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A typhoon or hurricane is one of the most destructive high-impact weather events. In this study, the genesis and development processes of Typhoon Nangka (2015), which occurred over the Western Pacific in 2015, were investigated based on the comprehensive observation data from three satellites, i.e., the Himawari-8 satellite, the CloudSat satellite and the Global Precipitation Measurement mission satellite (GPM), focusing on the characteristics of typhoon structure, precipitation and cloud. The results (Results) show that during the developing stage of Typhoon Nangka, the cloud system was relatively complex and changed significantly, with large raindrops dominating the precipitation around the eyewall in the first quadrant, and the convection in the eyewall and outer rainband burst upward to 17 km. In addition, three features were obvious: stratiform precipitation was dominant in the inner rainband, both the precipitation type (stratiform or convective) and intensity were distributed unevenly in the outer rainband, and large water content was located in the warm layer of clouds. Moreover, the collision growth and breakup of water droplets tended to be stable. The precipitation in the typhoon eyewall, inner rainband and outer rainband was significantly different; stratiform precipitation mainly occurred in the inner rainband, while convective precipitation mainly appeared in the eyewall and outer rainband. The cloud system was distributed asymmetrically, and the upper-layer and lower-layer clouds were closely related, dominated by single-layer clouds. There were deep convective clouds in the eyewall, and cirrus clouds with the broadest range across the eyewall. The coverage range of cirrus clouds was close to the radius of the typhoon. There were stratocumulus, altostratus and cumulus in the low levels. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Group B Streptococcus (GBS) is the major pathogen that causes invasive infectious diseases in neonates and infants. The development of preventive and therapeutic strategies against GBS infection has been becoming the most pressing subject worldwide. Group B carbohydrate (GBC), the group B‐specific polysaccharide that distinguishes GBS with other streptococci species, has been identified as an attractive antigen for diagnosis and vaccine development because of its highly conservative tetra‐antennary structure. In this paper, a highly convergent [3 + 5] glycosylation strategy for efficient synthesis of an octasaccharide derivative related to GBC oligosaccharide unit II has been developed. In this synthesis, each glycosylation reaction was efficiently constructed with glycosyl imidates, especially trifluoroacetimidate, as donors, and each glycosidic bond was stereoselectively controlled via the neighboring group participation effect of acyl group on the 2‐O‐position of imidate donors or the solvent effect of Et2O. Furthermore, the aminoethylphosphate group was smoothly installed on the 6‐O‐position of d‐glucitol residue using the phosphoramidite method. After global deprotection, the target octasaccharide was successfully obtained from d‐glucitol in 29 steps with an overall yield of 1.37%. The free amino group installed on the aminoethylphosphate spacer of the target molecule enables its modification with functionalized biomolecules for further biological studies. [ABSTRACT FROM AUTHOR]

Oracle bone inscriptions (OBIs) are ancient Chinese scripts originated in the Shang Dynasty of China, and now less than half of the existing OBIs are well deciphered. To date, interpreting OBIs mainly relies on professional historians using the rules of OBIs evolution, and the remaining part of the oracle's deciphering work is stuck in a bottleneck period. Here, we systematically analyze the evolution process of oracle characters by using the Siamese network in Few-shot learning (FSL). We first establish a dataset containing Chinese characters which have finished a relatively complete evolution, including images in five periods: oracle bone inscriptions, bronze inscriptions, seal inscriptions, official script, and regular script. Then, we compare the performance of three typical algorithms, VGG16, ResNet, and AlexNet respectively, as the backbone feature extraction network of the Siamese network. The results show that the highest F1 value of 83.3% and the highest recognition accuracy of 82.67% are obtained by the combination of VGG16 and Siamese network. Based on the analysis, the typical structural performance of each period is evaluated and we identified that the optimized Siamese network is feasible to study the evolution of the OBIs. Our findings provide a new approach for oracle's deciphering further. [ABSTRACT FROM AUTHOR]

