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Power MOSFETs are found to be very vulnerable to single-event burnout (SEB) in space irradiation environments, and the military components generally require that devices could operate reliably as the temperature varies from 218 K to 423 K (−55 °C to 150 °C); thus, the temperature dependence of single-event burnout (SEB) in power MOSFETs should be investigated. Our simulation results showed that the Si power MOSFETs are more tolerant to SEB at a higher temperature at the lower LET (10 MeV∙cm2/mg) due to the decrease of the impact ionization rate, which is in good agreement with the previous research. However, the state of the parasitic BJT plays a primary role in the SEB failure mechanism when the LET value is greater than 40 MeV∙cm2/mg, which exhibits a completely different temperature dependence from that of 10 MeV∙cm2/mg. Results indicate that with the temperature increasing, the lower difficulty to turn on the parasitic BJT and the increasing current gain all make it easier to build up the regenerative feedback process responsible for SEB failure. As a result, the SEB susceptibility of power MOSFETs increases as ambient temperature increases when the LET value is greater than 40 MeV∙cm2/mg.

Oily sludge, as a critical hazardous waste, requires appropriate treatment for resource recovery and harmfulness reduction. Here, fast microwave-assisted pyrolysis (MAP) of oily sludge was conducted for oil removal and fuel production. The results indicated the priority of the fast MAP compared with the MAP under premixing mode, with the oil content in solid residues after pyrolysis reaching below 0.2%. The effects of pyrolysis temperature and time on product distribution and compositions were examined. In addition, pyrolysis kinetics can be well described using the Kissinger-Akahira-Sunose (KAS) and the Flynn-Wall-Ozawa (FWO) methods, with the activation energy being 169.7–319.1 kJ/mol in the feedstock conversional fraction range of 0.2–0.7. Subsequently, the pyrolysis residues were further treated by thermal plasma vitrification to immobilize the existing heavy metals. The amorphous phase and the glassy matrix were formed in the molten slags, resulting in bonding and, hence, immobilization of heavy metals. Operating parameters, including working current and melting time, were optimized to reduce the leaching concentrations of heavy metals, as well as to decrease their volatilization during vitrification.

Based on Doppler radar observation and reanalysis data, the statistical characteristics of mesovortices (MVs) during the first rainy season (April–June) in Guangdong, South China, from 2017 to 2019 are studied, including their spatiotemporal distributions, structural features and favorable environmental conditions. The results show that the MVs usually exhibit short lifetimes; about 70% last for less than 30 min. The intensity and horizontal scale of the MVs are proportional to their lifetime. Long-lived MVs have larger horizontal scales and stronger intensities than short-lived ones. The MVs are mainly observed over the Pearl River Delta region, followed by western Guangdong Province, but relatively fewer in both eastern and northern Guangdong Province. The uneven spatial distribution of the MVs is closely related to the differences in the topographical features and the environment conditions over South China. MVs are prone to form over flat regions. The Pearl River Delta and eastern Guangdong regions are relatively flat compared to the more mountainous western and northern Guangdong regions. Moreover, the monsoonal south-westerlies, water vapor flux, atmospheric instability and vertical wind shear over southwest Guangdong are significantly larger than those in other regions and are favorable for the formation of MVs. The occurrence frequencies of MVs in central and southern parts of Guangdong display similar diurnal variations, reaching the peak during the late afternoon and early evening while dropping to the minimum overnight. However, the situation is opposite in northern Guangdong, with the peak overnight and the minimum during the late afternoon and early evening. The regional differences in diurnal variation are likely related to the moving direction of mesoscale convective systems (MCSs) in Guangdong.

Inflammatory pain is one of the most common symptoms of clinical pain that seriously affects patient quality of life, but it currently has limited therapeutic options. Proanthocyanidins, a group of polyphenols enriched in plants and foods, have been reported to exert anti-inflammatory pain-alleviating effects. However, the mechanism by which proanthocyanidins relieve inflammatory pain in the central nervous system is unclear. In the present study, we observed that intrathecal injection of proanthocyanidins inhibited mechanical and thermal pain sensitivity in mice with inflammatory pain induced by Complete Freund’s Adjuvant (CFA) injection. Electrophysiological results further showed that proanthocyanidins inhibited the frequency of spontaneous excitatory postsynaptic currents without affecting the spontaneous inhibitory postsynaptic currents or the intrinsic properties of parabrachial nucleus-projecting neurons in the spinal cord. The effect of proanthocyanidins may be mediated by their inhibition of phosphorylated activation of the PI3K/Akt/mTOR pathway molecules in dorsal root ganglia neurons. In summary, intrathecal injection of procyanidin induces an obvious anti-inflammatory pain effect in mice by inhibiting peripheral excitatory inputs to spinal neurons that send nociceptive information to supraspinal areas.

Student Dropout Prediction (SDP) is pivotal in mitigating withdrawals in Massive Open Online Courses. Previous studies generally modeled the SDP problem as a binary classification task, providing a single prediction outcome. Accordingly, some attempts introduce survival analysis methods to achieve continuous and consistent predictions over time. However, the volatility and sparsity of data always weaken the models' performance. Prevailing solutions rely heavily on data pre-processing independent of predictive models, which are labor-intensive and may contaminate authentic data. This paper proposes a Survival Analysis based Volatility and Sparsity Modeling Network (SAVSNet) to address these issues in an end-to-end deep learning framework. Specifically, SAVSNet smooths the volatile time series by convolution network while preserving the original data information using Long-Short Term Memory Network (LSTM). Furthermore, we propose a Time-Missing-Aware LSTM unit to mitigate the impact of data sparsity by integrating informative missingness patterns into the model. A survival analysis loss function is adopted for parameter estimation, and the model outputs monotonically decreasing survival probabilities. In the experiments, we compare the proposed method with state-of-the-art methods in two real-world MOOC datasets, and the experiment results show the effectiveness of our proposed model.

The deformation and fracture characterization of an Mg−2Sn−1Ca alloy were studied through uniaxial isothermal compression tests. The flow stress curves, the efficiency of power dissipation, the instability parameter and the fracture behavior of an Mg−2Sn−1Ca alloy under the condition of various hot working parameters were investigated according to the experimental data. Processing maps were established by superimposing the instability map over the power dissipation map. It was found that flow stress reduces with increases in the deformation temperature and decreases in the strain rate. The processing of Mg−2Sn−1Ca alloys should avoid the instability region in which the conditions are high strain under high temperature and low strain under low temperature. At 473 K or a high strain rate, unidirectional cracks and fish scale cracks can be produced, and cracks can be avoided under the optimum processing area of 623–723 K/0.001–0.1 s−1.

We present the astrometric calibration of the Beijing–Arizona Sky Survey (BASS). The BASS astrometry was tied to the International Celestial Reference Frame via the Gaia Data Release 2 reference catalog. For effects that were stable throughout the BASS observations, including differential chromatic refraction and the low charge transfer efficiency of the CCD, we corrected for these effects at the raw image coordinates. Fourth-order polynomial intermediate longitudinal and latitudinal corrections were used to remove optical distortions. The comparison with the Gaia catalog shows that the systematic errors, depending on color or magnitude, are less than 2 milliarcseconds (mas). The position systematic error is estimated to be about −0.01 ± 0.7 mas in the region between 30° and 60° of decl. and up to −0.07 ± 0.9 mas in the region north of decl. 60°.

