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Shaoqiu Zhang,1,* Qun Zhang,2,* Jian Wang,1,3,* Yifan Pan,4 Zhiyi Zhang,5 Yu Geng,1 Bei Jia,1 Bing Tian,2 Yali Xiong,1 Xiaomin Yan,1 Jie Li,1,3– 5 Huali Wang,6 Rui Huang,1,3– 5 Chao Wu1,3– 5 1Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 2Department of Infectious Diseases, Affiliated Zhongda Hospital of Southeast University, Nanjing, Jiangsu, People’s Republic of China; 3Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 5Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 6Department of General Practice, Nanjing Second Hospital, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chao Wu; Rui Huang, Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing, Jiangsu, 210008, People’s Republic of China, Tel +86-25-83105890, Fax +86-25-83307115, Email dr.wu@nju.edu.cn; doctor_hr@126.comBackground: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality rate. This study aimed to investigate the association of red blood cell distribution width (RDW) and mortality risk in hospitalized SFTS patients.Methods: Clinical data of SFTS patients was retrospectively collected from three hospitals between October 2010 and August 2022. Cox proportional hazards model was used to identity the risk factors for fatal outcome. The predictiv

Zhengyi Lyu,1,* Qiongying Shen,1,* Shuxin Tian,1,* Liyan Gong,2 Haizhou Lou,3 Guanai Bao,2 Zhuoxuan Wu,3 Chao Lu,2 Weiping Zhang,4 Rui Huang,5 Conghua Ji,6 Siyi Zheng,1 Wei Pan,1 Yinyin Ying,4 Jianwei Jin,4 Yi Liang4 1The Third Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 2Zhejiang Cancer Hospital, Hangzhou, Zhejiang, People’s Republic of China; 3Department of Medical Oncology, Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, People’s Republic of China; 4Department of Acupuncture, the Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China; 5Department of Acupuncture and Tuina, Wenzhou Central Hospital, Wenzhou, Zhejiang, People’s Republic of China; 6Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yi Liang, Department of Acupuncture, the Third Affiliated Hospital of Zhejiang Chinese Medical University, 219 Moganshan Road, Hangzhou City, Zhejiang Province, 310053, People’s Republic of China, Email liangyiwww@126.comBackground: Transcutaneous Electrical Acupoint Stimulation (TEAS) therapy opens up the possibility for individuals with Cancer-induced bone pain (CIBP) to receive a home-based, patient-controlled approach to pain management. The aim of this study is designed to evaluate the efficacy of patient-controlled TEAS (PC-TEAS) for relieving CIBP in patients with non-small cell lung cancer (NSCLC).Methods/Design: This is a study protocol for a prospective, triple-blind, randomized controlled trial. We anticipate enrolling 188 participants with NSCLC bone metastases who are also using potent opioid analgesics from 4 Chinese medical centers. These participants will be randomly assigned in a 1:1 ratio to either the true PC-TEAS or the sham PC-TEAS group. All participants will receive standard adjuvant onco

The activation of sulfite [S(IV)] by transition metals, a new generation of advanced oxidation processes, has been widely studied for water purification. However, the application of this process to oxidize and remove arsenite [As(III)] from water through Fe-based S(IV) activation and the associated mechanisms are not fully understood. In particular, rapid removal of As(III) and secondary metal contamination have presented challenges. Herein, we develop a novel sea urchin-like magnetic Fe-Mn bimetallic oxides (FeMnO)-activated S(IV) process to address these issues. Under neutral pH, the FeMnO/S(IV) system achieved a 99.2 % removal of As(III) within only 10 min with residual arsenic concentration below 10 µg/L, and the removed As(III) was fully oxidized to arsenate [As(V)]. Additionally, FeMnO was recyclable and capable of treating actual arsenic-contaminated water. Furthermore, the oxidation mechanism of non-radical active trivalent manganese [Mn(III)] was discovered during the reaction between the FeMnO/S(IV) system and As(III). The FeMnO catalyst activated S(IV) to generate oxysulfur radicals (i.e., SO5•–, SO4•– and SO3•–), but they were not the primary oxidizing species for As(III). Instead, As(III) oxidation was mainly attributed to the active Mn(III) generated by the electron transfer between the FeMnO catalyst and SO5•– radicals. The discovery of active Mn(III) species in this work may provide a new avenue for developing novel Fe-Mn-type adsorbents to purify arsenic-contaminated water.

Research on psychic distance in tourism studies has mainly focused on perceived psychic distance, while little attention has been paid to psychic distance stimuli. Applying the Cultural-Administrative-Geographic-Economic (CAGE) distance framework, this study employs a gravity model framework to investigate the relationship between psychic distance stimuli and international tourist flows and the moderating role of Internet popularity in such a relationship based on information asymmetry theory. Further, this study investigates the effects of psychic distance stimuli along the cultural, administrative, geographic, and economic dimensions. The empirical analysis is based on a panel dataset of bilateral tourist flows between 56 countries from 2006 to 2019. The results indicate that psychic distance stimuli negatively impact international tourist flows, but the negative effect decreases with increasing Internet penetration rate in countries of origin. The four distance dimensions exert negative effects on bilateral tourist flows. This study also provides implications for alleviating the impact of psychic distance stimuli between countries derived by COVID-19 on international tourism in the post-pandemic era.

Xin Chen,1– 3,* Xing Zhong,1,4,* Dan Luo,1– 3,* Yuhua Lei,1– 3 Rui Huang1– 3 1Cardiovascular Disease Center, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei Province, People’s Republic of China; 2Hubei Selenium and Human Health Institute, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshii, Hubei Province, People’s Republic of China; 3Hubei Provincial Key Laboratory of Selenium Resources and Bio applications, Enshii, Hubei Province, People’s Republic of China; 4Department of Medicine, Hubei Minzu University, Enshi, Hubei Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yuhua Lei; Rui Huang, Email yuhualei0319@163.com; henry0923@whu.edu.cnBackground: Heart failure (HF) is a chronic disease with a poor prognosis, making it extremely important to assess the prognosis of patients with HF for accurate treatment. Secreted modular calcium-binding protein 2 (SMOC2) is a cysteine-rich acidic secreted protein that plays a pathophysiological role in many diseases, including regulation of vascular growth factor activity. It has previously been found that SMOC2 plays an essential role in cardiac fibrosis in our previous preclinical study, but whether it can be used as a clinical marker in heart failure patients remains unclear. The purpose of this research was to evaluate the correlation between plasma levels of SMOC2 and the prognosis for individuals with HF.Methods: HF patients diagnosed with ischemic cardiomyopathy were enrolled from January to December 2021. Baseline plasma levels of SMOC2 were measured after demographic and clinical features were collected. Linear and nonlinear multivariate Cox regression models were used to determine the association between plasma SMOC2 and patient outcomes during follow-up. All analysis was performed using SPSS, EmpowerStats, and R software.Results: The study included 188 patients, and t

Semantic Scene Completion (SSC) aims to jointly infer semantics and occupancies of 3D scenes. Truncated Signed Distance Function (TSDF), a 3D encoding of depth, has been a common input for SSC. Furthermore, RGB-TSDF fusion, seems promising since these two modalities provide color and geometry information, respectively. Nevertheless, RGB-TSDF fusion has been considered nontrivial and commonly-used naive addition will result in inconsistent results. We argue that the inconsistency comes from the sparsity of RGB features upon projecting into 3D space, while TSDF features are dense, leading to imbalanced feature maps when summed up. To address this RGB-TSDF distribution difference, we propose a two-stage network with a 3D RGB feature completion module that completes RGB features with meaningful values for occluded areas. Moreover, we propose an effective classwise entropy loss function to punish inconsistency. Extensive experiments on public datasets verify that our method achieves state-of-the-art performance among methods that do not adopt extra data.