A series of poly(acrylonitrile-butadiene-styrene) (ABS) grafting modifiers were synthesized by emulsion grafting poly(acrylonitrile-styrene) (SAN) copolymer onto polybutadiene (PB) latex rubber particles. The chain transfer reagent tert-dodecyl mercaptan (TDDM) was used to regulate the grafting degree of ABS and the molecular weight of SAN copolymers. By blending these ABS modifiers with Chlorinated polyvinyl chloride (CPVC) resin, a series of CPVC/ABS blends were obtained. The morphology, compatibility, and the mechanical properties of CPVC/ABS blends were investigated. The scanning electron microscope (SEM) studies showed that the ABS domain all uniformly dispersed in CPVC matrix. Dynamic mechanical analyses (DMA) results showed that the compatibility between CPVC and SAN became enhanced with the TDDM content. From the mechanical properties study of the CPVC/ABS blends, it was revealed that the impact strength first increases and then decreases with the TDDM content, which means that the compatibility between CPVC and the SAN was not the only requirement for maximizing toughness. The decreasing of tensile strength and the elongations might attribute to the lower entanglement between chains of CPVC and SAN. POLYM. ENG. SCI., 52:820-825, 2012. ©2011 Society of Plastics Engineers, INTRODUCTION Chlorinated polyvinyl chloride (CPVC) is of significant commercial interest due to its higher glass transition temperature, high heat deflection temperature, outstanding flame and smoke properties, and chemical inertness (1). [...]

Grinding stones have provided a convenient proxy for the arrival of agriculture in Neolithic China. Not any more. Thanks to high-precision analyses of use-wear and starch residue, the authors show that early Neolithic people were mainly using these stones to process acorns. This defines a new stage in the long transition of food production from hunter-gatherer to farmer. Keywords: China, Neolithic, grinding stones, querns, millet, acorns, agriculture, Introduction The Peiligang culture (c. 7000-5000 BC) represents the earliest Neolithic settlement in the Middle Yellow River Valley and signals the emergence of food production and ritual complexity in the [...]

By combining an electron-rich triazatruxene unit (TAT) to an electron-deficient zinc porphyrin fluorophore (ZnPor) via an ethynyl bridge, a new two-photon fluorescent viscosity rotor (TAT-ZnPor) with typical donor-π-acceptor (D-π-A) electronic configuration was developed for the ratiometric two-photon fluorescent detection of intracellular viscosity. The TAT-ZnPor dyad exhibited highly improved fluorescence quantum yield (Φem = 0.40) and two-photon absorption cross-section (δTPA = 811 GM) in comparison to the individual components. In the methanol/glycerol system, TAT-ZnPor showed sensitive fluorescence responses toward the change of viscosity. Upon elevating the viscosity from 0.59 to 947 cp, the blue emission band around 410 nm gradually enhanced, while the red band at 647 nm concomitantly quenched, leading to a remarkable intensity ratio (I410/I647) change from 0.70 to 81 (116-fold). TAT-ZnPor also displayed good cell imaging performance under one- and two-photon excitation, and strong mitochondria targeting ability in living cells, thus was successfully applied in detecting the change of mitochondrial viscosity during the nystatin-induced degeneration. [ABSTRACT FROM AUTHOR]

Multiple upwelling systems develop in the Indian Ocean during the summer monsoon. The Sri Lanka dome (SLD), which occurs in the open ocean off the east coast of Sri Lanka from June to September, is distinct from those near the coast. The SLD is characterized by uplifted thermocline and increased chlorophyll concentration. Mechanisms of the upwelling and its biogeochemical response are not well understood. Here, we explored the dynamics of the chlorophyll and sea-to-air CO2 flux in the SLD using ocean color and altimetry remote sensing data, together with other reanalysis products. We found that the occurrence of high chlorophyll concentration and sea-to-air CO2 flux happens along the pathway of the southwest monsoon current (SMC). The annual cycle of chlorophyll in the SLD has a one-month lag relative to that in the southern coast of Sri Lanka. The positive wind stress curl that forms in the SLD during the summer does not fully explain the seasonal chlorophyll maximum. Transport of the SMC, eddy activity, and associated frontal processes also play an important role in regulating the variability in chlorophyll. In the SLD, upwelled subsurface water has excess dissolved inorganic carbon (DIC) relative to the conventional Redfield ratio between DIC and nutrients; thus, upwelling and sub-mesoscale processes determine this region to be a net carbon source to the atmosphere. [ABSTRACT FROM AUTHOR]

