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Drawing on word embeddings techniques and tracking the frequency and semantic change of hot words on Sina Weibo during the COVID-19 pandemic, this study investigates how language and discourse change during crisis. More specifically, correlation tests were conducted between word frequency ranks, pandemic data, and word meaning change ratio. Results indicated that the frequency of some hot words changed with both pandemic data and the frequency of other hot words, which were significantly correlated with the American pandemic data rather than that of China. Moreover, February of 2020 saw the most distinctive semantic changes marked by a large part of the nearest neighbors for WAR metaphors. The correlations between changes in the frequency and nearest neighbors of COVID-19 related hot words exhibited some acceptable peculiarities. This study proves the availability of studying discourse through language change by observing minor semantic change on connotation level from social media, which adds a new perspective to the impact of the COVID-19 pandemic.

Poverty is a chronic problem all over the world. Since the 18th National Congress of the Communist Party of China was held in 2012, the Chinese government has continuously increased its poverty alleviation efforts. In addition, absolute poverty in China was eliminated by the end of 2020. Tourism has played an important role in poverty alleviation. To explore the role of the tourism industry in reducing poverty, this paper takes the Liupan Mountain area of Gansu Province in western China, as a case site. An input–output evaluation index system was constructed, and a Super-SBM model was used to evaluate the tourism poverty alleviation efficiency in 40 districts and counties in the Liupan Mountain area from 2009 to 2018. The results show that the overall starting point of tourism poverty alleviation efficiency in the study area was high, which needed to be further optimized. The difference in tourism poverty alleviation efficiency among districts and counties tended to decrease in the time series. The restrictive factors were the lack of technological progress and lack of innovation. The spatial distribution of tourism poverty alleviation efficiency in the study area presented a pattern of high in the east and low in the west, high in the north and low in the south. In the future, the tourism poverty alleviation efficiency in the concentrated and contiguous destitute areas of the Liupan Mountain area in Gansu Province could be improved by cultivating the tourism industry, strengthening technological innovation, cultivating core growth poles, and exerting radiation effects.

Background Mineral elements are important for maintaining good human health besides heavy metals. Mining genes that control mineral elements are paramount for improving their accumulation in the wheat grain. Although previous studies have reported some loci for beneficial trace elements, they have mainly focused on Zn and Fe content. However, little information is available regarding the genetic loci differences in dissecting synchronous accumulation of multiple mineral elements in wheat grains, including beneficial and heavy elements. Therefore, a genome-wide association study (GWAS) was conducted on 205 wheat accessions with 24,355 single nucleotide polymorphisms (SNPs) to identify important loci and candidate genes for controlling Ca, Fe, Zn, Se, Cu, Mn, Cd, As, and Pb accumulation in wheat grains. Results A total of 101 marker-trait associations (MTAs) (P –5) loci affecting the content of nine mineral elements was identified on chromosomes 1B, 1D, 2A, 2B, 3A, 3B, 3D, 4A, 4B, 5A, 5B, 5D, 6B, 7A, 7B, and 7D. Among these, 17 major MTAs loci for the nine mineral elements were located, and four MTAs loci (P –5) were found on chromosomes 1B, 6B, 7B, and 7D. Eight multi-effect MTAs loci were detected that are responsible for the control of more than one trait, mainly distributed on chromosomes 3B, 7B, and 5A. Furthermore, sixteen candidate genes controlling Ca, Fe, Zn, Se, Cd, and Pb were predicted, whose functions were primarily related to ion binding, including metals, Fe, Ca, Cu, Mg, and Zn, ATP binding, ATPase activity, DNA binding, RNA binding, and protein kinase activity. Conclusions Our study indicated the existence of gene interactions among mineral elements based on multi-effect MTAs loci and candidate genes. Meanwhile this study provided new insights into the genetic control of mineral element concentrations, and the important loci and genes identified may contribute to the rapid development of beneficial mineral elements and a reduced content of harmful heavy metals in wheat grain.

