Multi-task hourglass network for online automatic diagnosis of developmental dysplasia of the hip.

Developmental dysplasia of the hip (DDH) is one of the most common diseases in children. Due to the experience-requiring medical image analysis work, online automatic diagnosis of DDH has intrigued the researchers. Traditional implementation of online diagnosis faces challenges with reliability and interpretability. In this paper, we establish an online diagnosis tool based on a multi-task hourglass network, which can accurately extract landmarks to detect the extent of hip dislocation and predict the age of the femoral head. Our method utilizes a multi-task hourglass network, which trains an encoder-decoder network to regress the landmarks and predict the developmental age for online DDH diagnosis. With the support of precise image analysis and fast GPU computing, our method can help overcome the shortage of medical resources and enable telehealth for DDH diagnosis. Applying this approach to a dataset of DDH X-ray images, we demonstrate 4.64 mean pixel error of landmark detection compared to the results of human experts. Moreover, we can improve the accuracy of the age prediction of femoral heads to 89%. Our online automatic diagnosis system has provided service to 112 patients, and the results demonstrate the effectiveness of our method.

PCSK9 inhibitor recaticimab for hypercholesterolemia on stable statin dose: a randomized, double-blind, placebo-controlled phase 1b/2 study.

BACKGROUND: Recaticimab (SHR-1209, a humanized monoclonal antibody against PCSK9) showed robust LDL-C reduction in healthy volunteers. This study aimed to further assess the efficacy and safety of recaticimab in patients with hypercholesterolemia. METHODS: In this randomized, double-blind, placebo-controlled phase 1b/2 trial, patients receiving stable dose of atorvastatin with an LDL-C level of 2.6 mmol/L or higher were randomized in a ratio of 5:1 to subcutaneous injections of recaticimab or placebo at different doses and schedules. Patients were recruited in the order of 75 mg every 4 weeks (75Q4W), 150Q8W, 300Q12W, 150Q4W, 300Q8W, and 450Q12W. The primary endpoint was percentage change in LDL-C from the baseline to end of treatment (i.e., at week 16 for Q4W and Q8W schedule and at week 24 for Q12W schedule). RESULTS: A total of 91 patients were enrolled and received recaticimab and 19 received placebo. The dose of background atorvastatin in all 110 patients was 10 or 20 mg/day. The main baseline LDL-C ranged from 3.360 to 3.759 mmol/L. The least-squares mean percentage reductions in LDL-C from baseline to end of treatment relative to placebo for recaticimab groups at different doses and schedules ranged from -48.37 to -59.51%. No serious treatment-emergent adverse events (TEAEs) occurred. The most common TEAEs included upper respiratory tract infection, increased alanine aminotransferase, increased blood glucose, and increased gamma-glutamyltransferase. CONCLUSION: Recaticimab as add-on to moderate-intensity statin therapy significantly and substantially reduced the LDL-C level with an infrequent administration schedule (even given once every 12 weeks), compared with placebo. TRIAL REGISTRATION: ClinicalTrials.gov , number NCT03944109.

Smart-Polypeptide-Coated Mesoporous Fe3O4 Nanoparticles: Non-Interventional Target-Embolization/Thermal Ablation and Multimodal Imaging Combination Theranostics for Solid Tumors.

Tumor theranostics hold great potential for personalized medicine in the future, and transcatheter arterial embolization (TAE) is an important clinical treatment for unresectable or hypervascular tumors. In order to break the limitation, simplify the procedure of TAE, and achieve ideal combinatorial theranostic capability, here, a kind of triblock-polypeptide-coated perfluoropentane-loaded mesoporous Fe3O4 nanocomposites (PFP-m-Fe3O4@PGTTCs) were prepared for non-interventional target-embolization, magnetic hyperthermia, and multimodal imaging combination theranostics of solid tumors. The results of systematic animal experiments by H22-tumor-bearing mice and VX2-tumor-bearing rabbits in vivo indicated that PFP-m-Fe3O4@PGTTC-6.3 has specific tumor accumulation and embolization effects. The tumors' growth has been inhibited and the tumors disappeared 4 weeks and ≤15 days post-injection with embolization and magnetic hyperthermia combination therapy, respectively. The results also showed an excellent effect of magnetic resonance/ultrasound/SPECT multimodal imaging. This pH-responsive non-interventional embolization combinatorial theranostics system provides a novel embolization and multifunctional theranostic candidate for solid tumors.

Dual Optical Path Based Adaptive Compressive Sensing Imaging System.

