Miracle-dz/UniFAR-FTUs huggingface dataset:
Simplified analysis of fracture behaviour of a Francis hydraulic turbine runner blade

Each welded connection between blades and band or crown of a Francis hydraulic turbine runner can be considered as a T-joint subjected to pure bending induced by the water action. A semi-elliptical crack is assumed to exist at the surface of one of the aforementioned welded connections. The actual geometry of the T-joint can be simplified, that is, only the cracked plate (representing the blade) under a given stress distribution acting on the defect faces is examined. A numerical procedure already proposed by the authors to compute the stress-intensity factor (SIF) along the crack front is here applied by introducing some changes to simplify such computations. The obtained values of SIF are compared with some results available in the literature.
Biomimetic oral mucin from polymer micelle networks

OF DISSERTATION BIOMIMETIC ORAL MUCIN FROM POLYMER MICELLE NETWORKS Mucin networks are formed by the complexation of bottlebrush-like mucin glycoprotein with other small molecule glycoproteins. These glycoproteins create nanoscale strands that then arrange into a nanoporous mesh. These networks play an important role in ensuring surface hydration, lubricity and barrier protection. In order to understand the functional behavior in mucin networks, it is important to decouple their chemical and physical effects responsible for generating the fundamental property-function relationship. To achieve this goal, we propose to develop a synthetic biomimetic mucin using a layer-by-layer (LBL) deposition approach. In this work, a hierarchical 3-dimensional structures resembling natural mucin networks was generated using affinity-based interactions on synthetic and biological surfaces. Unlike conventional polyelectrolyte-based LBL methods, preassembled biotin-functionalized filamentous (worm-like) micelles was utilized as the network building block, which from complementary additions of streptavidin generated synthetic networks of desired thickness. The biomimetic nature in those synthetic networks are studied by evaluating its structural and bio-functional properties. Structurally, synthetic networks formed a nanoporous mesh. The networks demonstrated excellent surface hydration property and were able capable of microbial capture. Those functional properties are akin to that of natural mucin networks. Further, the role of synthetic mucin as a drug delivery vehicle, capable of providing localized and tunable release was demonstrated. By incorporating antibacterial curcumin drug loading within synthetic networks, bacterial growth inhibition was also demonstrated. Thus, such bioactive interfaces can serve as a model for independently characterizing mucin network properties and through its role as a drug carrier vehicle it presents exciting future opportunities for localized drug delivery, in regenerative applications and as bio-functional implant coats.
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series

We study sparse principal component analysis (sparse PCA) for high dimensional multivariate vector autoregressive (VAR) time series. By treating the transition matrix as a nuisance parameter, we show that sparse PCA can be directly applied on analyzing multivariate time series as if the data are i.i. d. generated. Under a double asymptotic framework in which both the length of the sample period T and dimensionality d of the time series can increase (with possibly d T ), we provide explicit rates of convergence of the angle between the estimated and population leading eigenvectors of the time series covariance matrix. Our results suggest that the spectral norm of the transition matrix plays a pivotal role in determining the nal rates of convergence. Implications of such a general result is further illustrated using concrete examples. The results of this paper have impacts on dierent applications, including nancial time series, biomedical imaging, and social media, etc.
Ma-Huang-Fu-Zi-Xi-Xin Decoction for Allergic Rhinitis: A Systematic Review

Background The treatment effects and safety of Ma-Huang-Fu-Zi-Xi-Xin decoction for patients with allergic rhinitis have yet to be clarified. Objectives The aim of this study is to evaluate the effects and safety of Ma-Huang-Fu-Zi-Xi-Xin decoction in patients with allergic rhinitis. Methods We searched PubMed, EMBASE (Excerpta Medical Database), Cochrane Library, Chinese Cochrane Centre's Controlled Trials Register Platform, Wanfang Chinese Digital Periodical and Conference Database, China National Knowledge Infrastructure (CNKI) Database, and VIP Chinese Science and Technique Journals Database to collect randomized controlled trials of Ma-Huang-Fu-Zi-Xi-Xin decoction (MHFZXXD) for allergic rhinitis (AR) prior to May 8, 2017. RevMan 5.3 software was used to conduct a meta-analysis. GRADE methodology was applied to evaluate the evidence quality for each outcome. Results Six randomized controlled trials (RCTs) involving 576 participants (10–78 years old) were included. A meta-analysis revealed that the overall effect of MHFZXXD for AR was not better than western medical treatment (RR: 0.41; 95% CI: 0.26–0.65; P = 0.0001) for all included studies. However, the evidence quality of these western medical intervention studies was low or very low due to a high risk of bias, small sample sizes, and poor-quality design.
REST corepressors RCOR1 and RCOR2 and the repressor INSM1 regulate the proliferation–differentiation balance in the developing brain

