Green Construction: Status and Prospects of Shenzhen Construction Industry’s “Double Carbon” Goal

Shenzhen has extensive green construction experience as one of China’s new green development pilot cities.Shenzhen has experienced substantial economic growth as a result of the reform and opening up,but it has also had to face the burden of urbanization problems and difficulties.This article looks at the history of green construction in Shenzhen and how the spirit of the city influenced it.The work then divides the procedure into two phases and examines the issues that arise.Suggestions for achieving the“Double Carbon”aim in the building industry are sought through this effort.

Improved Design of a Hydraulically Expanded Overhead Cylinder for an Automotive Torsion Beam

The design of hydro-bulge molds,able to provide hollow parts with special-shaped cross-sections,is still a pretty complicated task(especially for what concerns the design of the related hydraulic system and its“synchronization”).In the present work,this task is addressed through the introduction of a new type of overhead cylinder hydraulic synchronization system,able to correct automatically any deviation from the optimal process.Using the AMESim software,the displacement synchronization curve of the piston rods of the two cylinders is obtained and it is verified that the system is able to implement an automatic deviation correction function by adjusting the bidirectional servo valve.A mathematical model for the synchronization system is presented,and the transfer function of the closed-loop control system is determined accordingly.The results show that the system response is generated at about 0.1∼0.2 s with the system reaching an equilibrium state at about 0.2 s.

Decoding hereditary spastic paraplegia pathogenicity through transcriptomic profiling

Hereditary spastic paraplegia(HSP)is a group of genetic motor neuron diseases resulting from length-dependent axonal degeneration of the corticospinal upper motor neurons.Due to the advancement of next-generation sequencing,more than 70 novel HSP disease-causing genes have been identified in the past decade.Despite this,our understanding of HSP physiopathology and the development of efficient management and treatment strategies remain poor.One major challenge in studying HSP pathogenicity is selective neuronal vulnerability,characterized by the manifestation of clinical symptoms that are restricted to specific neuronal populations,despite the presence of germline disease-causing variants in every cell of the patient.Furthermore,disease genes may exhibit ubiquitous expression patterns and involve a myriad of different pathways to cause motor neuron degeneration.In the current review,we explore the correlation between transcriptomic data and clinical manifestations,as well as the importance of interspecies models by comparing tissue-specific transcriptomic profiles of humans and mice,expression patterns of different genes in the brain during development,and single-cell transcriptomic data from related tissues.Furthermore,we discuss the potential of emerging single-cell RNA sequencing technologies to resolve unanswered questions related to HSP pathogenicity.

Antitumor activity of miR-188-3p in gastric cancer is achieved by targeting CBL expression and inactivating the AKT/mTOR signaling

BACKGROUND Altered miR-188-3p expression has been observed in various human cancers.AIM To investigate the miR-188-3p expression,its roles,and underlying molecular events in gastric cancer.METHODS Fifty gastric cancer and paired normal tissues were collected to analyze miR-188-3p and CBL expression.Normal and gastric cancer cells were used to manipulate miR-188-3p and CBL expression through different assays.The relationship between miR-188-3p and CBL was predicted bioinformatically and confirmed using a luciferase gene reporter assay.A Kaplan-Meier analysis was used to associate miR-188-3p or CBL expression with patient survival.A nude mouse tumor cell xenograft assay was used to confirm the in vitro data.RESULTS MiR-188-3p was found to be lower in the plasma of gastric cancer patients,tissues,and cell lines compared to their healthy counterparts.It was associated with overall survival of gastric cancer patients(P<0.001),tumor differentiation(P<0.001),lymph node metastasis(P=0.033),tumor node metastasis stage(I/II vs III/IV,P=0.024),and American Joint Committee on Cancer stage(I/II vs III/IV,P=0.03).Transfection with miR-188-3p mimics reduced tumor cell growth and invasion while inducing apoptosis and autophagy.CBL was identified as a direct target of miR-188-3p,with its expression antagonizing the effects of miR-188-3p on gastric cancer(GC)cell proliferation by inducing tumor cell apoptosis and autophagy through the inactivation of the Akt/mTOR signaling pathway.The in vivo data confirmed antitumor activity via CBL downregulation in gastric cancer.CONCLUSION The current data provides ex vivo,in vitro,and in vivo evidence that miR-188-3p acts as a tumor suppressor gene or possesses antitumor activity in GC.

A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence

Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of diabetes.At present,deep convolutional neural networks have achieved promising performance in automatic DR detection tasks.The convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for processing.However,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(e.g.hemorrhages and exudates)scattered throughout the whole image.The proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR detection.Patch-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as plaques.The Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained networks.Extensive experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets.

