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Edible fungi is a group of large fungi for culinary purpose and medicinal use, which used as folk medicine and healthy food from ancient times. Multiple bioactive components such as proteins, polysaccharides, terpenes, and lipids exist in them and therefore recently sparked much attention due to their therapeutic properties such as anti-cancer, immunomodulatory, anti-hypercholesterolemia, antiviral, antidiabetic, and anti-inflammatory effects. With the rapid development of global economy and growing concept of green and healthy diet, they are gaining popularity among consumers, putting forward higher requirements for the processed products. This article reviews the research progress on the nutrition, active substances, and processed products of edible fungi in recent years, in order to provide ideas for the high-quality and sustainable development of the edible fungi industry.

Abstract Salt marshes can export considerable nutrients and carbon to the ocean through submarine groundwater discharge (SGD). However, the complicated SGD processes in salt marshes remain poorly understood. Here, we first report the phenomenon of numerous highly saline artesian springs found in a salt marsh system of East China. Multiple methods including time‐series thermal monitoring, isotope signatures, and high‐resolution electrical resistivity tomography were combined to determine their origin and trajectory. Strong evidence suggests that these springs keep discharging even during high tide and represent a long‐term re‐distribution process of the ancient marine water trapped in the unconfined aquifer. This new pattern of spring‐derived groundwater flow indicates a hidden SGD pathway and has significant implications for studies concerning SGD‐derived fluxes in similar multi‐aquifer‐aquitard coastal systems.

Background: Pancreatic head cancer accompanied by obstructive jaundice is a common clinical situation. The aim of this study was to assess the impact of preoperative biliary drainage (PBD) on clinical outcomes in patients with severe obstructive jaundice. Methods: Patients with a bilirubin level of ≥250 μmol/L at diagnosis who underwent PBD were included. The primary endpoints and secondary endpoints were the postoperative severe complications rates. Secondary endpoints were the degree of improvement in general condition, predictors of severe postoperative complications, and the impact of PBD on patients with bilirubin levels >300 μmol/L. Results: In total, 289 patients were included, and 188 patients (65.1%) underwent PBD. The patients who met the American Society of Anesthesiologists (ASA) classification II–III stages decreased from 119 to 100 (P = 0.047) after PBD. The overall severe complications were significantly more frequent in the direct surgery (DS) group than in the PBD group (34.7% vs. 22.9%, P = 0.031), especially the postoperative hemorrhage (6/43 [14.0%] vs. 9/35 [25.7%], P = 0.038) and intra-abdominal infection (6/43 [14.0%] vs. 10/35 [28.6%], P = 0.018). The ASA classifications II–III (odds ratio [OR]=2.89, 95% confidence interval [CI]: 1.38–4.31), P = 0.01) and DS (OR = 3.65, 95% CI: 1.45–7.08; P = 0.003) were independently associated with severe postoperative complications. The occurrence rate of severe postoperative complications in patients with a bilirubin level >300 μmol/L who underwent PBD was significantly lower than in patients who underwent DS (25.6% vs. 40.6%, P = 0.028), but the benefit of PBD was not observed in patients who had a bilirubin level between 250 and 300 μmol/L. Conclusion: PBD is useful in reducing severe postoperative complications, especially in patients with bilirubin levels >300 μmol/L.

Abstract Medical care is a guarantee of people's daily life. Improving healthcare contributes to people's well-being. However, healthcare resources are characterized by uneven distribution. Financially well-off areas will have higher quality health care resources. Most of the medical resources are concentrated in public general hospitals, however, primary care institutions can hardly meet the growing needs of people. To solve this problem, Medical Union achieves efficient deployment of resources by integrating various medical institutions in the same area. In the process of logistics integration of the medical union, the scale of logistics distribution expands accordingly. Transportation vehicles have high operating costs and produce greenhouse gases in the process of distribution. The optimization of the driving path of logistics distribution vehicles can reduce the operating cost, fuel consumption and carbon emission. To solve this kind of decentralized and complex vehicle routing problem, this paper proposes a pollution routing problem model considering electrical vehicle usage, customer's soft time window expectation, open path and carbon cost. A modified Differential Search Algorithm with the comprehensive learning strategy and dynamic Cauchy variation strategy is advanced to solve the problem. Results show that the improved algorithm has good solving performance, and verifies the rationality of the proposed model, which will help to reduce carbon emissions and save the logistics and operating costs of medical devices.

Abstract Background To explore the effects of nutrition support team (NST) intervention on elderly patients with gastric cancer (GC). Methods The elderly GC patients (tumor stage I/II/III), admitted to our department from January 2015 to September 2021, were retrospectively analyzed and divided into NST group and traditional nutrition (TN) group according to nutritional management methods. The immune, inflammatory, nutrition-related indices, postoperative recovery and long-term prognosis of two groups were analyzed. Results A total of 258 elderly GC patients were included (NST group, n = 125; TN group, n = 133). After propensity score matching (PSM) in ratio of 1:1, 73 pairs of patients were matched. There were statistically significant differences in CD3 and CD4 level postoperative one month and IgG level postoperative one week between NST group and TN group (P 0.05). There were significant differences in body mass index (BMI) between the two groups postoperative one month (P 0.05). Conclusions Compared with TN management, NST intervention might be benefit to the immune function recovery and nutritional status, but there was no evidence that NST could improve the prognosis of elderly GC patients.

