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Abstract Background The development of pulmonary fibrosis involves a cascade of events, in which inflammation mediated by immune cells plays a pivotal role. Chemotherapeutic drugs have been shown to have dual effects on fibrosis, with bleomycin exacerbating pulmonary fibrosis and bortezomib alleviating tissue fibrotic processes. Understanding the intricate interplay between chemotherapeutic drugs, immune responses, and pulmonary fibrosis is likely to serve as the foundation for crafting tailored therapeutic strategies. Methods A model of bleomycin-induced pulmonary fibrosis was established, followed by treatment with bortezomib. Tissue samples were collected for analysis of immune cell subsets and functional assessment by flow cytometry and in vitro cell experiments. Additionally, multi-omics analysis was conducted to further elucidate the expression of chemokines and chemokine receptors, as well as the characteristics of cell populations. Results Here, we observed that the expression of CXCL16 and CXCR6 was elevated in the lung tissue of a pulmonary fibrosis model. In the context of pulmonary fibrosis or TGF-β1 stimulation in vitro, macrophages exhibited an M2-polarized phenotype and secreted more CXCL16 than those of the control group. Moreover, flow cytometry revealed increased expression levels of CD69 and CXCR6 in pulmonary CD4 T cells during fibrosis progression. The administration of bortezomib alleviated bleomycin-induced pulmonary fibrosis, accompanied by reduced ratio of M2-polarized macrophages and decreased accumulation of CD4 T cells expressing CXCR6. Conclusions Our findings provide insights into the key immune players involved in bleomycin-induced pulmonary fibrosis and offer preclinical evidence supporting the repurposing strategy and combination approaches to reduce lung fibrosis.

Multiscale Dense Network (MSDN) is a deep convolutional neural network method proposed to solve the loss of fine features in hyperspectral remote sensing images. Multiscale Dense Network (MSDN), which makes full use of the different scale information in the network, implements feature extraction of HSI in both horizontal and vertical dimensions. Since MSDN maintains all fine scales until the last layer of the network, the computational effort is large. To address this problem, this paper proposes a lightweight Inter layer Short Multiscale Dense Network (IMSDN) method for hyperspectral image classification. HSI classification is performed using network reduction and inert computation to avoid unnecessary computation, the MSDN network is divided into S blocks along the horizontal dimension, keeping the coarsest (S-i+1) scale only in the ith block and only down sampling the final output of each block in the Short Multiscale Dense Network (SMSDN) for HSI classification. On the basis of the SMSDN network, in order to maintain the classification accuracy of the network, the Lightweight Interlayer Multiscale Dense Network (IMSDN) utilizes three scales of convolution kernels in different horizontal directions to extract the image features separately, which are then fused for the classification of HSI. Experiments are conducted on two publicly available datasets and the results are compared with other methods to demonstrate that the IMSDN network has less computation and shortens the experiment time compared to the MSDN network while guaranteeing the classification accuracy.

ABSTRACTAiming the problems that the classification performance of hyperspectral images in existing classification algorithms is highly dependent on spatial-spectral information and that detailed features are ignored in single convolutional channel feature extraction, resulting in poor generalization performance of the feature extraction model, a multi-scale multi-channel convolutional neural network (MMC-CNN) model is proposed in this paper. First, the data set is divided into two kinds of pixel module, and then different channels are used for feature extraction. A channel-space attention mechanism module is also introduced, and a multi-scale multichannel convolutional neural network (CSAM-MMC) model with the introduction of channel-space attention mechanism is proposed for deeper spatial-spectral feature extraction of hyperspectral image elements while reducing the redundancy of convolutional pooling parameters to achieve better HSI classification. To evaluate the effectiveness of the proposed model, experiments were conducted on Indian Pines, Pavia Center and KSC datasets respectively, and the overall classification accuracies of this paper’s MMC-CNN model in the HSI dataset were 97.23%, 98.50%, and 97.85%, thus verifying the model’s high feature extraction accuracy. The CSAM-MMC model in this paper further improves 0.13%, 0.35%, and 0.71% relative to the MMC-CNN model, which provides higher overall accuracies relative to other state-of-the-art algorithms.

In this paper, we propose a stochastic primal-dual adaptive method based on an inexact augmented Lagrangian function to solve non-convex programs, referred to as the SPDAM. Different from existing methods, SPDAM incorporates adaptive step size and momentum-based search directions, which improve the convergence rate. At each iteration, an inexact augmented Lagrangian subproblem is solved to update the primal variables. A post-processing step is designed to adjust the primal variables to meet the accuracy requirement, and the adjusted primal variable is used to compute the dual variable. Under appropriate assumptions, we prove that the method converges to the ε-KKT point of the primal problem, and a complexity result of SPDAM less than O(ε−112) is established. This is better than the most famous O(ε−6) result. The numerical experimental results validate that this method outperforms several existing methods with fewer iterations and a lower running time.

In order to achieve the non-destructive testing and quality evaluation of stainless-steel resistance spot welding (RSW) joints, a portable ultrasonic spiral C-scan testing instrument was developed based on the principle of ultrasonic pulse reflection. A mathematical model for the quality evaluation of RSW joints was established, and the centroid of the ultrasonic C-scan image in the nugget zone of the RSW was determined based on the principle of static moment. The longest and shortest axes passing through the centroid in the image were extracted, and the ratio of the longest axis to the shortest axis (RLS) factor and the average of axis (AOA) factor were calculated, respectively, to evaluate the quality of the joint. To study the effectiveness of the detection results, tensile tests, and stereo analysis were conducted on the solder joints after sampling. The results indicate that this detection method can realize online detection and significantly improve the detection efficiency; the detection value of internal defect size is close to the true value with an error of 0.1 mm; the combination of RLS and AOA factors can be used to evaluate the mechanical properties of RSW joints. This technology can be used to solve the NDT, evaluate problems of RSW joints, and realize engineering applications.

