Miracle-dz/UniFAR-FTUs huggingface dataset:
Epithelial defect repair in the auricle and auditory meatus by grafting with cultured adipose-derived mesenchymal stem cell aggregate-extracellular matrix

Background: Several patients experience persistent otorrhea after a flawless surgical procedure because of insufficient epithelial healing. Several efforts, such as autologous tissue allograft and xenograft, have been made to halt otorrhea. However, a stable technology to induce temporal epithelial repair is yet to be established. Therefore, this study aims to investigate whether implantation of seeding adipose-derived mesenchymal stem cell (ADMSC) aggregates on extracellular matrix (ECM; herein, ADMSC aggregate-ECM) into damaged skin wound promotes skin regeneration. Methods: ADMSC aggregate-ECM was prepared using a previously described procedure that isolated ADMSCs from rabbits and applied to the auricle and auditory meatus wound beds of New Zealand white rabbits. Wound healing was assessed by general observation and hematoxylin and eosin (H&E) staining. Secretion of growth factor of the tissue was evaluated by western blotting. Two other groups, namely, ECM and control, were used. Comparisons of three groups were conducted by one-way analysis of variance analysis. Results: ADMSCs adhered tightly to the ECM and quickly formed cell sheets. At 2 weeks, general observation and H&E staining indicated that the wound healing rates in the ADMSC aggregate-ECM (69.02 ± 6.36%) and ECM (59.32 ± 4.10%) groups were higher than that in the control group (43.74 ± 12.15%; P = 0.005, P < 0.001, respectively) in ear auricle excisional wounds. At 7 weeks, The scar elevation index was evidently reduced in the ADMSC aggregate-ECM (2.08 ± 0.87) and ECM (2.31 ± 0.33) groups compared with the control group (4.06 ± 0.45; P < 0.001, P < 0.001, respectively). In addition, the scar elevation index of the ADMSC aggregate-ECM group reached the lowest rate 4 weeks in advance. In auditory meatus excisional wounds, the ADMSC aggregate-ECM group had the largest range of normal skin-like structure at 4 weeks. The ADMSC aggregate–ECM and ECM groups secreted increased amounts of growth factors that contributed to skin regeneration at weeks 1 and 2, respectively. Conclusions: ADMSC aggregate-ECM and ECM are effective repair materials for wound healing, especially ADMSC aggregate-ECM. This approach will provide a meaningful experimental basis for mastoid epithelium repair in subsequent clinical trials.
Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning

The ambiguous annotation criteria bring into the divergence of Chinese Word Segmentation (CWS) datasets with various granularities. Multi-criteria learning leverage the annotation style of individual datasets and mine their common basic knowledge. In this paper, we proposed a domain adaptive segmenter to capture diverse criteria of datasets. Our model is based on Bidirectional Encoder Representations from Transformers (BERT), which is responsible for introducing external knowledge. We also optimize its computational efficiency via model pruning, quantization, and compiler optimization. Experiments show that our segmenter outperforms the previous results on 10 CWS datasets and is faster than the previous state-of-the-art Bi-LSTM-CRF model.
GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks

Graph Neural Networks (GNNs) are a powerful tool for machine learning on graphs. GNNs combine node feature information with the graph structure by using neural networks to pass messages through edges in the graph. However, incorporating both graph structure and feature information leads to complex non-linear models and explaining predictions made by GNNs remains to be a challenging task. Here we propose GnnExplainer, a general model-agnostic approach for providing interpretable explanations for predictions of any GNN-based model on any graph-based machine learning task (node and graph classification, link prediction). In order to explain a given node's predicted label, GnnExplainer provides a local interpretation by highlighting relevant features as well as an important subgraph structure by identifying the edges that are most relevant to the prediction. Additionally, the model provides single-instance explanations when given a single prediction as well as multi-instance explanations that aim to explain predictions for an entire class of instances/nodes. We formalize GnnExplainer as an optimization task that maximizes the mutual information between the prediction of the full model and the prediction of simplified explainer model. We experiment on synthetic as well as real-world data. On synthetic data we demonstrate that our approach is able to highlight relevant topological structures from noisy graphs. We also demonstrate GnnExplainer to provide a better understanding of pre-trained models on real-world tasks. GnnExplainer provides a variety of benefits, from the identification of semantically relevant structures to explain predictions to providing guidance when debugging faulty graph neural network models.
A Unified Formulation for Visual Odometry*