Protein, starch, and their components are important for wheat grain yield and end-products, which are affected by wheat grain development. Therefore, QTL mapping and a genome-wide association study (GWAS) of grain protein content (GPC), glutenin macropolymer content (GMP), amylopectin content (GApC), and amylose content (GAsC) were performed on wheat grain development at 7, 14, 21, and 28 days after anthesis (DAA) in two environments using a recombinant inbred line (RIL) population of 256 stable lines and a panel of 205 wheat accessions. A total of 29 unconditional QTLs, 13 conditional QTLs, 99 unconditional marker−trait associations (MTAs), and 14 conditional MTAs significantly associated (p < 10−4) with four quality traits were found to be distributed on 15 chromosomes, with the phenotypic variation explained (PVE) ranging from 5.35% to 39.86%. Among these genomic variations, three major QTLs [QGPC3B, QGPC2A, and QGPC(S3|S2)3B] and SNP clusters on the 3A and 6B chromosomes were detected for GPC, and the SNP TA005876-0602 was stably expressed during the three periods in the natural population. The QGMP3B locus was detected five times in three developmental stages in two environments with 5.89%–33.62% PVE, and SNP clusters for GMP content were found on the 3A and 3B chromosomes. For GApC, the QGApC3B.1 locus had the highest PVE of 25.69%, and SNP clusters were found on chromosomes 4A, 4B, 5B, 6B, and 7B. Four major QTLs of GAsC were detected at 21 and 28 DAA. Most interestingly, both QTL mapping and GWAS analysis indicated that four chromosomes (3B, 4A, 6B, and 7A) were mainly involved in the development of protein, GMP, amylopectin, and amylose synthesis. Of these, the wPt-5870–wPt-3620 marker interval on chromosome 3B seemed to be most important because it played an important role in the synthesis of GMP and amylopectin before 7 DAA, in the synthesis of protein and GMP from 14 to 21 DAA, and in the development of GApC and GAsC from 21 to 28 DAA. Using the annotation information of IWGSC Chinese Spring RefSeq v1.1 genome assembly, we predicted 28 and 69 candidate genes for major loci from QTL mapping and GWAS, respectively. Most of them have multiple effects on protein and starch synthesis during grain development. These results provide new insights and information for the potential regulatory network between grain protein and starch synthesis.

The austenite grain growth and recrystallization behaviors of three pipeline steels with different Nb contents were investigated through reheating and thermal simulation compression experiments. The initiation conditions for dynamic and sub-dynamic recrystallization of austenite were analyzed, and sub-dynamic recrystallization equations in Avrami form were established. The influences of Nb content and deformation conditions on the evolution of grain size during austenite recrystallization was examined. The findings indicate that the austenite grain size of the three steels increases gradually with higher reheating temperatures, while the average grain size decreases with increasing Nb content. Sub-dynamic recrystallization initiation temperatures for the B150-steel, B145-steel, and 73-steel were found to be 920 °C for 10 s, 940 °C for 30 s, and 960 °C for 30 s, respectively. During high-temperature deformation, Nb in solid solution hindered recrystallization by impeding grain boundary and dislocation movement. At lower deformation temperatures, Nb(C, N) precipitation pinned grain boundaries and dislocations and consumed substantial free energy, thus competing with recrystallization. As Nb content increased, strain-induced precipitation became more pronounced, resulting in more effective inhibition of recrystallized grain growth.

Many existing deep learning algorithms for particle picking are not predictable on unseen datasets. Here the authors report an exemplar-based continual learning approach, EPicker, enabling accumulation of new knowledge of cryoEM particle picking without catastrophic forgetting of old knowledge.

Reproductive stage frost poses a major constraint for wheat production in countries such as Australia. However, little progress has been made in identifying key genes to overcome the constraint. In the present study, a severe frost event hit two large-scale field trials consisting of six doubled haploid (DH) wheat populations at reproductive stage (young microspore stage) in Western Australia, leading to the identification of 30 robust frost QTL on 17 chromosomes. The major 18 QTL with the phenotype variation over 9.5% were located on 13 chromosomes including 2A, 2B, 2D, 3A, 4A, 4B, 4D, 5A, 5D, 6D, 7A, 7B and 7D. Most frost QTL were closely linked to the QTL of anthesis, maturity, Zadok stages as well as linked to anthesis related genes. Out of those, six QTL were repetitively detected on the homologous regions on 2B, 4B, 4D, 5A, 5D, 7A in more than two populations. Results showed that the frost damage is associated with alleles of Vrn-A1a, Vrn-D1a, Rht-B1b, Rht-D1b, and the high copy number of Ppd-B1. However, anthesis QTL and anthesis related genes of Vrn-B1a and TaFT3-1B on chromosomes 5B and 1B did not lead to frost damage, indicating that these early-flowering phenotype related genes are compatible with frost tolerance and thus can be utilised in breeding. Our results also indicate that wild-type alleles Rht-B1a and Rht-D1a can be used when breeding for frost-tolerant varieties without delaying flowering time.