To achieve a wide range and high accuracy detection of the vacuum level, for example, in an encapsulated vacuum microcavity, a composite-type MEMS Pirani gauge has been designed and fabricated. The Pirani gauge consists of two gauges of different sizes connected in series, with one gauge having a larger heat-sensitive area and a larger air gap for extending the lower measurable limit of pressure (i.e., the high vacuum end) and the other gauge having a smaller heat-sensitive area and a smaller air gap for extending the upper measurable limit. The high-resistivity titanium metal was chosen as the thermistor; SiNx was chosen as the dielectric layer, considering the factors relevant to simulation and manufacturing. By simulation using COMSOL Multiphysics and NI Multisim, a range of measurement of 2 × 10−2 to 2 × 105 Pa and a sensitivity of 52.4 mV/lgPa were obtained in an N2 environment. The performance of the fabricated Pirani gauge was evaluated by using an in-house made vacuum test system. In the test, the actual points of measurement range from 6.6 × 10−2 to 1.12 × 105 Pa, and the highest sensitivity is up to 457.6 mV/lgPa. The experimental results are better in the range of measurement, sensitivity, and accuracy than the simulation results. The Pirani gauge proposed in this study is simple in structure, easy to manufacture, and suitable for integration with other MEMS devices in a microcavity to monitor the vacuum level therein.

Visual Simultaneous Localization and Mapping (SLAM) system is mainly used in real-time localization and mapping tasks of robots in various complex environments, while traditional monocular vision algorithms are struggling to cope with weak texture and dynamic scenes. To solve these problems, this work presents an object detection and clustering assisted SLAM algorithm (OC-SLAM), which adopts a faster object detection algorithm to add semantic information to the image and conducts geometrical constraint on the dynamic keypoints in the prediction box to optimize the camera pose. It also uses RGB-D camera to perform dense point cloud reconstruction with the dynamic objects rejected, and facilitates European clustering of dense point clouds to jointly eliminate dynamic features combining with object detection algorithm. Experiments in the TUM dataset indicate that OC-SLAM enhances the localization accuracy of the SLAM system in the dynamic environments compared with original algorithm and it has shown impressive performance in the localizition and can build a more precise dense point cloud map in dynamic scenes.

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection that often results in acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). An emerging mechanism of sepsis-induced ARDS involves neutrophils/macrophages undergoing cell death, releasing nuclear histones to cause tissue damage that exacerbates pulmonary injury. While published studies focus on unmodified histones, little is known about the role of citrullinated histone H3 (CitH3) in the pathogenesis of sepsis and ALI. In this study, we found that levels of CitH3 were elevated in the patients with sepsis-induced ARDS and correlated to PaO2/FiO2 in septic patients. Systematic administration of CitH3 peptide in mice provoked Caspase-1 activation in the lung tissue and caused ALI. Neutralization of CitH3 with monoclonal antibody improved survival and attenuated ALI in a mouse sepsis model. Furthermore, we demonstrated that CitH3 induces ALI through activating Caspase-1 dependent inflammasome in bone marrow derived macrophages and bone marrow derived dendritic cells. Our study suggests that CitH3 is an important mediator of inflammation and mortality during sepsis-induced ALI.

Background: Epilepsy is a complex chronic disease of the nervous system which influences the health of approximately 70 million patients worldwide. In the past few decades, despite the development of novel antiepileptic drugs, around one-third of patients with epilepsy have developed drug-resistant epilepsy. We performed a bioinformatic analysis to explore the underlying diagnostic markers and mechanisms of drug-resistant epilepsy.Methods: Weighted correlation network analysis (WGCNA) was applied to genes in epilepsy samples downloaded from the Gene Expression Omnibus database to determine key modules. The least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to screen the genes resistant to carbamazepine, phenytoin, and valproate, and sensitivity of the three-class classification SVM model was verified through the receiver operator characteristic (ROC) curve. A protein–protein interaction (PPI) network was utilized to analyze the protein interaction relationship. Finally, ingenuity pathway analysis (IPA) was adopted to conduct disease and function pathway and network analysis.Results: Through WGCNA, 72 genes stood out from the key modules related to drug resistance and were identified as candidate resistance genes. Intersection analysis of the results of the LASSO and SVM-RFE algorithms selected 11, 4, and 5 drug-resistant genes for carbamazepine, phenytoin, and valproate, respectively. Subsequent union analysis obtained 17 hub resistance genes to construct a three-class classification SVM model. ROC showed that the model could accurately predict patient resistance. Expression of 17 hub resistance genes in healthy subjects and patients was significantly different. The PPI showed that there are six resistance genes (CD247, CTSW, IL2RB, MATK, NKG7, and PRF1) that may play a central role in the resistance of epilepsy patients. Finally, IPA revealed that resistance genes (PRKCH and S1PR5) were involved in “CREB signaling in Neurons.”Conclusion: We obtained a three-class SVM model that can accurately predict the drug resistance of patients with epilepsy, which provides a new theoretical basis for research and treatment in the field of drug-resistant epilepsy. Moreover, resistance genes PRKCH and S1PR5 may cooperate with other resistance genes to exhibit resistance effects by regulation of the cAMP-response element-binding protein (CREB) signaling pathway.

Peptidylarginine deiminases (PADs) are a group of enzymes that catalyze post-translational modifications of proteins by converting arginine residues into citrullines. Among the five members of the PAD family, PAD2 and PAD4 are the most frequently studied because of their abundant expression in immune cells. An increasing number of studies have identified PAD2 as an essential factor in the pathogenesis of many diseases. The successes of preclinical research targeting PAD2 highlights the therapeutic potential of PAD2 inhibition, particularly in sepsis and autoimmune diseases. However, the underlying mechanisms by which PAD2 mediates host immunity remain largely unknown. In this review, we will discuss the role of PAD2 in different types of cell death signaling pathways and the related immune disorders contrasted with functions of PAD4, providing novel therapeutic strategies for PAD2-associated pathology.

Condition-based maintenance has been widely used in the maintenance strategy of equipment or systems. Aiming at the maintenance decision-making of the equipment with dynamic degradation characteristics, a dynamic condition-based maintenance model is proposed based on Inverse Gaussian process in this paper. Firstly, an Inverse Gaussian process with stochastic parameter is proposed to describe the change of the equipment degradation characteristics during operation, and the important stochastic properties related to condition-based maintenance is deduced. Secondly, the dynamic maintenance threshold function is proposed, and its different values at different degradation stages can reduce the early failure risk of the equipment while ensuring a lower expected cost ratio. On this basis, a dynamic maintenance decision-making model with multi-objectives is established. A numerical example is illustrated to verify the correctness and practicability of the proposed method, and the sensitivity analysis results of the related parameters prove the necessity of considering the dynamic degradation characteristics of equipment. The comparison result proves that the method proposed in this paper can obtain better safety and economy of maintenance than the method with fixed thresholds.