On the backdrop of dwindling conventional reserves, unconventional reservoirs have emerged as a pivotal chapter in resource extraction. Despite their challenges, such as low permeability, complex fluid storage, and flow mechanisms, hydraulic fracturing technology has underpinned the development of unconventional reservoirs. Consequently, this has brought about a shift in the sequence of flow regimes, e.g., the transient radial flow regime has been largely shortened by the lengthy transient linear flow regime due to the low permeability of unconventional reservoirs. Moreover, straight-line analysis (SLA), the simplest technique in rate transient analysis (RTA), is a fundamental and potent tool for swiftly extracting reservoir and hydraulic fracture information, estimating oil and gas reserves, and furnishing crucial initial data for subsequent historical matching processes. However, there is currently a dearth of review papers pertaining to a necessary guide of applying SLA in various transient linear flow (TLF) regimes and different unconventional reservoirs. Hence, this paper commences by elucidating the classification of TLF regimes, commonly used methods for recognizing flow regimes, and the diverse SLA methods used for different TLF regimes. Subsequently, it delves into a discussion of different modification techniques for variable rate/flowing pressure, gas phase, complex reservoir characteristics in unconventional reservoirs, and dynamic drainage area concepts etc. Furthermore, the application of SLA in specific domains, namely core analysis and the flowback period, is described. It culminates by surveying the advancements through an integration of novel technologies to enhance estimation accuracy. The paper also highlights certain drawbacks of current SLA technology and proposes new research directions. Ultimately, this paper would serve as an indispensable resource, offering foundational knowledge for the application of SLA in TLF to promote the production of global unconventional resources in a cost-effective and environmentally sustainable fashion in the face of a climate-resilient world.

Carbon dioxide (CO2) is an important heat-trapping gas, or greenhouse gas, that comes from the extraction and burning of fossil fuels. On the other hand, plastic is widely used for making various products, such as medical devices and packaging bags, but it causes pollution that damages human health and the environment. Therefore, biodegradable plastic materials synthesized by using CO2 is one of the most desirable alternatives of traditional non-biodegradable plastic materials to alleviate anthropogenic CO2 and non-degradable plastic pollution. Particularly, CO2-based poly(propylene carbonate) (PPC) has received increasing attention owing to its good functionalization modification advantages and its potential in the large-scale utilization of CO2. We review the synthetic routes of PPCs through incorporations of different functionalized third monomers to the polymer chains and their effects on properties of newly functionalized PPCs. The results show that the copolymerization of CO2 and propylene oxide (PO) provides a way to utilize excess CO2 for producing biodegradable and environmentally friendly polymerization products (i.e., CO2-based PPC). This offers a novel strategy for the preparation of new and potentially sustainable plastic materials.

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their impact on winter wheat in the Huang-Huai-Hai Plain from 1982 to 2020. High-temperature–drought events increased in frequency and expanded from north to south, with about 40% of observation stations recording such events from 2001 to 2020. In contrast, low-temperature–drought events decreased in frequency, affecting up to 80% of stations, but with lower frequency than high-temperature–drought events. Sensitivity analyses show winter wheat is most responsive to maximum and minimum temperature changes, with significant correlations to drought and temperature extremes. Copula analysis indicates temperature extremes and drought severity are crucial in determining compound event probability and return periods. High-temperature–drought events are likely under high temperatures and mild drought, while low-temperature–drought events are more common under low temperatures and mild drought. These findings highlight the need for effective agricultural adaptation strategies to mitigate future climate change impacts.

Abstract Background Peatlands contain about 500 Pg of carbon worldwide and play a dual role as both a carbon sink and an important methane (CH4) source, thereby potentially influencing climate change. However, systematic studies on peat properties, microorganisms, methanogenesis, and their interrelations in peatlands remain limited, especially in China. Therefore, the present study aims to investigate the physicochemical properties, archaeal community, and predominant methanogenesis pathways in three typical peatlands in China, namely Hani (H), Taishanmiao (T), and Ruokeba (R) peatlands, and quantitively determine their CH4 production potentials. Results These peatlands exhibited high water content (WC) and total carbon content (TC), as well as low pH values. In addition, R exhibited a lower dissolved organic carbon concentration (DOC), as well as higher total iron content (TFe) and pH values compared to those observed in T. There were also clear differences in the archaeal community between the three peatlands, especially in the deep peat layers. The average relative abundance of the total methanogens ranged from 10 to 12%, of which Methanosarcinales and Methanomicrobiales were the most abundant in peat samples (8%). In contrast, Methanobacteriales were mainly distributed in the upper peat layer (0–40 cm). Besides methanogens, Marine Benthic Group D/Deep-Sea Hydrothermal Vent Euryarchaeotic Group 1 (MBG–D/DHVEG–1), Nitrosotaleales, and several other orders of Bathyarchaeota also exhibited high relative abundances, especially in T. This finding might be due to the unique geological conditions, suggesting high archaeal diversity in peatlands. In addition, the highest and lowest CH4 production potentials were 2.38 and 0.22 μg g−1 d−1 in H and R, respectively. The distributions of the dominant methanogens were consistent with the respective methanogenesis pathways in the three peatlands. The pH, DOC, and WC were strongly correlated with CH4 production potentials. However, no relationship was found between CH4 production potential and methanogens, suggesting that CH4 production in peatlands may not be controlled by the relative abundance of methanogens. Conclusions The results of the present study provide further insights into CH4 production in peatlands in China, highlighting the importance of the archaeal community and peat physicochemical properties for studies on methanogenesis in distinct types of peatlands.