Change detection is the discovery of changes in remote sensing images of the same region obtained at different times. Change detection algorithms based on deep neural networks have significant advantages over the traditional algorithms on high-resolution images. State-of-the-art (SOTA) change detection methods require sufficient labeled data to achieve good results, but semantic change detection requires not only binary change masks but also “from–to” change information, so large quantities of change labels are difficult to obtain. Achieving better semantic change detection accuracy with a limited number of labels remains an open problem in the remote sensing field. In this article, we propose a feature-guided multitask change detection network (MCDnet). Feature guidance is characterized by three steps: First, a multitask learning network that uses Siamese encoders to learn segmentation and change detection features simultaneously to realize mutual guidance between tasks is designed, second, a fine-grained feature fusion module to integrate and enhance change information under the guidance of symmetrical change features is constructed, and third, a contrastive loss function based on the a priori knowledge that the features of the changed regions are different while those of the unchanged regions are the same is proposed. The experimental results show that MCDnet achieves SOTA results on three public change detection datasets, including WHU-CD (F1: 94.46\IoU: 89.50), LEVIR (F1: 92.11\IoU: 85.37), and SECOND (mIoU: 73.1\Sek: 22.8). In addition, it is surprising that MCDnet is comparable to the SOTA models while using only 20% of the full training data.

This article addresses the problem of superpixel-bases segmentation of synthetic aperture radar (SAR) images. Most superpixel segmentation methods have difficulties in segmenting adjacent regions with similar gray values, due to only considering spatial and gray information. To solve this problem and improve segmentation accuracy, this article proposes an SAR image segmentation method based on Fisher vector superpixel generation and label revision. First, the Fisher vector is obtained by processing the Gaussian mixture function. By introducing the Fisher vector, a distance formula is constructed for superpixel segmentation. Therefore, the adjacent regions with similar gray values can be segmented effectively in the generated superpixel map. Second, the superpixels are clustered using the K-means algorithm to obtain the initial label map. Then, with extracted edge information as constraints, the pixel labels obtained by K-means are repaired pixel by pixel to get the middle label map, according to the number and gray value difference of labels. This overcomes the influence of noise generated by K-means. Finally, the middle label map is relabeled using the region growth algorithm to divide pixel blocks. Isolated pixel blocks surrounded by similar labels are corrected, based on the gray mean difference. The final label result has a better segmentation accuracy. Experiments on synthetic SAR images and real images demonstrate that the proposed algorithm achieves higher segmentation accuracy than six state-of-the-art clustering algorithms for SAR image segmentation.

Abstract Environmental exposures interact with genetic factors has been thought to influence susceptibility of systemic lupus erythematosus (SLE) development. To evaluate the effects of environmental exposures on SLE, we conducted a population-based cohort study across Jiangsu Province, China, to examine the associations between the living environment including air and water pollution, population density, economic income level, etc. and the prevalence and mortality of hospitalized SLE (h-SLE) patients. A total of 2231 h-SLE patients were retrieved from a longitudinal SLE database collected by the Jiangsu Lupus Collaborative Group from 1999 to 2009. The results showed that: It existed regional differences on the prevalence of h-SLE patients in 96 administrative districts; The distribution of NO2 air concentration monitored by atmospheric remote sensors showed that three of the ultra-high-prevalence districts were located in the concentrated chemical industry emission area; h-SLE patient prevalence was positively correlated with the excessive levels of nitrogen in drinking water; The positive ratio of pericarditis and proteinuria was positively correlated with the prevalence of h-SLE patients and pollution not only induced a high h-SLE patient prevalence but also a higher mortality rate, which might be attributed to NOx pollution in the air and drinking water. In summary, our data suggested that NOx in air and drinking water may be one of the important predispositions of SLE, especially for patients with renal involvement.

Azobenzene mesogens have garnered considerable research attention in the realm of photo-responsive materials due to their reversible trans–cis isomerization. In this paper, we demonstrate an azobenzene inverse opal film synthesized via photo-polymerization from a SiO2 opal template. The proposed design exhibits intriguing optical properties, including dynamic fluorescent features, distinct fluorescent enhancement, and an anti-fake micropattern with a switchable structure color. This work holds significant importance for advancing the development of novel optical devices.

Due to rising living standards, it is important to improve wheat’s quality traits by adjusting its storage protein genes. The introduction or locus deletion of high molecular weight subunits could provide new options for improving wheat quality and food safety. In this study, digenic and trigenic wheat lines were identified, in which the 1Dx5+1Dy10 subunit, and NGli-D2 and Sec-1s genes were successfully polymerized to determine the role of gene pyramiding in wheat quality. In addition, the effects of ω-rye alkaloids during 1BL/1RS translocation on quality were eliminated by introducing and utilizing 1Dx5+1Dy10 subunits through gene pyramiding. Additionally, the content of alcohol-soluble proteins was reduced, the Glu/Gli ratio was increased and high-quality wheat lines were obtained. The sedimentation values and mixograph parameters of the gene pyramids under different genetic backgrounds were significantly increased. Among all the pyramids, the trigenic lines in Zhengmai 7698, which was the genetic background, had the highest sedimentation value. The mixograph parameters of the midline peak time (MPT), midline peak value (MPV), midline peak width (MPW), curve tail value (CTV), curve tail width (CTW), midline value at 8 min (MTxV), midline width at 8 min (MTxW) and midline integral at 8 min (MTxI) of the gene pyramids were markedly enhanced, especially in the trigenic lines. Therefore, the pyramiding processes of the 1Dx5+1Dy10, Sec-1S and NGli-D2 genes improved dough elasticity. The overall protein composition of the modified gene pyramids was better than that of the wild type. The Glu/Gli ratios of the type I digenic line and trigenic lines containing the NGli-D2 locus were higher than that of the type II digenic line without the NGli-D2 locus. The trigenic lines with Hengguan 35 as the genetic background had the highest Glu/Gli ratio among the specimens. The unextractable polymeric protein (UPP%) and Glu/Gli ratios of the type II digenic line and trigenic lines were significantly higher than those of the wild type. The UPP% of the type II digenic line was higher than that of the trigenic lines, while the Glu/Gli ratio was slightly lower than that of the trigenic lines. In addition, the celiac disease (CD) epitopes’ level of the gene pyramids significantly decreased. The strategy and information reported in this study could be very useful for improving wheat processing quality and reducing wheat CD epitopes.

