Miracle-dz/UniFAR-FTUs huggingface dataset:
Decellularized Extracellular Matrix for Cell Biology

The extracellular matrix (ECM) is an architecture that supports the cells in our bodies and regulates various cell functions. The ECM is composed of many proteins and carbohydrates, and these molecules activate various intracellular signaling pathways orchestrated to decide cell fates. Therefore, it is not enough to study the role of single ECM molecules to understand the roles of the ECM in the regulation of cell functions; it is necessary to understand how the ECM, as an assembly of various molecules, regulates cell functions as a whole. For this purpose, in vitro ECM models mimicking native ECM are required. Here, a decellularization technique is presented to reconstitute native ECM in vitro. In this article, methods for preparing decellularized ECM (dECM) are described for use in tumor and stem cell biology. Additionally, a method for confirmation of decellularization and a dECM modification method are described. These dECM types will be useful for comprehensive studies of ECM roles. © 2021 Wiley Periodicals LLC.
Protective role of resveratrol and apigenin against toxic effects of bisphenol a in rat salivary gland

Abstract Objectives The aim of this study was to investigate the cellular changes caused by Bisphenol A (BPA) exposure in salivary gland cells and to examine the protective role of resveratrol (RSV) and apigenin (APG) molecules against the negative effects of BPA. Materials and Methods Forty-two rats were randomly divided into 6 groups as; (i) control, (ii) BPA (130 mg/kg), (iii) BPA + RSV100 (100 mg/kg), (iv) BPA + RSV200 (200 mg/kg), (v) BPA + APG100 (100 mg/kg), and (vi) BPA + APG200 (200 mg/kg). In all experimental groups, the chemicals were given by gavage every day for a total of 28 days. Results The BPA administration caused a significant increase in tissue oxidative stress parameters as opposed to a significant decrease in tissue antioxidant levels (p < 0.05). On the other hand, it was observed that RSV and APG treatment reversed this situation (p < 0.05). The BPA administration did not cause a significant change in tissue prostaglandin E2 (PGE2) and nitric oxide levels, whereas low-dose RSV significantly reduced the tissue PGE2 levels compared to BPA (p < 0.05). BPA caused cytopathological changes and apoptosis in salivary gland cells. In the BPA group, edema, nuclear pleomorphism, and pyknotic nuclei were observed. Moreover, both RSV and APG were found to provide protection against BPA-induced cellular damage, while RSV provided better cellular protection than APG. The control group had a normal histological structure. Conclusion BPA caused cytopathological changes and apoptosis in salivary gland cells. As a result, it was observed that these phytochemicals probably have cytoprotective effects in BPA intoxication.
Seasonal monitoring of Cryptosporidium species and their genetic diversity in neonatal calves on two large‐scale farms in Xinjiang, China

To find out whether and how the prevalence and genetic diversity of Cryptosporidium in neonatal calves vary with the season, 380 fecal samples from neonatal calves on two large‐scale farms in Xinjiang (Alar and Wensu) were studied using molecular biology techniques. Cryptosporidium was detected in 48.7% (185/380) of the samples and was most frequent in summer (56.8%), followed by spring (50.0%), winter (46.8%), and autumn (41.7%; p > 0.05). Calves with diarrhea seem to be more likely infected by Cryptosporidium than those without diarrhea (p < 0.01). We also found that C. parvum (n = 173), C. bovis (n = 7), and C. ryanae (n = 3) were the Cryptosporidium species detected in this study, and co‐infections of these three species (n = 2) were also identified. Two subtypes (IIdA14G1 and IIdA15G1) of C. parvum were identified, and both can infect human. These results also show that neonatal calves commonly suffer diarrhea caused by C. parvum throughout the year.
Preventive treatment with sodium para-aminosalicylic acid inhibits manganese-induced apoptosis and inflammation via the MAPK pathway in rat thalamus

