plants have routinely been studied using whole plant tissues, which do not provide information on spatial tissue responses. The aim of this study was to assess the changes in the lipid profiles in a spatial manner and to quantify the changes in the elemental composition in roots of seedlings of four barley cultivars before and after a short‐term salt stress. We used a combination of liquid chromatography–tandem mass spectrometry, inductively coupled plasma mass spectrometry, matrix‐assisted laser desorption/ionization mass spectrometry imaging, and reverse transcription – quantitative real time polymerase chain reaction platforms to examine the molecular signatures of lipids, ions, and transcripts in three anatomically different seminal root tissues before and after salt stress. We found significant changes to the levels of major lipid classes including a decrease in the levels of lysoglycerophospholipids, ceramides, and hexosylceramides and an increase in the levels of glycerophospholipids, hydroxylated ceramides, and hexosylceramides. Our results revealed that modifications to lipid and transcript profiles in plant roots in response to a short‐term salt stress may involve recycling of major lipid species, such as phosphatidylcholine, via resynthesis from glycerophosphocholine.
Newly educated care managers’ experiences of providing care for persons with stress-related mental disorders in the clinical primary care context

Objective Our aim was to explore how the care managers put the complex care manager task into practice and how they perceived their task, which was to facilitate effective, person-centred treatment for stress-related disorder concordant with evidence-based guidelines in primary care. Design This was a qualitative study using examination reports from the course for care managers. Systematic text condensation according to Malterud was used for the analysis. Setting Primary health care centres Subject Twenty-eight newly educated care managers in primary health care participated in the study. The median age was 50 (31–68) years. Twenty-seven were women and one was a man. Twenty-one were employed as nurses and seven as counsellors. Results The informants perceived the role as care manager as meaningful but at times complicated. To participate in teams and to work closely with the general practitioner was experienced as important. The co-ordinating function was emphasised as especially important, as well as the increased continuity in care. The dual role as care manager and counsellor was sometimes experienced as problematic. Conclusion The informants took advantage of the knowledge they had attained during the course. They perceived themselves as being a bridge between patients and other professionals. The result of having dual roles at the primary health care centre unexpectedly revealed difficulties for some professionals. The nurses seemed more familiar with the new way of working.
Parametric inference with universal function approximators

Machine learning models often excel in the accuracy of their predictions but are opaque due to their non-linear and non-parametric structure. This makes statistical inference challenging and disqualifies them from many applications where model interpretability is crucial. This paper proposes the Shapley regression framework as an approach for statistical inference on non-linear or non-parametric models. Inference is performed based on the Shapley value decomposition of a model, a pay-off concept from cooperative game theory. I show that universal approximators from machine learning are estimation consistent and introduce hypothesis tests for individual variable contributions, model bias and parametric functional forms. The inference properties of state-of-the-art machine learning models - like artificial neural networks, support vector machines and random forests - are investigated using numerical simulations and real-world data. The proposed framework is unique in the sense that it is identical to the conventional case of statistical inference on a linear model if the model is linear in parameters. This makes it a well-motivated extension to more general models and strengthens the case for the use of machine learning to inform decisions.
A Spiking Network for Inference of Relations Trained with Neuromorphic Backpropagation

The increasing need for intelligent sensors in a wide range of everyday objects requires the existence of low power information processing systems which can operate autonomously in their environment. In particular, merging and processing the outputs of different sensors efficiently is a necessary requirement for mobile agents with cognitive abilities. In this work, we present a multi-layer spiking neural network for inference of relations between stimuli patterns in dedicated neuromorphic systems. The system is trained with a new version of the backpropagation algorithm adapted to on-chip learning in neuromorphic hardware: Error gradients are encoded as spike signals which are propagated through symmetric synapses, using the same integrate-and-fire hardware infrastructure as used during forward propagation. We demonstrate the strength of the approach on an arithmetic relation inference task and on visual XOR on the MNIST dataset. Compared to previous, biologically-inspired implementations of networks for learning and inference of relations, our approach is able to achieve better performance with less neurons. Our architecture is the first spiking neural network architecture with on-chip learning capabilities, which is able to perform relational inference on complex visual stimuli. These features make our system interesting for sensor fusion applications and embedded learning in autonomous neuromorphic agents.
Receptor-Like Kinase Phosphorylation of Arabidopsis Heterotrimeric G-Protein Gα - Subunit AtGPA1