Modeling count-valued time series has been receiving increasing attention since count time series naturally arise in physical and social domains. Poisson gamma dynamical systems (PGDSs) are newly-developed methods, which can well capture the expressive latent transition structure and bursty dynamics behind count sequences. In particular, PGDSs demonstrate superior performance in terms of data imputation and prediction, compared with canonical linear dynamical system (LDS) based methods. Despite these advantages, PGDS cannot capture the heterogeneous overdispersed behaviours of the underlying dynamic processes. To mitigate this defect, we propose a negative-binomial-randomized gamma Markov process, which not only significantly improves the predictive performance of the proposed dynamical system, but also facilitates the fast convergence of the inference algorithm. Moreover, we develop methods to estimate both factor-structured and graph-structured transition dynamics, which enable us to infer more explainable latent structure, compared with PGDSs. Finally, we demonstrate the explainable latent structure learned by the proposed method, and show its superior performance in imputing missing data and forecasting future observations, compared with the related models.

Multiscale convolutional neural network (CNN) has demonstrated remarkable capabilities in solving various vision problems. However, fusing features of different scales alwaysresults in large model sizes, impeding the application of multiscale CNNs in RGB-D saliency detection. In this paper, we propose a customized feature fusion module, called Saliency Enhanced Feature Fusion (SEFF), for RGB-D saliency detection. SEFF utilizes saliency maps of the neighboring scales to enhance the necessary features for fusing, resulting in more representative fused features. Our multiscale RGB-D saliency detector uses SEFF and processes images with three different scales. SEFF is used to fuse the features of RGB and depth images, as well as the features of decoders at different scales. Extensive experiments on five benchmark datasets have demonstrated the superiority of our method over ten SOTA saliency detectors., Comment: Accpeted by 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024)

Backdoor attack aims to deceive a victim model when facing backdoor instances while maintaining its performance on benign data. Current methods use manual patterns or special perturbations as triggers, while they often overlook the robustness against data corruption, making backdoor attacks easy to defend in practice. To address this issue, we propose a novel backdoor attack method named Spy-Watermark, which remains effective when facing data collapse and backdoor defense. Therein, we introduce a learnable watermark embedded in the latent domain of images, serving as the trigger. Then, we search for a watermark that can withstand collapse during image decoding, cooperating with several anti-collapse operations to further enhance the resilience of our trigger against data corruption. Extensive experiments are conducted on CIFAR10, GTSRB, and ImageNet datasets, demonstrating that Spy-Watermark overtakes ten state-of-the-art methods in terms of robustness and stealthiness., Comment: Accepted by ICASSP2024

Constructing vectorized high-definition maps from surround-view cameras has garnered significant attention in recent years. However, the commonly employed multi-stage sequential workflow in prevailing approaches often leads to the loss of early-stage information, particularly in perspective-view features. Usually, such loss is observed as an instance missing or shape mismatching in the final birds-eye-view predictions. To address this concern, we propose a novel approach, namely \textbf{HybriMap}, which effectively exploits clues from hybrid features to ensure the delivery of valuable information. Specifically, we design the Dual Enhancement Module, to enable both explicit integration and implicit modification under the guidance of hybrid features. Additionally, the perspective keypoints are utilized as supervision, further directing the feature enhancement process. Extensive experiments conducted on existing benchmarks have demonstrated the state-of-the-art performance of our proposed approach.

The Probability Ranking Principle (PRP) has been considered as the foundational standard in the design of information retrieval (IR) systems. The principle requires an IR module's returned list of results to be ranked with respect to the underlying user interests, so as to maximize the results' utility. Nevertheless, we point out that it is inappropriate to indiscriminately apply PRP through every stage of a contemporary IR system. Such systems contain multiple stages (e.g., retrieval, pre-ranking, ranking, and re-ranking stages, as examined in this paper). The \emph{selection bias} inherent in the model of each stage significantly influences the results that are ultimately presented to users. To address this issue, we propose an improved ranking principle for multi-stage systems, namely the Generalized Probability Ranking Principle (GPRP), to emphasize both the selection bias in each stage of the system pipeline as well as the underlying interest of users. We realize GPRP via a unified algorithmic framework named Full Stage Learning to Rank. Our core idea is to first estimate the selection bias in the subsequent stages and then learn a ranking model that best complies with the downstream modules' selection bias so as to deliver its top ranked results to the final ranked list in the system's output. We performed extensive experiment evaluations of our developed Full Stage Learning to Rank solution, using both simulations and online A/B tests in one of the leading short-video recommendation platforms. The algorithm is proved to be effective in both retrieval and ranking stages. Since deployed, the algorithm has brought consistent and significant performance gain to the platform., Comment: Accepted by WWW 2024

Click-point-based interactive segmentation has received widespread attention due to its efficiency. However, it's hard for existing algorithms to obtain precise and robust responses after multiple clicks. In this case, the segmentation results tend to have little change or are even worse than before. To improve the robustness of the response, we propose a structured click intent model based on graph neural networks, which adaptively obtains graph nodes via the global similarity of user-clicked Transformer tokens. Then the graph nodes will be aggregated to obtain structured interaction features. Finally, the dual cross-attention will be used to inject structured interaction features into vision Transformer features, thereby enhancing the control of clicks over segmentation results. Extensive experiments demonstrated the proposed algorithm can serve as a general structure in improving Transformer-based interactive segmenta?tion performance. The code and data will be released at https://github.com/hahamyt/scc., Comment: 10 pages, 6 figures, submitted to NeurIPS 2024

Despite growing recognition of the importance of social, economic, and political contexts for population health and health inequalities, research on pain disparities relies heavily on individual-level data, while neglecting overarching macrolevel factors such as state-level policies and characteristics. Focusing on moderate or severe arthritis-attributable joint pain-a common form of pain that considerably harms individuals quality of life-we (1) compared joint pain prevalence across US states; (2) estimated educational disparities in joint pain across states; and (3) assessed whether state sociopolitical contexts help explain these 2 forms of cross-state variation. We linked individual-level data on 407,938 adults (ages 25-80 years) from the 2017 Behavioral Risk Factor Surveillance System with state-level data on 6 measures (eg, the Supplemental Nutrition Assistance Program [SNAP], Earned Income Tax Credit, Gini index, and social cohesion index). We conducted multilevel logistic regressions to identify predictors of joint pain and inequalities therein. Prevalence of joint pain varies strikingly across US states: the age-adjusted prevalence ranges from 6.9% in Minnesota to 23.1% in West Virginia. Educational gradients in joint pain exist in all states but vary substantially in magnitude, primarily due to variation in pain prevalence among the least educated. At all education levels, residents of states with greater educational disparities in pain are at a substantially higher risk of pain than peers in states with lower educational disparities. More generous SNAP programs (odds ratio [OR] = 0.925; 95% confidence interval [CI]: 0.963-0.957) and higher social cohesion (OR = 0.819; 95% CI: 0.748-0.896) predict lower overall pain prevalence, and state-level Gini predicts higher pain disparities by education.