Significance Nervous system development involves a delicate balance between neural progenitor proliferation and neuronal differentiation. Repressors and corepressors each affect this balance, but in many cases, existence of the complexes in vivo has not been shown. Here, we identify a repressor/corepressor complex in embryonic brain consisting of Insulinoma-associated 1 (INSM1) and the RE1 Silencing Transcription factor (REST) corepressors RCOR1 and RCOR2. Elimination of RCOR1 and RCOR2, or INSM1, robustly promotes neural proliferation over neuronal and oligodendrocyte differentiation. Further, their elimination results in overexpression of REST, a direct target gene of INSM1. Normalizing REST levels in the RCOR1/2-deficient brain partially restores aberrant brain morphology. Our results identify a repressor complex required for critical events during normal brain development. The transcriptional events that lead to the cessation of neural proliferation, and therefore enable the production of proper numbers of differentiated neurons and glia, are still largely uncharacterized. Here, we report that the transcription factor Insulinoma-associated 1 (INSM1) forms complexes with RE1 Silencing Transcription factor (REST) corepressors RCOR1 and RCOR2 in progenitors in embryonic mouse brain. Mice lacking both RCOR1 and RCOR2 in developing brain die perinatally and generate an abnormally high number of neural progenitors at the expense of differentiated neurons and oligodendrocyte precursor cells. In addition, Rcor1/2 deletion detrimentally affects complex morphological processes such as closure of the interganglionic sulcus. We find that INSM1, a transcription factor that induces cell-cycle arrest, is coexpressed with RCOR1/2 in a subset of neural progenitors and forms complexes with RCOR1/2 in embryonic brain. Further, the Insm1−/− mouse phenocopies predominant brain phenotypes of the Rcor1/2 knockout. A large number of genes are concordantly misregulated in both knockout genotypes, and a majority of the down-regulated genes are targets of REST. Rest transcripts are up-regulated in both knockouts, and reducing transcripts to control levels in the Rcor1/2 knockout partially rescues the defect in interganglionic sulcus closure. Our findings indicate that an INSM1/RCOR1/2 complex controls the balance of proliferation and differentiation during brain development.
Double-Task Deep Q-Learning with Multiple Views

Deep Reinforcement learning enables autonomous robots to learn large repertories of behavioral skill with minimal human intervention. However, the applications of direct deep reinforcement learning have been restricted. For complicated robotic systems, these limitations result from high dimensional action space, high freedom of robotic system and high correlation between images. In this paper we introduce a new definition of action space and propose a double-task deep Q-Network with multiple views (DMDQN) based on double-DQN and dueling-DQN. For extension, we define multi-task model for more complex jobs. Moreover data augment policy is applied, which includes auto-sampling and action-overturn. The exploration policy is formed when DMDQN and data augment are combined. For robotic system's steady exploration, we designed the safety constraints according to working condition. Our experiments show that our double-task DQN with multiple views performs better than the single-task and single-view model. Combining our DMDQN and data augment, the robotic system can reach the object in an exploration way.
A Lytic Polysaccharide Monooxygenase with Broad Xyloglucan Specificity from the Brown-Rot Fungus Gloeophyllum trabeum and Its Action on Cellulose-Xyloglucan Complexes