As molecular on-off switches, heterotrimeric G protein complexes, comprised of a Gα subunit and an obligate Gβγ dimer, transmit extracellular signals received by G protein– coupled receptors (GPCRs) to cytoplasmic targets that respond to biotic and abiotic stimuli. Signal transduction is modulated by phosphorylation of GPCRs and G protein complexes. In Arabidopsis thaliana, the Gα subunit AtGPA1 is phosphorylated by the receptor-like kinase (RLK) BRI1-ASSOCIATED Kinase 1 (BAK1), but the extent that other RLKs phosphorylates AtGPA1 is unknown. We mapped 22 trans-phosphorylation sites on AtGPA1 by 12 RLKs hypothesized to act in the Arabidopsis G protein signaling pathway. Cis-phosphorylation sites on these RLKs were also identified. BRI1, BAK1, and SERK1 have been reported as Ser/Thr and Tyr dual specificity kinases. We identified 4 more dual specificity kinases: IOS1, PSY1R, PEPR1, and AT2G37050. Multiple sites are present in the core AtGPA1 functional units, including pSer52 and pThr53 of the conserved P-loop that directly binds nucleotide/phosphate, pThr164 and pSer175 from αE helix in the intramolecular domain interface for nucleotide exchange and GTP hydrolysis, and pThr193 or pThr194 in Switch I (SwI) that coordinates nucleotide exchange and protein partner binding. Several AtGPA1 S/T phosphorylation sites are nucleotide-dependent phosphorylation patterns, such as S52/T53 in the P-loop and T193 and/or T194 in SwI.
Video Generation From Single Semantic Label Map

This paper proposes the novel task of video generation conditioned on a SINGLE semantic label map, which provides a good balance between flexibility and quality in the generation process. Different from typical end-to-end approaches, which model both scene content and dynamics in a single step, we propose to decompose this difficult task into two sub-problems. As current image generation methods do better than video generation in terms of detail, we synthesize high quality content by only generating the first frame. Then we animate the scene based on its semantic meaning to obtain temporally coherent video, giving us excellent results overall. We employ a cVAE for predicting optical flow as a beneficial intermediate step to generate a video sequence conditioned on the initial single frame. A semantic label map is integrated into the flow prediction module to achieve major improvements in the image-to-video generation process. Extensive experiments on the Cityscapes dataset show that our method outperforms all competing methods.
A Newton-Like Adaptive Blind Decision Feedback Equalization Scheme

The paper aims to give considerable insights into how the use of the well-known second-order Newton method along with a whitening filter may help adaptive blind decision feedback equalizer (DFE) achieve excellent performances. Our analytical and simulation results confirmed that the proposed Newton-like adaptive blind DFE scheme significantly outperformed the ex-isting adaptive blind DFE scheme in terms of both the symbol error rate (SER) and the mean- squared error (MSE) perfor-mances.
2-Entity RANSAC for robust visual localization in changing environment

Visual localization has attracted considerable attention due to its low-cost and stable sensor, which is desired in many applications, such as autonomous driving, inspection robots and unmanned aerial vehicles. However, current visual localization methods still struggle with environmental changes across weathers and seasons, as there is significant appearance variation between the map and the query image. The crucial challenge in this situation is that the percentage of outliers, i.e. incorrect feature matches, is high. In this paper, we derive minimal closed form solutions for 3D-2D localization with the aid of inertial measurements, using only 2 point matches or 1 point match and 1 line match. These solutions are further utilized in the proposed 2-entity RANSAC, which is more robust to outliers as both line and point features can be used simultaneously and the number of matches required for pose calculation is reduced. Furthermore, we introduce three feature sampling strategies with different advantages, enabling an automatic selection mechanism. With the mechanism, our 2-entity RANSAC can be adaptive to the environments with different distribution of feature types in different segments. Finally, we evaluate the method on both synthetic and real-world datasets, validating its performance and effectiveness in inter-session scenarios.
Analyzing GPU Tensor Core Potential for Fast Reductions