Abstract Excessive exposure to manganese (Mn) may lead to neurotoxicity, referred to as manganism. In several studies, sodium para-aminosalicylic acid (PAS-Na) has shown efficacy against Mn-induced neurodegeneration by attenuating the neuroinflammatory response. The present study investigated the effect of Mn on inflammation and apoptosis in the rat thalamus, as well as the underlying mechanism of the PAS-Na protective effect. The study consisted of sub-acute (Mn treatment for 4 weeks) and sub-chronic (Mn and PAS-Na treatment for 8 weeks) experiments. In the sub-chronic experiments, pro-inflammatory cytokines, namely tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), and cyclooxygenase 2 (COX-2) were significantly increased in the Mn-exposed group compared to the control II. PAS-Na treatment led to a significant reduction in the Mn-induced neuroinflammation by inhibiting IL-1β and COX-2 mRNA expression and reducing IL-1β secretion and JNK/p38 MAPK pathway activity. Furthermore, immunohistochemical analysis showed that the expression of caspase-3 was significantly increased in both the sub-acute and sub-chronic experimental paradigms concomitant with a significant decrease in B-cell lymphoma 2 (Bcl-2) in the thalamus of Mn-treated rats. PAS-Na also decreased the expression levels of several apoptotic markers downstream of the MAPK pathway, including Bcl-2/Bax and caspase-3, while up-regulating anti-apoptotic Bcl-2 proteins. In conclusion, Mn exposure led to inflammation in the rat thalamus concomitant with apoptosis, which was mediated via the MAPK signaling pathway. PAS-Na treatment antagonized effectively Mn-induced neurotoxicity by inhibiting the MAPK activity in the same brain region.
Host Lung Environment Limits Aspergillus fumigatus Germination through an SskA-Dependent Signaling Response

Aspergillus fumigatus is an important human fungal pathogen particularly in immunocompromised individuals. Initiation of growth by A. fumigatus in the lung is important for its pathogenicity in murine models. ABSTRACT Aspergillus fumigatus isolates display significant heterogeneity in growth, virulence, pathology, and inflammatory potential in multiple murine models of invasive aspergillosis. Previous studies have linked the initial germination of a fungal isolate in the airways to the inflammatory and pathological potential, but the mechanism(s) regulating A. fumigatus germination in the airways is unresolved. To explore the genetic basis for divergent germination phenotypes, we utilized a serial passaging strategy in which we cultured a slow germinating strain (AF293) in a murine-lung-based medium for multiple generations. Through this serial passaging approach, a strain emerged with an increased germination rate that induces more inflammation than the parental strain (herein named LH-EVOL for lung homogenate evolved). We identified a potential loss-of-function allele of Afu5g08390 (sskA) in the LH-EVOL strain. The LH-EVOL strain had a decreased ability to induce the SakA-dependent stress pathway, similar to AF293 ΔsskA and CEA10. In support of the whole-genome variant analyses, sskA, sakA, or mpkC loss-of-function strains in the AF293 parental strain increased germination both in vitro and in vivo. Since the airway surface liquid of the lungs contains low glucose levels, the relationship of low glucose concentration on germination of these mutant AF293 strains was examined; interestingly, in low glucose conditions, the sakA pathway mutants exhibited an enhanced germination rate. In conclusion, A. fumigatus germination in the airways is regulated by SskA through the SakA mitogen-activated protein kinase (MAPK) pathway and drives enhanced disease initiation and inflammation in the lungs. IMPORTANCE Aspergillus fumigatus is an important human fungal pathogen particularly in immunocompromised individuals. Initiation of growth by A. fumigatus in the lung is important for its pathogenicity in murine models. However, our understanding of what regulates fungal germination in the lung environment is lacking. Through a serial passage experiment using lung-based medium, we identified a new strain of A. fumigatus that has increased germination potential and inflammation in the lungs. Using this serially passaged strain, we found it had a decreased ability to mediate signaling through the osmotic stress response pathway. This finding was confirmed using genetic null mutants demonstrating that the osmotic stress response pathway is critical for regulating growth in the murine lungs. Our results contribute to the understanding of A. fumigatus adaptation and growth in the host lung environment.
What's Behind the Couch? Directed Ray Distance Functions (DRDF) for 3D Scene Reconstruction