Abstract Due to its importance in clinical science, the estimation of physiological states (e.g., the severity of pathological tremor) has aroused growing interest in machine learning community. While the physiological state is a continuous variable, its continuity is lost when the physiological state is quantized into a few discrete classes during recording and labeling. The discreteness introduces misalignment between the true value and its label, meaning that these labels are unfortunately imprecise and coarse-grained. Most previous work did not consider the inaccuracy and directly utilized the coarse labels to train the machine learning algorithms, whose predictions are also coarse-grained. In this work, we propose to learn a precise, fine-grained estimation of physiological states using these coarse-grained ground truths. Established on mathematical rigorous proof, we utilize imprecise labels to restore the probabilistic distribution of precise labels in an approximate order-preserving fashion, then the deep neural network learns from this distribution and offers fine-grained estimation. We demonstrate the effectiveness of our approach in assessing the pathological tremor in Parkinson’s Disease and estimating the systolic blood pressure from bioelectrical signals.

We rethink on the contradiction between accuracy and efficiency in the field of video pose estimation. Large networks are typically exploited in previous methods to pursue superior pose estimation results. However, those methods can hardly meet the low-latency requirement for real-time applications because of their computationally expensive nature. We present a novel architecture, PosePropagation-Net (PPN), to generate poses across video frames accurately and efficiently. Instead of extracting temporal cues or knowledge someways to enforce geometric consistency as most of the previous methods do, we explicitly propagate well-estimated pose from the preceding frame to the current frame by leveraging pose propagation mechanism, endowing lightweight networks with the capability of performing accurate pose estimation in videos. The experiments on two large-scale benchmarks for video pose estimation show that our method significantly outperforms previous state-of-the-art methods in both accuracy and efficiency. Compared with the previous best method, our two representative configurations, PPN-Stable and PPN-Swift, achieve 2.5× and 6× FLOPs reduction respectively, as well as significant accuracy improvement.

A face does not only have rigid variations but also non-rigid distortions, which has influenced the performance of groupwise face alignment. A novel method for groupwise face alignment which considers both rigid variations of a face and non-rigid distortions was presented in the paper. The process for groupwise face alignment was divided into two stages, i.e. affine transformations and non-rigid distortions. At the stage of the affine transformations, the key points of a face were categorized into five groups and the affine transformations were used for each group of the key points. At the stage of the non-rigid distortions, a novel method was used for all of the key points in a face. Two stages were independent of each other, and moreover, iterations were made in each stage. Besides, the results from the stage of the affine transformations were used as the input of the non-rigid distortion stage. Experiments show that the method for groupwise face alignment in the paper is better than that only considering global affine variations, and is also better than that considering global affine variations and local non-rigid distortions. The method in the paper can be used as a novel method for groupwise face alignment.

This study investigates the sources of water under four modes, namely, normal fields, Raised Fields, single agriculture in Raised Fields, and agroforest system in Raised Fields, by using a combination of δ18O, δ2H and δ13C and their effects on crop yield and water use efficiency. The results show that the soil electrical conductivity of Raised Fields during summer maize seasons was lower than that during winter wheat seasons, and that in the marginal regions was higher than in the central regions, because of the Water Sources. Under agroforest conditions in Raised Fields, Soil Salinity can be reduced because approximately 10% of the water originates from tree trunks. The biomass yield and intrinsic water use efficiency of winter crops under agroforest was 15.1% and 5.5% higher than that under single agriculture, respectively. Thus, soil salinization can be reduced and productivity can be increased by controlling the Water Sources in ecosystems.

Researches on face alignment have made great progress, which benefits from the use of prior information and auxiliary models. However, that information lacks in a single face image has always affected the further development of these researches. The methods considering multiple face images provide a feasible way to solve the problem undoubtedly. Joint alignment where multiple face images are considered was presented in the paper. Face alignment was used for each face, and joint face alignment was used for optimizing the alignment results of all faces further. During joint alignment, both rigid variations of faces and non-rigid distortions were considered, however, they were regarded as two independent stages. Joint face alignment was a process where optimization was performed iteratively. In each iteration, both rigid variations and non-rigid distortions were performed sequentially, and moreover, the results of rigid variations were used as input of non-rigid distortions. At the stage of rigid variations, the key points of a face were divided into five groups to reduce the effect of global constraints which was imposed by face shape. After several iterations, the optimal solution of joint alignment can be obtained. The experimental results show that the joint alignment can obtain the optimal results than joint alignment using phased global rigid variations and non-rigid distortions and that using iterative global rigid variations and non-rigid distortions, and it can be used as a novel method for joint alignment.