ABSTRACT Fungi secrete a set of glycoside hydrolases and lytic polysaccharide monooxygenases (LPMOs) to degrade plant polysaccharides. Brown-rot fungi, such as Gloeophyllum trabeum, tend to have few LPMOs, and information on these enzymes is scarce. The genome of G. trabeum encodes four auxiliary activity 9 (AA9) LPMOs (GtLPMO9s), whose coding sequences were amplified from cDNA. Due to alternative splicing, two variants of GtLPMO9A seem to be produced, a single-domain variant, GtLPMO9A-1, and a longer variant, GtLPMO9A-2, which contains a C-terminal domain comprising approximately 55 residues without a predicted function. We have overexpressed the phylogenetically distinct GtLPMO9A-2 in Pichia pastoris and investigated its properties. Standard analyses using high-performance anion-exchange chromatography–pulsed amperometric detection (HPAEC-PAD) and mass spectrometry (MS) showed that GtLPMO9A-2 is active on cellulose, carboxymethyl cellulose, and xyloglucan. Importantly, compared to other known xyloglucan-active LPMOs, GtLPMO9A-2 has broad specificity, cleaving at any position along the β-glucan backbone of xyloglucan, regardless of substitutions. Using dynamic viscosity measurements to compare the hemicellulolytic action of GtLPMO9A-2 to that of a well-characterized hemicellulolytic LPMO, NcLPMO9C from Neurospora crassa revealed that GtLPMO9A-2 is more efficient in depolymerizing xyloglucan. These measurements also revealed minor activity on glucomannan that could not be detected by the analysis of soluble products by HPAEC-PAD and MS and that was lower than the activity of NcLPMO9C. Experiments with copolymeric substrates showed an inhibitory effect of hemicellulose coating on cellulolytic LPMO activity and did not reveal additional activities of GtLPMO9A-2. These results provide insight into the LPMO potential of G. trabeum and provide a novel sensitive method, a measurement of dynamic viscosity, for monitoring LPMO activity. IMPORTANCE Currently, there are only a few methods available to analyze end products of lytic polysaccharide monooxygenase (LPMO) activity, the most common ones being liquid chromatography and mass spectrometry. Here, we present an alternative and sensitive method based on measurement of dynamic viscosity for real-time continuous monitoring of LPMO activity in the presence of water-soluble hemicelluloses, such as xyloglucan. We have used both these novel and existing analytical methods to characterize a xyloglucan-active LPMO from a brown-rot fungus. This enzyme, GtLPMO9A-2, differs from previously characterized LPMOs in having broad substrate specificity, enabling almost random cleavage of the xyloglucan backbone. GtLPMO9A-2 acts preferentially on free xyloglucan, suggesting a preference for xyloglucan chains that tether cellulose fibers together. The xyloglucan-degrading potential of GtLPMO9A-2 suggests a role in decreasing wood strength at the initial stage of brown rot through degradation of the primary cell wall.
Computational investigation of surface freezing in a molecular model of water

Significance Ice nucleation at interfaces plays an important role in atmospheric processes. Because of the insufficient spatiotemporal resolution of the existing experimental techniques, however, it is very difficult to understand how interfaces affect freezing at the molecular level. In particular, whether a vapor–liquid interface enhances or suppresses freezing at its vicinity is still a major unresolved question in contemporary ice physics. We address this question computationally by directly calculating the ice nucleation rate in a freestanding nanofilm of supercooled water modeled using an accurate molecular model and observe seven orders of magnitude enhancement. We observe that freezing initiates away from the air–water interface, in regions of the film favorable to the formation of cubic ice. Water freezes in a wide variety of low-temperature environments, from meteors and atmospheric clouds to soil and biological cells. In nature, ice usually nucleates at or near interfaces, because homogenous nucleation in the bulk can only be observed at deep supercoolings. Although the effect of proximal surfaces on freezing has been extensively studied, major gaps in understanding remain regarding freezing near vapor–liquid interfaces, with earlier experimental studies being mostly inconclusive. The question of how a vapor–liquid interface affects freezing in its vicinity is therefore still a major open question in ice physics. Here, we address this question computationally by using the forward-flux sampling algorithm to compute the nucleation rate in a freestanding nanofilm of supercooled water. We use the TIP4P/ice force field, one of the best existing molecular models of water, and observe that the nucleation rate in the film increases by seven orders of magnitude with respect to bulk at the same temperature. By analyzing the nucleation pathway, we conclude that freezing in the film initiates not at the surface, but within an interior region where the formation of double-diamond cages (DDCs) is favored in comparison with the bulk. This, in turn, facilitates freezing by favoring the formation of nuclei rich in cubic ice, which, as demonstrated by us earlier, are more likely to grow and overcome the nucleation barrier. The films considered here are ultrathin because their interior regions are not truly bulk-like, due to their subtle structural differences with the bulk.
Preliminary validation of a self‐efficacy scale for pediatric chronic illness