We present an approach for full 3D scene reconstruction from a single unseen image. We train on dataset of realistic non-watertight scans of scenes. Our approach predicts a distance function, since these have shown promise in handling complex topologies and large spaces. We identify and analyze two key challenges for predicting such image conditioned distance functions that have prevented their success on real 3D scene data. First, we show that predicting a conventional scene distance from an image requires reasoning over a large receptive field. Second, we analytically show that the optimal output of the network trained to predict these distance functions does not obey all the distance function properties. We propose an alternate distance function, the Directed Ray Distance Function (DRDF), that tackles both challenges. We show that a deep network trained to predict DRDFs outperforms all other methods quantitatively and qualitatively on 3D reconstruction from single image on Matterport3D, 3DFront, and ScanNet.
DMRVisNet: Deep Multihead Regression Network for Pixel-Wise Visibility Estimation Under Foggy Weather

Scene perception is essential for driving decision-making and traffic safety. However, fog, as a kind of common weather, frequently appears in the real world, especially in mountain areas, making it difficult to accurately observe the surrounding environments. Therefore, precisely estimating the visibility under foggy weather can significantly benefit traffic management and safety. To address this, most current methods use professional instruments outfitted at fixed locations on the roads to perform the visibility measurement; these methods are expensive and less flexible. In this paper, we propose an innovative end-to-end convolutional neural network framework to estimate the visibility leveraging Koschmieder’s law and the image data. The proposed method estimates the visibility by integrating the physical model into the proposed framework, instead of directly predicting the visibility value via the convolutional neural network. Moreover, we estimate the visibility as a pixel-wise visibility map against those of previous visibility measurement methods which solely predict a single value for the entire image. Thus, the estimated result of our method is more informative, particularly in uneven fog scenarios, which can benefit to developing a more precise early warning system for foggy weather, thereby better protecting the intelligent transportation infrastructure systems and promoting their development. To validate the proposed framework, a virtual dataset, FACI, containing 3,000 foggy images in different concentrations, is collected using the AirSim platform, which is available at https://github.com/coutyou/FoggyAirsimCityImages. Detailed experiments show that the proposed method achieves performance competitive to those of state-of-the-art methods.
Preliminary study of a reverberation chamber method for multiple-source testing using intermodulation

The illumination of a system under test by multiple sources can lead to intermodulation (IM) effects that give rise to threat signals at the IM frequencies. The result of this is that the electromagnetic (EM) compatibility and signal integrity of that system may be compromised by two or more signals that are, individually, out of the frequency band of concern. As the EM environment continues to be increasingly polluted and electromagnetic compatibility (EMC) tests rely, predominantly, on a single-source illumination, this is an issue that is ripe for further investigation. The statistical nature of the reverberation chamber and its behaviour in isolating the test environment from the ambient (outside) environment indicates that this is a facility worth considering for multiple source (IM) testing. This study discusses the need for such an expansion in test methods, driven by an increasing interest in functional safety. It presents the results of a preliminary, simulation based, study of the reverberation chamber used with multiple sources. The purpose of this study is to demonstrate that the reverberation chamber can provide a facility where worst-case multiple-source EM interference effects can be tested. It concludes that the proposed approach has the potential to be viable and suggests experimental studies to confirm the behaviour and also to confirm that this approach can be used as an indirect method of reducing the lowest working frequency of the reverberation chamber.
Low Back Biomechanics during Repetitive Deadlifts: A Narrative Review