The use of finite entanglement scaling with matrix product states (MPS) has become a crucial tool for studying 1+1d critical lattice theories, especially those with emergent conformal symmetry. We argue that finite entanglement introduces a relevant deformation in the critical theory. As a result, the bipartite entanglement Hamiltonian defined from the MPS can be understood as a boundary conformal field theory with a physical and an entanglement boundary. We are able to exploit the symmetry properties of the MPS to engineer the physical conformal boundary condition. The entanglement boundary, on the other hand, is related to the concrete lattice model and remains invariant under this relevant perturbation. Using critical lattice models described by the Ising, Potts, and free compact boson CFTs, we illustrate the influence of the symmetry and the relevant deformation on the conformal boundaries in the entanglement spectrum., Comment: 6+7 pages,4+7 figures; add nn RVB iPEPS result

Suling Jiang,1,* Jian Wang,2,3,* Zhiyi Zhang,4,* Jie Zhan,1 Ruifei Xue,1 Yuanwang Qiu,5 Li Zhu,6 Shaoqiu Zhang,2 Yifan Pan,1 Xiaomin Yan,2 Yuxin Chen,3,7 Jie Li,1– 4 Xingxiang Liu,8 Chuanwu Zhu,6 Rui Huang,1– 4 Chao Wu1– 4 1Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 2Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 3Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 4Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 5Department of Infectious Diseases, The Fifth People’s Hospital of Wuxi, Wuxi, Jiangsu, People’s Republic of China; 6Department of Infectious Diseases, The Affiliated Infectious Diseases Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China; 7Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China; 8Department of Clinical Laboratory, Huai’an No. 4 People’s Hospital, Huai’an, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chao Wu, Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing, Jiangsu, 210008, People’s Republic of China, Tel +86-25-83105890, Fax +86-25-83307115, Email dr.wu@nju.edu.cn Rui Huang, Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, No. 321 Zhongshan Road, Nanjing, Jiangsu, 210008, People’s Republic of China, Ema

Satellite observations covering the last four decades reveal an ocean warming pattern resembling the negative phase of the Pacific Decadal Oscillation. This pattern has therefore been widely interpreted as a manifestation of natural climate variability. Here, we re-examine the observed warming pattern and find that the predominant warming over the subtropical oceans, while mild warming or even cooling over the subpolar ocean, is dynamically consistent with the convergence and divergence of surface water. By comparison of observations, paleo-reconstructions, and model simulations, we propose that the observed warming pattern is likely a short-term transient response to the increased CO2 forcing, which only emerges during the early stage of anthropogenic warming. On centennial to millennial timescales, the subpolar ocean warming is expected to exceed the temporally dominant warming of the subtropical ocean. This delayed but amplified subpolar ocean warming has the potential to reshape the ocean-atmosphere circulation and threaten the stability of marine-terminating ice sheets.

We present the results for the complete next-to-leading order electroweak corrections to $pp \to HH$ at the Large Hadron Collider, focusing on the dominant gluon-gluon fusion process. While the corrections at the total cross-section level are approximately $-4\%$, those near the energy of $HH$ production threshold exceed $+15\%$, and corrections at the high-energy region are around $-10\%$, leading to a shape distortion for the differential distributions. Our findings substantially diminish the theoretical uncertainties associated with this pivotal process, providing valuable input for understanding the shape of the Higgs boson potential upon comparison with experimental measurements., Comment: 7 pages, 4 figures, references added

Rui Huang,&ast; Yi-Ting Zhang,&ast; Yu Lin, Ru-Li Pang, Zhi Yang, Wei-Hua Zhao Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wei-Hua Zhao, Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Shuang-Yong Road 6, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China, Tel +86-771-5356746, Fax +86-771-5352681, Email zhaowh21@163.comObjective: The purpose of our study was to investigate the clinical characteristics, molecular biological characteristics and prognosis of acute myeloid leukemia (AML) patients with protein tyrosine phosphatase non-receptor type 11 (PTPN11) gene mutation.Methods: The clinical data of 30 newly diagnosed adult AML patients with PTPN11 gene mutation were analyzed retrospectively. Kaplan-Meier and Cox proportional risk regression model were examined for prognostic analysis and prognostic factor screening.Results: High-frequency mutation sites of PTPN11 gene are located in exon 3 of chromosome 12, which are D61 and A72 (16.7%), followed by E76 (13.3%). The median variant allele frequency (VAF) of PTPN11 mutant gene is 18.4%. The patients were divided into two groups according to PTPN11 VAF 35.3% (upper quartile). We observed that the peripheral blood leukocyte count in patients with VAF ≥ 35.3% was significantly higher than patients with VAF < 35.3% (p = 0.019) and also closely related to M5 (p = 0.016) and internal tandem duplication (ITD) of FMS-like tyrosine kinase 3 (FLT3) (FLT3-ITD) mutation (p = 0.048). Taking PTPN11 VAF 20% and 35.3% as the cutoff value, the patients were divided into two groups, and the overall survival and event-free survival (EFS) of the two groups were not significant. Multivariate analysis of Cox risk ratio model showed that white blood cell count and Eastern Coopera

Xing Zhong,1,&ast; Rui Huang,2,&ast; Xin Chen,2 Yuhua Lei2 1Cardiovascular Disease Center, Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Hubei Minzu University, Enshi, People’s Republic of China; 2Cardiovascular Disease Center, Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuhua Lei, Email yuhualei0319@163.comBackground: Engeletin (ENG) is a natural flavonoid compound known for its diverse physiological and pharmacological effects, such as anti-inflammatory, antioxidant, and immunomodulatory properties. It has garnered significant attention as a promising candidate for drug development.Objective: This article aims to comprehensively review the clinical application, pharmacological action, and potential mechanisms of ENG, while exploring its prospects in clinical pharmacology.Methods: We conducted a systematic search of PubMed, Science Direct, Google Scholar, Web of Science, Scopus, and MEDLINE for a thorough review of high-quality articles on the source, extraction, and application of ENG, or the primary active ingredient for improving bodily injuries.Results: ENG exhibits significant potential in treating a variety of diseases across different systems, attributed to its anti-inflammatory, antioxidant, anti-tumor, and metabolic regulatory activities. These effects are linked to direct or indirect interactions with multiple pathways involving key molecules upstream and downstream.Conclusion: While ENG shows promise, its development requires further exploration. Future studies should focus on elucidating its mechanisms of action, identifying targets through clinical studies, and optimizing compounds for drug development. These research directions are crucial for advancing the development and application of flavonoids. This review underscores the significant research potential of ENG, paving the way for its application

