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Embryonic stem cells (ESCs) can differentiate into all cell types of the embryonic germ layers. ESCs can also generate totipotent 2C-like cells and trophectodermal cells. However, these latter transitions occur at low frequency due to epigenetic barriers, the nature of which is not fully understood. Here, we show that treating mouse ESCs with sodium butyrate (NaB) increases the population of 2C-like cells and enables direct reprogramming of ESCs into trophoblast stem cells (TSCs) without a transition through a 2C-like state. Mechanistically, NaB inhibits histone deacetylase activities in the LSD1-HDAC1/2 corepressor complex. This increases acetylation levels in the regulatory regions of both 2C- and TSC-specific genes, promoting their expression. In addition, NaB-treated cells acquire the capacity to generate blastocyst-like structures that can develop beyond the implantation stage in vitro and form deciduae in vivo. These results identify how epigenetics restrict the totipotent and trophectoderm fate in mouse ESCs.

Wen-Jie Cong,1,* Zhi-Peng Liu,2,* Yi-Xin Liang,2 Sheng-Lie Ye,2 Zhong-Ming Cai,2 Hao-Man Chen,2 Cheng-Wei Liao,2 Qun-Li Lin,3 Ren-Qian Feng,2 Xu-Dong Zhou,4 Yan-Zhi Wu,2 Le-Qiu Sun,5 Xue-Rong Huang,6 Man-Man Zhang,7 Gui-Qian Huang,8 Bei-Lei Zhu7 1Department of Acupuncture and Physiotherapy, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 2The First Clinical School, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 3Department of Neurology, Yongjia People’s Hospital, Wenzhou, Zhejiang, People’s Republic of China; 4Department of Neurology, Pingyang People’s Hospital, Wenzhou, Zhejiang, People’s Republic of China; 5Department of Neurology, Affiliated Yueqing Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China; 6Department of Neurology, Ruian People’s Hospital, Wenzhou, Zhejiang, People’s Republic of China; 7Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University Wenzhou Zhejiang People’s Republic of China; 8School of Mental Health, Wenzhou Medical University, Wenzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bei-Lei Zhu, Tel +86 13567896076, Email doczbl@163.comPurpose: To explore the predictive value of nutritional risk for all-cause death and functional outcomes among elderly acute stroke patients.Patients and Methods: A total of 479 elderly acute stroke patients were enrolled in this study. The nutritional risk of patients was screened by the GNRI and NRS-2002. The primary outcome was all-cause death, and the secondary outcome was poor prognosis defined as a modified Rankin Scale (mRS) score ≥ 3.Results: Based on the NRS-2002, patients with nutritional risk had a higher risk of all-cause death at 3 months (adjusted OR: 3.642, 95% CI 1.046~12.689) and at 3 years (adjusted OR: 2.266, 95% CI 1.259

Molecular emitters with multi-emissive properties are in high demand in numerous fields, while these properties basically depend on specific molecular conformation and packing. For amorphous systems, special molecular arrangement is unnecessary, but it remains challenging to achieve such luminescent behaviors. Herein, we present a general strategy that takes advantage of molecular rigidity and S1-T1 energy gap balance for emitter design, which enables fluorescence-phosphorescence dual-emission properties in various solid forms, whether crystalline or amorphous. Subsequently, the amorphism of the emitters based polymethyl methacrylate films endowed an in situ regulation of the dual-emissive characteristics. With the ratiometric regulation of phosphorescence by external stimuli and stable fluorescence as internal reference, highly controllable luminescent color tuning (yellow to blue including white emission) was achieved. There properties together with a persistent luminous behavior is of benefit for an irreplaceable set of optical information combination, featuring an ultrahigh-security anti-counterfeiting ability. Our research introduces a concept of eliminating the crystal-form and molecular-conformational dependence of complex luminescent properties through emitter molecular design. This has profound implications for the development of functional materials. A molecular structural strategy enabling single emitter based dual-emission properties in various solid forms is presented. The developed amorphous films endow in situ regulation of the dual-emissive characteristics to show highly controllable multiple luminescent color tuning (yellow to blue including white emission), which benefits to the construction of an irreplaceable set of optical information combination.image, Funding Agencies|National Natural Science Foundation of China [2022-06725]; Swedish Research Council [22275038]; Russian Scientific Foundation [NAISS 2023/5-77]; National Academic Infrastructure for Supercomputing in Swede at the National Supercomputer Centre (NSC) at Linkoeping University; [2020-04600]; [23-73-10081]

Jiang-Peng Cao,1– 3 Yuan-Hao Du,1,2,4 Lan-Yu Jia,5 Xiu-Mei Yin,1– 3 Li-Hong Yang,1,2 Lin-Ling Chen,6 Tao Jiang,1,2 Man Zhang,4 Tian Qiu1– 3 1Department of Acupuncture and Moxibustion, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 2National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, People’s Republic of China; 3Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 4School of acupuncture & moxibustion and Tuina, Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 5Department of Geriatric medicine, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, People’s Republic of China; 6Department of Traditional Chinese Medicine, Huzhou Central Hospital, Huzhou, Zhejiang, People’s Republic of ChinaCorrespondence: Yuan-Hao Du, Email jpjs_cn@sina.comBackground: Cerebral blood flow and vascular structures serve as the fundamental components of brain metabolism and circulation. Acupuncture, an alternative and complementary medical approach, has demonstrated efficacy in treating cerebral ischemic stroke (CIS). Nevertheless, the mechanisms underlying the impact of acupuncture on vascular smooth muscle cell (VSMC) function remain uncertain. The objective of this systematic review and meta-analysis is to assess the alterations in VSMC function following acupuncture stimulation in CIS models.Methods: The databases PubMed, Web of Science, SCOPUS, and EMBASE were queried until November 2022 using a predetermined search strategy. The FORMAT BY SYRCLE guidelines were adhered to, and the risk of bias of the included studies was evaluated using the Risk of Bias tool developed by the Systematic Review Centre for Laboratory Animal Experimentation. The random-effects model was employed to estimate the standardized mean difference (SMD).Results: Eightee

Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns. Silhouette modality, renowned for its easy acquisition, simple structure, sparse representation, and convenient modeling, has been widely employed in controlled in-the-lab research. However, as gait recognition rapidly advances from in-the-lab to in-the-wild scenarios, various conditions raise significant challenges for silhouette modality, including 1) unidentifiable low-quality silhouettes (abnormal segmentation, severe occlusion, or even non-human shape), and 2) identifiable but challenging silhouettes (background noise, non-standard posture, slight occlusion). To address these challenges, we revisit gait recognition pipeline and approach gait recognition from a quality perspective, namely QAGait. Specifically, we propose a series of cost-effective quality assessment strategies, including Maxmial Connect Area and Template Match to eliminate background noises and unidentifiable silhouettes, Alignment strategy to handle non-standard postures. We also propose two quality-aware loss functions to integrate silhouette quality into optimization within the embedding space. Extensive experiments demonstrate our QAGait can guarantee both gait reliability and performance enhancement. Furthermore, our quality assessment strategies can seamlessly integrate with existing gait datasets, showcasing our superiority. Code is available at https://github.com/wzb-bupt/QAGait., Comment: Accepted by AAAI 2024

