Evolution of United States Technology Alliance Strategy and Reshaping of International Strategic Landscape

Building a technology alliance is the main strategy for the United States to maintain its scientific and technological hegemony under its technopolitical strategic framework.After Joe Biden took office,the United States implemented“small yard with high fences”strategy for scientific and technological competition,as the first step toward building a technology alliance.The main goal is to restrict the flow of strategic emerging technologies and factors of innovation to rival countries.

Zero-determinant strategies in iterated multi-strategy games

Self-serving,rational agents sometimes cooperate to their mutual benefit.The two-player iterated prisoner′s dilemma game is a model for including the emergence of cooperation.It is generally believed that there is no simple ultimatum strategy which a player can control the return of the other participants.The zero-determinant strategy in the iterated prisoner′s dilemma dramatically expands our understanding of the classic game by uncovering strategies that provide a unilateral advantage to sentient players pitted against unwitting opponents.However,strategies in the prisoner′s dilemma game are only two strategies.Are there these results for general multi-strategy games?To address this question,the paper develops a theory for zero-determinant strategies for multi-strategy games,with any number of strategies.The analytical results exhibit a similar yet different scenario to the case of two-strategy games.The results are also applied to the Snowdrift game,the Hawk-Dove game and the Chicken game.

Cavitation Diagnostics Based on Self-Tuning VMD for Fluid Machinery with Low-SNR Conditions

Variational mode decomposition(VMD)is a suitable tool for processing cavitation-induced vibration signals and is greatly affected by two parameters:the decomposed number K and penalty factorαunder strong noise interference.To solve this issue,this study proposed self-tuning VMD(SVMD)for cavitation diagnostics in fluid machinery,with a special focus on low signal-to-noise ratio conditions.A two-stage progressive refinement of the coarsely located target penalty factor for SVMD was conducted to narrow down the search space for accelerated decomposition.A hybrid optimized sparrow search algorithm(HOSSA)was developed for optimalαfine-tuning in a refined space based on fault-type-guided objective functions.Based on the submodes obtained using exclusive penalty factors in each iteration,the cavitation-related characteristic frequencies(CCFs)were extracted for diagnostics.The power spectrum correlation coefficient between the SVMD reconstruction and original signals was employed as a stop criterion to determine whether to stop further decomposition.The proposed SVMD overcomes the blindness of setting the mode number K in advance and the drawback of sharing penalty factors for all submodes in fixed-parameter and parameter-optimized VMDs.Comparisons with other existing methods in simulation signal decomposition and in-lab experimental data demonstrated the advantages of the proposed method in accurately extracting CCFs with lower computational cost.SVMD especially enhances the denoising capability of the VMD-based method.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

System Identification and Parameter Self-Tuning Controller on Deep-Sea Mining Vehicle

System identification is a quintessential measure for real-time analysis on kinematic characteristics for deep-sea mining vehicle, and thus to enhance the control performance and testing efficiency. In this study, the system identification algorithm, recursive least square method with instrumental variables(IV-RLS), is tailored to model ‘Pioneer I’, a deep-sea mining vehicle which recently completed a 1305-meter-deep sea trial in the Xisha area of the South China Sea in August, 2021. The algorithm operates on the sensor data collected from the trial to obtain the vehicle’s kinematic model and accordingly design the parameter self-tuning controller. The performances demonstrate the accuracy of the model, and prove its generalization capability. With this model, the optimal controller has been designed, the control parameters have been self-tuned, and the response time and robustness of the system have been optimized,which validates the high efficiency on digital modelling for precision control of deep-sea mining vehicles.

Engineering Strategies for Suppressing the Shuttle Effect in Lithium–Sulfur Batteries

Lithium–sulfur(Li–S)batteries are supposed to be one of the most potential next-generation batteries owing to their high theoretical capacity and low cost.Nevertheless,the shuttle effect of firm multi-step two-electron reaction between sulfur and lithium in liquid electrolyte makes the capacity much smaller than the theoretical value.Many methods were proposed for inhibiting the shuttle effect of polysulfide,improving corresponding redox kinetics and enhancing the integral performance of Li–S batteries.Here,we will comprehensively and systematically summarize the strategies for inhibiting the shuttle effect from all components of Li–S batteries.First,the electrochemical principles/mechanism and origin of the shuttle effect are described in detail.Moreover,the efficient strategies,including boosting the sulfur conversion rate of sulfur,confining sulfur or lithium polysulfides(LPS)within cathode host,confining LPS in the shield layer,and preventing LPS from contacting the anode,will be discussed to suppress the shuttle effect.Then,recent advances in inhibition of shuttle effect in cathode,electrolyte,separator,and anode with the aforementioned strategies have been summarized to direct the further design of efficient materials for Li–S batteries.Finally,we present prospects for inhibition of the LPS shuttle and potential development directions in Li–S batteries.