Abstract Background During a period of rapid growth in our understanding of the microbiology of the built environment in recent years, the majority of research has focused on bacteria and fungi. Viruses, while probably as numerous, have received less attention. In response, the Alfred P. Sloan Foundation supported a workshop entitled “Viruses in the Built Environment (VIBE),” at which experts in environmental engineering, environmental microbiology, epidemiology, infection prevention, fluid dynamics, occupational health, metagenomics, and virology convened to synthesize recent advances and identify key research questions and knowledge gaps regarding viruses in the built environment. Results Four primary research areas and funding priorities were identified. First, a better understanding of viral communities in the built environment is needed, specifically which viruses are present and their sources, spatial and temporal dynamics, and interactions with bacteria. Second, more information is needed about viruses and health, including viral transmission in the built environment, the relationship between virus detection and exposure, and the definition of a healthy virome. The third research priority is to identify and evaluate interventions for controlling viruses and the virome in the built environment. This encompasses interactions among viruses, buildings, and occupants. Finally, to overcome the challenge of working with viruses, workshop participants emphasized that improved sampling methods, laboratory techniques, and bioinformatics approaches are needed to advance understanding of viruses in the built environment. Conclusions We hope that identifying these key questions and knowledge gaps will engage other investigators and funding agencies to spur future research on the highly interdisciplinary topic of viruses in the built environment. There are numerous opportunities to advance knowledge, as many topics remain underexplored compared to our understanding of bacteria and fungi. Video abstract.

Abstract Background Although palliative care has been accepted throughout the cancer trajectory, accurate survival prediction for advanced cancer patients is still a challenge. The aim of this study is to identify pre-palliative care predictors and develop a prognostic nomogram for overall survival (OS) in mixed advanced cancer patients. Methods A total of 378 consecutive advanced cancer patients were retrospectively recruited from July 2013 to October 2015 in one palliative care unit in China. Twenty-three clinical and laboratory characters were collected for analysis. Prognostic factors were identified to construct a nomogram in a training cohort (n = 247) and validated in a testing cohort (n = 131) from the setting. Results The median survival time was 48.0 (95% CI: 38.1–57.9) days for the training cohort and 52.0 (95% CI: 34.6–69.3) days for the validation cohort. Among pre-palliative care factors, sex, age, tumor stage, Karnofsky performance status, neutrophil count, hemoglobin, lactate dehydrogenase, albumin, uric acid, and cystatin-C were identified as independent prognostic factors for OS. Based on the 10 factors, an easily obtained nomogram predicting 90-day probability of mortality was developed. The predictive nomogram had good discrimination and calibration, with a high C-index of 0.76 (95% CI: 0.73–0.80) in the development set. The strong discriminative ability was externally conformed in the validation cohort with a C-index of 0.75. Conclusions A validated prognostic nomogram has been developed to quantify the risk of mortality for advanced cancer patients undergoing palliative care. This tool may be useful in optimizing therapeutic approaches and preparing for clinical courses individually.

Abstract Background Little is known about the long-term shifts in distributions of three abdominal-obesity-related indicators, waist circumference (WC), waist-to-hip ratio (WHpR) and waist-to-height ratio (WHtR) among Chinese adults. Traditional mean regression models used in the previous analyses were limited in their ability to capture cross-distribution among effects. The current study aims to describe the shift in distribution of WC, WHpR, and WHtR over a period of 18 years (1993–2011) in China, and to reveal quantile-specific associations of the three indicators with key covariates. Methods Longitudinal data from seven waves of the China Health and Nutrition Surveys (CHNS) in 1993, 1997, 2000, 2004, 2006, 2009 and 2011 were analyzed. The LMS method was used to illustrate the gender-specific quantile curves of WC, WHtR and WHpR over age. Separate gender-stratified longitudinal quantile regressions were employed to investigate the effect of important factors on the trends of the three indicators. Results A total of 11,923 participants aged 18–65 years with 49,507 observations were included in the analysis. The density curves of WC, WHtR and WHpR shifted to right and became wider. The three outcomes all increased with age and increased more at upper percentiles. From the multivariate quantile regression, physical activity was negatively associated in both genders; smoking only had a negative effect on male indicators. Education and drinking behavior both had opposite effects on the three indicators between men and women. Marital status and income were positively associated with the shifts in WC, WHtR and WHpR in male and female WC, while urbanicity index had a positive effect on three outcomes in men but inconsistent effect among female outcomes. Conclusions The abdominal-obesity related indicators of the Chinese adults experienced rapid growth according to our population-based, age- and gender-specific analyses. Over the 18-year study period, major increases in WC, WHtR and WHpR were observed among Chinese adults. Specifically, these increases were greater at upper percentiles and in men. Age, physical activity, energy intake, drinking, smoking, education, income and urbanicity index were associated with elevated abdominal obesity indicators, and the effects differed among percentiles and between genders.

Objective We aimed to observe hair follicle (HF) development in the dorsal skin and elucidate the expression patterns of genes and proteins related to skin and HF development in Rex rabbits from birth to 8 weeks of age. Methods Whole-skin samples were obtained from the backs of Rex rabbits at 0, 2, 4, 6, and 8 weeks of age, the morphological development of primary and secondary HFs was observed, and the gene transcript levels of insulin-like growth factor-I (IGF-I), epidermal growth factor (EGF), bone morphogenetic protein 2 (BMP2), transforming growth factor β-1, 2, and 3 (TGFβ-1, TGFβ-2, and TGFβ-3) were examined using quantitative real-time polymerase chain reaction (PCR). Additionally, Wnt family member 10b (Wnt10b) and β-Catenin gene and protein expression were examined by quantitative real-time PCR and western blot, respectively. Results The results showed significant changes in the differentiation of primary and secondary HFs in Rex rabbits during their first 8 weeks of life. The IGF-I, EGF, TGFβ-2, and TGFβ-3 transcript levels in the rabbits were significantly lower at 2 weeks of age than at birth and gradually increased thereafter, while the BMP2 and TGFβ-1 transcript levels at 2 weeks of age were significantly higher than those at birth and gradually decreased thereafter. β-Catenin gene expression was also significantly affected by age, while the Wnt10b transcript level was not. However, the Wnt10b and β-catenin protein expression levels were the lowest at 2 and 4 weeks of age. Conclusion Our data showed that a series of changes in HFs in dorsal skin occurred during the first 8 weeks. Many genes, such as IGF-I, EGF, BMP2, TGFβ-1, TGFβ-2, TGFβ-3, and β-Catenin, participated in this process, and the related proteins Wnt10b and β-Catenin in skin were also affected by age.

The safe operation of dams is related to the lifeline of the national economy, the safety of the people, and social stability, and dam safety monitoring plays an essential role in scientifically controlling the safety of dams. Since the effects of environmental variables were not considered in conventional monitoring data repairing methods (such as the single time series model and spatial interpolation model), a spatial model for repairing monitoring data combining the variable importance for projection (VIP) method and cokriging was put forward in this paper. In order to improve the accuracy of the model, the influence of different combinations of covariates on it was discussed, and the VIPj value greater than 0.8 was proposed as the threshold of covariates. The engineering verification shows that the VIP-cokriging spatial model had the advantages of high precision and strong applicability compared with the inverse distance weighting (IDW) model, the ordinary kriging model, and the universal kriging model, and the overall error can be reduced by more than 60%, which could better realize the expansion of the monitoring effect variable to the whole area of the dam space. The engineering application of the PBG dam showed that the model scientifically correlated the existing monitoring points with the spatial location of the dam, and reasonably repaired the measured values of the stopping and abnormal measured points, effectively ensuring that the spatial regular of the monitoring data could truly reflect the actual safety and operational status of the dam.