Compressive Sensing (CS) has proved to be an effective theory in the field of image acquisition. However, in order to distinguish the difference between the measurement matrices, the CS imaging system needs to have a higher signal sampling accuracy. At the same time, affected by the noise of the light path and the circuit, the measurements finally obtained are noisy, which directly affects the imaging quality. We propose a dual-optical imaging system that uses the bidirectional reflection characteristics of digital micromirror devices (DMD) to simultaneously acquire CS measurements and images under the same viewing angle. Since deep neural networks have powerful modeling capabilities, we trained the filter network and the reconstruction network separately. The filter network is used to filter the noise in the measurements, and the reconstruction network is used to reconstruct the CS image. Experiments have proved that the method we proposed can filter the noise in the sampling process of the CS system, and can significantly improve the quality of image reconstruction under a variety of algorithms.

Trends in the occurrence and risk assessment of antibiotics in shallow lakes in the lower-middle reaches of the Yangtze River basin, China.

Antibiotics have become a global public concern because of their extensively usage and high toxicity on aquatic organisms, especially leading to the widespread of antibiotic resistance genes. The objective of this study was to evaluate the occurrence, spatial distribution and ecological risks of multi-classes commonly used human and veterinary antibiotics in both aqueous and sedimentary phases of 65 shallow lakes in the lower-middle reaches of the Yangtze River, China. In the target area, antibiotic concentrations in most of lakes (<20 ng/L in the water of 22 lakes and <20 ng/g in the sediments of 43 lakes) were generally lower than those documented in previous studies in China and other countries, and these differences were probably due to less pollutant sources, high temperatures and heavy rainfall in summer. The concentrations of antibiotics in water (>100 ng/L) or sediments (>100 ng/g) of nine lakes, such as Dianshan Lake, Ge Lake and Ce Lake, were comparable to those in rivers and lakes that were seriously polluted by urban and livestock wastewater in China. The Taihu lakes showed relatively higher antibiotic concentrations, followed by the Huaihe River lakes, Poyang lakes and Dongting lakes. The composition of antibiotics showed that agricultural source might be the main source of antibiotics in most of the lakes in the lower-middle reaches of the Yangtze River basin, China. The pseudo distribution coefficient (P-Kd) and significant relationship between antibiotics and environmental factors in the present study suggested the spatial of antibiotics in the lakes might be affected by antibiotics' physiochemical properties and environmental factors. The environmental risk assessment results showed that in general, sulfamethoxazole (SMX), erythromycin (ETM) and ofloxacin (OFX) in the surface water could pose medium risks to algae or bacteria in the aquatic ecosystem, while antibiotics ETM, roxithromycin (RTM), enrofloxacin (EFX) and sulfadiazine (SDZ) in the sediment might pose medium risks to algae or bacteria populations. High potential risk might occur in winter in most lakes due to lower water storage and less degradation. Overall, our study reveals the pollution trends and potential sources of antibiotics in shallow lakes in the lower-middle reaches of the Yangtze River basin.

Drug-target interaction prediction: databases, web servers and computational models.

Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.

H-BLAST: a fast protein sequence alignment toolkit on heterogeneous computers with GPUs.

Motivation: The sequence alignment is a fundamental problem in bioinformatics. BLAST is a routinely used tool for this purpose with over 118 000 citations in the past two decades. As the size of bio-sequence databases grows exponentially, the computational speed of alignment softwares must be improved. Results: We develop the heterogeneous BLAST (H-BLAST), a fast parallel search tool for a heterogeneous computer that couples CPUs and GPUs, to accelerate BLASTX and BLASTP-basic tools of NCBI-BLAST. H-BLAST employs a locally decoupled seed-extension algorithm for better performance on GPUs, and offers a performance tuning mechanism for better efficiency among various CPUs and GPUs combinations. H-BLAST produces identical alignment results as NCBI-BLAST and its computational speed is much faster than that of NCBI-BLAST. Speedups achieved by H-BLAST over sequential NCBI-BLASTP (resp. NCBI-BLASTX) range mostly from 4 to 10 (resp. 5 to 7.2). With 2 CPU threads and 2 GPUs, H-BLAST can be faster than 16-threaded NCBI-BLASTX. Furthermore, H-BLAST is 1.5-4 times faster than GPU-BLAST. Availability and Implementation: https://github.com/Yeyke/H-BLAST.git. Contact: yux06@syr.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Association of APEX1 and OGG1 gene polymorphisms with breast cancer risk among Han women in the Gansu Province of China.