The efficient and selective photocatalytic conversion of chemicals with visible light and naturally abundant resources has long been desired, but this requires finely designed sensitizers that are capable of converting light into chemical energy for the required energy/electron transfer, bond formation and scission, etc. Inspired by flavin (FL) based enzymes that are capable of initiating many redox reactions in biological systems in visible light, FL and naphthalimide chromophores were fused together as a heavy-atom-free triplet photosensitizer (NI-FL). It is expected that the extended conjugation within NI-FL may benefit absorption in the visible light range, promoting the intersystem crossing to triplet excited states for efficient chemoselective conversions. The absorption and emission maximum of NI-FL are redshifted by ∼40 nm and the absorption is more than doubled (1.53 × 104 M−1 cm−1 at 484 nm) with respect to FL (7.5 × 103 M−1 cm−1 at 439 nm), and a long-lived triplet excited state of intramolecular electron transfer nature was captured (τT = 45.3 μs). The performances of FL and NI-FL in the photooxidation of sulfides in air were also examined. Apart from nearly quantitative selectivity for sulfoxide, NI-FL demonstrates a 0.5–5 fold enhanced performance with respect to FL and the conversion proceeds through radical intermediates formed by electron transfer at excited states with substrates. Mechanistic investigation satisfactorily explained the observed photophysical properties and the dominant role of radical intermediates in the NI-FL catalyzed photooxidation. The findings may help to understand photooxidation sensitized by FL derivatives and benefit the design of novel efficient photosensitizers. [ABSTRACT FROM AUTHOR]

Chinese grammatical error correction (GEC) is under continuous development and improvement, and this is a challenging task in the field of natural language processing due to the high complexity and flexibility of Chinese grammar. Nowadays, the iterative sequence tagging approach is widely applied to Chinese GEC tasks because it has a faster inference speed than sequence generation approaches. However, the training phase of the iterative sequence tagging approach uses sentences for only one round, while the inference phase is an iterative process. This makes the model focus only on the current sentence's current error correction results rather than considering the results after multiple rounds of correction. In order to address this problem of mismatch between the training and inference processes, we propose a Chinese GEC method based on iterative training and sequence tagging (CGEC-IT). First, in the iterative training phase, we dynamically generate the target tags for each round by using the final target sentences and the input sentences of the current round. The final loss is the average of each round's loss. Next, by adding conditional random fields for sequence labeling, we ensure that the model pays more attention to the overall labeling results. In addition, we use the focal loss to solve the problem of category imbalance caused by the fact that most words in text error correction do not need error correction. Furthermore, the experiments on NLPCC 2018 Task 2 show that our method outperforms prior work by up to 2% on the F0.5 score, which verifies the efficiency of iterative training on the Chinese GEC model. [ABSTRACT FROM AUTHOR]

The effect of cyanobacterial blooms on aquatic ecosystems has received wide attention, yet little is known about their impacts on zooplankton genetic structure.For 26 months (April 2012–May 2014), we monitored zooplankton in a warm‐temperate ice‐free lake in Eastern China, with an emphasis on seasonal population dynamics of the cladoceran, Daphnia galeata. There was a seasonal succession in the zooplanktonic community (composed of Cladocera, Copepoda, and Rotifera).Genetic analysis (based on 14 microsatellite loci) of the 21 monthly samples in which D. galeata was present demonstrated that several clones could successfully overwinter and/or persist for many months. However, all clones, including these long‐lived clones, were completely replaced by new ones after October 2013, probably due to cyanobacteria blooms in that summer. A high clonal richness coupled with high turnover rate was observed in the D. galeata population overall, suggesting frequent sexual reproduction.Daphnia galeata experimentally fed with a diet of Microcystis aeruginosa (the most abundant toxic cyanobacterial species in the lake) had a substantially reduced survivorship, consistent with the field observations.Our findings highlight the changes of zooplanktonic population dynamics in terms of both community and clonal structure in a warm‐temperate ice‐free lake, and call for further investigation on ecological responses of zooplankton to cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