Unmanned aerial vehicles (UAVs) are important in reconnaissance missions because of their flexibility and convenience. Vitally, UAVs are capable of autonomous navigation, which means they can be used to plan safe paths to target positions in dangerous surroundings. Traditional path-planning algorithms do not perform well when the environmental state is dynamic and partially observable. It is difficult for a UAV to make the correct decision with incomplete information. In this study, we proposed a multi-UAV path planning algorithm based on multi-agent reinforcement learning which entails the adoption of centralized training–decentralized execution architecture to coordinate all the UAVs. Additionally, we introduced a hidden state of the recurrent neural network to utilize the historical observation information. To solve the multi-objective optimization problem, We designed a joint reward function to guide UAVs to learn optimal policies under the multiple constraints. The results demonstrate that by using our method, we were able to solve the problem of incomplete information and low efficiency caused by partial observations and sparse rewards in reinforcement learning, and we realized kdiff multi-UAV cooperative autonomous path planning in unknown environment.

In order to obtain high-quality through-silicon via (TSV) arrays for high voltage applications, we optimized the fabrication processes of the Si holes, evaluated the dielectric layers, carried out hole filling by Cu plating, and detected the final structure and electric properties of the TSVs. The Si through-hole array was fabricated in an 8-inch Si substrate as follows: First, a blind Si hole array was formed by the Si deep reactive etching (DRIE) technique using the Bosch process, but with the largest width of the top scallops reduced to 540 nm and the largest notch elimidiameternated by backside grinding, which also opens the bottom ends of the Si blind holes and forms 500-μm-deep Si through holes. Then, the sidewalls of the Si holes were further smoothed by a combination of thermal oxidation and wet etching of the thermal oxide. The insulating capability of the dielectric layers was evaluated prior to metal filling by using a test kit. The metal filling of the through holes was carried out by bottom-up Cu electroplating and followed by annealing at 300 °C for 1 h to release the electroplating stress and to prevent possible large metal thermal expansion in subsequent high-temperature processes. The TSV arrays with different hole diameters and spacing were detected: no visible defects or structure peeling was found by scanning electron microscopy (SEM) observations, and no detectable interdiffusion between Cu and the dielectric layers was detected by energy dispersive X-ray (EDX) analyses. Electric tests indicated that the leakage currents between two adjacent TSVs were as low as 6.80 × 10−10 A when a DC voltage was ramped up from 0 to 350 V, and 2.86 × 10−9 A after a DC voltage was kept at 100 V for 200 s.

Copper serves as a co-factor for a host of metalloenzymes, particularly cytochrome c oxidase (COX). Although it is known that impaired COX function can lead to the excessive accumulation of reactive oxygen species (ROS), the mechanisms underlying how copper depletion leads to cell damage are poorly understood. Here, we have investigated the role of copper depletion during ferroptosis. The bathocuproinedisulfonic (BCS) treatment depolarized the mitochondrial membrane potential, increased the total cellular ROS levels, stimulated oxidative stress, and reduced the glutathione levels. Moreover, the depletion of copper limited the protein expression of glutathione peroxidase 4 (GPX4), which is the only enzyme that is known to prevent lipid peroxidation. Furthermore, we found that copper depletion decreased the sensitivity of the dermal papilla cells (DPCs) to erastin (an inducer of ferroptosis), and the ferroptosis inhibitor ferrostatin-1 (Fer-1) partially prevented BCS-mediated cell death. Overall, these findings establish a direct link between copper and ferroptosis; BCS-mediated copper depletion strongly enhances ferroptosis via mitochondrial perturbation and a reduction in antioxidative mechanisms.

High-speed infrared thermography, micro-CT characterization and full-scale mesostructural simulation were jointly applied to reveal the impact deformation and damage mechanism of composite tubes. Two different failure modes, namely the Impact Side Dominated (ISD) and Impact-/Non-impact Side (INIS), were found to have relation with the braiding angle and localized temperature rise. The hybrid effect can not only prevent resin fragmentation in the triangle region at the lateral side and the diamond region at the non-impact side, but also inhibit the CFRP damage development at the lateral and non-impact side. In small-angle braided tube, the impact-side rebound trend of CFRP layer leads to mismatch at the CFRP-Al interface, which results in opening delamination. In large-angle braided tube, the non-impact-side damage plays an important role in further load-bearing capacity. Apart from the structure effect, temperature rise has an effect on composite damage mode by degrading the localized matrix stiffness.

Many of the existing reservoir dams are constructed in alpine and gorge regions, where the topography and geological conditions are complicated, bank slopes are steep, and landslides have a high potential to occur. Surges triggered by landslides in the reservoir are one of the major causes of dam overtopping failures. Many factors affect the slope stability of reservoir banks and the height of surges triggered by landslides, such as spatial variability of material properties, speed of landslides, etc. To reasonably evaluate dam overtopping risk caused by landslide-induced surges is a key technology in engineering that is urgent to be solved. Therefore, a novel risk analysis method for overtopping failures caused by waves triggered by landslides induced by bank instability considering the spatial variability of material parameters is proposed in this study. Based on the random field theory, the simulation method for the spatial variability of material parameters is proposed, and the most dangerous slip surface of the reservoir bank slope is determined with the minimum value of the safety factors. The proxy risk analysis models for both the slope instability and dam overtopping are constructed with the consideration of spatial variability of material parameters, and then the dam overtopping failure risk caused by landslide-induced surges is calculated using the Monte-Carlo sampling. The proposed models are applied to a practical engineering project. Results show that the spatial variability of material properties significantly affects the instability risk of slopes, without considering which the risks of slope instability and dam overtopping may be overestimated. This study gives a more reasonable and realistic risk assessment of dam overtopping failures, which can provide technical support for the safety evaluation and risk control of reservoir dams.

Both Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) establish the persistent, life-long infection primarily at the latent status, and associate with certain types of tumors, such as B cell lymphomas, especially in immuno-compromised individuals including people living with HIV (PLWH). Lytic reactivation of these viruses can be employed to kill tumor cells harboring latently infected viral episomes through the viral cytopathic effects and the subsequent antiviral immune responses. In this study, we identified that polo-like kinase 1 (PLK1) is induced by KSHV de novo infection as well as lytic switch from KSHV latency. We further demonstrated that PLK1 depletion or inhibition facilitates KSHV reactivation and promotes cell death of KSHV-infected lymphoma cells. Mechanistically, PLK1 regulates Myc that is critical to both maintenance of KSHV latency and support of cell survival, and preferentially affects the level of H3K27me3 inactive mark both globally and at certain loci of KSHV viral episomes. Furthremore, we recognized that PLK1 inhibition synergizes with STAT3 inhibition to efficiently induce KSHV reactivation. We also confirmed that PLK1 depletion or inhibition yields the similar effect on EBV lytic reactivation and cell death of EBV-infected lymphoma cells. Lastly, we noticed that PLK1 in B cells is elevated in the context of HIV infection and caused by HIV Nef protein to favor KSHV/EBV latency.