BACKGROUND: Genetic variations in key DNA repair genes may influence DNA repair capacity, DNA damage and breast carcinogenesis. The current study aimed to estimate the association of APEX1 and OGG1 polymorphisms with the risk of breast cancer development. METHODS: A total of 518 patients with histopathologically confirmed breast cancer and 921 region- and age-matched cancer-free controls were genotyped for the APEX1 polymorphisms rs3136817 and rs1130409 and the OGG1 polymorphisms rs1052133 and rs2072668 using a QuantStudio™ 12 K Flex Real-Time PCR System. RESULTS: The rs3136817 heterozygous TC genotype along with the rs3136817 dominant model (TC + CC) was strongly associated with breast cancer susceptibility (odds ratio [OR] = 0.670, 95% confidence interval [95% CI]: 0.513 - 0.873, P = 0.003; OR = 0.682, 95% CI: 0.526 - 0.883, P = 0.004, respectively). No significant associations were observed among rs1130409, rs1052133, rs2072668 and breast cancer risk. Furthermore, an allele combination analysis revealed that APEX1 haplotypes containing C-T (alleles rs3136817 and rs1130409) conferred a significantly lower risk (corrected P < 0.001). CONCLUSION: This research is the latest report showing that an APEX1 rs3136817 heterozygous genotype may have a positive influence on DNA repair capacity in patients with breast cancer and thus may have a potential protective effect for Chinese Han women.

Adaptive polarization-difference transient imaging for depth estimation in scattering media.

Introducing polarization into transient imaging improves depth estimation in participating media, by discriminating reflective from scattered light transport and calculating depth from the former component only. Previous works have leveraged this approach under the assumption of uniform polarization properties. However, the orientation and intensity of polarization inside scattering media is nonuniform, both in the spatial and temporal domains. As a result of this simplifying assumption, the accuracy of the estimated depth worsens significantly as the optical thickness of the medium increases. In this Letter, we introduce a novel adaptive polarization-difference method for transient imaging, taking into account the nonuniform nature of polarization in scattering media. Our results demonstrate a superior performance for impulse-based transient imaging over previous unpolarized or uniform approaches.

The crucial role of SEMA3F in suppressing the progression of oral squamous cell carcinoma.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common types of malignancy. Semaphorin 3F (SEMA3F) is highly conserved but present at a lower level in various cancers than in healthy tissues. While it has been reported that SEMA3F is involved in cancer cell proliferation, migration and invasion, its function in OSCC remains unknown. METHODS: The expression of SEMA3F in OSCC tissues and OSCC-derived cells was analyzed using qRT-PCR and western blotting. Using SAS and HSC2 cells, we also monitored the effect of SEMA3F on OSCC cell proliferation, migration and invasion using MTT, colony formation and transwell assays. The function of SEMA3F in OSCC tumor formation was also assessed in vivo. RESULTS: SEMA3F was significantly downregulated in OSCC tissues and OSCC-derived cells. SEMA3F shows growth inhibitory activity in SAS and HSC2 cells and may act as a tumor suppressor. It can inhibit the migration and invasion potential of OSCC cells. Our results also demonstrate that SEMA3F can suppress the growth of OSCC cells in vivo. CONCLUSIONS: This study revealed that SEMA3F plays a role as a tumor suppressor in OSCC cell proliferation, migration and invasion. Our finding provides new insight into the progression of OSCC. Therapeutically, SEMA3F has some potential as a target for OSCC treatment, given sufficient future research.

High speed BLASTN: an accelerated MegaBLAST search tool.

Sequence alignment is a long standing problem in bioinformatics. The Basic Local Alignment Search Tool (BLAST) is one of the most popular and fundamental alignment tools. The explosive growth of biological sequences calls for speedup of sequence alignment tools such as BLAST. To this end, we develop high speed BLASTN (HS-BLASTN), a parallel and fast nucleotide database search tool that accelerates MegaBLAST--the default module of NCBI-BLASTN. HS-BLASTN builds a new lookup table using the FMD-index of the database and employs an accurate and effective seeding method to find short stretches of identities (called seeds) between the query and the database. HS-BLASTN produces the same alignment results as MegaBLAST and its computational speed is much faster than MegaBLAST. Specifically, our experiments conducted on a 12-core server show that HS-BLASTN can be 22 times faster than MegaBLAST and exhibits better parallel performance than MegaBLAST. HS-BLASTN is written in C++ and the related source code is available at https://github.com/chenying2016/queries under the GPLv3 license.