Indoor scene generation has attracted significant attention recently as it is crucial for applications of gaming, virtual reality, and interior design. Current indoor scene generation methods can produce reasonable room layouts but often lack diversity and realism. This is primarily due to the limited coverage of existing datasets, including only large furniture without tiny furnishings in daily life. To address these challenges, we propose FurniScene, a large-scale 3D room dataset with intricate furnishing scenes from interior design professionals. Specifically, the FurniScene consists of 11,698 rooms and 39,691 unique furniture CAD models with 89 different types, covering things from large beds to small teacups on the coffee table. To better suit fine-grained indoor scene layout generation, we introduce a novel Two-Stage Diffusion Scene Model (TSDSM) and conduct an evaluation benchmark for various indoor scene generation based on FurniScene. Quantitative and qualitative evaluations demonstrate the capability of our method to generate highly realistic indoor scenes. Our dataset and code will be publicly available soon.

With the global concept of sustainable development gaining popularity, the three factors of environmental (E), social (S) and governance (G) are gradually increasing in the status of investment decisions. As an effective tool for evaluating the non-financial performance of a company, the ESG rating has been widely used in investment, risk management, corporate governance, and sustainable development. Investors, consumers, and regulators increasingly rely on ESG ratings to assess the sustainability of companies. Visualization techniques play a crucial role in showing ESG ratings and their differences more intuitively. With the help of visualization technology, investors can quickly grasp the ESG performance of companies, gain insight into the root causes of rating divergence, and make more informed investment decisions. At the same time, companies can use visualization technology to demonstrate their strengths and efforts in ESG and enhance public trust. Research shows that as data science and artificial intelligence technologies continue to advance, the visualization of ESG ratings will become more accurate, efficient, and personalized. This will help further promote the popularization and practice of the concept of sustainable development and contribute to the realization of global green development and corporate social responsibility.

Thanks to the powerful generative capacity of diffusion models, recent years have witnessed rapid progress in human motion generation. Existing diffusion-based methods employ disparate network architectures and training strategies. The effect of the design of each component is still unclear. In addition, the iterative denoising process consumes considerable computational overhead, which is prohibitive for real-time scenarios such as virtual characters and humanoid robots. For this reason, we first conduct a comprehensive investigation into network architectures, training strategies, and inference processs. Based on the profound analysis, we tailor each component for efficient high-quality human motion generation. Despite the promising performance, the tailored model still suffers from foot skating which is an ubiquitous issue in diffusion-based solutions. To eliminate footskate, we identify foot-ground contact and correct foot motions along the denoising process. By organically combining these well-designed components together, we present StableMoFusion, a robust and efficient framework for human motion generation. Extensive experimental results show that our StableMoFusion performs favorably against current state-of-the-art methods. Project page: https://h-y1heng.github.io/StableMoFusion-page

This paper investigates the short-circuit behavior of SiC MOSFETs in half bridge configuration during shoot-through event. The short-circuit peak current (ISCP) as well as the distribution of drain to source voltage (VDS) of half bridge configuration are analyzed under various mismatch operating condition. Further, the determinants on total amount and distribution of short-circuit energy (SC energy) are obtained. It is revealed that the device with the lowest short-circuit current carrying capacity determines the ISCP and the total SC energy of half bridge leg. Besides, the decrease of active switch common source inductance can mitigate the VDS and SC energy imbalance caused by load current. The conclusions are validated by experimental results., Part of ISBN 9798350316445QC 20240201

This paper gives a layout design principle for multichip SiC MOSFET power modules taking the transient current distribution among paralleled dies into consideration. A few typical power module layouts are analyzed and modeled with parasitic layout parameters. With the analysis and comparison, a universal and practical design principle is proposed, which is to make the direction of parallel connections perpendicular to the direction of current flow. Applying this design principle mitigates the di/dt through the parasitic inductance between the source terminals of the paralleled dies. Furthermore, this approach avoids current coupling effects, which aggravate transient current imbalances. The design principle is verified with experimental results., Part of ISBN 9789075815412QC 20231116

Polymer dots (PDs) have raised considerable research interest due to their advantages of designable nanostructures, high biocompatibility, versatile photoluminescent properties, and recyclability as nanophase. However, there remains a lack of in situ, real-time, and noncontact methods for synthesizing PDs. Here we report a rational strategy to synthesize PDs through a well-designed single-component precursor (an asymmetrical donor-acceptor-donor ' molecular structure) by photoirradiation at ambient temperature. In contrast to thermal processes that normally lack atomic economy, our method is mild and successive, based on an aggregation-promoted sulfonimidization triggered by photoinduced delocalized intrinsic radical cations for polymerization, followed by photooxidation for termination with structural shaping to form PDs. This synthetic approach excludes any external additives, rendering a conversion rate of the precursor exceeding 99%. The prepared PDs, as a single entity, can realize the integration of nanocore luminescence and precursor-transferred luminescence, showing 41.5% of the total absolute luminescence quantum efficiency, which is higher than most reported PD cases. Based on these photoluminescent properties, together with the superior biocompatibility, a unique membrane microenvironmental biodetection could be exemplified. This strategy with programming control of the single precursor can serve as a significant step toward polymer nanomanufacturing with remote control, high-efficiency, precision, and real-time operability.

Chao Tang,1,2,* Xiaoqing Deng,1,* Jingru Qu,1 Yahui Miao,1 Lei Tian,1 Man Zhang,1 Xiaoyu Li,1 Bei Sun,1 Liming Chen1 1NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, People’s Republic of China; 2The Affiliated Huzhou Hospital, Zhejiang University School of Medicine (Huzhou Central Hospital), Huzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liming Chen; Bei Sun, No. 6 North Huanrui Road, Beichen District, Tianjin, People’s Republic of China, Email xfx22081@vip.163.com; sun_peipei220@hotmail.comBackground: Diabetic kidney disease (DKD) is a major diabetic microvascular complication. Fatty acid-induced lipotoxicity and apoptosis were associated with the exacerbation of DKD. However, the association of lipotoxicity with renal tubular apoptosis and the effects of fenofibrate on DKD are not fully understood.Methods: Eight-week-old db/db mice were given fenofibrate or saline by gavage for 8 weeks. Human kidney proximal tubular epithelial (HK2) cells stimulated with palmitic acid (PA) and high glucose (HG) were used as a model of lipid metabolism disorders. Apoptosis was assessed with or without fenofibrate. The AMP-activated protein kinase (AMPK) activator 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) and AMPK inhibitor Compound C were used to determine the involvement of AMPK and Medium-chain acyl-CoA dehydrogenase (MCAD) in the regulation of lipid accumulation by fenofibrate. MCAD silencing was achieved by small interfering RNA (siRNA) transfection.Results: Fenofibrate reduced triglyceride (TG) content and lipid accumulation in DKD. Importantly, renal function and tubular cell apoptosis were significantly improved by fenofibrate. Fenofibrate reduced apoptosis, accompanied by increased activation of the AMPK/FOXA2/MCA