Mesenchymal stem cells (MSCs) have emerged as putative therapeutic tools due to their intrinsic tumor tropism, and anti-tumor and immunoregulatory properties. The limited passage and self-differentiation abilities of MSCs in vitro hinder preclinical studies on them. In this study, we focused on the safety of immortalized mesenchymal stem cells (im-MSCs) and, for the first time, studied the feasibility of im-MSCs as candidates for the treatment of glioma. The im-MSCs were constructed by lentiviral transfection of genes. The proliferative capacity of im-MSCs and the proliferative phenotype of MSCs and MSCs co-cultured with glioma cells (U87) were measured using CCK-8 or EdU assays. After long-term culture, karyotyping of im-MSCs was conducted. The tumorigenicity of engineered MSCs was evaluated using soft agar cloning assays. Next, the engineered cells were injected into the brain of female BALB/c nude mice. Finally, the cell membranes of im-MSCs were labeled with DiO or DiR to detect their ability to be taken up by glioma cells and target in situ gliomas using the IVIS system. Engineered cells retained the immunophenotype of MSC; im-MSCs maintained the ability to differentiate into mesenchymal lineages in vitro; and im-MSCs showed stronger proliferative capacity than unengineered MSCs but without colony formation in soft agar, no tumorigenicity in the brain, and normal chromosomes. MSCs or im-MSCs co-cultured with U87 cells showed enhanced proliferation ability, but did not show malignant characteristics in vitro. Immortalized cells continued to express homing molecules. The cell membranes of im-MSCs were taken up by glioma cells and targeted in situ gliomas in vivo, suggesting that im-MSCs and their plasma membranes can be used as natural drug carriers for targeting gliomas, and providing a safe, adequate, quality-controlled, and continuous source for the treatment of gliomas based on whole-cell or cell membrane carriers.

High-grade glioma is highly invasive and malignant, resistant to combined therapies, and easy to relapse. A better understanding of circular RNA (circRNA) biological function in high-grade glioma might contribute to the therapeutic efficacy. Here, a circRNA merely upregulated in high-grade glioma, circGLIS3 (hsa_circ_0002874, originating from exon 2 of GLIS3), was validated by microarray and Real-time quantitative reverse transcription PCR (qRT-PCR). The role of circGLIS3 in glioma was assessed by functional experiments both in vitro and in vivo. Fluorescence in situ hybridization (FISH), RNA pull-down, RNA immunoprecipitation (RIP), and immunohistochemical staining were performed for mechanistic study. Cocultured brain endothelial cells with glioma explored the role of exosome-derived circGLIS3 in the glioma microenvironment. We found that upregulation of circGLIS3 promoted glioma cell migration and invasion and showed aggressive characteristics in tumor-bearing mice. Mechanistically, we found that circGLIS3 could promote the Ezrin T567 phosphorylation level. Moreover, circGLIS3 could be excreted by glioma through exosomes and induced endothelial cell angiogenesis. Our findings indicate that circGLIS3 is upregulated in high-grade glioma and contributes to the invasion and angiogenesis of glioma via modulating Ezrin T567 phosphorylation.

For most cities, municipal governments have constructed basic building footprint datasets that need to be updated regularly for the management and monitoring of urban development and ecology. Cities are capable of changing in a short period of time, and the area of change is variable; hence, automated methods for generating up-to-date building footprints are urgently needed. However, the labels of current buildings or changed areas are usually lacking, and the conditions for acquiring images from different periods are not perfectly consistent, which can severely limit deep learning methods when attempting to learn deep information about buildings. In addition, common update methods can ignore the strictly accurate historical labels of unchanged areas. To solve the above problem, we propose a new update algorithm to update the existing building database to the current state without manual relabeling. First, the difference between the data distributions of different time-phase images is reduced using the image color translation method. Then, a semantic segmentation model predicts the segmentation results of the images from the latest period, and, finally, a post-processing update strategy is applied to strictly retain the existing labels of unchanged regions to attain the updated results. We apply the proposed algorithm on the Wuhan University change detection dataset and the Beijing Huairou district land survey dataset to evaluate the effectiveness of the method in building surface and complex labeling scenarios in urban and suburban areas. The F1 scores of the updated results obtained for both datasets reach more than 96%, which proves the applicability of our proposed algorithm and its ability to efficiently and accurately extract building footprints in real-world scenarios.

Background: Hereditary hearing loss (HHL) is the most common sensory deficit, which highly afflicts humans. With gene sequencing technology development, more variants will be identified and support genetic diagnoses, which is difficult for human experts to diagnose. This study aims to develop a machine learning-based genetic diagnosis model of HHL-related variants of GJB2, SLC26A4 and MT-RNR1. Methods: This case-control study included 1898 subjects, among which 1354 were HHL patients and 544 were carriers. Risk assessment models were established based on variants at 144 sites in three genes related to HHL by building six machine learning (ML) models. We compared the ML models with the genetic risk score (GRS) and expert interpretation (EI) to verify the clinical performance. Findings: Among the six ML models, the support vector machine (SVM) showed the best performance. For the prediction of HHL-related gene sites in subjects with variants, the area under the receiver operating characteristic (AUC) of the SVM model was 0.803 (0.680–0.814) in the 10-fold stratified cross-validation and 0.751 (0.635–0.779) in external validation. The predicted results were better than both EI and GRS. Furthermore, 11 sites were identified as the smallest feature set that can be accurately predicted. Interpretation: The developed SVM model has great potential to be an efficient and effective tool for HHL prediction when high throughput sequencing data are available.