This paper presents AlScN piezoelectric two-axis MEMS mirrors with gimbal-less and gimbaled designs fabricated in a CMOS-compatible manner. Integrated piezoelectric sensors provided feedback signals of the actual mirror positions. The mirror with a diameter of 1.5 mm possessed adjustable optical tilt angles of up to 22.6° @ 30 V, with a high resonance frequency of about 8.2 kHz, while the 3 mm mirror reached 48.5° @ 41 V. The mirror with the gimbaled structure exhibited an excellent field of view and good mechanical decoupling. Additionally, a significant improvement in mirror scanning performance was observed in a vacuum (4 Pa), proving that the optical field of view was magnified by more than a factor of 10.

Optimization with edge contact avoidance and contact stress minimization is essential for gear design. Due to the complex geometry of modified helical face gear drives, it is complicated to find the optimal design parameters with the consideration of issues including loading, assembly errors, and edge contact. As the finite element method is tedious and time-consuming, an optimization model with a simplified algorithm of the loaded tooth contact analysis with errors (ELTCA) for modified helical face gears is presented, and it can programmatically optimize the contact stress with edge contact avoidance. Firstly, a simplified ETCA algorithm is introduced, which reduces the five unknowns in the traditional contact equations to three. Secondly, the LTCA is analytically implemented according to the Hertz theory. Subsequently, an optimization model with the objective function of avoiding edge contact and reducing maximum contact stress is proposed. Furthermore, the proposed model is applied to reveal the effects of design parameters and assembly errors on the optimized contact path and stress. The results show that the optimization model is accurate and efficient; the design parameters and assembly errors have great effects on the meshing of modified helical face gears.

Existing studies on autonomous driving methods focus on the fusion of onboard sensor data. However, the driving behavior might be unsteady because of the uncertainties of environments. In this article, an expectation line is proposed to quantify the driving behavior motivated by the driving continuity of human drivers. Furthermore, the smooth driving could be achieved by predicting the future trajectory of the expectation line. First, a convolutional neural network-based method is applied to detect lanes in images sampled from driving video. Second, the expectation line is defined to model driving behavior of an autonomous vehicle. Finally, the long short-term memory-based method is applied to the expectation line so that the future trajectory of the vehicle could be predicted. By incorporating convolutional neural network- and long short-term memory-based methods, the autonomous vehicles could smoothly drive because of the prior information. The proposed method is evaluated using driving video data, and the experimental results demonstrate that the proposed method outperforms methods without trajectory predictions.

Background and Aims. Hepatic encephalopathy (HE) is characterized by recurrence and poor quality of life. Acute-on-chronic liver failure (ACLF) mainly occurs in patients with chronic liver diseases and often presents with HE. Several predictive models have been proposed to predict the outcomes of these patients. Our study is aimed at identifying associated risk factors and the prognostic accuracies of predictive models in HE patients with or without ACLF. Methods. Patients with liver cirrhosis were retrospectively enrolled. Risk factors were evaluated by multivariate regression analyses. The predictive capabilities of models were calculated using the receiver operating characteristic (ROC) curve analyses and compared by the DeLong tests. Outcomes were defined as in-hospital mortality, HE severity, and ACLF occurrence. Results. In multivariate regression analyses, serum biomarkers neutrophil and total bilirubin (TBIL) were independently correlated with in-hospital death. Alanine aminotransferase (ALT) and blood urea nitrogen (BUN) were independent serum biomarkers associated with HE severity. Hemoglobin, TBIL, BUN, and international normalized ratio (INR) were significant indicators associated with ACLF incidence. For prediction of in-hospital mortality, Child-Pugh was superior to the others in the whole patients, while NLR showed the best capability in the ACLF group. Conclusion. In cirrhotic patients present with HE, BUN is a risk factor associated with HE severity and ACLF incidence. Child-Pugh and NLR scores may be effective prognosticators in patients with HE.

Fecal indicator bacteria (FIB) are typically used to monitor microbial water quality but are poor representatives of viruses due to different environmental fate. Viral fecal indicators have been proposed as alternatives to FIB; however, data evaluating the persistence of emerging viral fecal indicators under realistic environmental conditions is necessary to evaluate their potential application. In this study, we examined the persistence of five viral fecal indicators, including crAssphage and pepper mild mottle virus (PMMoV), and three bacterial fecal indicators (E. coli, enterococci and HF183/BacR287) in large-scale experimental ponds and freshwater mesocosms. Observed inactivation rate constants were highly variable and ranged from a minimum of −0.09 d−1 for PMMoV to a maximum of −3.5 d−1 for HF183/BacR287 in uncovered mesocosms. Overall, viral fecal indicators had slower inactivation than bacterial fecal indicators and PMMoV was inactivated more slowly than all other targets. These results demonstrate that bacterial fecal indicators inadequately represent viral fate following aging of sewage contaminated water due to differential persistence, and that currently used fecal indicator monitoring targets demonstrate highly variable persistence that should be considered during water quality monitoring and risk assessment.

Peptidylarginine deiminases (PADs) are a family of calcium-dependent enzymes that are involved in a variety of human disorders, including cancer and autoimmune diseases. Although targeting PAD4 has shown no benefit in sepsis, the role of PAD2 remains unknown. Here, we report that PAD2 is engaged in sepsis and sepsis-induced acute lung injury in both human patients and mice. Pad2–/– or selective inhibition of PAD2 by a small molecule inhibitor increased survival and improved overall outcomes in mouse models of sepsis. Pad2 deficiency decreased neutrophil extracellular trap (NET) formation. Importantly, Pad2 deficiency inhibited Caspase-11–dependent pyroptosis in vivo and in vitro. Suppression of PAD2 expression reduced inflammation and increased macrophage bactericidal activity. In contrast to Pad2–/–, Pad4 deficiency enhanced activation of Caspase-11–dependent pyroptosis in BM-derived macrophages and displayed no survival improvement in a mouse sepsis model. Collectively, our findings highlight the potential of PAD2 as an indicative marker and therapeutic target for sepsis.

Under the action of electromagnetic force, mechanical force and gravity, the radial deformation of rotor supporting must meet the design standard while ensuring the lightest mass. At first, the mathematical model of single objective optimization is established. Then, the objective function is optimized by the combination of genetic algorithm and finite element method GA-FEM . With the help of this method, the optimal design parameters of the rotor supporting are obtained. This paper takes the actual rotor supporting of 7MW prototype as the optimization object. The optimal solution of this structure without the lightweight holes can be obtained by first optimization. And then, the optimal solution of the final structure with the lightweight holes is obtained by the second optimization. The final simulation shows that the stiffness can be met while reducing the mass by 40%.