Perioperative neurocognitive disorders (PNDs) are a type of cognitive dysfunction occurring with a higher incidence in elderly patients. However, the pathological mechanism of PND and effective treatment remain elusive. We generated a PND mouse model by providing wild-type mice with surgical trauma; in our case, we used tibial fracture to investigate PND pathology. Mice aged 7–8 months were randomly divided into two groups: the surgery (tibial fracture) group and the control (sham) group. All mice were subjected to anesthesia. We examined the transcriptome-wide response in the hippocampus, a brain region that is tightly associated with memory formation, of control mice and mice subjected to surgical trauma at day 1 and day 3 after the surgical procedure. We observed reduced transcript levels of respiratory complex components as early as day 1 after surgery, and subsequent protein changes were found at day 3 after surgical trauma. Consequently, the activities of respiratory complexes were reduced, and adenosine triphosphate (ATP) production was decreased in the hippocampus of mice with surgical operations, supporting that respiratory chain function was impaired. In support of these conclusions, the mitochondrial membrane potential (MMP) levels were decreased, and the reactive oxygen species (ROS) levels were significantly increased. Mechanistically, we demonstrated that surgery induced a significant increase in cytokine IL-1β levels at day 1 after surgery, which concomitantly occurred with transcript changes in respiratory complex components. We further uncovered that transcription factors PGC-1α and NRF-1 were responsible for the observed transcript changes in mitochondrial complex components. Importantly, HT22 cells treated with the cytokine IL-1β resulted in similar reductions in PGC-1α and NRF-1, leading to a reduction of both the transcript and protein levels of respiratory complex subunits. Consequently, respiratory function was impaired in HT22 cells treated with IL-1β. Taken together, we demonstrated that reductions in respiratory complex components and subsequent impairment in mitochondrial functions serve as a novel mechanism for PND pathology, providing a potential therapeutic target for PND treatment. [ABSTRACT FROM AUTHOR]

Relation extraction (RE) is the core link of downstream tasks, such as information retrieval, question answering systems, and knowledge graphs. Most of the current mainstream RE technologies focus on the sentence-level corpus, which has great limitations in practical applications. Moreover, the previously proposed models based on graph neural networks or transformers try to obtain context features from the global text, ignoring the importance of local features. In practice, the relation between entity pairs can usually be inferred just through a few keywords. This paper proposes a keyword detection and context filtering method based on the Self-Attention mechanism for document-level RE. In addition, a Self-Attention Memory (SAM) module in ConvLSTM is introduced to process the document context and capture keyword features. By searching for word embeddings with high cross-attention of entity pairs, we update and record critical local features to enhance the performance of the final classification model. The experimental results on three benchmark datasets (DocRED, CDR, and GBA) show that our model achieves advanced performance within open and specialized domain relationship extraction tasks, with up to 0.87% F1 value improvement compared to the state-of-the-art methods. We have also designed experiments to demonstrate that our model can achieve superior results by its stronger contextual filtering capability compared to other methods. [ABSTRACT FROM AUTHOR]

Dynamic context selector, a kind of mask idea, will divide the matrix into some regions, selecting the information of region as the input of model dynamically. There is a novel thought that improvement is made on the entity relation extraction (ERE) by applying the dynamic context to the training. In reality, most existing models of joint extraction of entity and relation are based on static context, which always suffers from the feature missing issue, resulting in poor performance. To address the problem, we propose a span-based joint extraction method based on dynamic context and multi-feature fusion (SPERT-DC). The context area is picked dynamically with the help of threshold in feature selecting layer of the model. It is noted that we also use Bi-LSTM_ATT to improve compatibility of longer text in feature extracting layer and enhance context information by combining with the tags of entity in feature fusion layer. Furthermore, the model in this paper outperforms prior work by up to 1% F1 score on the public dataset, which has verified the efficiency of dynamic context on ERE model. [ABSTRACT FROM AUTHOR]