Scattering robust 3D reconstruction via polarized transient imaging.

Reconstructing 3D structure of scenes in the scattering medium is a challenging task with great research value. Existing techniques often impose strong assumptions on the scattering behaviors and are of limited performance. Recently, a low-cost transient imaging system has provided a feasible way to resolve the scene depth, by detecting the reflection instant on the time profile of a surface point. However, in cases with scattering medium, the rays are both reflected and scattered during transmission, and the depth calculated from the time profile largely deviates from the true value. To handle this problem, we used the different polarization behaviors of the reflection and scattering components, and introduced active polarization to separate the reflection component to estimate the scattering robust depth. Our experiments have demonstrated that our approach can accurately reconstruct the 3D structure underlying the scattering medium.

EGb761 attenuates depressive-like behaviours induced by long-term light deprivation in C57BL/6J mice through inhibition of NF-κB-IL-6 signalling pathway.

Our previous investigation found that Ginkgo extract EGb761 could attenuate the depressive-like behaviours induced by a single injection of lipopolysaccharide in mice. However, it has not been investigated whether EGb761 is effective on depressive-like behaviours induced by long-term light deprivation and whether its effects are associated with the inhibition of NF-κB-IL-6 signalling pathway. In this study, three groups (vehicle group, EGb761 low-dose group, and EGb761 high-dose group) of C57BL/6J male mice were exposed to constant darkness for four weeks. The control mice remained on a 12 : 12 light-dark cycle. Depressive-like behaviours were evaluated by tail suspension test (TST), forced swim test (FST), and sucrose preference test (SPT). Spontaneous locomotor activity was evaluated by open field test (OFT). Levels of IL-6, IL-6 mRNA, NF-κB p65, phospho-NF-κB p65, IκBα, and phospho-IκBα were measured using Elisa, western blotting, or PCR assays. NF-κB p65 DNA binding activity was evaluated using Chemi Transcription Factor Assay Kit. Results showed long-term light deprivation prolonged the immobile time in TST and FST, shortened the latency to immobility in FST, reduced spontaneous locomotor activity in OFT, decreased sucrose preference in SPT, and increased levels of IL-6, IL-6 mRNA, NF-κB p65, phospho-NF-κB p65, and phospho-IκBα in hippocampal tissue. EGb761 dose-dependently reversed the changes of the above parameters induced by long-term light deprivation, without affecting spontaneous locomotor activity. We conclude that EGb761 could attenuate the depressive-like behaviours and inhibit the NF-κB-IL-6 signalling pathway in a light-deprivation-induced mouse model of depression.

Peroxiredoxin 1 protects the pea aphid Acyrthosiphon pisum from oxidative stress induced by Micrococcus luteus infection.

Reactive oxygen species (ROSs) are generated in organisms in response to infections caused by invading microbes. However, excessive ROSs will inflict oxidative damage on the host. Peroxiredoxins (Prxs) are antioxidative enzymes that may eliminate ROSs efficiently. In this study, ApPrx1 from the pea aphid Acyrthosiphon pisum was cloned, and its function was investigated in vitro and in vivo. In the presence of DTT, recombinant ApPrx1 protein from Escherichia coli showed antioxidative activity by eliminating H2O2 effectively. The H2O2 levels were significantly higher in Micrococcus luteus-infected aphids than in uninfected aphids, and ApPrx1 expression was remarkably up-regulated when the aphids were infected with M. luteus or injected with H2O2. When ApPrx1 expression was reduced by dsRNA injection, the survival of the aphids decreased significantly after M. luteus infection. Knockdown of ApPrx1 decreased M. luteus loads inside the aphids 48h post-infection. While under infection conditions, the H2O2 levels were much higher in ApPrx1 knockdown aphids than in dsGFP-injected aphids, indicating that the decreased survival of the aphids was caused by increased oxidative stress. Taken together, our results reveal that ApPrx1 plays a protective role in oxidative stress caused by bacterial infection.

The effects of EGb761 on lipopolysaccharide-induced depressive-like behaviour in C57BL/6J mice.