Transforming growth factor beta (TGF-beta) and Chloride channel-3 (CLC-3) are critical for inflammatory response, cellular proliferation and apoptosis in hippocampus neurons. However, the relationship between CLC-3 and TGF-beta/TGF-beta Receptor II (RII) pathway in diabetic encephalopathy (DE) is unknown. In this study, both diabetes rat model and diabetes cell model were employed to elucidate the mechanisms involved. The increased expressions of CLC-3 and TGF- beta RII with cognitive impairment were observed in diabetic rats. The most obvious reduction on the survival of HT22 cells was at 10 ng/ml or 15 ng/ml TGF- beta stimulation, while the expressions of CLC-3 and TGF-beta RII were significantly increased under high glucose condition. Moreover, the study showed that CLC-3 antagonists had no apparent effect on up-regulated TGF- beta RII, but TGF- beta 1 inhibitors could reduce the up-regulated CLC-3 under high glucose. Results from the present study indicated that CLC-3 and TGF- beta signals might be related to cognitive disorders. The CLC-3 might be modulated by TGF- beta /TGF- beta RII signaling pathway during the development of DE.

The development process of space Langmuir probe needs to complete a large number of tests and calibration tests on the ground. Due to the long calibration period, complexity and high cost of plasma environment calibration, calibration tests are usually carried out after the instrument has been developed, in order to conduct preliminary tests on Langmuir probe during the instrument development process to verify the performance, as well as to save the cost of calibration tests and increase the reliability of the instrument, An advanced spatial Langmuir probe volt-ampere(I-V) load simulator was designed in this paper. Based on the positive and negative polarity of the external bias voltage, the I-V characteristic curve of the Langmuir probe was divided into positive and negative characteristic curves, which were realized by the combination of the output characteristic curves of NPN and PNP transistors, and the diode switching selectivity. The laboratory test results were consistent with the theoretical curve, verifying the validity and compliance of the design, which can play an important role in supporting the development of the space Langmuir probe and the calibration of the plasma environment.

We propose a novel one-stage object detection network, called adaptively dense feature pyramid network (ADFPNet), to detect objects cross various scales. The proposed network is developed on single shot multibox detector (SSD) framework with a new proposed ADFP module, which is consisted of two components: a dense multi scales and receptive fields block (DMSRB) and an adaptively feature calibration block (AFCB). Specifically, DMSRB block extracts rich semantic information in a dense way through atrous convolutions with different atrous rates to extract dense features in multi scales and receptive fields; the AFCB block calibrate the dense features to retain features contributing more and depress features contributing less. The extensive experiments have been conducted on VOC 2007, VOC 2012, and MS COCO dataset to evaluate our method. In particular, we achieve the new state of the art accuracy with the mAP of 82.5 on VOC 2007 test set and the mAP of 36.4 on COCO test-dev set using a simple VGG-16 backbone. When testing with a lower resolution (300 × 300), we achieve an mAP of 81.1 on VOC 2007 test set with an FPS of 62.5 on an NVIDIA 1080ti GPU, which meets the requirement for real-time detection.

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Flour whiteness and colour are important factors that influence the quality of wheat flour and end-use products. In this study, a genome wide association study focusing on flour and dough sheet colour using a high density genetic map constructed with 90K single nucleotide polymorphism arrays in a panel of 205 elite winter wheat accessions was conducted in two different locations in 2 years. Eighty-six significant marker-trait associations (MTAs) were detected for flour whiteness and the brightness index (L* value), the redness index (a* value), and the yellowness index (b* value) of flour and dough sheets (P –4) on homologous group 1, 2, 5 and 7, and chromosomes 3A, 3B, 4A, 6A and 6B. Four, three, eleven, eleven MTAs for the flour whiteness, L* value, a* value, b* value, and one MTA for the dough sheet L* value were identified in more than one environment. Based on MATs, some important new candidate genes were identified. Of these, two candidate genes, TraesCS5D01G004300 and Gsp-1D, for BS00000020_51 were found in wheat, relating to grain hardness. Other candidate genes were associated with proteins, the fatty acid biosynthetic process, the ketone body biosynthetic process, etc.