The Nvidia GPU architecture has introduced new computing elements such as the tensor cores, which are special processing units dedicated to perform fast matrix-multiply-accumulate (MMA) operations and accelerate Deep Learning applications. In this work we present the idea of using tensor cores for a different purpose such as the parallel arithmetic reduction problem, and propose a new GPU tensor-core based algorithm as well as analyze its potential performance benefits in comparison to a traditional GPU-based one. The proposed method, encodes the reduction of n numbers as a set of m × m MMA tensor-core operations (for Nvidia’s Volta architecture m = 16) and takes advantage from the fact that each MMA operation takes just one GPU cycle. When analyzing the cost under a simplified GPU computing model, the result is that the new algorithm manages to reduce a problem of n numbers in $T\left( n \right) = 5{\log _{{m^2}}}\left( n \right)$ steps with a speedup of $S = \frac{4}{5}{\log _2}\left( {{m^2}} \right)$.
Chemical and Structural Diversity of Hybrid Layered Double Perovskite Halides.

Hybrid halide double perovskites are a class of compounds attracting growing interest because of their richness of structure and property. Two-dimensional (2D) derivatives of hybrid double perovskites are formed by the incorporation of organic spacer cations into three-dimensional (3D) double perovskites. Here, we report a series of seven new layered double perovskite halides with propylammonium (PA), octylammonium (OCA), and 1,4-butydiammonium (BDA) cations. The general formulae of the compounds are AmMIMIIIX8 (single-layered Ruddlesden-Popper with m = 4 and A = PA or OCA, and single-layered Dion-Jacobson with m = 2 and A = BDA, MI = Ag, MIII = In or Bi, X = Cl or Br) and PA2CsMIMIIIBr7 (bi-layered, with MI = Ag, MIII = In or Bi). These families of compounds demonstrate great versatility, with tunable layer thickness, the ability to vary the interlayer spacing, and the ability to selectively tune the band gap by varying the MI and MIII cations along with the halide anions. The band gap of the single-layered materials varies from 2.41 eV for PA4AgBiBr8 to 3.96 eV for PA4AgInCl8. Photoluminescent emission spectra of the layered double perovskites at low-temperature (100 K) are reported, and density functional theory electronic structure calculations are presented to understand the nature of the band gap evolution. The development of new structural and compositions in layered double perovskite halides enhances the understanding of structure-property relations in this important family.
An outbreak of hepatitis A in Canada: The use of a control bank to conduct a case-control study

Abstract An outbreak of 18 cases of hepatitis A virus infection across five Canadian provinces was investigated. Case onsets occurred between October 2017 and May 2018. A retrospective matched case-control study was conducted to identify the likely source of the outbreak. Three matched controls were recruited for each case using a previously established control bank, supplemented by landline and cell phone call lists. Univariate and multivariate matched analyses were conducted to identify a potential outbreak source. Seventy-two per cent of controls were recruited through the control bank, and required on average 25.5 calls per recruited control; 20% of controls were recruited through a landline sample and 8% of controls were recruited through a cell phone sample, requiring an average of 847.3 and 331.7 calls per recruited control, respectively. Results of the analysis pointed to shrimp/prawns (odds ratio (OR) 15.75, p = 0.01) and blackberries (OR 7.21, p = 0.02) as foods of interest, however, an outbreak source could not be confirmed. The control bank proved to be a more efficient method for control recruitment than random call lists. Expanding the control bank size and using alternative methods, such as online surveys, may prove beneficial for increasing the timeliness of a case-control study during an outbreak investigation.