The Hot Universe Baryon Surveyor (HUBS) is a proposed space-based X-ray telescope for detecting X-ray emissions from the hot gas content in our universe. With its unprecedented spatially-resolved high-resolution spectroscopy and large field of view, the HUBS mission will be uniquely qualified to measure the physical and chemical properties of the hot gas in the interstellar medium, the circumgalactic medium, the intergalactic medium, and the intracluster medium. These measurements will be valuable for two key scientific goals of HUBS, namely to unravel the AGN and stellar feedback physics that governs the formation and evolution of galaxies, and to probe the baryon budget and multi-phase states from galactic to cosmological scales. In addition to these two goals, the HUBS mission will also help us solve some problems in the fields of galaxy clusters, AGNs, diffuse X-ray backgrounds, supernova remnants, and compact objects. This paper discusses the perspective of advancing these fields using the HUBS telescope., Comment: 52 pages, 22 figures. Accepted for publication in Science China: Physics, Mechanics and Astronomy

We introduce the New-ANGELS program, an XMM-Newton survey of $\sim7.2\rm~deg^2$ area around M 31, which aims to study the X-ray populations in M 31 disk and the X-ray emitting hot gas in the inner halo of M 31 up to 30 kpc. In this first paper, we report the catalogue of 4506 detected X-ray sources, and attempt to cross-identify or roughly classify them. We identify 352 single stars in the foreground, 35 globular clusters and 27 supernova remnants associated with M 31, as well as 62 AGNs, 59 galaxies, and 1 galaxy clusters in the background. We uniquely classify 236 foreground stars and 17 supersoft sources based on their X-ray colors. X-ray binaries (83 LMXBs, 1 HMXBs) are classified based on their X-ray colors and X-ray variabilities. The remaining X-ray sources either have too low S/N to calculate their X-ray colors or do not have a unique classification, so are regarded as unclassified. The X-ray source catalogue is published online. Study of the X-ray source populations and the contribution of X-ray sources in the unresolved X-ray emissions based on this catalogue will be published in companion papers., Comment: 30 pages, 12 figures. Accepted for publication in APJS

We present an X-ray spectrum of the diffuse X-ray background (DXRB) between 1.5 and 120 keV, as measured with the Low-Energy Detector (LE) and the High-Energy Detector (HE) aboard the Insight-HXMT satellite, based on 'blank-sky' observations. LE covers a nominal energy range of 1-15 keV and HE 20-250 keV, but calibration issues and data quality narrowed the energy range for this work. The LE background was directly measured with `blind' detector modules, while the HE background was derived from Earth-occultation data. With the LE data alone, the measured DXRB spectrum can be well described by a power law; fitting the LE and HE data jointly, however, a spectral cut-off must be introduced in the model to account for the measurements above 30 keV. Modelling the combined spectrum with a cut-off power law, the best-fit photon index is 1.40, normalisation $9.57$~$\rm ph~cm^{-2}~s^{-1}~keV^{-1}~sr^{-1} $ (at 1 keV), and cut-off energy 55 keV, after correcting for the effects of the Earth albedo and atmospheric emission (which are significant in the HE band). Based on the best-fit cut-off power law, we derived the spectral energy distribution (SED) of the DXRB. The shape of the SED is in general agreement with the published measurements, but the overall normalization is lower by varying amounts, except for the HEAO-1 result, with which our result is in good agreement., Comment: 9 pages, 14 figures, published in MNRAS

Huimei Bu,1 Rui Huang,1 Shiyu Liang,2 Xia Liao3 1School of Business, Macau University of Science and Technology, Macau, People’s Republic of China; 2School of Economics and Management, Guangzhou Vocational University of Science and Technology, Guangzhou, People’s Republic of China; 3Business School, Guangzhou College of Technology and Business, Guangzhou, People’s Republic of ChinaCorrespondence: Shiyu Liang, School of Economics and Management, Guangzhou Vocational University of Science and Technology, Guangzhou, 510000, People’s Republic of China, Tel +86 13927551241, Email loengsikjyu@outlook.comPurpose: Numerous time-honored brand restaurants are gradually losing their authenticity in the development process. Brand authenticity serves as a symbol of China’s unique culinary culture, and consistency lies at the core of preserving its authenticity. Failure to integrate innovative elements into the original components can potentially erode the brand’s consistent image, leading to a negative impact on perceived authenticity and purchase intention (PI). However, existing research has largely neglected to investigate the influence of consumer perceived brand innovativeness (CPBI) and consumer perceived brand authenticity (CPBA) specifically within the context of time-honored brand restaurants. Additionally, there is a lack of research examining the individual differences of consumers and how these intersect with time-honored brands. Therefore, our research aims to address these research gaps.Methods: The list of Chinese time-honored brands issued by the Ministry of Commerce of China served as the basis for the study’s choice of time-honored restaurant brands. 689 relevant consumers were obtained through convenience sampling within China and the self-report method was adopted for data collection. Using the partial least squares structural equation modeling method and the SmartPLS software, the data was analyzed and the hypotheses were tested.Results: CPBI p

Yinhua Luo,1,&ast; Jinbo Zhao,2,&ast; Xueru Chen,3,&ast; Rui Huang,2 Ling Hou,2 Ke Su,2 Yuhua Lei,2 Yuanhong Li1,2 1Department of Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Shiyan, Hubei Province, 442000, People’s Republic of China; 2Cardiovascular Disease Center, Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Enshi Prefecture, Hubei Province, 445000, People’s Republic of China; 3Department of General Practice, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, 510120, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuanhong Li, Cardiovascular Disease Center, Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Enshi Prefecture, People’s Republic of China, Email shaoyiju75482@163.comBackground: Ischemic cardiomyopathy (ICM) with high mobility and mortality is closely linked to immunology, oxidative stress, inflammatory response and so on. Early diagnosis counts for the effective treatment of ICM. However, there are still no distinctive diagnostic signatures. This research aims to investigate effective signatures and build the diagnostic model for ICM.Methods: The Gene Expression Omnibus was used to retrieve the microarray data of GSE9800 and GSE580, which were obtained from tissue biopsy samples. Differentially expressed genes (DEGs), GO, and KEGG analyses were then carried out on the microarray data. The PPI network was constructed via STRING database.Following that, CIBERSORT techniques in conjunction with the LM22 feature matrix were used to assess the immune infiltration of the samples.The expression of a few chosen genes served as the predictor variable, and the occurrence of ICM served as the responder variable, in the construction of the best subset stepwise regression model.Results: A total of 28 DEGs were found. And according to the G