Since hyperspectral remote sensing images are three-dimensional data cubes with spatial and spectral information, with many wavebands and high inter-band correlation, the number of training samples required for classification is greatly increased. In order to achieve better classification of hyperspectral remote sensing images with small samples, this paper proposes a hyperspectral remote sensing image classification method based on Multi-Scale Dense Network (MSDN) with 3D Gabor filter. The method extracts the texture features of hyperspectral remote sensing images by using 3D Gabor filter; then extracts the spatial spectral features of hyperspectral remote sensing images at different scales in both horizontal and vertical directions by using Multiscale Dense Network; and finally achieves the classification of hyperspectral remote sensing images by using Softmax classifier. The introduction of 3D Gabor filter in this method can improve the extraction effect of the features of hyperspectral remote sensing images, and at the same time reduce the dependence of the multiscale dense network on the labeled samples in the classification of hyperspectral remote sensing images. Experiments are conducted on three publicly available hyperspectral remote sensing datasets, and the experimental results are compared with other classification methods to prove that the method has better classification performance.

In this study, we aim to minimize light loss and achieve high power conversion efficiencies (PCE) in perovskite solar cells (PSCs) by employing a spectral conversion film component with antireflection properties. In our scheme, NaYF4:Tm, Yb, and Gd luminescent nanorod/silica nanosphere-based thin films are applied on CH3NH3PbI3 PSCs to improve the device efficiency. The film was fabricated by spin coating an aged silica sol containing NaYF4:Tm, Yb, and Gd luminescent nanorods. The size and the spectral conversion properties of the NaYF4:Tm, Yb, and Gd luminescent nanorods were controlled by tuning the Gd3+ ion concentration. The microstructure and the transmittance properties of the thin film were controlled by changing the concentration of NaYF4:Tm, Yb, and Gd luminescent nanorod in silica sol. The thin films have excellent spectral conversion properties while exhibiting a maximum transmittance. The photovoltaic performance of PSCs with NaYF4:Tm, Yb, and Gd luminescent nanorod/silica nanosphere-based thin films was systematically investigated. The light transmittance was optimized to 95.1% on a cleaned glass substrate, which resulted in an average increase of about 3.0% across the broadband range of 400–800 nm. The optimized films widen the spectrum of light absorbed by conventional PSC cells and reduce reflections across a broad range, enhancing the photovoltaic performance of PSCs. As a result, the PCE of the PSC increased from 14.51% for the reference device without a thin film to 15.67% for the PSC device with an optimized thin film. This study presents a comprehensive solution to the problem of Fresnel reflection and spectral response mismatch of the PSCs, which provides new ideas for the light management of PSCs.

Excessive reactive oxygen species (ROS), a highly reactive substance that contains oxygen, induced by ultraviolet A (UVA) cause oxidative damage to skin. We confirmed that hemin can catalyze the reaction of tyrosine (Tyr) and hydrogen peroxide (H2O2). Catalysis was found to effectively reduce or eliminate oxidative damage to cells induced by H2O2 or UVA. The scavenging effects of hemin for other free-radical ROS were also evaluated through pyrogallol autoxidation, 1,1-diphenyl-2-picrylhydrazyl radical (DPPH·)-scavenging assays, and phenanthroline–Fe2+ assays. The results show that a mixture of hemin and tyrosine exhibits strong scavenging activities for H2O2, superoxide anion (O2−·), DPPH·, and the hydroxyl radical (·OH). Furthermore, the inhibition of oxidative damage to human skin keratinocyte (HaCaT) cells induced by H2O2 or UVA was evaluated. The results show that catalysis can significantly reduce the ratio of cell apoptosis and death and inhibit the release of lactate dehydrogenase (LDH), as well as accumulation of malondialdehyde (MDA). Furthermore, the resistance to apoptosis was found to be enhanced. These results show that the mixture of hemin and tyrosine has a significantly protective effect against oxidative damage to HaCaT cells caused by UVA, suggesting it as a protective agent for combating UVA damage.

Many natural product biosynthetic gene clusters are found not to harbor a full set of necessary genes and must utilize enzymes encoded elsewhere (hidden) in the genome for biosynthesis. Here, the authors establish a global correlation network bridging the gap between lanthipeptide precursors and hidden proteases.

Despite the apparent absence of physical barriers in the ocean to prevent dispersal, recent studies have highlighted the importance of biological, geographical, physical, and historical barriers in the genetic structuring of marine species populations. This representation is essential for the sustainable exploitation of natural marine resources and for the setup of efficient protected area networks for the conservation of marine species. In this study, we used extensive sampling of Sebastiscus marmoratus, a commercially important inshore rockfish with high site fidelity, to characterize their population genetic structure along the China–Japan coast and to determine the effect of past geological and current biological–physical barriers on the current genetic footprint. A 461-bp fragment of the mtDNA hypervariable portion control region was sequenced for 675 individuals from 15 geographical locations. A total of 292 haplotypes were identified. The population of S. marmoratus showed high haplotype and nucleotide diversity. Pairwise fixation index (FST) and analysis of molecular variance (AMOVA) revealed significant genetic differentiation among populations. The Bayesian skyline plots and neutrality statistics showed a sudden expansion of the S. marmoratus population around the Pleistocene. The Beibu Gulf group had the lowest mean number of pairwise differences, the lowest significant genetic differentiation, and the lowest haplotype and nucleotide diversity, and should be prioritized for protection in the future. Ocean currents, seascape discontinuity, geographical distance, and ecological characteristics may play an important role in shaping the contemporary phylogeographical patterns and population structures of S. marmoratus.