Training animals to pull agricultural equipment and wheeled transport significantly shaped and advanced human economic systems. In this context the use of large domestic animals such as cattle was a milestone event in human history, part of what Sherratt memorably termed the Secondary Products Revolution: the use of the products of live animals such as milk, wool and traction power. It is commonly assumed that male cattle were generally preferred for traction because of their greater strength compared with females, and the importance of the latter for breeding and, in some societies, for milk and for dairy products, but surprisingly little is known of this aspect of the Secondary Products Revolution in prehistoric China. Here we apply established morphometric models to 10 assemblages of cattle bones from Chinese Bronze Age (ca. 2000–221 BCE) contexts. Our results indicate a process of intensified cattle labour exploitation at this time and, intriguingly, we also observe the earliest labour employment of female cattle during the Late Shang dynasty (ca. 1300–1046 BCE). It is proposed that female cattle may have been required for traction because of the large numbers of male cattle, especially bulls, that were sent for ritual sacrifice. Such a strategy reveals a sophisticated social management, upon which the Late Shang civilisation eventually developed. [ABSTRACT FROM AUTHOR]

Lycium ruthenicum is a characteristic plant resource in Northwest China. The fruit with high anthocyanin content is the main reason for its high nutritional value and economic value, while the regulation of key genes regulating anthocyanin biosynthesis in black fruit is not clear. In this study, high-throughput sequencing technology was used to compare the expression differences of all genes in black and purple fruits. The purple samples obtained 45.13 and 51.49 M Raw reads, while the black fruit samples measured 53.85 and 47.38 M Raw Reads. After splicing and assembly, 162,842 transcripts were obtained after removing redundant and duplicated results. Homology comparison of all predicted proteins found that 36,978 (22.43%) genes in Lycium ruthenicum were homologous to Solanum tuberosum, followed by 24,459 (14.84%) genes were homologous to Capsicum annuum. Overall, 3685 genes were up-regulated in purple fruit, 2837 genes were down-regulated in purple fruit, and the remaining 156320 genes were not differentially expressed in black and purple fruit. Through homology comparison of anthocyanin biosynthesis and metabolism structure genes in Lycium ruthenicum, 63 homologous genes, 4 MYB transcription factors and 5 bHLH transcription factors were screened. LrAN2p (909 bp) in purple fruit was 136 bp more upstream of 'ATG' than LrAN2 (774 bp) in black fruit. Three highly expressed copies of bHLH transcription factors AN1b with different lengths were screened in black fruit, but they were almost not expressed in purple fruit. This study possibly identified the major LrAN1b genes regulating the black fruit trait. [ABSTRACT FROM AUTHOR]

Background. Emerging studies support the oncogenic role of WD repeat domain 62 (WDR62) in few tumors, while no pan-cancer analysis is available. In this study, we analyzed systematically the oncogenic role of WDR62 across a series of human tumors based on bioinformatic data mining. Methods. The expression level of WDR62 was analyzed via GEPIA2, TIMER, UALCAN, and StarBase databases. The prognostic role was analyzed via GEPIA2, TIMER, UALCAN, StarBase, TISIDB, TCGA portal, Kaplan-Meier Plotter, and PrognoScan databases. Then, we explored the causes for WDR62 abnormal expression via TCGA portal and UALCAN databases. Subsequently, the STRING and GeneMANIA databases were used to find the interactive networks for WDR62. Furthermore, we analyzed the correlation between WDR62 expression and immune features via TIMER and TISIDB databases. Results. We found that WDR62 was significantly upregulated in most of the tumors and correlated with poor prognosis mainly in 6 candidate tumors—BLCA, BRCA, KIRC, KIRP, LIHC, and LUAD. Abnormal WDR62 expression may be probably attributed to TP53 mutation and promoter DNA methylation. Relative network analysis demonstrated that WDR62 was mainly involved in MAPK and toll-like receptor signaling pathway. WDR62 expression was associated with various immune cell infiltrations, especially cancer-associated fibroblasts (CAF) and T cell regulatory (Treg) cells, and was markedly correlated with poor prognosis. Moreover, WDR62 expression was closely associated with the expression of some immunomodulators such as PD-L1 and has a significant prognostic value. Conclusions. Our study revealed that WDR62 could serve as a diagnostic and prognostic biomarker for several cancers. Importantly, WDR62 was closely associated with various immune cell infiltration, and to a certain extent, it can predict the effect of immunotherapy in particular PD1/PD-L1 inhibitors. Our pan-cancer study provided useful information on the oncogenic role of WDR62, contributing to further exploring the underlying mechanisms. [ABSTRACT FROM AUTHOR]