BACKGROUND Tracking self-efficacy may be useful for identifying children at risk for medical noncompliance. We created the Pediatric Rating of Chronic Illness Self-Efficacy (PRCISE) to measure self-efficacy in youth dealing with a chronic illness. METHOD Data were collected from 217 families where one child aged 7-20 (Mage = 13.62, SDage = 2.92; 62.7% Latino, 58.1% female) had a chronic illness. Parent participants provided demographic information. Youth completed a depression measure, the Patient Health Questionnaire for Adolescents and the PRCISE. To determine the underlying latent structure of the scale, an exploratory factor analysis was conducted using parallel analysis. We also carried out two multiple linear regressions to explore the data and establish preliminary predictive validity. RESULTS The measure was reduced to 15 items, demonstrating a one-factor solution with strong reliability. Predictors of lower self-efficacy included having parents who had not attended college, being African American, and having higher Patient Health Questionnaire for Adolescents scores, R2 = . 23, F(11, 174) = 5.62, p < . 001. Main effects were qualified by a two-way interaction, such that the decrease in PRCISE scores associated with depressive symptoms was attenuated in children with less educated parents. In terms of predictive validity, higher PRCISE scores unexpectedly predicted more number of emergency room visits, R2 = . 12, F(9, 113) = 2.73, p < . 01. CONCLUSIONS The PRCISE appears to be a reliable measure of a single self-efficacy construct. Secondary analyses revealed important health disparities in pediatric chronic illness self-efficacy. Next steps may include validation of the PRCISE using confirmatory factor analysis.
Listeria monocytogenes in Stone Fruits Linked to a Multistate Outbreak: Enumeration of Cells and Whole-Genome Sequencing

ABSTRACT In 2014, the identification of stone fruits contaminated with Listeria monocytogenes led to the subsequent identification of a multistate outbreak. Simultaneous detection and enumeration of L. monocytogenes were performed on 105 fruits, each weighing 127 to 145 g, collected from 7 contaminated lots. The results showed that 53.3% of the fruits yielded L. monocytogenes (lower limit of detection, 5 CFU/fruit), and the levels ranged from 5 to 2,850 CFU/fruit, with a geometric mean of 11.3 CFU/fruit (0.1 CFU/g of fruit). Two serotypes, IVb-v1 and 1/2b, were identified by a combination of PCR- and antiserum-based serotyping among isolates from fruits and their packing environment; certain fruits contained a mixture of both serotypes. Single nucleotide polymorphism (SNP)-based whole-genome sequencing (WGS) analysis clustered isolates from two case-patients with the serotype IVb-v1 isolates and distinguished outbreak-associated isolates from pulsed-field gel electrophoresis (PFGE)-matched, but epidemiologically unrelated, clinical isolates. The outbreak-associated isolates differed by up to 42 SNPs. All but one serotype 1/2b isolate formed another WGS cluster and differed by up to 17 SNPs. Fully closed genomes of isolates from the stone fruits were used as references to maximize the resolution and to increase our confidence in prophage analysis. Putative prophages were conserved among isolates of each WGS cluster. All serotype IVb-v1 isolates belonged to singleton sequence type 382 (ST382); all but one serotype 1/2b isolate belonged to clonal complex 5. IMPORTANCE WGS proved to be an excellent tool to assist in the epidemiologic investigation of listeriosis outbreaks. The comparison at the genome level contributed to our understanding of the genetic diversity and variations among isolates involved in an outbreak or isolates associated with food and environmental samples from one facility. Fully closed genomes increased our confidence in the identification and comparison of accessory genomes. The diversity among the outbreak-associated isolates and the inclusion of PFGE-matched, but epidemiologically unrelated, isolates demonstrate the high resolution of WGS. The prevalence and enumeration data could contribute to our further understanding of the risk associated with Listeria monocytogenes contamination, especially among high-risk populations.
Pharmacokinetic de-risking tools for selection of monoclonal antibody lead candidates