Objectives: This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. Materials and Methods: 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: 1. Correlation between these two estimations; 2. Exploring the dynamic patterns using these two estimations between moderate and severe groups.Results: The Spearman’s correlation coefficient between these two estimation methods was 0.920 (prd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. Conclusions: The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.

In order to solve the problems of heavy labor burden, cumbersome work, patients can not get comfortable care and low medical efficiency, an intelligent drip infusion control system based on Huawei Internet of things platform is designed. The system first describes the system implementation technical principle, hardware design idea, Huawei cloud platform upper management application solution idea, using NB-IoT to communicate with Huawei cloud platform, Huawei cloud server design, web back-end, web front-end and mobile app design process. The test results show that the system has the functions of web page and mobile app remote centralized monitoring, remote speed regulation and remote run out alarm, which reduces the burden of nurses, reduces the contact time between nurses and patients, and improves the medical efficiency.

The first-order reliability method is widely used for structural reliability analysis; however, its accuracy would become worse for nonlinear problems. This paper proposes the accuracy analysis method of the first-order reliability method, which considers the worst cases when using the first-order reliability method and gives the possible value range of the probability of safety. The accuracy analysis method can evaluate the reliability level of the first-order reliability method when the failure surfaces are nonlinear. The calculation formula for the possible value range of the probability of safety is proposed, and its trend as the dimensions and reliability rise is also discussed in this paper. A numerical example and a honeycomb crashworthiness design are presented to validate the accuracy of the first-order reliability method, and the results show that they are located within the possible value range proposed in this paper.

The application of design-point-based reliability-based design optimization (RBDO) methods is hindered by the challenge of multiple-design-point problems. In this article, to improve the commonalit...

This study investigates how floods are presented as newsworthy in the photo galleries of Associated Press (AP) and Xinhua News Agency (Xinhua), two news outlets with different cultural and political backgrounds. A distinction is made between international floods, that is, Their floods, and domestic floods, that is, Our floods. The data consists of around 1500 photo-caption complexes. The analysis adopts the framework of Discursive News Values Analysis. The findings show a similar tendency to highlight Negativity, Impact, Personalization and Superlativeness in presenting Their floods by AP and Xinhua, though the two differ in Proximity and Positivity. By contrast, Our floods are presented differently. Negativity, Impact and Personalization are foregrounded in AP’s presentation of floods in the United States, whereas Xinhua’s presentation of floods in China gives prominence to Negativity, Positivity, Personalization and Superlativeness. The study is significant for its attention to cross-cultural comparison and the genre of online photo galleries.

To dissect the genetic control of the sensory and textural quality traits of Chinese white noodles, a population of recombinant inbred lines (RILs), derived from the cross of waxy wheat Nuomai 1 (NM1) and Gaocheng 8901 (Gc8901), was used. The RILs were tested in three different environments to determine the role of environmental effects on quantitative trait loci (QTL) analysis. A total of 45 QTLs with additive effects for 17 noodle sensory and textural properties under three environments were mapped on 15 chromosomes. These QTLs showed 4.23–42.68% of the phenotypic variance explained (PVE). Nineteen major QTLs were distributed on chromosomes 1B, 1D, 2A, 3B, 3D, 4A, and 6A, explaining more than 10% of the phenotypic variance (PV). Clusters were detected on chromosomes 2B (3 QTLs), 3B (11 QTLs) and 4A (5 QTLs). The cluster detected on chromosome 4A was close to the Wx-B1 marker. Five co-located QTLs with additive effects were identified on chromosomes 2B, 3D, 4A, 6A, and 7B. The two major QTLs, Qadh.sdau-3B.1 and Qspr.sdau-3B.1 , in cluster wPt666008–wPt5870 on chromosome 3B were detected in three different environments, which perhaps can be directly applied to improve the textural properties of noodles. These findings could offer evidence for the selection or development of new wheat varieties with noodle quality using molecular marker-assisted selection (MAS).