Monocular Odometry systems can be broadly categorized as being either Direct, Indirect, or a hybrid of both. While Indirect systems process an alternative image representation to compute geometric residuals, Direct methods process the image pixels directly to generate photometric residuals. Both paradigms have distinct but often complementary properties. This paper presents a Unified Formulation for Visual Odometry, referred to as UFVO, with the following key contributions: (1) a tight coupling of photometric (Direct) and geometric (Indirect) measurements using a joint multi-objective optimization, (2) the use of a utility function as a decision maker that incorporates prior knowledge on both paradigms, (3) descriptor sharing, where a feature can have more than one type of descriptor and its different descriptors are used for tracking and mapping, (4) the depth estimation of both corner features and pixel features within the same map using an inverse depth parametrization, and (5) a corner and pixel selection strategy that extracts both types of information, while promoting a uniform distribution over the image domain. Experiments show that our proposed system can handle large inter-frame motions, inherits the sub-pixel accuracy of direct methods, can run efficiently in real-time, can generate an Indirect map representation at a marginal computational cost when compared to traditional Indirect systems, all while outperforming state of the art in Direct, Indirect and hybrid systems.
Environmental Toxicology and Chemistry

Quagga mussels (Dreissena rostriformis burgensis) are a highly invasive aquatic species to North America, capable of filtering large volumes of water and causing severe ecological and economic impacts. Their range has been expanding since they first invaded the Great Lakes in the 1980s. To predict their spread, it is crucial to understand environmental parameters, which facilitate their range expansion. Two factors likely to influence their distribution include calcium and temperature, because the former is vital for shell development and the latter for metabolic activity. When these factors are optimal for mussels’ fitness, the filtration rate has the potential to be maximized if other environmental conditions are also favorable, thus enabling mussels to exploit their growth potential. Deviations from optimal conditions likely result in filtration‐ rate decline. We identify calcium concentrations and temperatures that maximize the mussel filtration rate for 2 phytoplankton species: Ankistrodesmus facaltus, a common food source for quagga mussels, and a less palatable Microcystis icthyoblabe. In laboratory experiments, filtration rates were measured through cell counts after 24 h of filtration when exposed to a range of temperatures between 2 and 30 °C, and calcium concentrations between 0 and 180mg/L. Response surface methodology was used to identify a maximum filtration rate, which occurred at 22mL/mg/h at 137mg/L of calcium carbonate and 26 °C when fed Ankistrodesmus. To establish a quagga mussel population in a new water source, optimum conditions are required; thus, this information can be used to rank the relative susceptibility of water bodies to invasion by quagga mussels. Environ Toxicol Chem 2020;39:410–418. © 2019 SETAC
Partial Order Pruning: For Best Speed/Accuracy Trade-Off in Neural Architecture Search

Achieving good speed and accuracy trade-off on a target platform is very important in deploying deep neural networks in real world scenarios. However, most existing automatic architecture search approaches only concentrate on high performance. In this work, we propose an algorithm that can offer better speed/accuracy trade-off of searched networks, which is termed "Partial Order Pruning''. It prunes the architecture search space with a partial order assumption to automatically search for the architectures with the best speed and accuracy trade-off. Our algorithm explicitly takes profile information about the inference speed on the target platform into consideration. With the proposed algorithm, we present several Dongfeng (DF) networks that provide high accuracy and fast inference speed on various application GPU platforms. By further searching decoder architectures, our DF-Seg real-time segmentation networks yield state-of-the-art speed/accuracy trade-off on both the {target embedded device} and the high-end GPU.
Brief Story on Prostaglandins, Inhibitors of their Synthesis, Hematopoiesis, and Acute Radiation Syndrome

Prostaglandins and inhibitors of their synthesis (cyclooxygenase (COX) inhibitors, non-steroidal anti-inflammatory drugs) were shown to play a significant role in the regulation of hematopoiesis. Partly due to their hematopoiesis-modulating effects, both prostaglandins and COX inhibitors were reported to act positively in radiation-exposed mammalian organisms at various pre- and post-irradiation therapeutical settings. Experimental efforts were targeted at finding pharmacological procedures leading to optimization of therapeutical outcomes by minimizing undesirable side effects of the treatments. Progress in these efforts was obtained after discovery of selective inhibitors of inducible selective cyclooxygenase-2 (COX-2) inhibitors. Recent studies have been able to suggest the possibility to find combined therapeutical approaches utilizing joint administration of prostaglandins and inhibitors of their synthesis at optimized timing and dosing of the drugs which could be incorporated into the therapy of patients with acute radiation syndrome.
The Year of the Rat: The Rat Genome Database at 20: a multi-species knowledgebase and analysis platform