In modern industrial engineered systems, variant working conditions disturb the distributions of machines' operational data, which results in different feature distributions (DFD) problems for fault prognostics. Domain adaptation (DA) have been proved good at dealing DFD problems, and several deep DA-based methods have been also proposed in fault prognostics filed. However, existing methods refer to the DA tasks from one working condition to another, without considerations of transferring between datasets under complex working conditions. The prior distribution of working conditions will influence the distributions of machines' operational data, and few studies take prior distribution of working conditions into consideration of DA for fault prognostics. Thus, in this paper, a working-condition-based deep domain adaptation network (Deep wcDAN) is proposed to overcome the DFD problems caused by variant complex working conditions. In the proposed method, CNNs combines LSTMs with domain adaptive transfer technique to minimize the distribution discrepancy between training and testing datasets. Furthermore, a working-condition-based MMD (wcMMD) is proposed to optimize the DA process based on the prior distribution of each working condition. The performance of proposed model is evaluated and the negative transfer effects have been analyzed based on C-MAPSS datasets. The results show that the proposed method performs better than baseline methods on predicting remaining useful life (RUL) with DFD problems.

A multi-objective optimization method for constant stress accelerated degradation test is proposed in order to solve the problem of different or even conflicted test configuration under different optimization objectives. The inverse Gaussian process is used as a degradation model, and the unknown parameters are solved by maximum likelihood estimation. The two optimization criteria of the maximum determinant of the information matrix and the minimum asymptotic variance of P-quantile are considered. The improved multi-objective particle swarm optimization algorithm is proposed to search test optimal configuration, and the Pareto solution set for dual-objectives is obtained. Finally, the effectiveness of the method is illustrated by a group of examples of electrical connectors. Compared with the single-objective optimization design, the proposed method is more reasonable and convenient for test configuration. The performance index of the test function indicates that the optimal algorithm we proposed has some obvious advantages over the NSGA-II in diversity and convergence of the Pareto solutions and it is significant in guiding engineering practice.

IntroductionThis longitudinal study aims to characterize distinct body mass index (BMI) trajectories during early to mid-life adulthood and to explore the association between BMI change from young adulthood to midlife and incident diabetes.Research design and methodsThis study included 7289 adults who had repeatedly measured BMI 3–9 times during 1989–2011 and information on incident diabetes. Latent class growth mixed model (LCGMM) was used to identify different BMI trajectories. Cox proportional hazard models were used to investigate the association between the trajectory group membership and incident hyperglycemia, adjusting for covariates. The hyperglycemia group included individuals with prediabetes or diabetes. The model-estimated BMI levels and slopes were calculated at each age point in 1-year intervals according to the model parameters and their first derivatives, respectively. Logistic regression analyses were used to examine the association of model-estimated levels and slopes of BMI at each age point with incident hyperglycemia. The area under the curve (AUC) was computed from longitudinal growth curve models during the follow-up for each individual. Prior to the logistic regression analyses, quartiles of total, baseline, and incremental AUC values were calculated.ResultsThree distinct trajectories were characterized by LCGMM, comprising of low-increasing group (n=5136), medium-increasing group (n=1914), and high-increasing group (n=239). Compared with the low-increasing group, adjusted HRs and 95% CIs were 1.21 (0.99 to 1.48) and 1.56 (1.06 to 2.30) for the medium-increasing and the high-increasing group, respectively. The adjusted standardized ORs of model-estimated BMI levels increased among 20–50 years, ranging from 0.98 (0.87 to 1.10) to 1.19 (1.08 to 1.32). The standardized ORs of level-adjusted linear slopes increased gradually from 1.30 (1.16 to 1.45) to 1.42 (1.21 to 1.67) during 20–29 years, then decreased from 1.41 (1.20 to 1.66) to 1.20 (1.08 to 1.33) during 30–43 years, and finally increased to 1.20 (1.04 to 1.38) until 50 years. The fourth quartile of incremental AUC (OR=1.31, 95% CI 1.03 to 1.66) was significant compared with the first quartile, after adjustment for covariates.ConclusionsThese findings indicate that the BMI trajectories during early adulthood were significantly associated with later-life diabetes. Young adulthood is a crucial period for the development of diabetes, which has implications for early prevention.

Neuro-glia antigen 2/chondroitin sulfate proteoglycan 4 (NG2/CSPG4, also called MCSP, HMW-MAA, MSK16, MCSPG, MEL-CSPG, or gp240) is a large cell-surface antigen and an unusual cell membrane integral glycoprotein frequently expressed on undifferentiated precursor cells in multiple solid organ cancers, including cancers of the liver, pancreas, lungs, and kidneys. It is a valuable molecule involved in cancer cell adhesion, invasion, spreading, angiogenesis, complement inhibition, and signaling. Although the biological significance underlying NG2/CSPG4 proteoglycan involvement in cancer progression needs to be better defined, based on the current evidence, NG2/CSPG4+ cells, such as pericytes (PCs, NG2+/CD146+/PDGFR-β+) and cancer stem cells (CSCs), are closely associated with the liver malignancy, hepatocellular carcinoma (HCC), pancreatic malignancy, and pancreatic ductal adenocarcinoma (PDAC) as well as poor prognoses. Importantly, with a unique method, we successfully purified NG2/CSPG4-expressing cells from human HCC and PDAC vasculature tissue blocks (by core needle biopsy). The cells appeared to be spheres that stably expanded in cultures. As such, these cells have the potential to be used as sources of target antigens. Herein, we provide new information on the possibilities of frequently selecting NG2/CSPG4 as a solid organ cancer biomarker or exploiting expressing cells such as CSCs, or the PG/chondroitin sulfate chain of NG2/CSPG4 on the cell membrane as specific antigens for the development of antibody- and vaccine-based immunotherapeutic approaches to treat these cancers.

Accurate and efficient measurements of the piezoelectric properties of AlN and AlScN films are very important for the design and simulation of micro-electro-mechanical system (MEMS) sensors and actuator devices. In this study, a process control monitor (PCM) structure compatible with the device manufacturing process is designed to achieve accurate determination of the piezoelectric coefficients of MEMS devices. Double-beam laser interferometry (DBLI) and laser Doppler vibrometry (LDV) measurements are applied and combined with finite element method (FEM) simulations, and values of the piezoelectric parameters d33 and d31 are simultaneously extracted. The accuracy of d31 is verified directly by using a cantilever structure, and the accuracy of d33 is verified by in situ synchrotron radiation X-ray diffraction; the comparisons confirm the viability of the results obtained by the novel combination of LDV, DBLI and FEM techniques in this study.