Wheat starch is closely related to yield and quality of wheat-based final products. This genome-wide association study focused on total starch content and its components using single nucleotide polymorphisms (SNPs) in a panel of 205 elite winter wheat accessions. Twenty-nine significant marker-trait associations (MTAs) were detected for total starch (TSC), amylose (AMS) and amylopectin (AMP) contents under four environmental regimes. Nine MTAs were detected for two traits, and eleven MTAs were found for all three traits. These SNPs were distributed across seven chromosomes, explaining 11.26–23.83% of the phenotypic variance (PVE). Furthermore, eighteen MTAs related to the ratio of AMS and AMP under four environmental conditions explained 5.92–17.2% of the phenotypic variance. One important multi-trait MTA on chromosome 3A at the 93 cM position was found for thousand kernel weight, AMP, AMS and TSC. A set of elite alleles was identified, including allele Kukri_c5615_1214-A, which increased AMS and AMP by 5.80% and 15.32%, respectively. The allele Excalibur_c16376_351-T increased AMP by 4.43%, and the T allele of marker BS00022255_51 and T allele of marker D_contig25392_201 had the most significant effects, increasing the ratio of AMS to AMP by 3.77%. Fourteen candidate genes associated with significant markers were identified. For example, TRIAE_CS42_2AL_TGACv1_093900_AA0288950 participated in carbohydrate metabolism and hydrolysed O-glycosyl compounds. The lines that carry these elite alleles could be used as genetic stock for breeding to improve these traits. These results could lay the foundation for molecular marker-assisted selection in improving wheat quality.

Genome-wide association studies have become a wide spread method of quantitative trait locus identification for many crops, including wheat (Triticum aestivum L.). Its benefit over traditional biparental mapping approaches depends on the extent of linkage disequilibrium (LD) in natural populations. We estimated the genetic diversity, population structure, and LD decay rate in a winter wheat association mapping panel (n = 205) and identified markers associated with thousand-kernel weight (TKW) and related traits. The panel was genotyped with a high-density Illumina iSelect 90 K single nucleotide polymorphism assay. PIC values were 0.047–0.375 with a mean of 0.277. Structural analysis suggested the association mapping panel contained four subpopulations. LD decay rates extended to longer genetic distances within the D genome (11.0 cM) relative to the A and B genomes (1.5 and 1.8 cM, respectively). A total of 271 marker-trait associations (MTAs) were identified for TKW and related traits, explaining 5.49–9.86 % of variation in individual traits. Among them, 11 highly significant markers (p

Object detection across different scales is challenging as the variances of object scales. Thus, a novel detection network, Top-Down Feature Fusion Single Shot MultiBox Detector (TDFSSD), is proposed. The proposed network is based on Single Shot MultiBox Detector (SSD) using VGG-16 as backbone with a novel, simple yet efficient feature fusion module, namely, the Top-Down Feature Fusion Module. The proposed module fuses features from higher-level features, containing semantic information, to lower-level features, containing boundary information, iteratively. Extensive experiments have been conducted on PASCAL VOC2007, PASCAL VOC2012, and MS COCO datasets to demonstrate the efficiency of the proposed method. The proposed TDFSSD network is trained end to end and outperforms the state-of-the-art methods across the three datasets. The TDFSSD network achieves 81.7% and 80.1% mAPs on VOC2007 and 2012 respectively, which outperforms the reported best results of both one-stage and two-stage frameworks. In the meantime, it achieves 33.4% mAP on MS COCO test-dev, especially 17.2% average precision (AP) on small objects. Thus all the results show the efficiency of the proposed method on object detection. Code and model are available at: https://github.com/dongfengxijian/TDFSSD .