The zonal flow and volume transport in the Luzon Strait play a crucial role in modulating the circulation, heat and material balance, and biogeochemical processes in the South China Sea (SCS), but the quantitative values remain unclear due to lack of long-term direct observations. Here, this knowledge gap is bridged by analyzing 4-year velocity measurements from a mooring array along 119.9 degrees E. Based on the novel data, the mean value of the upper-layer Luzon Strait transport (i.e., LST_up) is estimated at -4.54 +/- 1.69 Sv. Seasonally, the westward LST_up attains its peak and trough in January and June with values of -6.80 +/- 1.46 Sv and -2.59 +/- 0.76 Sv, respectively. At the interannual time scale, the LST_up was strongest in 2016-2017 but weakest in 2017-2018. Further analysis suggested that local winds and the combination of local winds and upstream Kuroshio transport are likely the dominant modulation mechanisms for its seasonal and interannual variations, respectively. In the middle layer, a quasi-steady cyclonic flow structure is identified and the volume transport is therefore trivial. We further found that seasonal variation of the middle-layer transport is dominated by the eastward flow of this cyclonic structure. Corresponding to the gravest-mode response in the Luzon Strait, seasonal-to-interannual variations of this middle-layer eastward flow are nearly in-phase with the upper-layer westward flow. Overall, the above observational results provide a benchmark for the flow and transport in the Luzon Strait which can help understand the dynamics of the SCS circulation and validate and improve regional numerical simulations. Plain Language Summary The Luzon Strait is the main channel connecting the South China Sea (SCS) with the Pacific Ocean and the volume transport through the strait is crucial in regulating physical and biogeochemical processes in the SCS. However, given the sparsity of long-term direct observations, the knowledge of zonal flow and

Creating a taxonomy of interests is expensive and human-effort intensive: not only do we need to identify nodes and interconnect them, in order to use the taxonomy, we must also connect the nodes to relevant entities such as users, pins, and queries. Connecting to entities is challenging because of ambiguities inherent to language but also because individual interests are dynamic and evolve. Here, we offer an alternative approach that begins with bottom-up discovery of $\mu$-topics called pincepts. The discovery process itself connects these $\mu$-topics dynamically with relevant queries, pins, and users at high precision, automatically adapting to shifting interests. Pincepts cover all areas of user interest and automatically adjust to the specificity of user interests and are thus suitable for the creation of various kinds of taxonomies. Human experts associate taxonomy nodes with $\mu$-topics (on average, 3 $\mu$-topics per node), and the $\mu$-topics offer a high-level data layer that allows quick definition, immediate inspection, and easy modification. Even more powerfully, $\mu$-topics allow easy exploration of nearby semantic space, enabling curators to spot and fill gaps. Curators' domain knowledge is heavily leveraged and we thus don't need untrained mechanical Turks, allowing further cost reduction. These $\mu$-topics thus offer a satisfactory "symbolic" stratum over which to define taxonomies. We have successfully applied this technique for very rapidly iterating on and launching the home decor and fashion styles taxonomy for style-based personalization, prominently featured at the top of Pinterest search results, at 94% precision, improving search success rate by 34.8% as well as boosting long clicks and pin saves.

Recent advancements in vision-language pre-training (e.g. CLIP) have shown that vision models can benefit from language supervision. While many models using language modality have achieved great success on 2D vision tasks, the joint representation learning of 3D point cloud with text remains under-explored due to the difficulty of 3D-Text data pair acquisition and the irregularity of 3D data structure. In this paper, we propose a novel Text4Point framework to construct language-guided 3D point cloud models. The key idea is utilizing 2D images as a bridge to connect the point cloud and the language modalities. The proposed Text4Point follows the pre-training and fine-tuning paradigm. During the pre-training stage, we establish the correspondence of images and point clouds based on the readily available RGB-D data and use contrastive learning to align the image and point cloud representations. Together with the well-aligned image and text features achieved by CLIP, the point cloud features are implicitly aligned with the text embeddings. Further, we propose a Text Querying Module to integrate language information into 3D representation learning by querying text embeddings with point cloud features. For fine-tuning, the model learns task-specific 3D representations under informative language guidance from the label set without 2D images. Extensive experiments demonstrate that our model shows consistent improvement on various downstream tasks, such as point cloud semantic segmentation, instance segmentation, and object detection. The code will be available here: https://github.com/LeapLabTHU/Text4Point

Yuhao Zeng,1,&ast; Sha Zhu,1,&ast; Zilin Wang,1 Junru Chen,1 Jindong Dai,1 Zhenhua Liu,1 Guangxi Sun,1 Jiayu Liang,1 Xingming Zhang,1 Zhipeng Wang,1 Jinge Zhao,1 Yuchao Ni,1 Jiyu Yang,1 Minghao Wang,1 Qiang Wei,1 Xiang Li,1 Ni Chen,2 Zhiping Li,3 Xin Wang,3 Yali Shen,3 Jin Yao,4 Rui Huang,5 Jiyan Liu,6 Diming Cai,7 Hao Zeng,1 Pengfei Shen1 1Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 3Department of Oncology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 4Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 5Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 6Department of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 7Department of Medical Ultrasound, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Pengfei Shen; Hao Zeng, Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, People’s Republic of China, Email cdhx510@163.com; kucaizeng@163.comPurpose: Multidisciplinary team (MDT) discussion is a widely used model to manage patients diagnosed with cancer. However, there has been no direct evidence to prove its effect on the prognosis of metastatic renal cell carcinoma (mRCC) patients, so this study explored the impact of MDT discussion on mRCC patient survival.Methods: The clinical data of 269 mRCC patients were retrospectively collected from 2012 to 2021. The cases were grouped into the MDT and non-MDT groups, then subgroup analysis was performed according to different histology types, as well as exploring the

Objectives: To examine the association between visit-to-visit blood pressure variability (BPV) and incident diabetes mellitus (DM) risk in a Chinese population. Methods: Data comes from China Health and Nutrition Survey (n = 15,084). BPV was estimated as the average real variability (ARV) using at least three BP measurements from the year preceding the event and was divided into quartiles. Participants were also categorized into 9 groups on the basis of combinations of systolic BPV (SBPV) and diastolic BPV (DBPV) tertiles. Cox proportional hazards regression models were used. Results: During a median follow-up of 16.8 years, 1,030 (6.8%) participants developed diabetes (incidence rate: 4.65/1,000 person-years). The HRs (95% CIs) for the highest quartile (vs. the lowest quartile) of SBPV and DBPV were 1.60 (1.30–1.97) and 1.37 (1.13–1.67), respectively. Participants with both highest SBPV and DBPV tertile had an ≈89% higher risk of DM (HR, 1.89; 95% CI, 1.47–2.42) compared with those in the both SBPV and DBPV tertile 1 group. Conclusion: Higher SBP ARV and DBP ARV were independently associated with increased risk of incident DM, which was augmented when both presented together. Copyright © 2023 Zhou, Li, Liu, Huang, Liu, Yuan, Zheng, Zou and Wu.