Abstract Background Gold nanoparticles (AuNPs) have been widely studied for biomedical applications, although their safety and potential toxicity in pregnancy remains unknown. The aim of this study is to explore the effect of AuNPs maternal exposure at different gestational ages on fetal survival and development, as well as the potential mechanism of AuNPs affecting embryos and fetuses. Methods Thirty nm polyethylene glycol (PEG)-coated AuNPs (A30) were administered to pregnant mice via intravenous injection (5 μg Au/g body weight) over three days at either early or late pregnancy. Fetal abortion rate and morphological development in E16.5 were then detected in detail. The pregnant mice physiological states with A30 exposure were examined by biochemical, histological or imaging methods; and materno-fetal distribution of gold elements was assayed by electron microscopy and mass spectrometry. Murine embryonic stem cells derived embryoid-bodies or neuroectodermal cells were treated with A30 (0.0025 to 0.25 μg Au/mL) to examine A30 effects on expression levels of the germ differentiation marker genes. Tukey’s method was used for statistical analysis. Results Exposure to A30 during early (A30E) but not late (A30L) pregnancy caused a high abortion rate (53.5%), lower fetal survival rate and abnormal decidualization compared with non-exposed counterparts. The developmental damage caused by A30 followed an “all-or-nothing” pattern, as the non-aborted fetuses developed normally and pregnancies maintained normal endocrine values. A30 caused minor impairment of liver and kidney function of A30E but not A30L mice. TEM imaging of fetal tissue sections confirmed the transfer of A30 into fetal brain and live as aggregates. qPCR assays showed A30 suppressed the expression of ectodermal, but not mesodermal and endodermal differentiation markers. Conclusions These results illustrate that maternal A30 exposure in early pregnant results in A30 transfer into embryonic tissues, inhibiting ectodermal differentiation of embryonic stem cells, leading to abnormal embryonic development and abortion. While exposure to A30 during late pregnancy had little or no impact on dams and fetuses. These findings suggest the safety of biomedical applications employing AuNPs during pregnancy is strongly influenced by fetal maturity and gestational age at exposure and provide the clues for AuNPs safe application period in pregnancy.

Deploying multiple heterogeneous controllers at the control level of a software-defined data center is an effective way to increase security.In view of the deployment strategy of controllers under different security requirements of the network,a game model was presented.Specifically,firstly,the game theory was used to depict the attack and defense game model and solve the Nash equilibrium,and then guided the design of security strategy.Secondly,the impact of the strategy of attack and defense on the security status of the control layer were analyzed.Finally,the simulation results show the effectiveness of the proposed equilibrium strategy,and describe the dynamic interaction strategy.

For clusters of UAVs, the scale and density of the cluster determine its ability to solve the task. With the increasing density of aerial vehicles, effectively planning a reasonable flight path and avoiding conflicts among flight paths have become key problems for UAV clusters. The traditional control method is to detect potential conflicts through radar monitoring or location reporting in the air and to then change the flight path, including the height, heading, and speed, through manual instruction. To solve the problem of path conflicts for UAV clusters, a method for calculating the collision probabilities of UAVs is established under the constraints of mission space and the number of UAVs. In cluster flight mode, automatic tracking and prediction of UAV cluster tracks are implemented to avoid path conflicts in clusters. In addition, to address the inconsistency problem because of noise caused by the state information of multi UAV communication under a dynamic environment, a state estimation method is proposed based on the Kalman algorithm. To achieve aircraft track planning, cluster state prediction and collision probability are eventually calculated to avoid the clusters of formation UAVs conflicting on paths during flight. Finally, the simulation results verify the validity and effectiveness of the proposed method in multi UAV formation flight planning.

With the development of artificial intelligence technology, data-driven fault diagnostics and prognostics in industrial systems have been a hot research area since the large volume of industrial data is being collected from the industrial process. However, imbalanced distributions exist pervasively between faulty and normal samples, which leads to imprecise fault diagnostics and prognostics. In this paper, an effective imbalance learning algorithm Easy-SMT is proposed. Easy-SMT is an integrated ensemble-based method, which comprises synthetic minority oversampling technique (SMOTE)-based oversampling policy to augment minority faulty classes and EasyEnsemble to transfer an imbalanced class learning problem into an ensemble-based balanced learning subproblem. We validate the feasibility and effectiveness of the proposed method in a real wind turbine failure forecast challenge, and our solution has won the third place among hundreds of teams. Moreover, we also evaluate the method on prognostics and health management 2015 challenge datasets, and the results show that the model could also achieve good performance on multiclass imbalance learning task compared with baseline classifiers.

Explosive increase of industrial data collected from sensors has brought increasing attractions to the data-driven predictive maintenance for industrial machines in cyber-physical systems (CPSs). Since machinery faults are always caused by performance deterioration of components, learning the deteriorating mode from observed sensor data facilitates the prognostics of impeding faults and predicting the remaining useful life (RUL). In modern CPSs, several key performance indicators (KPIs) are monitored to detect the corresponding fine-grained deteriorating modes of industrial machines. However, the overall deterioration estimation and RUL prediction based on these KPIs with various patterns have been a great challenge, especially without labels of deteriorating index or uninterpretable of root causes. In this paper, we proposed K-PdM, a cluster-based hidden Markov model for the machinery deterioration estimation and RUL prediction based on multiple KPIs. The method uncovers the fine-grained deteriorating modes of machines through each unlabeled KPI data and learns a mapping between each deteriorating KPI index and RULs. Accordingly, an overall deterioration estimation and RUL prediction of machine are able to be achieved based on the combination of each KPI's deterioration estimation. Moreover, a set of interpretable semantic rules are setup to analyze the root cause of performance deterioration among KPIs. An experimental application is proposed to demonstrate its applicability based on the PHM08 data sets. The obtained results show their effectiveness to predict the RULs of machines.

Abstract Background The lymphocytes played an important role in the natural history of cancer. The aim of this study was to explore the prognostic value of lymphocyte count and percentage for survival in advanced cancer patients receiving palliative care. Methods A retrospective review of clinicopathological data from 378 consecutive advanced cancer patients and 106 extended follow-up patients treated with palliative care was conducted. Kaplan–Meier curves and multivariate cox regression analyses were used to evaluate the relationships of peripheral lymphocyte count (LC) and lymphocyte to white blood cell ratio (LWR) with overall survival (OS). Results The median values for pretreatment LC and LWR were 1.1 (IQR, 0.8 ~ 1.5 × 109/L) and 0.138 (IQR, 0.086 ~ 0.208). The median survival times across LWR quartiles were 19, 47, 79, and 101 days (P

Abstract Background According to the current official guidelines, at least 12 lymph nodes (LNs) are qualified as an adequate sampling for colon cancer patients. However, patients evaluated with less nodes were still common in the United States, and the prevalence of positive nodal disease may be under-estimated because of the false-negative assessment. In this study, we present a statistical model that allows preoperative determination of the minimum number of lymph nodes needed to confirm a node-negative disease with certain confidence. Methods Adenocarcinoma colon cancer patients with stage T1-T3, diagnosed between 2004 and 2013, who did not receive neoadjuvant therapies and had at least one lymph node pathologically examined, were extracted from the Surveillance, Epidemiology and End Results (SEER) database. A beta binomial distribution was used to estimate the probability of an occult nodal disease is truly node-negative as a function of total number of LNs examined and T stage. Results A total of 125,306 patients met study criteria; and 47,788 of those were node-positive. The probability of falsely identifying a patient as node-negative decreased with an increasing number of nodes examined for each stage, and was estimated to be 72% for T1 and T2 patients with a single node examined and 57% for T3 patients with a single node examined. To confirm an occult nodal disease with 90% confidence, 3, 8, and 24 nodes need to be examined for patients from stage T1, T2, and T3, respectively. Conclusions The false-negative rate of diagnosed node negative, together with the minimum number of examined nodes for adequate staging, depend preoperatively on the clinical T stage. Predictive tools can recommend a threshold on the minimum number of examined nodes regarding to the favored level of confidence for each T stage.