Space weather events can have damaging effects on ground-based infrastructure. Geomagnetically induced currents (GIC) caused by rapid magnetic field fluctuations during geomagnetic storms can negatively affect power networks, railways as well as navigation systems. To reduce such negative impacts, good forecasting capability is essential. In this study we assess the performance of contemporary magnetohydrodynamic (MHD) models in predicting the external-only ground magnetic field perturbations at three United Kingdom observatories during two severe space weather events: September 2017 and March 2015. Simulated magnetic data were acquired via Community Coordinated Modeling Center (CCMC), using the following models: Space Weather Modeling Framework (SWMF), Open Geospace General Circulation Model (Open GGCM) and Lyon–Fedder–Mobarry (LFM) combined with the Rice Convection Model (RCM). All simulations use spacecraft measurements at L1 as their solar wind input in calculating ground perturbations. Qualitative and quantitative comparison between measured and modelled values suggest that the performance of MHD models vary with latitude, the magnetic component and the characteristics of the storm analysed. Most models tend to exaggerate the magnitude of disturbances at lower latitudes but better capture the fluctuations at the highest latitude. For the two storms investigated, the addition of RCM tends to result in overestimation of the amplitude of ground perturbations. The observed data-model discrepancies most likely arise due to the many approximations required in MHD modelling, such as simplified solar wind input or shift in location of the electrojets in the simulated magnetospheric and ionospheric currents. It was found that no model performs consistently better than any other, implying that each simulation forecasts different aspects of ground perturbations with varying level of accuracy. Ultimately, the decision of which model is most suitable depends on specific nee

Huajie Yang,1,* Zhuohua Wu,2,* Xiang Huang,3,4,* Man Zhang,3 Yu Fu,5 Yijuan Wu,2 Lei Liu,2 Yiheng Li,2 Harry HX Wang5 1School of Health Technology, Guangdong Open University (Guangdong Polytechnic Institute), Guangzhou, People’s Republic of China; 2The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China; 3Sanxiang Community Health Service Centre of Zhongshan, Zhongshan, People’s Republic of China; 4Faculty of Medicine, Macau University of Science and Technology, Macau SAR, People’s Republic of China; 5School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Harry HX Wang, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China, Tel +86 20 87330672, Email wanghx27@mail.sysu.edu.cn Yiheng Li, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, People’s Republic of China, Tel +86 20 83062721, Email ehengs@qq.comIntroduction: Timely access to emergency treatment during in-hospital care phase is critical for managing the onset of acute ischaemic stroke (AIS), particularly in developing countries. We aimed to explore in-hospital emergency treatment delay and the relation of door-to-needle (DTN) time to ambulance arrivals vs walk-in arrivals.Methods: Data were collected from 1276 Chinese AIS patients admitted to a general, tertiary-level hospital for intravenous thrombolysis. Information on patients’ characteristics and time taken during in-hospital emergency treatment was retrieved from the hospital registry data and medical records. Ambulance arrival was defined as being transported by emergency ambulance services, while walk-in arrival was defined as arriving at hospital by regular vehicle. In-hospital emergency treatment delay occurred when the DTN time exceeded 60 minutes. We performed multivariable logistic regression

Recently, CLIP has found practical utility in the domain of pixel-level zero-shot segmentation tasks. The present landscape features two-stage methodologies beset by issues such as intricate pipelines and elevated computational costs. While current one-stage approaches alleviate these concerns and incorporate Visual Prompt Training (VPT) to uphold CLIP's generalization capacity, they still fall short in fully harnessing CLIP's potential for pixel-level unseen class demarcation and precise pixel predictions. To further stimulate CLIP's zero-shot dense prediction capability, we propose SPT-SEG, a one-stage approach that improves CLIP's adaptability from image to pixel. Specifically, we initially introduce Spectral Prompt Tuning (SPT), incorporating spectral prompts into the CLIP visual encoder's shallow layers to capture structural intricacies of images, thereby enhancing comprehension of unseen classes. Subsequently, we introduce the Spectral Guided Decoder (SGD), utilizing both high and low-frequency information to steer the network's spatial focus towards more prominent classification features, enabling precise pixel-level prediction outcomes. Through extensive experiments on two public datasets, we demonstrate the superiority of our method over state-of-the-art approaches, performing well across all classes and particularly excelling in handling unseen classes. Code is available at:https://github.com/clearxu/SPT., Comment: AAAI2024 Accepted

Complex software systems, e.g., Cyber-Physical Systems (CPSs), interact with the real world; thus, they often behave unexpectedly in uncertain environments. Testing such systems is challenging due to limited resources, time, complex testing infrastructure setup, and the inherent uncertainties in their operating environment. Devising uncertainty-aware testing solutions supported with test optimization techniques can be considered as a mandate for tackling this challenge. This paper proposes an uncertainty-aware and time-aware test case prioritization approach, named UncerPrio, for optimizing a sequence of tests to execute with a multi-objective search. To guide the prioritization with uncertainty, we identify four uncertainty measures: uncertainty measurement (AUM), uncertainty space (PUS), the number of uncertainties (ANU), and uncertainty coverage (PUU). Based on these measures and their combinations, we proposed 10 uncertainty-aware and multi-objective test case prioritization problems, and each problem was additionally defined with one cost objective (execution cost, PET) to be minimized and one effective measure (model coverage, PTR) to be maximized. Moreover, considering time constraints for test executions (i.e., time-aware), we defined 10 time budgets for all the 10 problems for identifying the best strategy in solving uncertainty-aware test prioritization. In our empirical study, we employed four well-known Multi-Objective Search Algorithms (MuOSAs): NSGA-II, MOCell, SPEA2, and CellDE with five use cases from two industrial CPS subject systems, and used Random Algorithm (RS) as the comparison baseline. Results show that all the MuOSAs significantly outperformed RS. The strategy of Prob.6 f(PET,PTR,AUM,ANU) (i.e., the problem with uncertainty measures AUM and ANU combined) achieved the overall best performance in observing uncertainty when using 100% time budget.