Jinbo Zhao,1,&ast; Ling Hou,2,&ast; Ni Zhu,3,&ast; Rui Huang,1 Ke Su,1 Yuhua Lei,1 Yuanhong Li1 1Cardiovascular Disease Center, Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Enshi Prefecture, Hubei Province, 445000, People’s Republic of China; 2Department of Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Shiyan, Hubei Province, 442000, People’s Republic of China; 3Department of Pathology, Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Enshi Prefecture, Hubei Province, 445000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuanhong Li, Email lyh0101@vip.comObjective: The CHA2DS2-VASc score, a system which has been initially recommended for the assessment of thromboembolic risk in patients with atrial fibrillation (AF), arouses attention in the field of adverse coronary events. The purpose of this study was to explore the predictive value of preprocedural CHA2DS2-VASc score on ISR in patients after drug-eluting stent (DES) implantation.Methods: To further investigate the relationship between CHA2DS2-VASc scores and ISR after DES, a retrospective study of DES was carried on. Additionally, the preoperative variables for the ISR and control groups were contrasted. Predictive factors were chosen using the optimal subset regression. We validate the model using internal validation. The prediction model was evaluated using the receiver operator characteristic (ROC) analysis.Results: We used a 3:7 ratio to create an experimental group and a validation group, and then ran a stepwise regression with the data from each of the two groups. The results showed that CHA2DS2-VASc score was an independent risk factor for ISR in both the experimental (p = 0.0139) and validation groups (p = 0.0014), and both had significant predictive value for ISR. The area of the ROC curve was greater than 0.5 in

Current 3D scene segmentation methods are heavily dependent on manually annotated 3D training datasets. Such manual annotations are labor-intensive, and often lack fine-grained details. Importantly, models trained on this data typically struggle to recognize object classes beyond the annotated classes, i.e., they do not generalize well to unseen domains and require additional domain-specific annotations. In contrast, 2D foundation models demonstrate strong generalization and impressive zero-shot abilities, inspiring us to incorporate these characteristics from 2D models into 3D models. Therefore, we explore the use of image segmentation foundation models to automatically generate training labels for 3D segmentation. We propose Segment3D, a method for class-agnostic 3D scene segmentation that produces high-quality 3D segmentation masks. It improves over existing 3D segmentation models (especially on fine-grained masks), and enables easily adding new training data to further boost the segmentation performance -- all without the need for manual training labels., Comment: Project Page: http://segment3d.github.io

Current instruction-based editing methods, such as InstructPix2Pix, often fail to produce satisfactory results in complex scenarios due to their dependence on the simple CLIP text encoder in diffusion models. To rectify this, this paper introduces SmartEdit, a novel approach to instruction-based image editing that leverages Multimodal Large Language Models (MLLMs) to enhance their understanding and reasoning capabilities. However, direct integration of these elements still faces challenges in situations requiring complex reasoning. To mitigate this, we propose a Bidirectional Interaction Module that enables comprehensive bidirectional information interactions between the input image and the MLLM output. During training, we initially incorporate perception data to boost the perception and understanding capabilities of diffusion models. Subsequently, we demonstrate that a small amount of complex instruction editing data can effectively stimulate SmartEdit's editing capabilities for more complex instructions. We further construct a new evaluation dataset, Reason-Edit, specifically tailored for complex instruction-based image editing. Both quantitative and qualitative results on this evaluation dataset indicate that our SmartEdit surpasses previous methods, paving the way for the practical application of complex instruction-based image editing., Comment: Project page: https://yuzhou914.github.io/SmartEdit

In this work, we aim to detect the changes caused by object variations in a scene represented by the neural radiance fields (NeRFs). Given an arbitrary view and two sets of scene images captured at different timestamps, we can predict the scene changes in that view, which has significant potential applications in scene monitoring and measuring. We conducted preliminary studies and found that such an exciting task cannot be easily achieved by utilizing existing NeRFs and 2D change detection methods with many false or missing detections. The main reason is that the 2D change detection is based on the pixel appearance difference between spatial-aligned image pairs and neglects the stereo information in the NeRF. To address the limitations, we propose the C-NERF to represent scene changes as directional consistency difference-based NeRF, which mainly contains three modules. We first perform the spatial alignment of two NeRFs captured before and after changes. Then, we identify the change points based on the direction-consistent constraint; that is, real change points have similar change representations across view directions, but fake change points do not. Finally, we design the change map rendering process based on the built NeRFs and can generate the change map of an arbitrarily specified view direction. To validate the effectiveness, we build a new dataset containing ten scenes covering diverse scenarios with different changing objects. Our approach surpasses state-of-the-art 2D change detection and NeRF-based methods by a significant margin.

Although the development of artificial molecular machines has garnered considerable attention in recent years, the construction of multifunctional solid-state molecular machines still faces several challenges. Herein, we report a supramolecular approach as an efficient strategy for building multifunctional trigger systems. In crystals composed of [Ni(dmit)2]- with a spin of S = 1/2 and supramolecular structures consisting of 4-aminopyridinium+ and benzo[18]crown-6, supramolecular cations with dynamic degrees of freedom affect the magnetic and dielectric properties and induce negative thermal expansion (NTE). The supramolecular cations in the crystals form one-dimensional columns. Two adjacent columns form a supramolecular ladder structure via pi center dot center dot center dot pi interactions between the phenylene groups of benzo[18]crown-6 and are arranged within a two-dimensional layer. A disorder between the two sites of the phenylene ring was observed in one of the crystallographically independent benzo[18]crown-6. Disordered benzo[18]crown-6 formed polar domains within the crystal, resulting in relaxor ferroelectricity. With increasing temperature, the supramolecular ladders elongated and the translational motion of benzo[18]crown-6 caused the molecular ladder to move closer to each other. Consequently, the crystals shrunk in the direction perpendicular to the ladder, exhibiting uniaxial NTE, and the magnetic exchange interaction between the [Ni(dmit)2]- crystals was disrupted.

Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields. However, their proficiency within specialized domains such as biomolecular studies remains limited. To address this challenge, we introduce Mol-Instructions, a comprehensive instruction dataset designed for the biomolecular domain. Mol-Instructions encompasses three key components: molecule-oriented instructions, protein-oriented instructions, and biomolecular text instructions. Each component aims to improve the understanding and prediction capabilities of LLMs concerning biomolecular features and behaviors. Through extensive instruction tuning experiments on LLMs, we demonstrate the effectiveness of Mol-Instructions in enhancing large models' performance in the intricate realm of biomolecular studies, thus fostering progress in the biomolecular research community. Mol-Instructions is publicly available for ongoing research and will undergo regular updates to enhance its applicability., Comment: ICLR 2024. Project homepage: https://github.com/zjunlp/Mol-Instructions

How the ocean circulation changes in a warming climate is an important but poorly understood problem. Using a global ocean model, we decompose the problem into distinct responses to changes in sea surface temperature, salinity, and wind. Our results show that the surface warming effect, a robust feature of anthropogenic climate change, dominates and accelerates the upper ocean currents in 77% of the global ocean. Specifically, the increased vertical stratification intensifies the upper subtropical gyres and equatorial currents by shoaling these systems, while the differential warming between the Southern Ocean upwelling zone and the region to the north accelerates surface zonal currents in the Southern Ocean. In comparison, the wind stress and surface salinity changes affect regional current systems. Our study points a way forward for investigating ocean circulation change and evaluating the uncertainty.