Wastewater treatment plants are typically monitored using fecal indicator bacteria to ensure adequate microbial water quality of the treated effluent. Fecal indicator bacteria exhibit poor correlation with virus fate in the environment, including during wastewater treatment. Viral-based microbial source tracking methods have the potential to overcome this limitation. The recently discovered human gut bacteriophage crAssphage is a promising viral human fecal indicator. In this current study, primary influent, primary effluent, secondary effluent, and final effluent of a conventional activated sludge wastewater treatment plant were analyzed for a suite of fecal indicators to evaluate the suitability of crAssphage as a wastewater process indicator for virus removal. CrAssphage was the most abundant fecal indicator measured through the wastewater treatment process. Culturable and molecular bacterial fecal pollution indicators showed higher removal than viral fecal pollution indicators, including crAssphage, confirming the necessity of a viral-specific fecal monitoring target. CrAssphage was strongly correlated with adenovirus and polyomavirus molecular indicators through the wastewater treatment process. Literature comparison demonstrated site-specific removal of molecular fecal indicators during wastewater treatment highlighting the need for local performance validation. The high abundance of crAssphage and correlation with pathogenic viruses suggests the potential suitability of crAssphage as a viral fecal pollution process indicator during wastewater treatment. Keywords: crAssphage, Wastewater treatment, Virus, Activated sludge, Water quality, Adenovirus, Polyomavirus

Sepsis results in millions of deaths every year, with acute lung injury (ALI) being one of the leading causes of mortality in septic patients. As neutrophil extracellular traps (NETs) are abundant in sepsis, neutralizing components of NETs may be a useful strategy to improve outcomes of sepsis. Citrullinated histone H3 (CitH3) has been recently shown to be involved in the NET formation. In this study, we demonstrate that CitH3 damages human umbilical vein endothelial cells (HUVECs) and potentiates NET formation through a positive feedback mechanism. We developed a novel CitH3 monoclonal antibody to target peptidylarginine deiminase (PAD) 2 and PAD 4 generated CitH3. In a mouse model of lethal lipopolysaccharide (LPS) induced shock, neutralizing CitH3 with the newly developed anti-CitH3 monoclonal antibody attenuates inflammatory responses, ameliorates ALI, and improves survival. Our study suggests that effectively blocking circulating CitH3 might be a potential therapeutic method for the treatment of endotoxemia.

For modern high earth dams, sufficient safety margin is considered in the designs of flood discharge capacity and dam crest elevation to prevent flood overtopping. However, for high earth dams which may induce catastrophic consequences, during their long operational period, extremely hazardous scenarios which could occur and threaten dam safety need to be considered. For the earth dams located in areas with intensive seismicity, there is a possible scenario that the release structures fail due to seismic landslides and gate failures caused by a severe earthquake when the flood begins to enter the reservoir. Thus, it is desirable to investigate the influence of failure duration of release structures on dam overtopping risk. Based on the Bayesian network, a methodology for overtopping risk analysis of earth dams considering effects of failure duration of release structures is proposed. The overtopping risk of the PBG earth-rockfill dam was analyzed to illustrate the methodology. The critical release structures which dominate the dam overtopping risk are identified. The dam overtopping risk is most sensitive to the failure duration of the spillway. The tolerable failure duration of the spillway is approximately 3 days, and when the failure duration of the spillway reaches 4 days, the dam overtopping risk drastically rises to an unacceptable level. The case study suggests that the proposed methodology could be helpful to analyze the influences of possible failure durations of release structures on dam overtopping risk and could facilitate preparation for emergency plans.

Background Isoform-specific histone deacetylase inhibitors (HDACIs) MC1568 and ACY1083 are comparable to the non-selective HDACI valproic acid (VPA) in improving survival in rodents undergoing lethal hemorrhage. However, the organ-specific properties of isoform-specific HDACIs have not been fully evaluated. Also, whether they can act synergistically is not known. We hypothesized that isoform-specific HDACIs are superior to VPA in attenuating intestinal injury and act synergistically when coadministered.Methods Sprague Dawley rats were hemorrhaged (40% of total blood volume) and randomized to receive (n=4 per group) (1) MC1568 (5 mg/kg), (2) ACY1083 (30 mg/kg), (3) MC1568+ACY1083 (combination: 5 mg/kg + 30 mg/kg, respectively), (4) VPA (250 mg/kg), or (5) normal saline (NS; vehicle; 250 μL). Animals were observed for 3 hours, after which blood samples were collected and samples of the ileum were harvested. Expression of interleukin 1 beta (IL-1β), tumor necrosis factor alpha (TNF-α), and cytokine-induced neutrophil chemoattractant 1 (CINC-1) was assessed in the tissues using enzyme-linked immunosorbent assay. Intestinal cleaved caspase 3 (c-caspase 3) levels were assessed as a marker of apoptosis, and histologic sections of the ileum were examined for signs of bowel injury. Levels of IL-1β and TNF-α were also measured in the serum as global markers of inflammation.Results Treatments with MC1568, ACY1083, MC1568+ACY1083, and VPA were associated with decreased IL-1β levels in the intestine and serum compared with NS. IL-1β and TNF-α levels were significantly lower in the ACY1083 group compared with the VPA group. CINC-1 levels were significantly lower in the isoform-specific HDACI groups compared with the NS; however, no significant differences were seen with VPA. All treatment groups had a lower expression of intestinal c-caspase 3 compared with NS. Furthermore, MC1568 and ACY1083 groups had lower apoptosis compared with the VPA group. Bowel injury scores were significantly lower in the isoform-specific HDACI groups compared with the NS group; however, the attenuation in the VPA-treated animals did not reach statistical significance.Discussion Isoform-specific HDACIs provide superior intestinal protection compared with VPA in a rodent model of hemorrhagic shock.Level of evidence Preclinical study.

Abstract This study investigated the influence of dietary fiber levels on the growth performance, digestion, metabolism, and cecal microbial community of rabbits with different diets at different age. The different levels of dietary natural detergent fiber (NDF) were formulated accordingly: 400(A), 350(B), 300(C), 250(D) g/kg original matter basis, respectively; the different ages were 52, 62, and 72 days. With NDF increasing, the average daily feed intake (ADFI) and feed conversion rate (FCR) were increased, whereas average daily gain (ADG) and mortality were decreased (p

In order to carry out various detections of system indicators during the research and development phase of infrared guided missiles, the article first analyzes several main design schemes of the infrared guided missile detection simulator and finds that it has the disadvantages of difficult processing technology and low detection accuracy. The overall structure of the detection device was designed, including the design of the rotation and swing mechanism, lens mechanism, optical system and control system. The optical system error analysis is performed on the infrared guided missile detection simulator. The position of the receiving light source is obtained by analyzing the mechanism characteristics of the detection simulator and the kinematics model of the device. The phase difference analysis of the eccentricity and tilt system is obtained. The image quality was evaluated by the optical transfer function (MTF), and the system error was found to meet the requirements of imaging quality. The experiments show that the simulation of 1.7~4.9 um medium wave infrared dynamic target signals provides an accurate and reasonable experimental environment for the missile and the verification of the light source target and meets the experimental requirements.