Drug resistance mechanisms in cancers:Execution of prosurvival strategies

One of the quintessential challenges in cancer treatment is drug resistance.Several mechanisms of drug resistance have been described to date,and new modes of drug resistance continue to be discovered.The phenomenon of cancer drug resistance is now widespread,with approximately 90% of cancer-related deaths associated with drug resistance.Despite significant advances in the drug discovery process,the emergence of innate and acquired mechanisms of drug resistance has impeded the progress in cancer therapy.Therefore,understanding the mechanisms of drug resistance and the various pathways involved is integral to treatment modalities.In the present review,I discuss the different mechanisms of drug resistance in cancer cells,including DNA damage repair,epithelial to mesenchymal transition,inhibition of cell death,alteration of drug targets,inactivation of drugs,deregulation of cellular energetics,immune evasion,tumor-promoting inflammation,genome instability,and other contributing epigenetic factors.Furthermore,I highlight available treatment options and conclude with future directions.

How do the landslide and non-landslide sampling strategies impact landslide susceptibility assessment? d A catchment-scale case study from China

The aim of this study is to investigate the impacts of the sampling strategy of landslide and non-landslide on the performance of landslide susceptibility assessment(LSA).The study area is the Feiyun catchment in Wenzhou City,Southeast China.Two types of landslides samples,combined with seven non-landslide sampling strategies,resulted in a total of 14 scenarios.The corresponding landslide susceptibility map(LSM)for each scenario was generated using the random forest model.The receiver operating characteristic(ROC)curve and statistical indicators were calculated and used to assess the impact of the dataset sampling strategy.The results showed that higher accuracies were achieved when using the landslide core as positive samples,combined with non-landslide sampling from the very low zone or buffer zone.The results reveal the influence of landslide and non-landslide sampling strategies on the accuracy of LSA,which provides a reference for subsequent researchers aiming to obtain a more reasonable LSM.

Overview of the immunological mechanisms in hepatitis B virus reactivation:Implications for disease progression and management strategies

Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

LDAS&ET-AD:Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation

Adversarial distillation(AD)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial training.However,fixed sample-agnostic and student-egocentric attack strategies are unsuitable for distillation.Additionally,the reliability of guidance from static teachers diminishes as target models become more robust.This paper proposes an AD method called Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation(LDAS&ET-AD).Firstly,a learnable distillation attack strategies generating mechanism is developed to automatically generate sample-dependent attack strategies tailored for distillation.A strategy model is introduced to produce attack strategies that enable adversarial examples(AEs)to be created in areas where the target model significantly diverges from the teachers by competing with the target model in minimizing or maximizing the AD loss.Secondly,a teacher evolution strategy is introduced to enhance the reliability and effectiveness of knowledge in improving the generalization performance of the target model.By calculating the experimentally updated target model’s validation performance on both clean samples and AEs,the impact of distillation from each training sample and AE on the target model’s generalization and robustness abilities is assessed to serve as feedback to fine-tune standard and robust teachers accordingly.Experiments evaluate the performance of LDAS&ET-AD against different adversarial attacks on the CIFAR-10 and CIFAR-100 datasets.The experimental results demonstrate that the proposed method achieves a robust precision of 45.39%and 42.63%against AutoAttack(AA)on the CIFAR-10 dataset for ResNet-18 and MobileNet-V2,respectively,marking an improvement of 2.31%and 3.49%over the baseline method.In comparison to state-of-the-art adversarial defense techniques,our method surpasses Introspective Adversarial Distillation,the top-performing method in terms of robustness under AA attack for the CIFAR-10 dataset,with enhancements of 1.40%and 1.43%for ResNet-18 and MobileNet-V2,respectively.These findings demonstrate the effectiveness of our proposed method in enhancing the robustness of deep learning networks(DNNs)against prevalent adversarial attacks when compared to other competing methods.In conclusion,LDAS&ET-AD provides reliable and informative soft labels to one of the most promising defense methods,AT,alleviating the limitations of untrusted teachers and unsuitable AEs in existing AD techniques.We hope this paper promotes the development of DNNs in real-world trust-sensitive fields and helps ensure a more secure and dependable future for artificial intelligence systems.