Introduction Radiation-induced lung injury (RILI) is one of the most clinically-challenging toxicities and dose-limiting factors during and/or after thoracic radiation therapy for oesophageal squamous cell carcinoma (ESCC). With limited effective protective drugs against RILI, the main strategy to reduce the injury is strict adherence to dose-volume restrictions of normal lungs. RILI can manifest as acute radiation pneumonitis with cellular injury, cytokine release and cytokine recruitment to inflammatory infiltrate, and subsequent chronic radiation pulmonary fibrosis. Pirfenidone inhibits the production of inflammatory cytokines, scavenges-free radicals and reduces hydroxyproline and collagen formation. Hence, pirfenidone might be a promising drug for RILI prevention. This study aims to evaluate the efficacy and safety of pirfenidone in preventing RILI in patients with locally advanced ESCC receiving chemoradiotherapy.Methods and analysis This study is designed as a randomised, placebo-controlled, double-blinded, single-centre phase 2 trial and will explore whether the addition of pirfenidone during concurrent chemoradiation therapy (CCRT) could prevent RILI in patients with locally advanced ESCC unsuitable for surgery. Eligible participants will be randomised at 1:1 to pirfenidone and placebo groups. The primary endpoint is the incidence of grade >2 RILI. Secondary endpoints include the incidence of any grade other than grade >2 RILI, time to RILI occurrence, changes in pulmonary function after CCRT, completion rate of CCRT, disease-free survival and overall survival. The follow-up period will be 1 year. In case the results meet the primary endpoint of this trial, a phase 3 multicentre trial with a larger sample size will be required to substantiate the evidence of the benefit of pirfenidone in RILI prevention.Ethics and dissemination This study was approved by the Ethics Committee of Fujian Union Hospital (No. 2021YF001-02). The findings of the trial will be disseminated through peer-reviewed journals, and national and international conference presentations.Trial registration number ChiCTR2100043032.

The evidence linking sleep duration and metabolic body size phenotypes is limited, especially in young adulthood. In this study, we aimed to examine the association between sleep duration and metabolic body size phenotypes among Chinese young workers and investigate whether discrepancies exist among shift and non-shift workers. A cross-sectional study was performed between 2018 and 2019 in Wuhan, China and 7,376 young adults aged 20–35 years were included. Self-reported sleep duration was coded into four groups:

The world is endowed with a tremendous amount of coal resources, which are unevenly distributed in a few nations. While sustainable energy resources are being developed and deployed, fossil fuels dominate the current world energy consumption. Thus, low-carbon clean technologies, like underground coal gasification (UCG), ought to play a vital role in energy supply and ensuring energy security in the foreseeable future. This paper provides a state-of-the-art review of the world's development of UCG for enhanced hydrogen production. It is revealed that the world has an active interest in decarbonizing the coal industry for hydrogen-oriented research in the context of UCG. While research is ongoing in multiple coal-rich nations, China dominates the world's efforts in both industrial-scale UCG pilots and laboratory experiments. A variety of coal ranks were tested in UCG for enhanced hydrogen output, and the possibilities of linking UCG with other prospective technologies had been proposed and critically scrutinized. Moreover, it is found that transborder collaborations are in dire need to propel a faster commercialization of UCG in an ever-more carbon-conscious world. Furthermore, governmental and financial support is necessary to incentivize further UCG development for large-scale hydrogen production.

Chaenomeles speciosa (Sweet) Nakai has been long used as a folk medicine for rheumatic diseases treatment. This study aimed to investigate the effects and underlying mechanism of polysaccharides in Chaenomeles speciosa (CSP) on the pro-inflammatory cytokines and MAPK pathway in complete Freund’s adjuvant (CFA)-induced arthritis and LPS-induced NR8383 cells. We used acetic acid (HAc)-induced writhing and CFA induced paw edema to determine the analgesic activity and anti-inflammatory activity, respectively. CFA rats were administered CSP (12.5, 25.0, and 50.0 mg/kg) daily for 3 weeks via oral gavage. The analgesic test was done using three different doses of the extract (50, 100, and 200 mg/kg). The anti-arthritic evaluation involved testing for paw swelling, swelling inhibition, and histological analysis in CFA rats. Finally, ELISA, western blot, qRT-PCR were done to determine the effect of CSP on the activation of MAPK pathway, production of pro-inflammatory cytokines in lipopolysaccharide (LPS)-stimulated NR838 macrophage cells. In pain models, oral uptake of CSP greatly reduced pain perception. Furthermore, in CFA rats, CSP substantially decreased paw swelling as well as synovial tissue proliferation and inflammatory cell infiltration. In addition, CSP was shown to inhibit pro-inflammatory cytokines (TNF-α, IL-1β, and COX-2) as well as JNK and ERK1/2 phosphorylation in LPS-stimulated NR8383 cells. Thus, pro-inflammatory cytokine secretion and MAPK signaling downregulation promoted the analgesic and anti-arthritic effects of CSP.