In recent years, the rapid advancement of Large Language Models (LLMs) such as the Generative Pre-trained Transformer (GPT) has attracted increasing attention due to their potential in a variety of practical applications. The application of LLMs with Embodied Intelligence has emerged as a significant area of focus. Among the myriad applications of LLMs, navigation tasks are particularly noteworthy because they demand a deep understanding of the environment and quick, accurate decision-making. LLMs can augment embodied intelligence systems with sophisticated environmental perception and decision-making support, leveraging their robust language and image-processing capabilities. This article offers an exhaustive summary of the symbiosis between LLMs and embodied intelligence with a focus on navigation. It reviews state-of-the-art models, research methodologies, and assesses the advantages and disadvantages of existing embodied navigation models and datasets. Finally, the article elucidates the role of LLMs in embodied intelligence, based on current research, and forecasts future directions in the field. A comprehensive list of studies in this survey is available at https://github.com/Rongtao-Xu/Awesome-LLM-EN

Autonomous driving systems (ADSs) are capable of sensing the environment and making driving decisions autonomously. These systems are safety-critical, and testing them is one of the important approaches to ensure their safety. However, due to the inherent complexity of ADSs and the high dimensionality of their operating environment, the number of possible test scenarios for ADSs is infinite. Besides, the operating environment of ADSs is dynamic, continuously evolving, and full of uncertainties, which requires a testing approach adaptive to the environment. In addition, existing ADS testing techniques have limited effectiveness in ensuring the realism of test scenarios, especially the realism of weather conditions and their changes over time. Recently, reinforcement learning (RL) has demonstrated great potential in addressing challenging problems, especially those requiring constant adaptations to dynamic environments. To this end, we present DeepQTest, a novel ADS testing approach that uses RL to learn environment configurations with a high chance of revealing abnormal ADS behaviors. Specifically, DeepQTest employs Deep Q-Learning and adopts three safety and comfort measures to construct the reward functions. To ensure the realism of generated scenarios, DeepQTest defines a set of realistic constraints and introduces real-world weather conditions into the simulated environment. We employed three comparison baselines, i.e., random, greedy, and a state-of-the-art RL-based approach DeepCOllision, for evaluating DeepQTest on an industrial-scale ADS. Evaluation results show that DeepQTest demonstrated significantly better effectiveness in terms of generating scenarios leading to collisions and ensuring scenario realism compared with the baselines. In addition, among the three reward functions implemented in DeepQTest, Time-To-Collision is recommended as the best design according to our study., Comment: 40 pages, 7 figures, 13 tables

Point cloud analysis faces computational system overhead, limiting its application on mobile or edge devices. Directly employing small models may result in a significant drop in performance since it is difficult for a small model to adequately capture local structure and global shape information simultaneously, which are essential clues for point cloud analysis. This paper explores feature distillation for lightweight point cloud models. To mitigate the semantic gap between the lightweight student and the cumbersome teacher, we propose bidirectional knowledge reconfiguration (BKR) to distill informative contextual knowledge from the teacher to the student. Specifically, a top-down knowledge reconfiguration and a bottom-up knowledge reconfiguration are developed to inherit diverse local structure information and consistent global shape knowledge from the teacher, respectively. However, due to the farthest point sampling in most point cloud models, the intermediate features between teacher and student are misaligned, deteriorating the feature distillation performance. To eliminate it, we propose a feature mover's distance (FMD) loss based on optimal transportation, which can measure the distance between unordered point cloud features effectively. Extensive experiments conducted on shape classification, part segmentation, and semantic segmentation benchmarks demonstrate the universality and superiority of our method., Comment: Accepted by IEEE Transactions on Multimedia (TMM)

The advent of Large Language Models (LLMs) has paved the way for complex tasks such as role-playing, which enhances user interactions by enabling models to imitate various characters. However, the closed-source nature of state-of-the-art LLMs and their general-purpose training limit role-playing optimization. In this paper, we introduce RoleLLM, a framework to benchmark, elicit, and enhance role-playing abilities in LLMs. RoleLLM comprises four stages: (1) Role Profile Construction for 100 roles; (2) Context-Based Instruction Generation (Context-Instruct) for role-specific knowledge extraction; (3) Role Prompting using GPT (RoleGPT) for speaking style imitation; and (4) Role-Conditioned Instruction Tuning (RoCIT) for fine-tuning open-source models along with role customization. By Context-Instruct and RoleGPT, we create RoleBench, the first systematic and fine-grained character-level benchmark dataset for role-playing with 168,093 samples. Moreover, RoCIT on RoleBench yields RoleLLaMA (English) and RoleGLM (Chinese), significantly enhancing role-playing abilities and even achieving comparable results with RoleGPT (using GPT-4)., Comment: 30 pages, repo at https://github.com/InteractiveNLP-Team/RoleLLM-public

Due to its importance and widespread use in industry, automated testing of REST APIs has attracted major interest from the research community in the last few years. However, most of the work in the literature has been focused on black-box fuzzing. Although existing fuzzers have been used to automatically find many faults in existing APIs, there are still several open research challenges that hinder the achievement of better results (e.g., in terms of code coverage and fault finding). For example, under-specified schemas are a major issue for black-box fuzzers. Currently, EvoMaster is the only existing tool that supports white-box fuzzing of REST APIs. In this paper, we provide a series of novel white-box heuristics, including for example how to deal with under-specified constrains in API schemas, as well as under-specified schemas in SQL databases. Our novel techniques are implemented as an extension to our open-source, search-based fuzzer EvoMaster. An empirical study on 14 APIs from the EMB corpus, plus one industrial API, shows clear improvements of the results in some of these APIs.

Weakly-supervised temporal action localization (WTAL) is a practical yet challenging task. Due to large-scale datasets, most existing methods use a network pretrained in other datasets to extract features, which are not suitable enough for WTAL. To address this problem, researchers design several modules for feature enhancement, which improve the performance of the localization module, especially modeling the temporal relationship between snippets. However, all of them neglect the adverse effects of ambiguous information, which would reduce the discriminability of others. Considering this phenomenon, we propose Discriminability-Driven Graph Network (DDG-Net), which explicitly models ambiguous snippets and discriminative snippets with well-designed connections, preventing the transmission of ambiguous information and enhancing the discriminability of snippet-level representations. Additionally, we propose feature consistency loss to prevent the assimilation of features and drive the graph convolution network to generate more discriminative representations. Extensive experiments on THUMOS14 and ActivityNet1.2 benchmarks demonstrate the effectiveness of DDG-Net, establishing new state-of-the-art results on both datasets. Source code is available at \url{https://github.com/XiaojunTang22/ICCV2023-DDGNet}., Comment: Accepted by ICCV2023

ZrO2-based ceramics are widely used in biomedical applications due to its color, biocompatibility, and excellent mechanical properties. However, low-temperature degradation (LTD) introduces a potential risk for long-term reliability of these materials. The development of innovative nondestructive techniques, which can explore LTD in zirconia-derived compounds, is strongly required. Yttria stabilized zirconia, 3Y-TZP, is one of the well-developed ZrO2-based ceramics with improved resistance to LTD for dental crown and implant applications. Here, 3Y-TZP ceramic powders were pressed and sintered to study the LTD phenomenon by phase transition behavior. The LTD-driven tetragonal-to-monoclinic phase transition was confirmed by XRD. XPS analysis demonstrated that induced LTD reduced the oxygen vacancies which supports these findings. It is proved that after the degradation, the 3Y-TZP ceramics show the decreased dielectric permittivity at terahertz frequencies due to the crystallographic phase transformation. Terahertz nondestructive probe is a promising method to investigate LTD in zirconia ceramics.