OCCUPATIONAL APPLICATIONS Heavy deadlifting is used as a screening tool or training protocol for recruitment and retention in physically-demanding occupations, especially in the military. Spinal loads experienced during heavy deadlifts, particularly shearing forces, are well above recommended thresholds for lumbar spine injury in occupational settings. Although members of the noted occupation likely have stronger musculoskeletal systems compared to the general population, experiencing shearing forces that are 2 to 4 times larger than the threshold of injury, particularly under repetitive deadlift, may transform a screening tool or training protocol to an occupationally-harmful physical activity. TECHNICAL ABSTRACT Background: Low back pain is a significant problem and one of the primary musculoskeletal conditions affecting active duty service members. There is a need to comprehensively assess the effects of repetitive deadlifts as a physical training modality on lumbar spine loads and the potential mechanisms involved in lumbosacral injuries among soldiers. Purpose: The purpose of this narrative review is to summarize studies of low back biomechanics during repetitive deadlifts as used in training programs to improve lifting capacity. Methods: PubMed and Google Scholar were searched for studies of lifting that met our inclusion and exclusion criteria. Only full text articles in English were included, and their reference lists were further searched. Results: Heavy deadlifts can result in large compressive and shearing spinal loads that range from 5 − 18 kN, and 1.3 − 3.2 kN, respectively. No studies of lower back biomechanics during repetitive deadlifts were found. However, findings of studies that investigated lower back biomechanics during other types of repetitive lifting suggest a high likelihood for adverse changes in lower back biomechanics that can increase risk of lower back injury. Conclusion: Repetitive deadlifting is increasingly implemented as a training modality to develop maximal lifting capacities required in military occupations. Further research is needed to understand the effects of such a training modality on lower back biomechanics and risk of injury.
Crew Factors in Flight Operations XV: Alertness Management in General Aviation Education Module

Regional operations encompass a broad range of pilots and equipment. This module is intended to help all those involved in regional aviation, including pilots, schedulers, dispatchers, maintenance technicians, policy makers, and others, to understand the physiological factors underlying fatigue, how flight operations affect fatigue, and what can be done to counteract fatigue and maximize alertness and performance in their operations. The overall purpose of this module is to promote aviation safety, performance, and productivity. It is intended to meet three specific objectives: (1) to explain the current state of knowledge about the physiological mechanisms underlying fatigue; (2) to demonstrate how this knowledge can be applied to improving flight crew sleep, performance, and alertness; and (3) to offer strategies for alertness management. Aviation Safety Reporting System (ASRS) and National Transportation Safety Board (NISH) reports are used throughout this module to demonstrate that fatigue is a safety issue in the regional operations community. The appendices at the end of this module include the ASRS reports used for the examples contained in this publication, brief introductions to sleep disorders and relaxation techniques, summaries of relevant NASA publications, and a list of general readings on sleep, sleep disorders, and circadian rhythms.
Promoting effect of the recombinant resuscitation promoting factors‐2 of Rhodococcus erythropolis on petroleum degradation and cultivable bacterial diversities of the oil‐contaminated soils

Resuscitation‐promoting factors (Rpfs) belong to peptidoglycan hydrolases, which participate in recovery of dormant cells and promoting bacteria growth. In this study, the resuscitation promoting factor rpf2 gene of Rhodococcus erythropolis KB1 was expressed in Escherichia coli and purified by Ni2+ affinity chromatography. The purified recombinant fusion protein Rpf2 showed a closely 50 kDa band on sodium dodecyl sulphate polyacrylamide gel electrophoresis. The protein showed muralytic activity, with a specific activity of 1503 ± 123 U mg−1 when determined with 4‐methylumbelliferyl‐β‐d‐N, N′,N″‐triacetotri‐ylchitoside as substrate. It also showed protease activity when measured with azocasein as substrate, with a specific activity of 1528 ± 411 U mg−1. The addition of the recombinant Rpf2 protein significantly increased petroleum degradation efficiency of the indigenous micro‐organisms and the petroleum degradation rates increased from 30·86 to 43·45%, 45·20 and 49·23% in the treatment groups. The recombinant protein also increased the petroleum‐degrading bacterial diversities enriched from the contaminated soils. The cultivable bacterial flora of the treatment groups supplemented with different concentrations of Rpf2 increased from 82 genera in 9 phyla to 116 genera in 16 phyla and 138 genera in 16 phyla respectively. Thirteen extra petroleum‐degrading bacteria strains were isolated from the petroleum‐contaminated soils in the groups containing the recombinant Rpf2.
The Effect of Model Size on Worst-Group Generalization