Abstract Background Elderly population’s health is a major concern for most industrial nations. National health surveys provide a measure of the state of elderly health. One such survey is the Chinese Longitudinal Healthy Longevity Survey. It collects data on risk factors and outcomes on the elderly. We examine these longitudinal survey data to determine the changes in health and to identify risk factors as they impact health outcomes including the elderly’s ability to do a physical check. Methods We use a Partitioned GMM logistic regression model to identify risk factors. The model also accounts for the correlation between lagged time-dependent covariates and the outcomes. It addresses present and past measures of time-dependent covariates on simultaneous outcomes. The relation produces additional regression coefficients as byproduct of the Partitioned model, identifying the immediate, delayed effects (lag − 1), further delayed (lag-2), etc. Therefore, the model presents the opportunity for decision makers to monitor the covariate over time. This technique is particularly useful in healthcare and health related research. We use the Chinese Longitudinal Health Longevity Survey data to identify those risk factors and to display the utility of the model. Results We found that one’s ability to make own decisions, frequently consuming vegetables, exercise frequently, one’s ability to transfer without assistance, having visual difficulties and being able to pick book from floor while standing had varying effects of significance on one’s health and ability to complete physical checks as they get older. Conclusions The partitioning of the covariates as immediate effect, delayed effect or further delayed effect are important measures in a declining population.

A behavior description helps analyze tiny objects, similar objects, objects with weak visual information, and objects with similar visual information. It plays a fundamental role in the identification and classification of dynamic objects in microscopic videos. To this end, we propose foldover features to describe the behavior of dynamic objects. Foldover is defined as: Each frame of an object's motion is superimposed on the same spatial plane in the spacetime order of the motion, the result of the superposition is the foldover of the object's motion. Foldover of an object contains temporal information, spatial information, behavior features and static features. Therefore, the features extracted based on the foldover of the object are the foldover features. In this work, we first generate foldover for each object in microscopic videos in X, Y and Z directions, respectively. Then, we extract foldover features from the X, Y and Z directions with statistical methods, respectively. The core content of this paper is to construct the foldovers and extract the foldover features. Through these two steps, the temporal information, spatial information, behavior features and static features of the object are enhanced and included in the foldover features. Furthermore, the description of the behavior of dynamic objects by the foldover features is strengthened. Finally, we use four different classifiers to test the effectiveness of the proposed foldover features. In the experiment, we use a microscopic sperm video dataset to evaluate the proposed foldover features, including three types of 1374 sperms, and obtain the highest classification accuracy of 96.5%.

Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of breast cancers. To improve the accuracy and objectivity of Breast Histopathological Image Analysis (BHIA), Artificial Neural Network (ANN) approaches are widely used in the segmentation and classification tasks of breast histopathological images. In this review, we present a comprehensive overview of the BHIA techniques based on ANNs. First of all, we categorize the BHIA systems into classical and deep neural networks for in-depth investigation. Then, the relevant studies based on BHIA systems are presented. After that, we analyze the existing models to discover the most suitable algorithms. Finally, publicly accessible datasets, along with their download links, are provided for the convenience of future researchers.

In recent years, researches are concentrating on the effectiveness of Transfer Learning (TL) and Ensemble Learning (EL) techniques in cervical histopathology image analysis. However, there have been very few investigations that have described the stages of differentiation of cervical histopathological images. Therefore, in this article, we propose an Ensembled Transfer Learning (ETL) framework to classify well, moderate and poorly differentiated cervical histopathological images. First of all, we have developed Inception-V3, Xception, VGG-16, and Resnet-50 based TL structures. Then, to enhance the classification performance, a weighted voting based EL strategy is introduced. After that, to evaluate the proposed algorithm, a dataset consisting of 307 images, stained by three immunohistochemistry methods (AQP, HIF, and VEGF) is considered. In the experiment, we obtain the highest overall accuracy of 97.03% and 98.61% on AQP staining images and poor differentiation of VEGF staining images, individually. Finally, an additional experiment for classifying the benign cells from the malignant ones is carried out on the Herlev dataset and obtains an overall accuracy of 98.37%.

Anaerobic oxidation of methane (AOM), an important biological process to reduce global methane emissions to the atmosphere, can utilize methane as an electron donor to reduce sulfate, nitrate, nitrite, iron, manganese, AQDS (9,10-anthraquinone-2,6-disulfonate), etc.; thus, AOM has been a hot topic in global climate change research in recent years. In addition, nitrogen deposition of terrestrial ecosystems can input more nitrogen to nitrogen-limited peatlands, which could impact the AOM process. However, the effect of nitrogen addition on AOM is not well studied. Here, we investigated the effects of two forms of nitrogen on the vertical distribution (0–100 cm) of AOM in the Zoige peatlands (China) using an anaerobic incubation experiment. The results show that the concentrations of inorganic nitrogen species changed with nitrogen addition, but it did not significantly promote the potential of AOM. The cumulative AOM of treatments without nitrogen (CK) and ammonium chloride (Nred) was 2343.43 ± 18.96 µg·g−1 and 2340.76 ± 16.11 µg·g−1, respectively, which were significantly higher than that of sodium nitrate (Nox) addition treatment (2098.13 ± 13.59 µg·g−1). In addition, the potential of AOM increased with depth, but different soil layers had different responses to the two forms of nitrogen, which could reflect the variable need for different forms of nitrogen in the different soil layers. The soil water content (SWC), dissolved organic carbon (DOC), iron content (Fe3+), and pH played important roles in the potential of AOM in the Zoige peatlands. Overall, our results found that nitrogen addition did not increase the potential of AOM, but instead had an inhibitory effect on it. This study provides a basis for understanding the response of AOM to nitrogen addition in peatlands, which has important implications for global climate change.