Controlling phase separation and transition plays a core role in establishing and maintaining the function of diverse self-assembled systems. However, it remains challenging to achieve wide-range continuous phase transition for dynamically producing a variety of assembled structures. Here, we developed a far-from-equilibrium system, upon the integration of photoexcitation-induced aggregation molecules and block copolymers, to establish an in situ phase-volume ratio photocontrol strategy. Thus, full-scale phase-diagram structures, from lamellar structure to gyroidal, cylindrical, and finally to a spherical one, can be accessed under different irradiation periods. Moreover, the phase transition was accompanied by considerable aggregation-induced phosphorescence and hydrophilicity/hydrophobicity change for building a functional surface. This strategy allows for a conceptual advance of accessing a wide range of distinct self-assembled structures and functions in real time.

In industry, RESTful APIs are widely used to build modern Cloud Applications. Testing them is challenging, because not only they rely on network communications, but also they deal with external services like databases. Therefore, there has been a large amount of research sprout in recent years on how to automatically verify this kind of web services. In this paper, we review the current state-of-the-art on testing RESTful APIs, based on an analysis of 92 scientific articles. This review categories and summarizes the existing scientific work on this topic, and discusses the current challenges in the verification of RESTful APIs.

The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces an automated solution for GraphQL APIs testing. We present a full framework for automated APIs testing, from the schema extraction to test case generation. In addition, we consider two kinds of testing: white-box and black-box testing. The white-box testing is performed when the source code of the GraphQL API is available. Our approach is based on evolutionary search. Test cases are evolved to intelligently explore the solution space while maximizing code coverage and fault-finding criteria. The black-box testing does not require access to the source code of the GraphQL API. It is therefore of more general applicability, albeit it has worse performance. In this context, we use a random search to generate GraphQL data. The proposed framework is implemented and integrated into the open-source EvoMaster tool. With enabled white-box heuristics, i.e., white-box mode, experiments on 7 open-source GraphQL APIs show statistically significant improvement of the evolutionary approach compared to the baseline random search. In addition, experiments on 31 online GraphQL APIs reveal the ability of the black-box mode to detect real faults.

Remote Procedure Call (RPC) is a communication protocol to support client-server interactions among services over a network. RPC is widely applied in industry for building large-scale distributed systems, such as Microservices. Modern RPC frameworks include for example Thrift, gRPC, SOFARPC and Dubbo. Testing such systems is very challenging, due to the complexity of distributed systems and various RPC frameworks the system could employ. To the best of our knowledge, there does not exist any tool or solution that could enable automated testing of modern RPC-based services. To fill this gap, in this paper we propose the first approach in the literature, together with an open-source tool, for white-box fuzzing modern RPC-based APIs with search. To assess our novel approach, we conducted an empirical study with two artificial and four industrial APIs selected by our industrial partner. The tool has been integrated into a real industrial pipeline, and could be applied to real industrial development process for fuzzing RPC-based APIs. To further demonstrate its effectiveness and application in industrial settings, we also report results of employing our tool for fuzzing another 50 industrial APIs autonomously conducted by our industrial partner in their testing processes. Results show that our novel approach is capable of enabling automated test case generation for industrial RPC-based APIs (i.e., two artificial and 54 industrial). We also compared with a simple grey-box technique and existing manually written tests. Our white-box solution achieves significant improvements on code coverage. Regarding fault detection, by conducting a careful review with our industrial partner of the tests generated by our novel approach in the selected four industrial APIs, a total of 41 real faults were identified, which have now been fixed. Another 8,377 detected faults are currently under investigation.

With several microservice architectures comprising of thousands of web services in total, used to serve 630 million customers, companies like Meituan face several challenges in the verification and validation of their software. The use of automated techniques, especially advanced AI-based ones, could bring significant benefits here. EvoMaster is an open-source test case generation tool for web services, that exploits the latest advances in the field of Search-Based Software Testing research. This paper reports on our experience of integrating the EvoMaster tool in the testing processes at Meituan. Experiments were carried out to evaluate its performance in detail on two industrial web services which are parts of a large e-commerce microservices. A questionnaire and interviews were carried out with the engineers and managers at Meituan, to better understand the applicability and usability of fuzzing tools like EvoMaster in real industrial settings. On the one hand, the results of these analyses clearly show that existing tools like EvoMaster are already of benefits for practitioners in industry, e.g., EvoMaster detected 21 real faults and achieved an average of 71.3% coverage for code defining endpoints and 51.7% coverage for code implementing business logic, on two industrial APIs. On the other hand, there are still many critical challenges that the research community has to investigate.

RESTful APIs are a type of web services that are widely used in industry. In the last few years, a lot of effort in the research community has been spent in designing novel techniques to automatically fuzz those APIs to find faults in them. Many real faults were automatically found in a large variety of RESTful APIs. However, usually the analyzed fuzzers treat the APIs as black-box, and no analysis of what is actually covered in these systems is done. Therefore, although these fuzzers are clearly useful for practitioners, we do not know what are their current limitations and actual effectiveness. Solving this is a necessary step to be able to design better, more efficient and effective techniques. To address this issue, in this paper we compare seven state-of-the-art fuzzers on 18 open-source and one industrial RESTful APIs. We then analyzed the source code of which parts of these APIs the fuzzers fail to generate tests for. This analysis points to clear limitations of these current fuzzers, listing concrete challenges for the research community to follow up on.

The mature soybean plants are of complex architecture with pods frequently touching each other, posing a challenge for in-situ segmentation of on-branch soybean pods. Deep learning-based methods can achieve accurate training and strong generalization capabilities, but it demands massive labeled data, which is often a limitation, especially for agricultural applications. As lacking the labeled data to train an in-situ segmentation model for on-branch soybean pods, we propose a transfer learning from synthetic in-vitro soybean pods. First, we present a novel automated image generation method to rapidly generate a synthetic in-vitro soybean pods dataset with plenty of annotated samples. The in-vitro soybean pods samples are overlapped to simulate the frequently physically touching of on-branch soybean pods. Then, we design a two-step transfer learning. In the first step, we finetune an instance segmentation network pretrained by a source domain (MS COCO dataset) with a synthetic target domain (in-vitro soybean pods dataset). In the second step, transferring from simulation to reality is performed by finetuning on a few real-world mature soybean plant samples. The experimental results show the effectiveness of the proposed two-step transfer learning method, such that AP$_{50}$ was 0.80 for the real-world mature soybean plant test dataset, which is higher than that of direct adaptation and its AP$_{50}$ was 0.77. Furthermore, the visualizations of in-situ segmentation results of on-branch soybean pods show that our method performs better than other methods, especially when soybean pods overlap densely., Comment: Accepted by CVPR 2022 Vision for Agriculture Workshop