Rural dog populations have long been recognized to be inadequately managed in terms of disease control and prevention. In this study we consider dog management in rural Shanghai and its implications for rabies control in the entire metropolitan area of Shanghai. The prerequisite to improve rabies vaccination coverage in rural Shanghai depends on a proper enumeration of the total rural dog population. In this study we selected one of the nine administrative districts in Shanghai (Jiading), within which there are 7 towns and 2 industrial zones (township-level division) that contain agricultural areas. A total of 9 villages (rabies model villages) were chosen from each township-level division in Jiading, and an additional 3 non-model villages were also included in the study. A household questionnaire survey was implemented in all 12 villages recruited. In 3 of the model villages and the 3 non-model villages chosen as a comparison, two methods of enumeration—a sight-resight survey and a household census survey—were implemented. Results from the household survey in these 6 villages showed that among the total 1,560 owned dogs, 80.4% were Chinese Garden Dogs, 69.1% were aged 1 to 3 years, 49.2% were homebred, and 88.3% were kept for the purpose of guarding the house. However, only 3.7% of the owned dogs were desexed. There was a higher proportion of chained or confined dogs in model compared to non-model villages. The model villages had an absolute rabies vaccination coverage of 100% among its owned dog population and a smaller number of stray dogs. It was also identified that the two enumeration methods yielded similar counts (P = 0.12), particularly within smaller villages. From the questionnaire survey implemented within all 12 villages and based on the average human-to-dog ratio, the total rural dog population of Jiading district was estimated to be 24,058. This study generated information on the general demographics of the rural dog population in Jiading, and demonstrates an approach to the study of rural dog populations within the context of a megacity. In such a context, rural dog populations need to be considered as a critical component of animal and public health.

The ecological and efficient use of saline–alkaline lands is very important worldwide. The main objective of this paper is to identify an eco-farming system suitable for saline–alkaline lands via emergetic and cosmic exergy-based ecological assessments. Three ecosystems were compared: an agriculture-free system, a local agricultural system, and a superior agricultural system. In the latter two systems, crops (winter wheat and summer maize), animal husbandry and orchards were integrated in raised fields. In the superior agricultural system, conservation tillage, intercropping, and farming-grazing system were used. After 15 years, the electrical conductivity of the soil in 0–30 cm depth was 49.2% reduced using the raised field. In 2018, the average soil electrical conductivity of the superior agricultural system was 20.1% and 14.8% lower than that of the agricultural-free system and local agricultural system, respectively. The superior agricultural system was more sustainable than both the agriculture-free system and the local agricultural system by the footprint investment per unit of footprint delivered method. The renewability and sustainability of the superior agricultural system were higher than the other systems. The economic benefit of the superior agricultural system was the highest among the three systems, which is 1.34 times higher than that of the local agricultural system. These results suggest that the superior agricultural system is better than the other two systems because it promotes the flow of materials and energy and takes advantage of the mutually beneficial effects by using conservation tillage, intercropping, and farming-grazing system. This study contributes to the theoretical foundation for policy-making in saline–alkaline regions worldwide.

Abstract Background Growing evidences indicate that circular RNAs (circRNAs) play an important role in the regulation of biological behavior of tumor. We aim to explore the role of circRNA in glioma and elucidate how circRNA acts. Methods Real-time PCR was used to examine the expression of circPTN in glioma tissues and normal brain tissues (NBT). Assays of dual- luciferase reporter system, biotin label RNA pull-down and FISH were used to determine that circPTN could sponge miR-145-5p and miR-330-5p. Tumor sphere formation assay was performed to determine self- renewal of glioma stem cell (GSCs). Cell counting Kit-8 (CCK8), EdU assay and flow cytometry were used to investigate proliferation and cell cycle. Intracranial xenograft was established to determine how circPTN impacts in vivo. Tumor sphere formation assay was performed to determine self- renewal of glioma stem cell (GSCs). Results We demonstrated circPTN was significantly higher expression in glioma tissues and glioma cell lines, compared with NBT and HEB (human astrocyte). In gain- and loss-of-function experiments, circPTN significantly promoted glioma growth in vitro and in vivo. Furthermore, we performed dual-luciferase reporter assays and RNA pull-down assays to verify that circPTN acts through sponging miR-145-5p and miR-330-5p. Increasing expression of circPTN rescued the inhibition of proliferation and downregulation of SOX9/ITGA5 in glioma cells by miR-145-5p/miR-330-5p. In addition, we found that circPTN promoted self-renewal and increased the expression of stemness markers (Nestin, CD133, SOX9, and SOX2) via sponging miR-145-5p. Moreover, this regulation was disappeared when circPTN binding sites in miR-145-5p were mutated. Conclusions Our results suggest that circPTN is an oncogenic factor that acts by sponging miR-145-5p/miR-330-5p in glioma.

The relationship between groundwater and lakes in Qaidam Basin is often overlooked. Therefore, we employed Landsat satellite images and meteorological data to investigate the causes of lake expansion through model calculation and statistical analysis and then determine groundwater sources through isotope analysis (2H, 3H, and 18O). In the two study periods of 2003–2011 and 2011–present, temperature, precipitation, and runoff increased at a steady rate, whereas the expansion rate of Tuosu Lake increased from 1.22 km2/yearr to 3.38 km2/yearr. This significant increase in the rate of lake expansion reflects the substantial contribution of groundwater to lake expansion. The groundwater contribution to the lake includes not only the glacial meltwater that infiltrates the piedmont plain but also other, more isotopically deleted water sources from other basins. It is speculated that the 2003 Ms 6.4 earthquake in the northwest of the Delingha region was a possible mechanism for lake expansion. Earthquakes can enhance crustal permeability and keep fractures open, which promotes groundwater contribution to lakes and in turn causes rapid lake expansion and an increased groundwater level. This study is important for understanding the sources, circulation, and evolution of groundwater in Qaidam Basin.