Rationale Acute lymphoblastic leukemia (ALL) has acute and severe onset characterized by fever, moderate to severe anemia, bone and joint pain, and sternal tenderness. It is easy to be misdiagnosed as rheumatic disease when joint pain is the first symptom. Patient concerns A male Han, 18 years of age was admitted on July 15th, 2016 for multi-joint swelling and pain with intermittent fever for half a year which had aggravated in the last 10 days. Diagnosis Based on symptoms, imaging, family history, and blood tests, he was first diagnosed with ankylosing spondylitis, but he was refractory to treatment. Bone marrow biopsy then revealed acute B-lymphoblastic leukemia (possibility Pro-B-ALL). Interventions The patient was transferred to the hematology department on July 23rd, 2016 for chemotherapy. Outcomes No joint pain occurred during follow-up, which ended on November 4th, 2018. Lessons ALL may present with symptoms suggestive of rheumatic diseases like ankylosing spondylitis. Physicians should be aware of this possibility, especially in young patients.

Fibrosarcoma is an aggressive and highly metastatic cancer of the connective tissue, for which effective therapeutic methods are limited. Recently, there has been a renewed interest in small molecular compounds from natural products in the treatment of cancer. In the present study, we investigated the compound, scutellarein, extracted from the perennial herb Scutellaria lateriflora, and it was found to possess anticancer potential. Cell proliferation assay and cell cycle analysis revealed that the proliferation rate of HT1080 human fibrosarcoma cells was significantly suppressed by treatment with scutellarein through the induction of apoptosis. Moreover, an in vivo experiment using Balb/c nude mice revealed that the volume and weight of the tumors were markedly reduced following treatment with scutellarein. We also analyzed the effects of scutellarein on the markers of metastasis, using the HT1080 cells. The results indicated that scutellarein potently inhibited cell migration, invasion and the expression and activity of matrix metalloproteinase (MMP)-2, -9 and -14. Furthermore, MMP activation and cell survival were suppressed due to the scutellarein-mediated downregulation of nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) activation. In conclusion, our data suggest that scutellarein has the ability to attenuate the development of fibrosarcoma and inhibit cancer cell metastasis.

Previous phylogenetic analyses have led to incongruent evolutionary relationships between tree shrews and other suborders of Euarchontoglires. What caused the incongruence remains elusive. In this study, we identified 6845 orthologous genes between seventeen placental mammals. Tree shrews and Primates were monophyletic in the phylogenetic trees derived from the first or/and second codon positions whereas tree shrews and Glires formed a monophyly in the trees derived from the third or all codon positions. The same topology was obtained in the phylogeny inference using the slowly and fast evolving genes, respectively. This incongruence was likely attributed to the fast substitution rate in tree shrews and Glires. Notably, sequence GC content only was not informative to resolve the controversial phylogenetic relationships between tree shrews, Glires, and Primates. Finally, estimation in the confidence of the tree selection strongly supported the phylogenetic affiliation of tree shrews to Primates as a monophyly.

Micro-Doppler signature produced by micro-motion contains movement and structure information which is useful for radar classification and recognition. In order to recognize the wheeled vehicle and the tracked vehicle in ground battle, the motion dynamics and echo models of the scattering point on wheeled vehicle and tracked vehicle are set up respectively. Then the micro-Doppler features of them are quantitatively analyzed. Furthermore, the smoothed pseudo Winger-Ville distribution method is proposed for extracting micro-Doppler modulation. Finally, simulation results demonstrate the correctness of the theoretic analysis and the validity of the extraction method.

A fixture is a special tool used to accurately and stably locate the workpiece during machining process. Proper fixture design improves the quality and production of parts and also facilitates the interchangeability of parts that is prevalent in much of modern manufacturing. This study combines the rule-based reasoning (RBR) and case-based reasoning (CBR) method for machining fixture design in a VR based integrated system. In this paper, an approach combines the RBR and fuzzy comprehensive judgment method is proposed for reasoning suitable locating schemes and locating features. Based on the reasoning results, a CBR method for machining fixture design is then presented. This method could help designers, by referencing previous design cases, to make a conceptual fixturing solution quickly. Finally, the implementation of proposed system is outlined and cases study has been used to demonstrate the applicability of the proposed approach.