Use of graphene-based materials as carriers of bioactive agents

Graphene possesses a large specific surface area, a high Young’s modulus, high fracture strength, high electrical conductivity, and excellent optical performance. It has been widely studied for biomedical use since its first appearance in the literature. This article offers an overview of the latest advances in the design of graphene-based materials for delivery of bioactive agents. To enhance the translation of these carriers into practical use, the toxicity involved is needed to be examined in future research in more detail. In addition, guidelines for standardizing experimental conditions during the evaluation of the performance of graphene-based materials are required to be established so that candidates showing higher practical potential can be more effectively identified for further development. This can streamline the optimization and use of graphene-based materials in delivery applications.

Alginate-based complex fibers with the Janus morphology for controlled release of co-delivered drugs

Hydrogels are soft materials consisting of a three-dimensional network of polymer chains.Over the years,hydrogels with different compositions have been developed as drug carriers for diverse biomedical applications,ranging from cancer therapy and wound care to the treatment of neurodegenerative and inflammatory diseases.Most of these carriers,however,are designed only to deliver single agents.Carriers based on hydrogels for co-delivery of multiple agents,with the release rate of each of the co-delivered agents tunable,are lacking.This study reports a one-pot method of fabricating alginate-based complex fibers with the Janus morphology,with carboxymethyl cellulose sodium functioning as a polymeric modifier of the properties of each of the fiber compartments.By using malachite green and minocycline hydrochloride as model drugs,the generated fibers demonstrate the capacity of enabling the release profile of each of the co-delivered drugs to be precisely controlled.Along with their negligible toxicity and the retention of the activity of the loaded drugs,the complex fibers reported in this study warrant further development and optimization for applications that involve co-delivery of multiple agents.

Research on the Multiple Exclusion Phenomenon in the Chinese“Core Weeaboo”Group

Among the subcultures that have developed rapidly in recent years,weeaboo culture covers a growing number of people.Meanwhile,corresponding differentiation has taken place among the weeaboos,typically including“core weeaboo”group and“pan weeaboo”group.Generally,“core weeaboos”refer to a group of people who are deeply involved in the weeaboo culture.On one hand,in the online community,“core weeaboos”tend to reject normal interaction with“pan weeaboos”,who they think are not deeply involved in the culture;on the other hand,due to the long-term prejudice of the mainstream culture against the weeaboos,the“core weeaboo”group has also suffered from the exclusion from the mainstream culture for a long time,thus forming a unique chain of“multiple exclusion”.With the“core weeaboo”group as the research object,this paper conducts online and field research on the phenomenon of“multiple exclusion”in the relevant groups by means of questionnaire and interview.It is found that the phenomenon of“multiple exclusion”in essence can be considered a two-way interaction between the“core weeaboo”group and the mainstream culture.In order to alleviate this phenomenon,this paper advocates that mainstream culture should increase its understanding of subcultural groups,and actively encourage high-quality“fusion”,so as to reduce the adverse effects on corresponding subcultural groups.

磁控微机器人的选择性与独立控制——综述

磁驱动方法具有无线连接和高安全性的特点,是一种常见的微机器人驱动技术,适用于微流体操作以及医疗微机器人导航等应用。然而,由于微型机器人或被驱动的目标暴露在同一片磁场环境中的,使得选择性地控制单个机器人或多个目标中的某一部分变得具有挑战性。本文回顾了磁场驱动的多微型机器人或多关节微型机器人系统的选择性和独立控制方法的最新进展。这些选择性和独立的控制方法将全局磁场解码为特定配置,用于多个微型机器人的独立驱动。这些方法包括将机器人设计成具有与众不同的物理属性或者在工作空间中的不同位置产生性质各异的磁场。对选定目标的独立控制使多个微型机器人能够有效协作以完成更复杂的操作。在这篇综述中,我们提供了一个独特的视角来解释如何在磁场中操纵单个微型机器人以在小尺度机器人中实现高水平的群体智能,这有助于加速微型机器人技术在现实生活中应用的转化和发展。

Structural insights into substrate recognition and translocation of human peroxisomal ABC transporter ALDP