In the present study, four large-scale field trials using two doubled haploid wheat populations were conducted in different environments for two years. Grain protein content (GPC) and 21 other yield-related traits were investigated. A total of 227 QTL were mapped on 18 chromosomes, which formed 35 QTL clusters. The potential candidate genes underlying the QTL clusters were suggested. Furthermore, adding to the significant correlations between yield and its related traits, correlation variations were clearly shown within the QTL clusters. The QTL clusters with consistently positive correlations were suggested to be directly utilized in wheat breeding, including 1B.2, 2A.2, 2B (4.9–16.5 Mb), 2B.3, 3B (68.9–214.5 Mb), 4A.2, 4B.2, 4D, 5A.1, 5A.2, 5B.1, and 5D. The QTL clusters with negative alignments between traits may also have potential value for yield or GPC improvement in specific environments, including 1A.1, 2B.1, 1B.3, 5A.3, 5B.2 (612.1–613.6 Mb), 7A.1, 7A.2, 7B.1, and 7B.2. One GPC QTL (5B.2: 671.3–672.9 Mb) contributed by cultivar Spitfire was positively associated with nitrogen use efficiency or grain protein yield and is highly recommended for breeding use. Another GPC QTL without negatively pleiotropic effects on 2A (50.0–56.3 Mb), 2D, 4D, and 6B is suggested for quality wheat breeding.

Exploring relations among different local methods for face alignment is a problem to be solved crucially. It is of significance for face recognition and face tracking. In this study, a general framework for local face alignment is presented. On this basis, three classical methods are described, i.e. method using structured support vector machine, that using regularised landmark mean‐shift (RLMS), and that using multiview and mixtures of trees. Comparisons of performance among different methods are carried out on four datasets, i.e. BioID, LFW, Helen, and LFPW. For each face, five facial landmarks are used, i.e. tip of nose, inner corner of left eye, inner corner of right eye, left mouth corner, and right mouth corner. Average alignment time and average alignment precision are used as metrics. Test results show that methods using RLMS have better performance on the whole.

Spike number per m2 (SN), kernel number per spike (KNPS) and thousand-kernel weight (TKW) are the three main components determining wheat (Triticum aestivum L.) yield. To evaluate the relationships among them a doubled haploid (DH) population consisting of 168 lines grown at three locations for three years was analyzed by unconditional and conditional QTL mapping. Thirty-three unconditional QTL and fifty-nine conditional QTL were detected. Among them, two QTL (QSN-DH-2B and QSN-DH-3A-1.1) improved SN, with no effect on KNPS. QKNPS-DH-2B-2.1 improved KNPS, with no effect on SN. QKNPS-DH-1A-1.1, QKNPS-DH-2D-1.1 and QKNPS-DH-6A improved KNPS, with no effect on SN or TKW. QKNPS-DH-6B was associated with increased SN and TKW. In addition, QTKW-DH-4B, QTKW-DH-5B and QTKW-DH-7B increased TKW without decreasing KNPS. These results provide useful information for marker assisted selection (MAS) and improvement in wheat yield.

A compact, continuous-wave, solid-state laser at 578 nm has been demonstrated, for the first time to our knowledge, by use of intracavity sum-frequency mixing from a branched cavity with an LBO crystal. Two gain mediums, namely, the Nd:YAG single crystal and the Yb:YAG single crystal (with a disk laser setup), are used to generate the two fundamental 1319- and 1030-nm waves, respectively. The maximum output power of 37.5 mW is obtained at a total pump power of 14 W. The power stability value of the output laser is better than 4.3% in 30 min.

In plant tissues, sugar levels are determined by the balance between sugar import, export, and sugar synthesis. So far, water soluble carbohydrate (WSC) dynamics have not been investigated in a diurnal context in wheat stems as compared to the dynamics in flag leaves during the terminal phases of grain filling. Here, we filled this research gap and tested the hypothesis that WSC dynamics interlink with gene expression of TaSUT1. The main stems and flag leaves of two genotypes, Westonia and Kauz, were sampled at four hourly intervals over a 24 h period at six developmental stages from heading to 28 DAA (days after anthesis). The total levels of WSC and WSC components were measured, and TaSUT1 gene expression was quantified at 21 DAA. On average, the total WSC and fructan levels in the stems were double those in the flag leaves. In both cultivars, diurnal patterns in the total WSC and sucrose were detected in leaves across all developmental stages, but not for the fructans 6-kestose and bifurcose. However, in stems, diurnal patterns of the total WSC and fructan were only found at anthesis in Kauz. The different levels of WSC and WSC components between Westonia and Kauz are likely associated with leaf chlorophyll levels and fructan degradation, especially 6-kestose degradation. High correlation between levels of TaSUT1 expression and sucrose in leaves indicated that TaSUT1 expression is likely to be influenced by the level of sucrose in leaves, and the combination of high levels of TaSUT1 expression and sucrose in Kauz may contribute to its high grain yield under well-watered conditions.