Overparameterization is shown to result in poor test accuracy on rare subgroups under a variety of settings where subgroup information is known. To gain a more complete picture, we consider the case where subgroup information is unknown. We investigate the effect of model size on worst-group generalization under empirical risk minimization (ERM) across a wide range of settings, varying: 1) architectures (ResNet, VGG, or BERT), 2) domains (vision or natural language processing), 3) model size (width or depth), and 4) initialization (with pre-trained or random weights). Our systematic evaluation reveals that increasing model size does not hurt, and may help, worst-group test performance under ERM across all setups. In particular, increasing pre-trained model size consistently improves performance on Waterbirds and MultiNLI. We advise practitioners to use larger pre-trained models when subgroup labels are unknown.
Data-driven forward-inverse problems and modulational instability for Yajima-Oikawa system using deep learning with parameter regularization

We investigate data-driven forward-inverse problems for Yajima-Oikawa system by employing two technologies which improve the performance of PINN in deep physics-informed neural network (PINN), namely neuron-wise locally adaptive activation functions and L norm parameter regularization. In particular, we not only recover three different forms of vector rogue waves (RWs) in the forward problem of Yajima-Oikawa (YO) system, including bright-bright RWs, intermediatebright RWs and dark-bright RWs, but also study the inverse problem of YO system by data-driven with noise of different intensity. Compared with PINN method using only locally adaptive activation function, the PINN method with two strategies shows amazing robustness when studying the inverse problem of YO system with noisy training data, that is, the improved PINN model proposed by us has excellent noise immunity. The asymptotic analysis of wavenumber k and the MI analysis for YO system with unknown parameters are derived systematically by applying the linearized instability analysis on plane wave.
Specializing Versatile Skill Libraries using Local Mixture of Experts

A long-cherished vision in robotics is to equip robots with skills that match the versatility and precision of humans. For example, when playing table tennis, a robot should be capable of returning the ball in various ways while precisely placing it at the desired location. A common approach to model such versatile behavior is to use a Mixture of Experts (MoE) model, where each expert is a contextual motion primitive. However, learning such MoEs is challenging as most objectives force the model to cover the entire context space, which prevents specialization of the primitives resulting in rather low-quality components. Starting from maximum entropy reinforcement learning (RL), we decompose the objective into optimizing an individual lower bound per mixture component. Further, we introduce a curriculum by allowing the components to focus on a local context region, enabling the model to learn highly accurate skill representations. To this end, we use local context distributions that are adapted jointly with the expert primitives. Our lower bound advocates an iterative addition of new components, where new components will concentrate on local context regions not covered by the current MoE. This local and incremental learning results in a modular MoE model of high accuracy and versatility, where both properties can be scaled by adding more components on the fly. We demonstrate this by an extensive ablation and on two challenging simulated robot skill learning tasks. We compare our achieved performance to LaDiPS and HiREPS, a known hierarchical policy search method for learning diverse skills.
Outage management systems: surviving the implementation

Electric utilities are looking for better ways to manage operations and satisfy customers. To this end, many electric utilities are actively installing or are considering installing an outage management system (OMS) for their electric distribution operations. While these systems are costly, they provide superb capabilities for swift and accurate dispatching of restoration resources as well as the ability to manage nearly overwhelming amounts of data in an organized manner. While the technical challenges of installing such a system are significant, there are also nontechnical issues that impact the success of the new system. This presentation identifies some of these key issues that are critical to ensure successful implementation of the new system.