Lake Taihu suffers from severe algal blooms every year, which is attributed primarily to the release of sediment phosphorus (P), namely the internal P loading. However, the overall internal P loading and the P hotspots in sediment have not been fully studied. This paper presents several methods, including sequential P extraction, the use of diffusive gradient in thin film (DGT), and intact core incubation to give a detailed investigation of sediment internal P loading as well as its roles in algal dominated zones (ADZs) and grass dominated zones (GDZs) in Lake Taihu. Sediment microbial composition was also analyzed to investigate its relationship with P fractions. The results indicate that the total P and the mobile P fraction in the ADZ sediments are generally higher than those of the GDZ sediments. The percentage of sediment mobile P to TP is similar to the mobile P in their distributions. In contrast, calcium bound P accounts for most of the TP in GDZ, while mobile P contributes the most to TP in ADZ. Overall, sediment can release 256 tons of TP and 217 tons of soluble reactive phosphorus (SRP) over a period of six months in the warmer seasons. Similarly, a high concentration of DGT-measured P was observed in ADZs that are recognized as P hotspots in Lake Taihu. Sediments in ADZ and GDZ was dominated by the bacteria Firmicutes and Proteobacteria, respectively and which were closely related with mobile P and calcium bound P in sediment, respectively. GZD seems to be able to retain more P in sediments, thereby reducing its contribution to of internal P loading. These results indicate that the difference in sediment composition between ADZ and GDZ affects their roles in sediment internal P loading, therefore, different management strategies should be used to combat sediment internal P loads in the two zones. © 2022

Significant progress has been made in direct air capture (DAC) in recent years. Evidence suggests that the large-scale deployment of DAC by adsorption would be technically feasible for gigatons of CO2 capture annually. However, great efforts in adsorption-based DAC technologies are still required. This review provides an exhaustive description of materials development, adsorbent shaping, in situ characterization, adsorption mechanism simulation, process design, system integration, and techno-economic analysis of adsorption-based DAC over the past five years; and in terms of adsorbent development, affordable DAC adsorbents such as amine-containing porous materials with large CO2 adsorption capacities, fast kinetics, high selectivity, and long-term stability under ultra-low CO2 concentration and humid conditions. It is also critically important to develop efficient DAC adsorptive processes. Research and development in structured adsorbents that operate at low-temperature with excellent CO2 adsorption capacities and kinetics, novel gas-solid contactors with low heat and mass transfer resistances, and energy-efficient regeneration methods using heat, vacuum, and steam purge is needed to commercialize adsorption-based DAC. The synergy between DAC and carbon capture technologies for point sources can help in mitigating climate change effects in the long-term. Further investigations into DAC applications in the aviation, agriculture, energy, and chemical industries are required as well. This work benefits researchers concerned about global energy and environmental issues, and delivers perspective views for further deployment of negative-emission technologies.

Huajie Yang,1,* Xiang Huang,2,* Chunyu Yang,3 Sufen Zhu,4 Xiaoyi Chen,5 Man Zhang,2 Xiao Yu,3 Harry HX Wang3,6,7 1School of Health Technology, Guangdong Open University (Guangdong Polytechnic Institute), Guangzhou, People’s Republic of China; 2Department of Public Health, Sanxiang Community Health Service Centre of Zhongshan, Zhongshan, People’s Republic of China; 3School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China; 4Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; 5School of Nursing, Sun Yat-Sen University, Guangzhou, People’s Republic of China; 6Department of General Practice, The Second Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 7JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region*These authors contributed equally to this workCorrespondence: Harry HX Wang, School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China, Tel +86 20 87330672, Email wanghx27@mail.sysu.edu.cn; haoxiangwang@cuhk.edu.hk Huajie Yang, School of Health Technology, Guangdong Open University (Guangdong Polytechnic Institute), Guangzhou, 510091, People’s Republic of China, Tel +86 760 89911522, Email hjyang@gdpi.edu.cnIntroduction: Time-to-treatment window is critical for managing acute ischaemic stroke. The community healthcare practitioners (CHPs) who deliver frontline care in the health system play an important role in stroke prevention and treatment.Methods: A multi-stage sampling design was adopted in Guangdong province, China. A total of 997 CHPs who participated in the survey were divided into two groups (the awareness group vs the unawareness group) according to their knowledge on the time window for stroke management. Logistic regression analysis was performed to explore factors associated with the awareness of “time windo

BackgroundSleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.MethodsThe study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.ResultsWe identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10-8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.ConclusionsWe have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

Objectives: To explore the associations of FKBP4 and FKBP5 gene polymorphisms with disease susceptibility, glucocorticoid (GC) efficacy, anxiety, depression, and health-related quality of life (HRQOL) in systemic lupus erythematosus (SLE) patients. Methods: All subjects were collected from the First and the Second Affiliated Hospital of Anhui Medical University in Hefei, China, during 2011 to 2015. In the case–control study, 541 SLE patients and 543 controls were recruited. In the follow-up study, 466 patients completed the 12-week follow-up and then were divided into GC-sensitive and GC-insensitive groups. Genotyping was determined using Multiplex SNaPshot technique. Data were analyzed using chi-square test and univariate and multivariate logistic regression analyses. Results: rs4713904, rs9368878, and rs7757037 of FKBP5 were associated with depression in SLE patients (rs4713904, PBH = 0.037; rs9368878, PBH = 0.001; rs7757037, PBH = 0.003). Moreover, rs4713904 was associated with GC efficacy in males with SLE (PBH = 0.011). The rs755658 of FKBP5 was associated with improvement in social function (PBH = 0.022) and mental component summary (PBH = 0.028). The rs4713907 of FKBP5 was related to improvement in total score of SF-36, bodily pain, and mental component summary score (all PBH = 0.018). Furthermore, the rs12582595 of FKBP4 was correlated with general health improvement (PBH = 0.033). No associations were seen between FKBP4/FKBP5 gene polymorphisms and SLE susceptibility and anxiety. Conclusions: FKBP5 gene polymorphisms may be associated with depression and GC efficacy of SLE patients. Meanwhile, the genetic polymorphisms of FKBP4 and FKBP5 genes may be associated with HRQOL improvement in SLE patients.Key Points• FKBP5 gene polymorphisms were associated with depression of SLE patients.• FKBP5 gene polymorph

Numerous efforts have been invested in improving the uniform rearrangement in photoinduced crystal engineering due to the fact that molecular ordering is hardly addressed via a traditional photochemical process as a whole. Herein, we present a nonequilibrium strategy, photoexcitation-induced molecular realignment, to manipulate crystal growth and transformation. This strategy allows a dynamic change of molecular conformation upon continuous photoirradiation, wherein the molecular structure remains intact. Consequently, crystal photomanipulation from solution growth to single crystals, polycrystals, and finally to doped films is achieved, accompanied by the phototuning of a series of crystal optical behaviors (e.g. absorption, refraction, fluorescence, and room-temperature phosphorescence). The developed materials are stable because of the molecular conformation kinetically trapped within the minimum energy on the basis of a steady-state design conception. This strategy, relying on the materialization of photoexcitation, provides a paradigm for controlling molecular ordering by light.