Abstract Formed in late 1999, the Rat Genome Database (RGD, https://rgd.mcw.edu) will be 20 in 2020, the Year of the Rat. Because the laboratory rat, Rattus norvegicus, has been used as a model for complex human diseases such as cardiovascular disease, diabetes, cancer, neurological disorders and arthritis, among others, for >150 years, RGD has always been disease-focused and committed to providing data and tools for researchers doing comparative genomics and translational studies. At its inception, before the sequencing of the rat genome, RGD started with only a few data types localized on genetic and radiation hybrid (RH) maps and offered only a few tools for querying and consolidating that data. Since that time, RGD has expanded to include a wealth of structured and standardized genetic, genomic, phenotypic, and disease-related data for eight species, and a suite of innovative tools for querying, analyzing and visualizing this data. This article provides an overview of recent substantial additions and improvements to RGD’s data and tools that can assist researchers in finding and utilizing the data they need, whether their goal is to develop new precision models of disease or to more fully explore emerging details within a system or across multiple systems.
Lenses and Learners

Lenses are a well-established structure for modelling bidirectional transformations, such as the interactions between a database and a view of it. Lenses may be symmetric or asymmetric, and may be composed, forming the morphisms of a monoidal category. More recently, the notion of a learner has been proposed: these provide a compositional way of modelling supervised learning algorithms, and again form the morphisms of a monoidal category. In this paper, we show that the two concepts are tightly linked. We show both that there is a faithful, identity-on-objects symmetric monoidal functor embedding a category of asymmetric lenses into the category of learners, and furthermore there is such a functor embedding the category of learners into a category of symmetric lenses.
Gradient Descent based Optimization Algorithms for Deep Learning Models Training

In this paper, we aim at providing an introduction to the gradient descent based optimization algorithms for learning deep neural network models. Deep learning models involving multiple nonlinear projection layers are very challenging to train. Nowadays, most of the deep learning model training still relies on the back propagation algorithm actually. In back propagation, the model variables will be updated iteratively until convergence with gradient descent based optimization algorithms. Besides the conventional vanilla gradient descent algorithm, many gradient descent variants have also been proposed in recent years to improve the learning performance, including Momentum, Adagrad, Adam, Gadam, etc., which will all be introduced in this paper respectively.
Glucose-Regulated Protein 78 Signaling Regulates Hypoxia-Induced Epithelial–Mesenchymal Transition in A549 Cells

Objective: Metastasis and therapeutic resistance are the major determinants of lung cancer progression and high mortality. Epithelial–mesenchymal transition (EMT) plays a key role in the metastasis and therapeutic resistance. Highly expressed glucose-regulated protein 78 (GRP78) is a poor prognostic factor in lung cancer and possibly correlated with EMT. This study aims to examine whether the up-regulation of GRP78 is involved in EMT in lung adenocarcinoma and explore the underlying downstream molecular pathways. Study Design: EMT was assessed by analysis of cell morphology and expression of EMT protein markers in A549 cells under normoxia, hypoxia and silencing GRP78 conditions. The expression levels of Smad2/3, Src, and MAPK (p38, ERK, and JNK) proteins were examined by Western blot analysis under hypoxia and treatments with phosphorylation inhibitors. Results: Under hypoxic conditions, the EMT morphology significantly changed and the GRP78 expression was significantly up-regulated in A549 cells compared with those in normoxia control. The expression and phosphorylation levels of smad2/3, Src, p38, ERK, and JNK were also upregulated. When GRP78 was silenced, EMT was inhibited, and the levels of phospho-smad2/3, phospho-Src, phospho-p38, phospho-ERK, and phospho-JNK were suppressed. When the activation of Smad2/3, Src, p38, ERK, and JNK was inhibited, EMT was also inhibited. The inhibition effect on EMT by these phosphorylation inhibitors was found to be weaker than that of GRP78 knockdown. Conclusions: Hypoxia-induced EMT in A549 cells is regulated by GRP78 signaling pathways. GRP78 promotes EMT by activating Smad2/3 and Src/MAPK pathways. Hence, GRP78 might be a potential target for treatment of lung adenocarcinoma.
Sustainable Strategies to Prevent Iron Deficiency, Improve Yield and Berry Composition in Blueberry (Vaccinium spp.)

The aim of this investigation was to study the effect of sustainable strategies to correct iron deficiency in blueberries, based on Fe-heme applications or intercropping with graminaceous species, on yield, and berry quality variables. The experiment was conducted in a blueberry orchard established in a sub-alkaline soil. The association with grasses increased the crop load and yield (only Festuca rubra), and decreased the skin/flesh ratio. In addition, these treatments increased anthocyanins as well as some hydroxybenzoic acids, hydroxycinnamic acids, flavanols, and flavonol concentrations in skins with a similar effectiveness as Fe-EDDHA, whereas the Fe-heme applications did not influence such parameters. Moreover, data revealed that the association with both grasses decreased the firmness of the berries, whereas none of the treatments assessed changed the soluble solids, pH, acidity, and the soluble solids/acidity rate compared to the control. These results suggest that Fe nutrition is crucial for yield and berry quality in blueberry, and that intercropping with grasses may be an effective and sustainable alternative to counteract Fe deficiency in blueberry, with a similar effect on berries to that achieved with Fe-EDDHA.
TDHF Theory and Its Extensions for the Multinucleon Transfer Reaction: A Mini Review