The surging demand for logistics systems brought about by the vigorous development of e-commerce makes urban traffic more and more congested. The need for a sustainable transition in terms of urban transportation infrastructure also encourages the further innovation of logistics systems. The urban underground logistics system (ULS) emerges as a promising alternative for realizing efficient large-scale freight distribution in megacities. However, there are relatively few studies that have explored the factors that determine the uptake of ULSs in practice. This paper thus aims to identify the critical success factors of ULSs throughout project life cycle stages. Firstly, a desktop study and a study using the Delphi method were conducted to extract the critical success factors (CSFs) of ULS projects. Secondly, a questionnaire survey was conducted to collect data on the perceived significance of the selected success factors from ULS professionals. Thirdly, the intergroup comparison of the significance of CSFs and exploratory factory analysis were used to ascertain the critical factors and latent determinants influencing the development of ULS projects. In total, 36 CSFs in the four life cycle stages of ULS projects were finalized. The identified factors represent the seven latent determinants in developing a ULS project, namely, overall feasibility and acceptance of the ULS, prototype system, and business model, competence and resources for ULS construction and operation, station layout and intermodal transportation, government policies and incentives, long-term planning of the underground space and logistics network, and market investigation and forecasting. The research findings of the paper help guide practitioners and policy makers on decisions made during ULS planning and construction and provide a reference performance evaluation framework for ULS projects.

Improving eco-efficiency can promote sustainable development. This study first evaluated the urban eco-efficiency of 84 cities in Western China from 2004 to 2017 by the undesirable-super-slack-based measure (US-SBM) and analysed their spatiotemporal characteristics, and then investigated its influencing factors using spatial econometric models. The results indicated that the urban eco-efficiency in Western China was at a relatively low level and showed a fluctuating upward trend with the highest average value of 0.65; however, capital cities of Western China have improved their eco-efficiency rapidly. Furthermore, there were obvious spatial spill-over impacts of the urban eco-efficiency in Western China. This paper also found that both the economic development level and urbanization level have “U” shaped impacts on Western China’s urban eco-efficiency, which decreases at first and then rises. Similarly, increasing the proportion of secondary industry promotes urban eco-efficiency, and FDI, trade activities, improved environmental regulations as well as technological innovation capabilities have a positive impact on urban eco-efficiency in Western China. This paper also put forward corresponding policy suggestions to promote Western China’s urban eco-efficiency. The present study may be helpful for policy-makers to balance economic development and environmental protection in Western China.

The peatlands of the Zoige Plateau are an important global carbon source that is currently under threat as a result of drainage for grazing. How drainage affects the microbial diversity and activity in peatlands is unclear. This study examined the response of microbial communities at two sites to short-term drainage (3 years) and long-term drainage (48 years) in combination with three different water table treatments. Our objective was to examine the changes in the physicochemical properties of the soil, composition of bacterial and fungal communities, and microbial activity. Our results indicated that (1) both duration of drainage and water table drawdown had significant effects on the diversity and composition of the bacterial and fungal communities in the soil, and certain bacteria were replaced by fungal decomposers; (2) duration of drainage affected the structure of fungal communities more than that of bacterial communities, and interactions between microbial species were more complex in peatlands with long-term drainage; (3) drainage significantly altered concentrations of dissolved inorganic nitrogen (NH4+-N and NO3−-N), and these changes correlated with structure of bacterial and fungal communities as well as with changes in abundance of certain dominant microbial species; and (4) fungal communities explained a larger part of microbial activity than bacterial communities. Overall, these findings suggest that fungi play a much more important role than bacteria in microbial-mediated ecosystem functioning in peatlands undergoing drainage.

Abstract Background Primula is a large genus of flowering herbs well known for their heterostyly. Currently few natural hybrids are known and reproductive barriers in this genus in the wild have received little attention. However, there is instance of hybridization between rare and widely-spread species, and conservation implications of such situation is poorly understood. In the present study, we investigated hybridization patterns and reproductive barriers between a wide spread species, Primula poissonii and a rare species P. anisodora, of which only three populations are currently known. Results Pollinator-mediated reproductive isolation was strong between parental species but not significant between hybrids and parental species. Hand pollination experiments showed significant reduction of both fruit- and seed-set for heterospecific pollination as compared with conspecific pollination for both parental species. Furthermore, hybrids had higher fruit- and seed-set when pollinated with P. anisodora pollen as opposed to P. poissonii pollen. Microsatellites identified backcrosses to P. anisodora in two of the three populations of P. anisodora, and additionally more individuals of P. anisodora showed introgression from P. poissonii than vice versa. Conclusions These results provide evidence for potential genetic swamping of the P. anisodora populations, which could pose a serious threat for this locally endemic species.