Dysfunctions of ATP-binding cassette,subfamily D,member 1(ABCD1)cause X-linked adrenoleukodystrophy,a rare neurodegenerative disease that affects all human tissues.Residing in the peroxisome membrane,ABCD1 plays a role in the translocation of very long-chain fatty acids for theirβ-oxidation.Here,the six cryo-electron microscopy structures of ABCD1 in four distinct conformational states were presented.In the transporter dimer,two transmembrane domains form the substrate translocation pathway,and two nucleotide-binding domains form the ATP-binding site that binds and hydrolyzes ATP.The ABCD1 structures provide a starting point for elucidating the substrate recognition and translocation mechanism of ABCD1.Each of the four inward-facing structures of ABCD1 has a vestibule that opens to the cytosol with variable sizes.Hexacosanoic acid(C26:0)-CoA substrate binds to the transmembrane domains(TMDs)and stimulates the ATPase activity of the nucleotide-binding domains(NBDs).W339 from the transmembrane helix 5(TM5)is essential for binding substrate and stimulating ATP hydrolysis by substrate.ABCD1 has a unique C-terminal coiled-coil domain that negatively modulates the ATPase activity of the NBDs.Furthermore,the structure of ABCD1 in the outward-facing state indicates that ATP molecules pull the two NBDs together and open the TMDs to the peroxisomal lumen for substrate release.The five structures provide a view of the substrate transport cycle and mechanistic implication for disease-causing mutations.

ANOTHER ‘CHINA SHOCK?’

During U.S.Treasury Secretary Janet Yellen's April visit to China,one of the issues covered was the U.S.concern about China's“overcapacity.”Since late 2023,the U.S.has claimed that in China-U.S.economic relations,the most pressing issue facing the Biden administration is the“threat”posed by China's exports of green en-ergy products on the U.S.'trillion-dollar industries.

Impact analysis of false data injection attacks on power system static security assessment

Static security assessment(SSA) is an important procedure to ensure the static security of the power system.Researches recently show that cyber-attacks might be a critical hazard to the secure and economic operations of the power system. In this paper, the influences of false data injection attack(FDIA) on the power system SSA are studied. FDIA is a major kind of cyber-attacks that can inject malicious data into meters, cause false state estimation results, and evade being detected by bad data detection. It is firstly shown that the SSA results could be manipulated by launching a successful FDIA, which can lead to incorrect or unnecessary corrective actions. Then,two kinds of targeted scenarios are proposed, i.e., fake secure signal attack and fake insecure signal attack. The former attack will deceive the system operator to believe that the system operates in a secure condition when it is actually not. The latter attack will deceive the system operator to make corrective actions, such as generator rescheduling, load shedding, etc. when it is unnecessary and costly. The implementation of the proposed analysis is validated with the IEEE-39 benchmark system.

The era of personalized treatments:Updates on immunotherapy within urothelial of bladder cancer

Bladder cancer is a complex disease of the urinary system with high morbidity and mortality.Recently,the introduction of immunother-apies such as immune checkpoint inhibitors(eg,programmed cell death protein 1/programmed death-ligand 1)has proven to be a re-liable means of improving survival outcomes,including patients with limited response to conventional treatment.Nevertheless,difficult questions remain in clinical practice,such as how to select appropriate patients for personalized treatment,how to predict and assess therapeutic efficacy in advance,and how to enhance the therapeutic benefits of immunotherapy treatment.These issues require urgent attention.Herein,we describe recent clinical applications of immune checkpoint inhibitors in bladder cancer therapy,examine underlying mechanisms for treatment failure in a subset of patients,and discuss potential approaches to improve their therapeutic effects.

Magnetically driven microrobots moving in a flow:a review

Magnetically driven microrobots hold great potential to perform specific tasks more locally and less invasively in the human body.To reach the lesion area in vivo,microrobots should usually be navigated in flowing blood,which is much more complex than static liquid.Therefore,it is more challenging to design a corresponding precise control scheme.A considerable amount of work has been done regarding control of magnetic microrobots in a flow and the corresponding theories.In this paper,we review and summarize the state-of-the-art research progress concerning magnetic microrobots in blood flow,including the establishment of flow systems,dynamics modeling of motion,and control methods.In addition,current challenges and limitations are discussed.We hope this work can shed light on the efficient control of microrobots in complex flow environments and accelerate the study of microrobots for clinical use.

Controlled islanding schemes for interconnected power systems based on coherent generator group identification and wide-area measurements

A reasonable islanding strategy of a power system is the final resort for preventing a cascading failure and/or a large-area blackout from occurrence. In recent years, the applications of wide area measurement systems(WAMS) in emergency control of power systems are increasing. Therefore, a new WAMS-based controlled islanding scheme for interconnected power systems is proposed. First, four similarity indexes associated with the trajectories of generators are defined, and the weights of these four indexes are determined by using the well-developed entropy theory. Then, a coherency identification algorithm based on hierarchical clustering is presented to determine the coherent groups of generators.Secondly, an optimization model for determining controlled islanding schemes based on the coherent groups of generators is developed to seek the optimal cutset. Finally, a 16-generator68-bus power system and a reduced WECC 29-unit 179-bus power system are employed to demonstrate the proposed WAMS-based controlled islanding schemes, and comparisons with existing slow coherency based controlled islanding strategies are also carried out.