Time-dependent Hartree-Fock (TDHF) theory has been a powerful tool in describing a variety of complex nuclear dynamics microscopically without empirical parameters. In this contribution, recent advances in nuclear dynamics studies with TDHF and its extensions are briefly reviewed, along the line with the study of multinucleon transfer (MNT) processes in low-energy heavy-ion reactions. The latter processes lie at the core of this Research Topic, whose application for production of extremely neutron-rich nuclei has been extensively discussed. Having in mind the ongoing theoretical developments, how microscopic theories contribute to the future MNT study is envisaged.
Effects of Fluoride on NiTi Orthodontic Archwires: An X-ray Diffraction Study

Objective: To explore the changes in nickel-titanium (NiTi) archwires after exposure to fluoride-containing acetic acid solutions. Materials and methods: Preformed rectangular NiTi wires were immersed in either an acidulated fluoride solution, a neutral fluoride solution or distilled water (control) for 1.5 hours at 37°C. After immersion, the unloading force values at four deflection points were measured by three-point bending test. Scanning electron microscopy and X-ray diffraction analysis were also performed to characterize the effects of the fluoride exposure on the wire. Results: Unloading force values of NiTi orthodontic wires were significantly decreased after exposure to both fluoride solutions (p < 0.001). Corrosive changes in surface topography were observed for both fluoride solutions. Wires exposed to acidic fluoride appeared as more severely affected. X-ray diffraction analysis showed no change in crystal lattice of NiTi wires in both solutions. Conclusion: The results suggest that using topical fluoride agents with NiTi wire could decrease the functional unloading mechanical properties of the wire and contribute to prolonged orthodontic treatment.
Monitoring exercise-induced muscle damage indicators and myoelectric activity during two weeks of knee extensor exercise training in young and old men

This study considered the effects of repeated bouts of short-term resistive exercise in old (age: 64.5±5.5 years; n = 10) and young men (age: 25.1±4.9 years; n = 10) who performed six knee extension exercise bouts over two weeks using various markers of exercise-induced muscle damage and electromyographic activity. We found that time-course changes in quadriceps isometric torque, creatine kinase activity, and muscle soreness in the two groups were similar. However, recovery in the acute torque deficit was mediated by more favourable electromyographic activity changes in the young group than in the older adults group. Muscle elastic energy storage and re-use assessed with dynamometry was selectively improved in the young group by the end of the protocol. Serum myoglobin concentration increased selectively in old group, and remained elevated with further bouts, suggesting higher sarcolemma vulnerability and less effective metabolic adaptation in the older adults, which, however, did not affect muscle contractility.
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints

As neural networks continue their reach into nearly every aspect of software operations, the details of those networks become an increasingly sensitive subject. Even those that deploy neural networks embedded in physical devices may wish to keep the inner working of their designs hidden -- either to protect their intellectual property or as a form of protection from adversarial inputs. The specific problem we address is how, through heavy system stack, given noisy and imperfect memory traces, one might reconstruct the neural network architecture including the set of layers employed, their connectivity, and their respective dimension sizes. Considering both the intra-layer architecture features and the inter-layer temporal association information introduced by the DNN design empirical experience, we draw upon ideas from speech recognition to solve this problem. We show that off-chip memory address traces and PCIe events provide ample information to reconstruct such neural network architectures accurately. We are the first to propose such accurate model extraction techniques and demonstrate an end-to-end attack experimentally in the context of an off-the-shelf Nvidia GPU platform with full system stack. Results show that the proposed techniques achieve a high reverse engineering accuracy and improve the one's ability to conduct targeted adversarial attack with success rate from 14.6\%$\sim$25.5\% (without network architecture knowledge) to 75.9\% (with extracted network architecture).
An overview about DNA methylation in childhood obesity: Characteristics of the studies and main findings

Childhood obesity is a global burden affecting millions of children worldwide. It is well‐known that the adiposity profile in children is critical for future occurrence of diseases. As a multifactorial disease, obesity is associated with genetic and environmental factors. Epigenetic mechanisms link the plethora of environmental clues to a given phenotype. DNA methylation is the most studied epigenetic mark and its importance in several diseases was acknowledged. In childhood obesity, specifically, the studies show a consistent association between adiposity and methylation at the gene and genome‐wide scales. The relationship between DNA methylation and childhood obesity has been proved strong for some genes and pathways. However, the studies are heterogeneous in their design, methodologies, and results. The aim of this review is to discuss this heterogeneity and point out some aspects that should be considered in future studies to clarify the role of DNA methylation in childhood obesity.