In this paper, a novel multilayer hidden conditional random fields (MHCRFs)-based cervical histopathology image classification (CHIC) model is proposed to classify well, moderate and poorly differentiation stages of cervical cancer using a weakly supervised learning strategy. First, the color, texture, and deep learning features are extracted to represent the histopathological image patches. Then, based on the extracted features, artificial neural network, support vector machine, and random forest classifiers are designed to calculate the patch-level classification probabilities. Third, effective classifiers are selected to generate unary and binary potentials. At last, using the generated potentials, the final image-level classification results are predicted by our MHCRF model, and an overall accuracy around 77.32% is obtained on six practical cervical histopathological image datasets with more than 600 immunohistochemical (IHC) stained samples. Among the six test accuracies, the highest reaches 88%. Furthermore, we also test our MHCRF method with a gastric hematoxylin-eosin (HE) stained histopathological image dataset including 200 images for an extended experiment, and achieve an accuracy of 93%.

The impacts of human activities on Zoige peatlands are poorly documented. We determined the concentrations and accumulation rates of As and Hg in a 210Pb-dated peat profile collected from this area and analyzed the correlations between accumulation rates of both As and Hg and other physicochemical properties. To reconstruct recent conditions of As and Hg, we analyzed peat sediments of Re’er Dam peatland in Zoige using 210Pb and 137Cs dating technologies. The concentrations of total As (86.38 to 174.21 μg kg−1) and Hg (7.30 to 32.13 μg kg−1) in the peat profile clearly increased after the first industrial revolution. From AD 1824 to AD 2010, the average accumulation rates were 129.77 μg m−2 yr−1 for As and 18.24 μg m−2 yr−1 for Hg. Based on our results, anthropogenic emissions significantly affected the atmospheric fluxes of As and Hg throughout the past 200 years, and As was also likely to be affected by other factors than atmospheric deposition, which needs further identification by future studies. The historical variations in As and Hg concentrations in Re’er Dam peatland in Zoige mirror the industrial development of China.

Ruminants contribute significantly to global methane (CH4) emissions. This study aimed to evaluate the in vitro effects of monensin sodium salt (MSS) and disodium fumarate (DF) on CH4 production, rumen fermentation, and microbial community, with different substrates. The addition of MSS and DF, alone and in combination, significantly reduced the concentration and production of CH4 (p < 0.05), and while with vinasse as substrate, the CH4 production was higher for forage. The highest propionate production and lowest acetate and propionic ratio (A:P) values were all observed in cultures added to the combination of 14 mmol/L DF and 80 mg/kg MSS in both substrates, suggesting that these additives improved the rumen fermentation efficiency. The diversity indexes of prokaryotic microbiota with forage as the substrate were significantly higher than vinasse, and there were different effects on diversity indexes with the addition of MSS and DF depending on the incubated substrate. Supplementation with MSS and DF increased the number of starch degradation and fumarate reducing bacteria, decreased the number of methanogens, but had no significant effect on the number of fibrolytic bacteria. pH, NH3-N, and rumen volatile fatty acids (VFA) were the main factors influencing prokaryotic community structure. In conclusion, basal substrates (forage and vinasse) and CH4 mitigation additives (MSS and DF) have interactions on the in vitro rumen fermentation and microbial composition.

The alpine meadow of Zoige Plateau plays a key role in local livestock production of cattle and sheep. However, it remains unclear how animal grazing or its intensity affect nitrous oxide (N2O) emissions, and the main driving factors. A grazing experiment including four grazing intensities (G0, G0.7, G1.2, G1.6 yak ha−1) was conducted between January 2013 and December 2014 to evaluate the soil nitrous oxide (N2O) fluxes under different grazing intensities in an alpine meadow on the eastern Qinghai–Tibet Plateau of China. The N2O fluxes were examined with gas collected by the static chamber method and by chromatographic concentration analysis. N2O emissions in the growing seasons (from May to September) were lower than that in non-growing seasons (from October to April) in 2013, 1.94 ± 0.30 to 3.37 ± 0.56 kg N2O ha−1 yr−1. Annual mean N2O emission rates were calculated as 1.17 ± 0.50 kg N2O ha−1 yr−1 in non-grazing land (G0) and 1.94 ± 0.23 kg N2O ha−1 yr−1 in the grazing land (G0.7, G1.2, and G1.6). The annual mean N2O flux showed no significant differences between grazing treatments in 2013. However, there were significantly greater fluxes from the G0.7 treatment than from the G1.6 treatment in 2014, especially in the growing season. Over the two years, the soil N2O emission rate was significantly negatively correlated with soil water-filled pore space (WFPS) and dissolved organic carbon (DOC) content as well as positively correlated with soil available phosphorus (P). No relationship was observed between soil N2O emission rate and temperature or rainfall. Our results showed that the meadow soils acted as a source of N2O for most periods and turned into a weak sink of N2O later during the sampling period. Our results highlight the importance of proper grazing intensity in reducing N2O emissions from alpine meadow. The interaction between grazing intensity and N2O emissions should be of more concern during future management of pastures in Zoige Plateau.

When detecting the cracks in the tunnel lining image, due to uneven illumination, there are generally differences in brightness and contrast between the cracked pixels and the surrounding background pixels as well as differences in the widths of the cracked pixels, which bring difficulty in detecting and extracting cracks. Therefore, this paper proposes a dynamic partitioned Gaussian crack detection algorithm based on the projection curve distribution. First, according to the distribution of the image projection curve, the background pixels are dynamically partitioned. Second, a new dynamic partitioned Gaussian (DPG) model was established, and the set rules of partition boundary conditions, partition number, and partition corresponding threshold were defined. Then, the threshold and multi-scale Gaussian factors corresponding to different crack widths were substituted into the Gaussian model to detect cracks. Finally, crack morphology and the breakpoint connection algorithm were combined to complete the crack extraction. The algorithm was tested on the lining gallery captured on the site of the Tang-Ling-Shan Tunnel in Liaoning Province, China. The optimal parameters in the algorithm were estimated through the Recall, Precision, and Time curves. From two aspects of qualitative and quantitative analysis, the experimental results demonstrate that this algorithm could effectively eliminate the effect of uneven illumination on crack detection. After detection, Recall could reach more than 96%, and after extraction, Precision was increased by more than 70%.