Electric Load Clustering in Smart Grid:Methodologies,Applications,and Future Trends

With the increasingly widespread of advanced metering infrastructure,electric load clustering is becoming more essential for its great potential in analytics of consumers’energy consumption patterns and preference through data mining.Moreover,a variety of electric load clustering techniques have been put into practice to obtain the distribution of load data,observe the characteristics of load clusters,and classify the components of the total load.This can give rise to the development of related techniques and research in the smart grid,such as demand-side response.This paper summarizes the basic concepts and the general process in electric load clustering.Several similarity measurements and five major categories in electric load clustering are then comprehensively summarized along with their advantages and disadvantages.Afterwards,eight indices widely used to evaluate the validity of electric load clustering are described.Finally,vital applications are discussed thoroughly along with future trends including the tariff design,anomaly detection,load forecasting,data security and big data,etc.

Theory and techniques for“intellicise”wireless networks

With the acceleration of a new round of global scientific,technological,and industrial revolution,the next generation of information and communication technology,i.e.,6G,will inject new momentum into industry transformation and upgrading,as well as into economic innovation and development.This will subsequently promote a global industrial integration.Wireless communication will be ubiquitous in all areas of future society,supporting novel applications with various performance requirements.

A Super-resolution Perception-based Incremental Learning Approach for Power System Voltage Stability Assessment with Incomplete PMU Measurements

This paper develops a fully data-driven,missingdata tolerant method for post-fault short-term voltage stability(STVS)assessment of power systems against the incomplete PMU measurements.The super-resolution perception(SRP),based on a deep residual learning convolutional neural network,is employed to cope with the missing PMU measurements.The incremental broad learning(BL)is used to rapidly update the model to maintain and enhance the online application performance.Being different from the state-of-the-art methods,the proposed method is fully data-driven and can fill up missing data under any PMU placement information loss and network topology change scenario.Simulation results demonstrate that the proposed method has the best performance in terms of STVS assessment accuracy and missing-data tolerance among the existing methods on the benchmark testing system.

Dividend or No Dividend in Delegated Blockchain Governance:A Game Theoretic Analysis

Delegated blockchain governance is the frontier of blockchain design issues that is to improve the scalability of blockchain networks.Delegated proof of stake(DPoS)blockchains such as EOS must select a few super nodes for transaction verification.In particular,the blockchain community has debated recently on whether dividend should be allowed when electing super nodes,which might be considered as unethical or unfair,leading to an open research topic and a new research gap that has theoretical value for both academia and industry.In this paper,we build a theoretical framework to study how dividend affects user decisions and welfare in a DPoS blockchain.Based on game theory,we propose a three-player Hotelling model with two policies to study the behaviors of voters and candidates.We first use a static game analysis to show that the benefits of dividend for voters and for candidates vary with the size of reward and there exists an interval,in which the zero dividend policy would be good for the welfare of both candidates and voters.Then,we use an evolutionary game analysis to examine the process dynamics of super node selection,we find that the campaign strategy of candidates has to do with the size of platform reward given to the candidates by the blockchain platform.Especially in the asymmetric case,we find that higher level of platform reward turns to benefit candidates with large number of votes even more.Our findings are instrumental for designing dividend policies in DPoS blockchains and can stimulate more potential research in blockchain governance.

Attention shifting during child-robot interaction:a preliminary clinical study for children with autism spectrum disorder

There is an increasing need to introduce socially interactive robots as a means of assistance in autism spectrum disorder(ASD) treatment and rehabilitation, to improve the effectiveness of rehabilitation training and the diversification of treatment, and to alleviate the shortage of medical personnel in China's Mainland and other places in the world. In this preliminary clinical study, three different socially interactive robots with different appearances and functionalities were tested in therapy-like settings in four different rehabilitation facilities/institutions in Shenzhen, China. Seventy-four participants, including 52 children with ASD, whose processes of interacting with robots were recorded by three different cameras, all received a single-session three-robot intervention. Data were collected from not only the videos recorded, but also the questionnaires filled mostly by parents of the participants. Some insights from the preliminary results were obtained. These can contribute to the research on physical robo it design and evaluations on robots in therapy-like settings. First, when doing physical robot design, some preferential focus should be on aspects of appearances and functionalities. Second, attention analysis using algorithms such as estimation of the directions of gaze and head posture of a child in the video clips can be adopted to quantitatively measure the prosocial behaviors and actions(e.g., attention shifting from one particular robot to other robots) of the children. Third, observing and calculating the frequency of the time children spend on exploring/playing with the robots in the video clips can be adopted to qualitatively analyze such behaviors and actions. Limitations of the present study are also presented.