There is an increasing body of evidence for the involvement of inflammation and brain-derived neurotrophic factor (BDNF) in depression. Ginkgo extract EGb761 possesses anti-inflammatory, anti-oxidative, anti-arteriosclerosis, and neuroprotective activities. But the effect of EGb761 on lipopolysaccharide (LPS)-induced depressive-like behaviours has not been investigated. The present study mainly aimed to examine the antidepressant-like activities of Ginkgo extract EGb761 in mice after lipopolysaccharide administration. C57BL/6J male mice were pretreated with EGb761 or vehicle for 10 days. Then, a single dose of lipopolysaccharide was intraperitoneally administrated to mice to induce depressive-like behaviour. Forced swim test (FST), tail suspension test (TST), and sucrose preference test were performed to evaluate the depressive-like behaviours of the mice. Locomotor activity was examined by open field test. Levels of brain-derived neurotrophic factor, TNF-α, IL-1ß, IL-6, IL-17A, and IL-10 in hippocampus tissue homogenate were measured using ELISA kits. We found that LPS administration induced significant depressive-like behaviours, higher levels of tumour necrosis factor α (TNF-α), interleukin (IL) 1ß, IL-6, and IL-17A, but lower levels of BDNF and IL-10 in hippocampus tissue homogenate of the mice from the vehicle group compared to the control mice. Pretreatment with middle dose (100 mg/kg/day) and high dose (150 mg/kg/day) of EGb761 significantly attenuated depressive-like behaviours without affecting spontaneous locomotor activity, and inhibited the changes of hippocampal cytokines and BDNF induced by LPS administration. We conclude that EGb761 has antidepressant-like activities in mice with LPS-induced depressive-like behaviours.

Efficient Dynamic Correspondence Network.

We tackle the problem of establishing dense correspondences between a pair of images in an efficient way. Most existing dense matching methods use 4D convolutions to filter incorrect matches, but 4D convolutions are highly inefficient due to their quadratic complexity. Besides, these methods learn features with fixed convolutions which cannot make learnt features robust to different challenge scenarios. To deal with these issues, we propose an Efficient Dynamic Correspondence Network (EDCNet) by jointly equipping pre-separate convolution (Psconv) and dynamic convolution (Dyconv) to establish dense correspondences in a coarse-to-fine manner. The proposed EDCNet enjoys several merits. First, two well-designed modules including a neighbourhood aggregation (NA) module and a dynamic feature learning (DFL) module are combined elegantly in the coarse-to-fine architecture, which is efficient and effective to establish both reliable and accurate correspondences. Second, the proposed NA module maintains linear complexity, showing its high efficiency. And our proposed DFL module has better flexibility to learn features robust to different challenges. Extensive experimental results show that our algorithm performs favorably against state-of-the-art methods on three challenging datasets including HPatches, Aachen Day-Night and InLoc.

Adaptive Prototype Learning for Weakly-supervised Temporal Action Localization.

Weakly-supervised Temporal Action Localization (WTAL) aims to localize action instances with only video-level labels during training, where two primary issues are localization incompleteness and background interference. To relieve these two issues, recent methods adopt an attention mechanism to activate action instances and simultaneously suppress background ones, which have achieved remarkable progress. Nevertheless, we argue that these two issues have not been well resolved yet. On the one hand, the attention mechanism adopts fixed weights for different videos, which are incapable of handling the diversity of different videos, thus deficient in addressing the problem of localization incompleteness. On the other hand, previous methods only focus on learning the foreground attention and the attention weights usually suffer from ambiguity, resulting in difficulty of suppressing background interference. To deal with the above issues, in this paper we propose an Adaptive Prototype Learning (APL) method for WTAL, which includes two key designs: (1) an Adaptive Transformer Network (ATN) to explicitly model background and learn video-adaptive prototypes for each specific video, (2) an OT-based Collaborative (OTC) training strategy to guide the learning of prototypes and remove the ambiguity of the foreground-background separation by introducing an Optimal Transport (OT) algorithm into the collaborative training scheme between RGB and FLOW streams. These two key designs can work together to learn video-adaptive prototypes and solve the above two issues, achieving robust localization. Extensive experimental results on two standard benchmarks (THUMOS14 and ActivityNet) demonstrate that our proposed APL performs favorably against state-of-the-art methods.

Abrupt shift in the organic matter input to sediments in Lake Liangzi, a typical macrophyte-dominated shallow lake in Eastern China, and its response to anthropogenic impacts.