In this paper, we present a novel thermoresistive gas flow sensor with a high-yield and low-cost volume production by using front-side microfabricated technology. To best improve the thermal resistance, a micro-air-trench between the heater and the thermistors was opened to minimize the heat loss from the heater to the silicon substrate. Two types of gas flow sensors were designed with the optimal thermal-insulation configuration and fabricated by a single-wafer-based single-side process in (111) wafers, where the type A sensor has two thermistors while the type B sensor has four. Chip dimensions of both sensors are as small as 0.7 mm × 0.7 mm and the sensors achieve a short response time of 1.5 ms. Furthermore, without using any amplification, the normalized sensitivity of type A and type B sensors is 1.9 mV/(SLM)/mW and 3.9 mV/(SLM)/mW for nitrogen gas flow and the minimum detectable flow rate is estimated at about 0.53 and 0.26 standard cubic centimeter per minute (sccm), respectively.

A simple, rapid, accurate, and selective quantitative nuclear magnetic resonance method for the determination of tadalafil in bulk drugs and its tablets was established and evaluated. Spectra were obtained in dimethylsulfoxide-d6 using 2,4-dinitrotoluene as the internal standard. In this study, the method’s linearity, range, limit of quantification, stability, precision, and accuracy were validated. The results were consistent with those obtained from high-performance liquid chromatography analysis. Thus, the proposed method is a useful and practical tool for the determination of tadalafil in bulk drugs and its tablets.

Abstract Therapy for large symptomatic keloids is often plagued with complicated reconstruction manner and recurrence. This article reports a rare treatment combination for a chest keloid with internal mammary artery perforator flap reconstruction and radiation therapy. We excised the keloid and covered the defect with an internal mammary artery perforator flap. Immediate electron-beam irradiation therapy was applied on the second postoperative day. There was no sign of recurrence over the follow-up period of 18 months. The combination of internal mammary artery perforator flap and immediate radiation therapy is useful when faced with chest keloids of similar magnitude and intractability.

A series of novel amphiphilic block polyurethanes (PUHE) have been successfully synthesized by solution polymerization of the derived PHB-diol and poly(ethylene glycol) with a coupling agent of 1,6-hexamethylene diisocyanate (HDI), while the PHB-diol was prepared via the transesterification of PHB and ethylene glycol. The hydroxyl contents in PHB-diols range from 1.36 to 1.99 (the molar ratio) as determined by nonaqueous titration. The molecular weight and chemical compositions of PUHE and PHB-diol were investigated by GPC, 1H NMR, and FTIR in detail, which confirm the successful synthesis of PUHE. The tensile strength and elongation at break of PUHE could reach as high as 20 MPa and 210%, as the content of PHB in PUHE is 33%. TGA curves indicate that block-bonding between PHB-diol and PEG increases the thermal stability of PHB-diol. Film degradation of PUHE was studied by weight loss and scanning electron microscope (SEM). It could be concluded that degradation occurred gradually from the surface to the inside and that the degradation rate could be controlled by adjusting the PHB/PEG ratios. These properties make PUHE able to be used as a biodegradable thermoplastic elastomer.

Background: Various programmes and models for post-intensive care unit (ICU) follow-up services have been developed worldwide. In China, post-ICU follow-up remains in the exploratory stage and little is known regarding the appropriate form and challenges of implementation, which need to be further explored. Aim: This study aimed to explore and describe the barriers to and facilitators of post-ICU follow-up services from the perspective of critical care professionals. Design: This was a descriptive qualitative study. Semi-structured interviews were conducted with 21 health care workers whose units had offered ICU survivors different forms of follow-up services; the data were analysed by qualitative content analysis during August 2022 and December 2022. Setting: The study was conducted at 14 ICUs in 11 tertiary hospitals in Shanghai, China. Findings: Seventeen subthemes were extracted as barriers and facilitators in the follow-up of ICU survivors. In the initiating process, the barriers included the restriction of decision-making rights and scope of practice, indifferent attitude towards survivors and repeated work. The facilitators included admitted significance, the needs of ICU survivors, the conscientiousness of professionals and the pioneers and leadership support. In the implementation process, lack of confidence, lack of cooperation in medical consortium, distrusted relationships, restrictions of medical insurance, ageing problems and insufficient human resources acted as barriers, whereas lessons learned, positive feedback and digital support served as facilitators. Furthermore, recommendations and tips were identified for offering follow-up services. Conclusion: Medical personnel can better utilize available resources and develop strategies to overcome constraints by gaining insights into the abovementioned barriers and facilitators. The findings of this study can provide a useful reference for structured and systematic follow-ups to ameliorate post-intensive care syndrome in low- and middle-income countries. Relevance to Clinical Practice: Publicity and educational measures play a crucial role in enhancing the awareness of survivors and the consensus of health care professionals from medical consortium regarding impairments after critical care. Leadership and policy support can address numerous obstacles to guiding follow-up services. [ABSTRACT FROM AUTHOR]