The electronic structure and photophysical properties of a series of N-methyl and N-acetyl substituted alloxazines (AZs) were investigated with extensive density functional theory (DFT) and time-dependent density functional theory (TD–DFT) based calculations. We showed that non-radiative decays from the lowest singlet and triplet excited states of these AZs are dominant over their radiative counterparts. The fast non-radiative decays of the excited AZs can be attributed to the energy consumption (Ereorg) through structural reorganization facilitated by the intrinsic normal modes of the alloxazine framework, as well as their coupling with those of the functional groups. Substitution with functional groups may lead to further perturbation of the electronic structure of the AZ chromophore, which may enhance intersystem crossing with the ππ* states of the AZs. Due to the different bonding of N1 and N3 within the alloxazine framework, substitution may result in AZs with different photophysical properties. Specifically, functionalization at N1 may help in maintaining or even reducing Ereorg and would promote the absorption and radiative decay from the excited AZs. However, the strong coupling of the vibrational modes of acetyl at N3 with the intrinsic normal modes of the alloxazine framework would contribute significantly to Ereorg, and benefit the non-radiative decay of the excited AZs. We expect that the findings would pave the way for rational design of novel AZs with extraordinary photophysical properties. [ABSTRACT FROM AUTHOR]

Micro-Doppler-based continuous human motion recognition (HMR) has gained considerable attention recently. However, existing methods mainly rely on individual recurrent neural network or sliding-window-based approaches, which makes them hard to effectively exploit all the temporal information to predict motions. Additionally, they need to represent the raw radar data into other domains and then perform feature extraction and classification. Thus, the representation cannot be optimized, and its high computational complexity and independence from learning model make the network consume significant time. In this article, to address these issues, we propose a new end-to-end network that uses radar radios to recognize continuous motion. Specifically, the fusion layer fuses the raw I & Q radar data without the need of representations, and it is integrated with subsequent networks in an end-to-end manner for jointly optimization. Moreover, the attention-based encoder-decoder structure encodes the fused data and selects useful temporal information for recognition, which guarantees the effective use of all the temporal information. The experiments show that in continuous HMR, the proposed network outperforms existing methods in terms of accuracy and inference time. [ABSTRACT FROM AUTHOR]

The application of micro-Doppler-based continuous human motion recognition (HMR) is greatly hindered by non-target micro motion interference, due to the deformation of micro-Doppler signatures of target human motion caused by such interference. In this paper, we propose a novel continuous HMR method using micro-Doppler signatures that can work in the scenario with non-target micro motion interference. Specifically, a signal preprocessing architecture is designed, where the empirical mode decomposition is employed to remove the interference in radar raw signal and the multiwindow time-frequency representation is used to generate the time-frequency distribution (TFD) with high concentration. Moreover, a tailored network, that integrates multiscale squeeze-and-excitation network for feature sequence extraction, stacked bidirectional long short-term memory for sequence labeling and connectionist temporal classification algorithm for label transcription, is employed to recognize continuous human motion from TFD. The experimental results show that the proposed method outperforms existing methods in terms of recognition accuracy and generalization. [ABSTRACT FROM AUTHOR]