Understanding the historical variations in organic matter (OM) input to lake sediments and the possible mechanisms regulating this phenomenon is important for studying carbon cycling and burial in lake systems; however, this topic remains poorly addressed for macrophyte-dominated lakes. To bridge these gaps, we analyzed bulk OM and molecular geochemical proxies in a dated sediment core from Lake Liangzi, a typical submerged macrophyte-dominated lake in East China, to infer changes in OM input to sediments over the past 169 years due to the intensification of human activities in the catchment. A relatively primitive OM input pattern was observed in ca. 1841-1965, during which the lowest hydrogen index (HI), short-chain n-alkane abundance, and n-C17/n-C16 alkane indicated minimal input from phytoplankton, whereas the high Paq (proxy of aquatic macrophyte input) and long-chain n-alkane abundance suggested dominant and subordinate inputs from submerged and emergent macrophytes, respectively. OM input transitioned during ca. 1965-1993, with the highest Paq and lowest long-chain n-alkane abundance, indicating an increase of submerged macrophyte input and concurrent decline of emergent macrophyte input, probably caused by hydrological regulation practices and land reclamation in the 1960s, respectively. A further shift in OM input was observed since ca. 1993, characterized by the beginning of an increase in phytoplankton input, as indicated by the greater HI, short-chain n-alkane abundance, and n-C17/n-C16 alkane in sediments. Moreover, a lower Paq and higher abundance of long-chain n-alkanes indicated a decline in input from submerged macrophytes and an elevated input from terrestrial plants. The increase in αß-hopane abundance and homohopane index value indicated that petroleum-sourced OM was first introduced into the sediments. The causes of these OM input changes included nutrient influx associated with domestic and industrial discharge, aquaculture within the lake, and widespread deforestation and land clearance in the catchment.

Environment change recorded by lake sediment magnetism in the Songnen Plain, northeastern China.

Stratigraphic determination of the Anthropocene, the "Great Acceleration", requires more key globally synchronous stratigraphic markers which reflect the significant human impacts on Earth. Lacustrine sediment magnetic characteristics are of considerable importance in Anthropocene studies because they respond sensitively to environmental changes. There are many shallow lakes in the Songnen Plain (SNP) in northeast China, which are conducive to obtaining Anthropocene sedimentary records. This study explored magnetic materials in lacustrine sediment responses to environmental evolution impact by human activities on the SNP by measuring magnetic parameters in dated sediment cores from 5 shallow lakes in the SNP, northeast China. The results revealed that detrital magnetite and hematite dominated the magnetic minerals in lake sediments. The persistently low value of magnetic susceptibility might be caused by the low content of natural ferrimagnetic minerals in Quaternary fluvial deposits and humus-rich black soil in the catchment, and the loss of magnetic materials during the transport process. In Lake Longjiangpao (LJP), the magnetic concentrations significantly responded to regional precipitation, whereas in the other 4 lakes in the center of the plain, the parameters tended to reflect complex human activities. However, the isothermal remanent magnetization ratio (S-300), which is indicative of the ratio of hematite to magnetite, exhibited relatively consistent variations in the 5 studied lakes. After 1950, the "Great Acceleration", the increase of S-300 indicated a relative proportion of magnetite in sediments, and was positively correlated with the growth of human-activity proxies (Gross Domestic Product (GDP) and population). Thus, this proxy can be regarded as a useful indicator of the beginning of the Anthropocene in the studied region. This study provides new insights into the estimation of local human activities in history and possible evidence for the global definition of the Anthropocene.

Prototype-Augmented Self-Supervised Generative Network for Generalized Zero-Shot Learning.

Generalized Zero-Shot Learning (GZSL) aims at recognizing images from both seen and unseen classes by constructing correspondences between visual images and semantic embedding. However, existing methods suffer from a strong bias problem, where unseen images in the target domain tend to be recognized as seen classes in the source domain. To address this issue, we propose a Prototype-augmented Self-supervised Generative Network by integrating self-supervised learning and prototype learning into a feature generating model for GZSL. The proposed model enjoys several advantages. First, we propose a Self-supervised Learning Module to exploit inter-domain relationships, where we introduce anchors as a bridge between seen and unseen categories. In the shared space, we pull the distribution of the target domain away from the source domain and obtain domain-aware features. To our best knowledge, this is the first work to introduce self-supervised learning into GZSL as learning guidance. Second, a Prototype Enhancing Module is proposed to utilize class prototypes to model reliable target domain distribution in finer granularity. In this module, a Prototype Alignment mechanism and a Prototype Dispersion mechanism are combined to guide the generation of better target class features with intra-class compactness and inter-class separability. Extensive experimental results on five standard benchmarks demonstrate that our model performs favorably against state-of-the-art GZSL methods.