Author Posting. © American Geophysical Union, 2022. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 49(12), (2022): e2021GL097598, https://doi.org/10.1029/2021GL097598., The ocean is inhomogeneous in hydrographic properties with diverse water masses. Yet, how this inhomogeneity has evolved in a rapidly changing climate has not been investigated. Using multiple observational and reanalysis datasets, we show that the spatial standard deviation (SSD) of the global ocean has increased by 1.4 ± 0.1% in temperature and 1.5 ± 0.1% in salinity since 1960. A newly defined thermohaline inhomogeneity index, a holistic measure of both temperature and salinity changes, has increased by 2.4 ± 0.1%. Climate model simulations suggest that the observed ocean inhomogeneity increase is dominated by anthropogenic forcing and projected to accelerate by 200%–300% during 2015–2100. Geographically, the rapid upper-ocean warming at mid-to-low latitudes dominates the temperature inhomogeneity increase, while the increasing salinity inhomogeneity is mainly due to the amplified salinity contrast between the subtropical and subpolar latitudes., This work is supported by the Strategic Priority Research Program of Chinese Academy of Sciences (grant XDB42000000 and XDB40000000), the National Key R&D Program of China (2017YFA0603200), and the Shandong Provincial Natural Science Foundation (ZR2020JQ17), and the U.S. National Science Foundation Physical Oceanography Program (OCE- 2048336)., 2022-12-23

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 52(7), (2022): 1415–1430. https://doi.org/10.1175/JPO-D-21-0147.1., Strong subinertial variability near a seamount at the Xisha Islands in the South China Sea was revealed by mooring observations from January 2017 to January 2018. The intraseasonal deep flows presented two significant frequency bands, with periods of 9–20 and 30–120 days, corresponding to topographic Rossby waves (TRWs) and deep eddies, respectively. The TRW and deep eddy signals explained approximately 60% of the kinetic energy of the deep subinertial currents. The TRWs at the Ma, Mb, and Mc moorings had 297, 262, and 274 m vertical trapping lengths, and ∼43, 38, and 55 km wavelengths, respectively. Deep eddies were independent from the upper layer, with the largest temperature anomaly being >0.4°C. The generation of the TRWs was induced by mesoscale perturbations in the upper layer. The interaction between the cyclonic–anticyclonic eddy pair and the seamount topography contributed to the generation of deep eddies. Owing to the potential vorticity conservation, the westward-propagating tilted interface across the eddy pair squeezed the deep-water column, thereby giving rise to negative vorticity west of the seamount. The strong front between the eddy pair induced a northward deep flow, thereby generating a strong horizontal velocity shear because of lateral friction and enhanced negative vorticity. Approximately 4 years of observations further confirmed the high occurrence of TRWs and deep eddies. TRWs and deep eddies might be crucial for deep mixing near rough topographies by transferring mesoscale energy to small scales., This work was supported by the National Natural Science Foundation of China (92158204, 91958202, 42076019, 41776036, 91858203), the Open Project Program of State Key Laboratory of Tropical Oceanography (project LTOZZ2001), and Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0304)., 2022-12-16

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 52(6), (2022): 1233-1244, https://doi.org/10.1175/jpo-d-21-0223.1., The Sverdrup relation is the backbone of wind-driven circulation theory; it is a simple relation between the meridional transport of the wind-driven circulation in the upper ocean and the wind stress curl. However, the relation is valid for steady circulation only. In this study, a time-dependent Sverdrup relation is postulated, in which the meridional transport in a time-dependent circulation is the sum of the local wind stress curl term and a time-delayed term representing the effect of the eastern boundary condition. As an example, this time-dependent Sverdrup relation is evaluated through its application to the equatorial circulation in the Indian Ocean, using reanalysis data and a reduced gravity model. Close examination reveals that the southward Somali Current occurring during boreal winter is due to the combination of the local wind stress curl in the Arabian Sea and delayed signals representing the time change of layer thickness at the eastern boundary., This work is supported by NSFC (41822602, 41976016, 42005035, 42076021), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB42000000, XDA 20060502), Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0306), Guangdong Basic and Applied Basic Research Foundation (2021A1515011534), Youth Innovation Promotion Association CAS, ISEE2021ZD01, and LTOZZ2002. The numerical simulation is supported by the High-Performance Computing Division in the South China Sea Institute of Oceanology., 2022-11-27

Stacking nanoscale-building blocks into one-dimensional (1D) assemblies with collective physical properties is a frontier in designing materials. However, the formation of 1D arrays using weak magnetic fields and an in-depth understanding of their magnetic properties remain challenging. Here, low-dimensional assemblies of iron oxide nanocubes with a disordered arrangement are fabricated at the diethylene-glycol/air interface in the presence of assembly fields (0/1/3/5/30/50 mT). Ring-shaped assemblies gradually transform as the assembly field increases from 0 to 50 mT, first to a porous network consisting of elongated assemblies and then to an aligned array of filaments, in which the aligned filaments are formed when the assembly field is >= 3 mT and duration t > 14 min. Spin-glass characteristics and static (dynamic) anisotropy factors similar to 2(3) are achieved by tuning the strength of the assembly field. In the presence of a relatively weak assembly field, the interplay between dipolar interactions and disorder with respect to magnetic easy axis alignment leads to spin-glass characteristics. The alignment of the magnetic easy axes and the strength of the dipolar interactions increase with increasing assembly field, resulting in the disappearance of spin-glass characteristics and enhancement of the magnetic anisotropy. This study presents a strategy for obtaining magnetic assemblies with spin-glass behavior and controllable anisotropy while shedding light on the magnetic interactions of low-dimensional assemblies.

Using Na-encapsulated benzo[18]crown-6 (Na)(B18C6) as a counter cation, we successfully magnetically isolated a fluoride-bridging Dy dinuclear complex {[(PW11O39)Dy(H2O)(2)](2)F} (Dy2POM) with lacunary Keggin ligands. (Na)(B18C6) formed two types of tetramers through C-HMIDLINE HORIZONTAL ELLIPSISO, pi MIDLINE HORIZONTAL ELLIPSIS pi and C-HMIDLINE HORIZONTAL ELLIPSIS pi interactions, and each tetramer aligned in one dimension along the c-axis to form two types of channels. One channel was partially penetrated by a supramolecular cation from the +/- a-axis direction, dividing the channel in the form of a bamboo node. Dy2POM was spatially divided by this bamboo node, which magnetically isolated one portion from the other. The temperature dependence of the magnetic susceptibility indicated a weak ferromagnetic interaction between the Dy ions bridged by fluoride. Dy2POM exhibited the magnetic relaxation characteristics of a single-molecule magnet, including the dependence of AC magnetic susceptibility on temperature and frequency. Magnetic relaxation can be described by the combination of thermally active Orbach and temperature-independent quantum tunneling processes. The application of a static magnetic field effectively suppressed the relaxation due to quantum tunneling.

ObjectiveThis study examines how onset of chronic pain affects characteristics of personal social networks among adults aged 51+ across Europe.MethodsWe used population-based data from the Survey of Health, Ageing and Retirement in Europe (SHARE; 2011-2015; n = 12,647). Using a change score analysis approach, we tracked changes in personal social networks of respondents experiencing new-onset chronic pain (n = 3803) compared to pain-free counterparts (n = 8844) in 11 European countries over four years.ResultsOverall, consistent with network activation theory, respondents with new-onset mild-to-moderate chronic pain reported increases in sizes and diversity of their personal social networks, compared to their pain-free counterparts. However, consistent with the "pain as threat to the social self" theory, respondents with new-onset moderate pain or mild-to-moderate pain reported a decrease over time in perceived satisfaction and closeness with networks, respectively. Estimates from interactions between new-onset pain severity and sex show that men with new-onset pain experienced greater decreases in network satisfaction (mild pain) and closeness (severe pain) than did women.DiscussionThis study highlights the complex social consequences of chronic pain, which may vary based on pain severity, gender, and type of social outcome considered.