To predict what products customers will buy in next transaction is an important task. Existing work in next-basket prediction can be summarized into two paradigms. One is the item-centric paradigm, where sequential patterns are mined from customers' transactional data and leveraged for prediction. However, these approaches usually suffer from the data sparseness problem. The other is the user-centric paradigm, where collaborative filtering techniques have been applied on customers' historical data. However, these methods ignore the sequential behaviors of customers which is often crucial for next-basket prediction. In this paper, we introduce a hybrid method, namely the Co-Factorization model over Sequential and Historical purchase data (CFSH for short) for next-basket recommendation. Compared with existing methods, our approach conveys the following merits: 1) By mining global sequential patterns, we can avoid the sparseness problem in traditional item-centric methods; 2) By factorizing product-product and customer-product matrices simultaneously, we can fully exploit both sequential and historical behaviors to learn customer and product representations better; 3) By using a hybrid recommendation method, we can achieve better performance in next-basket prediction. Experimental results on three real-world purchase datasets demonstrated the effectiveness of our approach as compared with the state-of-the-art methods.

Due to the raising economy development of Shenzhen, environmental problems brought by road transport have become more serious. Promoting liquefied natural gas vehicle in the road freight is a key to reduce emissions, change the direction for road freight development, and build a resource-saving society. This article studies the application of liquefied natural gas vehicle in Shenzhen in-depth through official data sets, field investigation, expert consultation, and so on. Economic benefit analysis shows that liquefied natural gas vehicle has the advantage of saving considerable fuel costs for enterprises. Moreover, the Monte-Carlo method is used to evaluate the economic benefits considering a lot of factors. The economic analysis shows that the liquefied natural gas vehicle is more affordable than the diesel vehicle. Finally, the current issues of liquefied natural gas vehicles on the promotion are discussed and some advices are proposed to improve air quality and reduce emissions.

Due to their excellent electrical insulation properties and processability, polymer materials are used in many electrical products. It is widely believed that space charge plays an important role for the electric field distribution, conduction, ageing, and electric breakdown of polymeric insulation. This paper reviews measurements and characteristics of space charge behavior which mainly determined by the pulsed electro-acoustic (PEA) measurement technique. Particular interests are the effects of the applied voltage, the electrodes, temperature, humidity, microstructure, additives, and filler materials on accumulation, distribution, transport, and the decay of space charge in polymeric materials. This review paper is to provide an overview on various space charge effects under different conditions, and also to summarize the information for polymeric materials with suppressed space charge and improved electrical behavior.

A satellite image time series (SITS) contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests) and human activities (for example, deforestation and urbanisation) will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM) networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1) illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

Semantic-level land-use scene classification is a challenging problem, in which deep learning methods, e.g., convolutional neural networks (CNNs), have shown remarkable capacity. However, a lack of sufficient labeled images has proved a hindrance to increasing the land-use scene classification accuracy of CNNs. Aiming at this problem, this paper proposes a CNN pre-training method under the guidance of a human visual attention mechanism. Specifically, a computational visual attention model is used to automatically extract salient regions in unlabeled images. Then, sparse filters are adopted to learn features from these salient regions, with the learnt parameters used to initialize the convolutional layers of the CNN. Finally, the CNN is further fine-tuned on labeled images. Experiments are performed on the UCMerced and AID datasets, which show that when combined with a demonstrative CNN, our method can achieve 2.24% higher accuracy than a plain CNN and can obtain an overall accuracy of 92.43% when combined with AlexNet. The results indicate that the proposed method can effectively improve CNN performance using easy-to-access unlabeled images and thus will enhance the performance of land-use scene classification especially when a large-scale labeled dataset is unavailable.

Owing to the randomness in the fracture flow system, the seepage system beneath a complex rock mass dam is inherently complex and highly uncertain, an investigation of the dam leakage by estimating the spatial distribution of the seepage field by conventional methods is quite difficult. In this paper, the entropy theory, as a relation between the definiteness and probability, is used to probabilistically analyze the characteristics of the seepage system in a complex rock mass dam. Based on the principle of maximum entropy, an equation for the vertical distribution of the seepage velocity in a dam borehole is derived. The achieved distribution is tested and compared with actual field data, and the results show good agreement. According to the entropy of flow velocity in boreholes, the rupture degree of a dam bedrock has been successfully estimated. Moreover, a new sampling scheme is presented. The sampling frequency has a negative correlation with the distance to the site of the minimum velocity, which is preferable to the traditional one. This paper demonstrates the significant advantage of applying the entropy theory for seepage velocity analysis in a complex rock mass dam.

Fire detection based on multi-temporal remote sensing data is an active research field. However, multi-temporal detection processes are usually complicated because of the spatial and temporal variability of remote sensing imagery. This paper presents a spatio-temporal model (STM) based forest fire detection method that uses multiple images of the inspected scene. In STM, the strong correlation between an inspected pixel and its neighboring pixels is considered, which can mitigate adverse impacts of spatial heterogeneity on background intensity predictions. The integration of spatial contextual information and temporal information makes it a more robust model for anomaly detection. The proposed algorithm was applied to a forest fire in 2009 in the Yinanhe forest, Heilongjiang province, China, using two-month HJ-1B infrared camera sensor (IRS) images. A comparison of detection results demonstrate that the proposed algorithm described in this paper are useful to represent the spatio-temporal information contained in multi-temporal remotely sensed data, and the STM detection method can be used to obtain a higher detection accuracy than the optimized contextual algorithm.