Controllable aggregation-induced emission luminogens (AIEgens) by photoexcitation can be conducted within a single solvent, thus opening new opportunities for preparing and processing smart materials. However, undesired side-reactions like photooxidation that can easily occur in the organic phase remain, limiting their applications. To enhance the operability of photoexcitation-controlled AIEgens (to specifically produce a phosphorescence characteristic) in the organic phase, in this work, we employ a typical prototype, hexathiobenzene, usually as the specific phosphorescent group, and investigate a series of physical and chemical factors, such as light intensity, dissolved oxygen content, and solvent polarity, to explore ways to control the photoexcitation-controllable AIEgens against the impurities from side-reactions. An organogel strategy was also developed to minimize interference factors and improve the practical application ability. We believe that the presented results provide new insights into the further development of the photoexcitation-based functional materials and the promotion of their practical usage.

Aggregation-induced emission (AIE) has been much employed for visualizing material aggregation and self-assembly. However, water is generally required for the preparation of the AIE aggregates, the operation of which limits numerous material processing behaviors. Employing hexathiobenzene-based small molecules, monopolymers, and block copolymers as different material prototypes, we herein achieve AIE in pure organic phases by applying a nonequilibrium strategy, photoexcitation-controlled aggregation. This strategy enabled a dynamic change of molecular conformation rather than chemical structure upon irradiation, leading to a continuous aggregation-dependent luminescent enhancement (up to similar to 200-fold increase of the luminescent quantum yield) in organic solvents. Accompanied by the materialization of the nonequilibrium strategy, photoconvertible self-assemblies with a steady-state characteristic can be achieved upon organic solvent processing. The visual monitoring with the luminescence change covered the whole solution-to-film transition, as well as the in situ photoprocessing of the solid-state materials.

Ferroelectric domain walls (DWs) are important nanoscale interfaces between two domains. It is widely accepted that ferroelectric domain walls work idly at terahertz (THz) frequencies, consequently discouraging efforts to engineer the domain walls to create new applications that utilize THz radiation. However, the present work clearly demonstrates the activity of domain walls at THz frequencies in a lead-free Aurivillius phase ferroelectric ceramic, Ca0.99Rb0.005Ce0.005Bi2Nb2O9, examined using THz-time-domain spectroscopy (THz-TDS). The dynamics of domain walls are different at kHz and THz frequencies. At low frequencies, domain walls work as a group to increase dielectric permittivity. At THz frequencies, the defective nature of domain walls serves to lower the overall dielectric permittivity. This is evidenced by higher dielectric permittivity in the THz band after poling, reflecting decreased domain wall density. An elastic vibrational model has also been used to verify that a single frustrated dipole in a domain wall represents a weaker contribution to the permittivity than its counterpart within a domain. The work represents a fundamental breakthrough in understanding the dielectric contributions of domain walls at THz frequencies. It also demonstrates that THz probing can be used to read domain wall dielectric switching.

It is crucial and desirable to develop green and high-efficient strategies to regulate solid-state structures and their related material properties. However, relative to solution, it is more difficult to break and generate chemical bonds in solid states. In this work, a rubbing-induced photoluminescence on the solid states of ortho-pyridinil phenol family was achieved. This rubbing response relied on an accurately designed topochemical tautomerism, where a negative charge, exactly provided by the triboelectric effect of a rubber, can induce a proton transfer in a double H-bonded dimeric structure. This process instantaneously led to a bright-form tautomer that can be stabilized in the solid-state settings, leading to an up to over 450-fold increase of the fluorescent quantum yield of the materials. The property can be repeatedly used due to the reversibility of the tautomerism, enabling encrypted applications. Moreover, a further modification to the structure can be accomplished to achieve different properties, opening up more possibilities for the design of new-generation smart materials. Changes in molecular properties due to stimuli response are critically important for the development of new materials. However, most processes are slow or inefficient in the solid state. Here the authors demonstrate property switching in the solid state using a rubbing-induced tautomerism in multiple hydrogen-bonded donor-acceptor couples.

Sodium saccharin is a common artificial sweetener. However, due to its possible carcinogenic effects and causing metabolic disorders, many countries have strictly regulated its use in food. In the study, we prepared a specific monoclonal antibody (mAb 2H11) using the new hapten (6-carboxylsaccharin) and developed a direct competitive enzyme-linked immunosorbent assay (dcELISA) for the screening of sodium saccharin residue in food. The half-maximum inhibition concentration (IC50 ) and working range (IC20 -IC80 , the concentrations causing 20% and 80% inhibition by sodium saccharin) were 32.5 and 6.47 to 164 ng/mL, which was 6.5 times more sensitive than the previously reported immunoassay. The average recoveries of sodium saccharin in spiked food samples detected by dcELISA ranged from 82.1% to 117%. Among 70 food samples bought in the physical stores and online, sodium saccharin residues were only detected in four samples purchased online (one canned pineapple, two winter jujube, and one kimchi). The content measured by dcELISA agreed well with those determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The developed dcELISA was proved to be a sensitive and accurate method for determining sodium saccharin in food. PRACTICAL APPLICATION: Quantitation of sodium saccharin residue in food is very necessary and important for consumers and regulatory agencies.

Ferroelectric materials exhibit anomalous behavior due to the presence of domains and domain walls which are related to the spontaneous polarization inherent in the crystal structure. Control of ferroelectric domains and domain walls has been used to enhance device performances in ultrasound, pyroelectric detectors, and photovoltaic systems with renewed interest in nanostructuring for energy applications. It is also known that ferroelectrics including domain walls can double photocatalytic rate and increase carrier lifetime from microsecond to millisecond. However, there remains a lack of understanding on the different contributions of the domain and domain walls to photocatalytic activities. Herein it is found, by comparing samples of nanostructured Ba(x)Sr(1-)(x)TiO(3)with and without a polar domain, that the material with polar domains has a faster reaction rate (k= 0.18 min(-1)) than the nonpolar one (k= 0.11 min(-1)). It is further revealed that the observed enhanced photoactivity of perovskite ferroelectric materials stems from the inherent polarization of the domain instead of domain walls. Here, the new understanding of the underlying physics of materials with a spontaneous dipole opens a door to enhance the performance of light induced energy harvesting systems.