Yale Yang,1 Wuling Zhong,1 Yali Zhang,1 Yalan Cheng,1 Hejin Lai,1 Huimin Yu,1 Ning Feng,1 Yumo Han,2 Rui Huang,1 Qiwei Zhai1,2 1CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China; 2School of Life Science and Technology, ShanghaiTech University, Shanghai, People’s Republic of ChinaCorrespondence: Qiwei Zhai, Shanghai, 200031, People’s Republic of China, Tel +86 21 5492 0903, Fax +86 21 5492 0291, Email qwzhai@sibs.ac.cnBackground: Sustained inflammation is implicated in a variety of pathological conditions like infection, obesity and type 2 diabetes. Lipid metabolism is crucial to support immune response during infection of bacteria. However, how sustained inflammation affects lipid metabolism, especially in white adipose tissue remains largely unknown.Methods: Sustained inflammation was induced by daily injection of Lipopolysaccharide (LPS). Tlr4 knockout mice were used to study the mechanism. Inflammation and lipid metabolism were evaluated by quantitative PCR, white blood cell counting, nuclear magnetic resonance, fat cell size quantification, lipolysis and fatty acid uptake assays, respiratory exchange ratio, and energy expenditure.Results: Here, we found that sustained inflammation leads to fat loss in mice with a quick loss and gradual increase manner. Moreover, LPS injection leads to inflammation, anorexia, decreased lipid anabolism, and increased lipid catabolism. Mechanically, we show that LPS induces fat loss, inflammation, anorexia, and alteration of lipid metabolism mainly dependent on Tlr4. Interestingly, sustained inflammation induces less fat loss, especially in epididymal white adipose tissue, than pair-feeding, and pair-feeding has no significant effect on inflammation and leads to less fatty acid uptake, more lipid catabolism and energy expenditure than LPS injection. In addition, w

This is the accepted version of the following article:Chen X., Huang R.K., Takahashi K., et al. A Proton Conductive Porous Framework of an 18-Crown-6-Ether Derivative Networked by Rigid Hydrogen Bonding Modules. Angewandte Chemie - International Edition 61, e202211686 (2022), which has been published in final form at https://doi.org/10.1002/anie.202211686. This article may be used for non-commercialpurposes in accordance with the Wiley Self-ArchivingPolicy [https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html], A rigid hydrogen-bonded organic framework (HOF) was constructed from a C3-symmetric hexatopic carboxylic acid with a hydrophilic 18-crown-6-ether (18C6) component. Despite the flexible macrocyclic structure with many conformations, the derivative with three 4,4’-dicarboxy-o-terphenyl moieties in the periphery yielded a rigid layered porous framework through directional intermolecular hydrogen bonding. Interestingly, the HOF possesses 1D channels with bottleneck composed of 18C6 rings. The HOF shows proton conductivity (1.12×10−7 S cm−1) through Grotthuss mechanism (Ea=0.27 eV) under 98 %RH. The present unique water channel structure provides an inspiration to create molecular porous materials.

Visual Place Recognition is an essential component of systems for camera localization and loop closure detection, and it has attracted widespread interest in multiple domains such as computer vision, robotics and AR/VR. In this work, we propose a faster, lighter and stronger approach that can generate models with fewer parameters and can spend less time in the inference stage. We designed RepVGG-lite as the backbone network in our architecture, it is more discriminative than other general networks in the Place Recognition task. RepVGG-lite has more speed advantages while achieving higher performance. We extract only one scale patch-level descriptors from global descriptors in the feature extraction stage. Then we design a trainable feature matcher to exploit both spatial relationships of the features and their visual appearance, which is based on the attention mechanism. Comprehensive experiments on challenging benchmark datasets demonstrate the proposed method outperforming recent other state-of-the-art learned approaches, and achieving even higher inference speed. Our system has 14 times less params than Patch-NetVLAD, 6.8 times lower theoretical FLOPs, and run faster 21 and 33 times in feature extraction and feature matching. Moreover, the performance of our approach is 0.5\% better than Patch-NetVLAD in Recall@1. We used subsets of Mapillary Street Level Sequences dataset to conduct experiments for all other challenging conditions., Comment: CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW)

Change detection (CD) is to decouple object changes (i.e., object missing or appearing) from background changes (i.e., environment variations) like light and season variations in two images captured in the same scene over a long time span, presenting critical applications in disaster management, urban development, etc. In particular, the endless patterns of background changes require detectors to have a high generalization against unseen environment variations, making this task significantly challenging. Recent deep learning-based methods develop novel network architectures or optimization strategies with paired-training examples, which do not handle the generalization issue explicitly and require huge manual pixel-level annotation efforts. In this work, for the first attempt in the CD community, we study the generalization issue of CD from the perspective of data augmentation and develop a novel weakly supervised training algorithm that only needs image-level labels. Different from general augmentation techniques for classification, we propose the background-mixed augmentation that is specifically designed for change detection by augmenting examples under the guidance of a set of background-changing images and letting deep CD models see diverse environment variations. Moreover, we propose the augmented & real data consistency loss that encourages the generalization increase significantly. Our method as a general framework can enhance a wide range of existing deep learning-based detectors. We conduct extensive experiments in two public datasets and enhance four state-of-the-art methods, demonstrating the advantages of our method. We release the code at https://github.com/tsingqguo/bgmix., Comment: AAAI 2023 Accepted

Text-video retrieval is an important multi-modal learning task, where the goal is to retrieve the most relevant video for a given text query. Recently, pre-trained models, e.g., CLIP, show great potential on this task. However, as pre-trained models are scaling up, fully fine-tuning them on text-video retrieval datasets has a high risk of overfitting. Moreover, in practice, it would be costly to train and store a large model for each task. To overcome the above issues, we present a novel $\textbf{Cross-Modal Adapter}$ for parameter-efficient fine-tuning. Inspired by adapter-based methods, we adjust the pre-trained model with a few parameterization layers. However, there are two notable differences. First, our method is designed for the multi-modal domain. Secondly, it allows early cross-modal interactions between CLIP's two encoders. Although surprisingly simple, our approach has three notable benefits: (1) reduces $\textbf{99.6}\%$ of fine-tuned parameters, and alleviates the problem of overfitting, (2) saves approximately 30% of training time, and (3) allows all the pre-trained parameters to be fixed, enabling the pre-trained model to be shared across datasets. Extensive experiments demonstrate that, without bells and whistles, it achieves superior or comparable performance compared to fully fine-tuned methods on MSR-VTT, MSVD, VATEX, ActivityNet, and DiDeMo datasets. The code will be available at \url{https://github.com/LeapLabTHU/Cross-Modal-Adapter}., Comment: Tech Report