ABSTRACT Pharmacokinetic studies play an important role in all stages of drug discovery and development. Recent advancements in the tools for discovery and optimization of therapeutic proteins have created an abundance of candidates that may fulfill target product profile criteria. Implementing a set of in silico, small scale in vitro and in vivo tools can help to identify a clinical lead molecule with promising properties at the early stages of drug discovery, thus reducing the labor and cost in advancing multiple candidates toward clinical development. In this review, we describe tools that should be considered during drug discovery, and discuss approaches that could be included in the pharmacokinetic screening part of the lead candidate generation process to de-risk unexpected pharmacokinetic behaviors of Fc-based therapeutic proteins, with an emphasis on monoclonal antibodies.
A Comparative Study on the Textile Processing of Carbon and Multifunctional Glass Fiber Sensor Yarns for Structural Health Monitoring  

In this comparative study two sensor yarns, such as carbon filament yarns and carbon nanotube coated glass filament yarns are analyzed regarding their electrical property changes during textile manufacturing into multi‐layer weft knitted structures as well as during compression molding into a composite plate due to the different electro‐mechanical behavior, various sensitivities, and changing ways of acting as an in‐situ sensor: yarns act either as a conductive fiber itself (carbon) or as an electrical conductive sizing (CNT‐coated glass). Both sensor yarns under investigation have to be considered differently with regard to changes in the electrical conductivity due to mechanical loading during textile processing and possible healing of cracks during compression molding.
Learning-Based Inverse Dynamics of Human Motion

In this work we propose a learning-based algorithm for the inverse dynamics problem of human motion. Our method uses Random Forest regression to predict joint torques and ground reaction forces from motion patterns. For this purpose we extend temporally incomplete force plate data via a direct Random Forest regression from motion parameters to force vectors. Based on the resulting completed data we estimate underlying joint torques using a modified physics-based predictive dynamics approach. The optimization results for model states and controls act as predictors and responses for the final Random Forest regression from motion to joint torques and ground reaction forces. The evaluation of our method includes a comparison to state-of-the-art results and to measured force plate data and a demonstration of the robust performance under influence of noisy and occluded input.
The Development of a Novel Controlled Release Drug Delivery System

The aim of this research was to formulate, characterise and assess the feasibility of a novel drug delivery system known as the in situ gelling matrix (ISGM) where a hydrophilic polymer is suspended in a non-aqueous solvent that converts into a gel when injected subcutaneously or intramuscularly thus giving a controlled release matrix for a drug. Although the concept has been patented with claims that this kind of drug delivery is achievable in theory for a wide variety of candidate substances, actual formulation studies for making a commercially viable product for this technology are completely lacking in practice. The research embodied in this thesis addresses this lack. Initial studies involved conducting a biocompatibility study using the HET-CAM (hens egg test – chorioallantoic membrane) test on a range of possible ingredients for the delivery system. The materials deemed biocompatible were then carried through to a screening process where the physical stability of the hydrophilic polymers in non-aqueous solvents was monitored. It was found that the hydrophilic polymers tested sedimented rapidly in the non-aqueous solvents indicating such a system was not physically stable. Consequently, density-inducing or viscosity-inducing agents were added to the non-aqueous solvents to retard the sedimentation rate. The addition of polycarbophil, a viscosity-inducing agent, clearly increased the viscosity of the system. However, undesirable formation of polycarbophil globules occurred during the manufacturing process, which caused batch-to-batch variations in the viscosity of the continuous phase. Various manufacturing methods were tested before arriving at the optimum procedure to prevent globule formation using a high speed dispersion tool. A final physical sedimentation analysis of candidate continuous phases and hydrophilic polymers was conducted for determining the ideal combination of ingredients to use in the system. These investigations finally led to the adoption of an optimum mix of components consisting of 10% (w/w) hydroxypropyl methylcellulose (HPMC) (the hydrophilic polymer) suspended in a continuous phase of propylene glycol (the non-aqueous solvent) containing 0.67% (w/w) polycarbophil (the viscosity inducing agent). Using this mix of components, the in situ gelling matrix system was then subjected to various characterisation studies including infrared (IR), differential