The early presence of crops from East Asia and Southwest Asia in the Inner Asian Mountain Corridor (IAMC) has drawn attention to the Bronze Age mountain archaeology of Central Asia. Namely, the Bronze Age diffusion and utilization of grains in this region remains unknown as contrasts and extremes characterize the territory in environmental terms, especially elevation. Researchers continue to reflect on how, during the second millennium BC, Bronze Age populations used new crops and local animal resources to adapt to different elevation environments of the IAMC. In this study, we analyzed the 41 latest stable carbon and nitrogen isotopic results from human and faunal bones from six Bronze Age sites in the IAMC, 261 previously published stable isotopic datasets, and 12 archaeobotanical and four zooarchaeological results to investigate the dietary strategies of populations from different elevation environments in the Bronze Age IAMC. The results show an altitudinal gradient in dietary choices among Bronze Age populations in the IAMC, with mixed C-4 and C-3 consumption at the low-mid elevations and notable C-3 consumption at the high elevations. Archaeobotanical and faunal remains also support these isotopic results. Our study further highlights that the differentiated dietary strategies adopted by the Bronze Age population in IAMC may have been the product of adaptation to local geographic environments. Social interaction may have also played a role in certain types of special dietary consumption.

Background The outbreak of coronavirus disease 2019 (COVID-19) has posed stress on the health and well-being of both Chinese people and the public worldwide. Global public interest in this new issue largely reflects people's attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine global public awareness of COVID-19 using Google Trends. Methods Using Google Trends, we retrieved public query data for terms of "2019-nCoV + SARS-CoV-2 + novel coronavirus + new coronavirus + COVID-19 + Corona Virus Disease 2019" between the 31st December 2019 and the 24th February 2020 in six major English-speaking countries, including the USA, the UK, Canada, Ireland, Australia, and New Zealand. Dynamic series analysis demonstrates the overall change trend of relative search volume (RSV) for the topic on COVID-19. We compared the top-ranking related queries and sub-regions distribution of RSV about COVID-19 across different countries. The correlation between daily search volumes on the topic related to COVID-19 and the daily number of people infected with SARS-CoV-2 was analyzed. Results The overall search trend of RSV regarding COVID-19 increased during the early period of observing time and reached the first apex on 31st January 2020. A shorter response time and a longer duration of public attention to COVID-19 was observed in public from the USA, the UK, Australia, and Canada, than that in Ireland and New Zealand. A slightly positive correlation between daily RSV about COVID-19 and the daily number of confirmed cases was observed (P < 0.05). People across countries presented a various interest to the RSV on COVID-19, and public awareness of COVID-19 was different in various sub-regions within countries. Conclusions The results suggest that public response time to COVID-19 was different across countries, and the overall duration of public attention was short. The current study reminds us that governments should strengthen the publicity

The early presence of crops from East Asia and Southwest Asia in the Inner Asian Mountain Corridor (IAMC) has drawn attention to the Bronze Age mountain archaeology of Central Asia. Namely, the Bronze Age diffusion and utilization of grains in this region remains unknown as contrasts and extremes characterize the territory in environmental terms, especially elevation. Researchers continue to reflect on how, during the second millennium BC, Bronze Age populations used new crops and local animal resources to adapt to different elevation environments of the IAMC. In this study, we analyzed the 41 latest stable carbon and nitrogen isotopic results from human and faunal bones from six Bronze Age sites in the IAMC, 261 previously published stable isotopic datasets, and 12 archaeobotanical and four zooarchaeological results to investigate the dietary strategies of populations from different elevation environments in the Bronze Age IAMC. The results show an altitudinal gradient in dietary choices among Bronze Age populations in the IAMC, with mixed C-4 and C-3 consumption at the low-mid elevations and notable C-3 consumption at the high elevations. Archaeobotanical and faunal remains also support these isotopic results. Our study further highlights that the differentiated dietary strategies adopted by the Bronze Age population in IAMC may have been the product of adaptation to local geographic environments. Social interaction may have also played a role in certain types of special dietary consumption.

Analog and digital converters (ADCs) are the most inevitable part of today’s high-speed human interacted devices. Continuous efforts are being made to improve their performance. Despite working for the improvement of whole ADC, efforts to improve sub-modules are also significant. Comparators are also a vital part of ADC. In this work, we have proposed a novel high-speed Balanced-Input Balanced-Output (BIBO) preamplifier latch based comparator design, to be used for the designing of an Asynchronous Successive Approximation Resister (SAR) ADC. In order to make comparison faster, we have employed Preamplifier-Latch based comparator. Transistor fingering is used to save area and makes large transistor easy to handle without changing their aspect ratio. We have implemented this latch using two back to back connected inverters. These inverters are farming a positive feedback arrangement that also prohibits the comparator from bursting into the oscillation. Latch circuit uses three non-overlapping phases namely phi1, phi2 and phi3 and dissipates less power when operated on a single 1V supply voltage. All these features collectively made this comparator expedient and obtained results confirm that it can be used effectively for the designing of SAR ADC.

The aim of our study was to assess the associations of HSP90AB1 copy number variations (CNVs) with systemic lupus erythematosus (SLE) risk and glucocorticoids (GCs) efficacy, as well as the relationship between HSP90AB1 single-nucleotide polymorphisms (SNPs) and GCs efficacy. HSP90AB1 CNVs and SLE risk were analysed in 519 patients and 538 controls. Patients treated with GCs were followed up for 12 weeks and were divided into sensitive and insensitive groups to investigate the effects of CNVs (419 patients) and SNPs (457 patients) on the efficacy of GCs. Health-related quality of life (HRQoL) was also measured by SF-36 at baseline and week 12 to explore the relationship between CNVs/SNPs and HRQoL improvements in Chinese SLE patients. Our results indicated a statistically significant association between HSP90AB1 CNVs and SLE (PBH = 0.039), and this association was more pronounced in the female subgroup (PBH = 0.039). However, we did not detect association of HSP90AB1 CNVs/SNPs with efficacy of GCs. But we found a marginal association between SNP rs13296 and improvement in Role-emotional, while this association was not strong enough to survive in the multiple testing corrections. Collectively, our findings suggest that the copy number of HSP90AB1 is associated with SLE susceptibility. But copy number and polymorphisms of HSP90AB1 may not be associated with efficacy of GCs.

Local adaptation to climate allows plants to cope with temporally and spatially heterogeneous environments, and parallel phenotypic clines provide a natural experiment to uncover the genomic architecture of adaptation. Though extensive effort has been made to investigate the genomic basis of local adaptation to climate across the latitudinal range of tree species, less is known for altitudinal clines. We used exome capture to genotype 451 Populus trichocarpa genotypes across altitudinal and latitudinal gradients spanning the natural species range, and phenotyped these trees for a variety of adaptive traits in two common gardens. We observed clinal variation in phenotypic traits across the two transects,which indicates climate-driven selection, and coupled gene-based genotype–phenotype and genotype–environment association scans to identify imprints of climatic adaptation on the genome. Although many of the phenotype-and climate-associated genes were unique to one transect, we found evidence of parallelism between latitude and altitude, as well as significant convergence when we compared our outlier genes with those putatively involved in climatic adaptation in two gymnosperm species. These results suggest that not only genomic constraint during adaptation to similar environmental gradients in poplar but also different environmental contexts, spatial scale, and perhaps redundant function among potentially adaptive genes and polymorphisms lead to divergent adaptive architectures.