Interpretation of Chinese Expert Consensus on the Diagnosis and Management Strategy of Patients with Statin Intolerance: A guiding file for helping to lipid management for Chinese population

It is well-known that elevated low-density lipoprotein cholesterol(LDL-C)is a causal risk factor for atheroscler-otic cardiovascular disease(ASCVD),statins are cornerstone drugs for the cause-based treatment of ASCVD,which has created a new era for ASCVD therapy.However,statin intolerance is not clinically uncommon,which there are several issues with confu-sion and misunderstandings.Hence,a file named Chinese Expert Consensus on the Diagnosis and Management Strategy of Pa-tients With Statin Intolerance,like a navigator,has recently been published written by a team of experts from the Cardiovascular Metabolic Medicine Professional Committee,Expert Committee of the National Center for Cardiovascular Diseases aiming to en-hance the standardized clinical application of statins and improve the prevention and clinical outcome.In this article,author briefly summarized the key points of above consensus in order to helping to comprehending the content of the consensus sugges-tions.

Eradication Treatment of Helicobacter pylori Infection: Evaluation of Therapeutic Strategies in N’Djamena

Background: Helicobacter pylori (Hp) infection is the most widespread bacterial infection in the world. The infection is generally acquired in childhood, but can persist into adulthood. Eradication therapy has undergone several modifications. The aim of this study was to evaluate the different therapeutic strategies used in the eradication of Helicobacter pylori infection in the Centre Hospitalier Universitaire La Reference Nationale of N’Djaména. Patients and Methods: This was a prospective, descriptive analytical study spread over one year, from September 2021 to September 2022. Patients at least 15 years of age presenting with dyspeptic symptoms, seen consecutively in a hepato-gastroenterology consultation and with a positive stool test for H. pylori infection, were included in the study. Equally, 1/3 of patients were treated with dual or triple therapy. The remaining third received quadritherapy. Results: A total of 268 patients were included in the study (mean age 38.40 ± 14.66 with extremes of 16 and 80 years). Males predominated in 58% of cases. Overall therapeutic efficacy was 88.9%. According to different therapeutic strategies, efficacy was 90.75% for dual therapy with PPI (Rabeprazole) and Amoxicillin. On the other hand, efficacy was 87% and 88.88% for PPI-based triple therapy and dual antibiotic therapy, and for PPI-based quadruple therapy and triple antibiotic therapy. Conclusion: H. pylori infection is a common disease in Chad. Dual therapy with rabeprazole combined with a high dose of amoxicillin over a period of at least two weeks showed similar if not better efficacy than triple or quadruple therapy.

Live-streaming selling strategies for competitive firms

The booming live-streaming commerce has significantly changed the traditional e-commerce model,thus attracting much attention from both industry and academia.In recent years,an increasing number of scholars have applied analytical models to explore live-streaming strategies for firms in different scenarios.However,the previous literature mainly considers monopolists,while in the real world,competition is not rare.To fill this gap between the literature and practical observations,this paper applies a game theoretical model to study live-streaming adoption and pricing strategy for firms under competitive environments.The results show that,for competitive firms,the equilibrium strategy depends on the relation between the commission rate and the intensity of the market expansion effect.Additionally,compared to the case in which no firm adopts live-streaming,competitive firms do not always benefit from the adoption of live-streaming selling.The paper also shows that competition plays a negative role in inducing a firm to adopt live-streaming.

Spheroid construction strategies and application in 3D bioprinting

Tissue engineering has been striving toward designing and producing natural and functional human tissues.Cells are the fundamental building blocks of tissues.Compared with traditional two-dimensional cultured cells,cell spheres are threedimensional(3D)structures that can naturally form complex cell–cell and cell–matrix interactions.This structure is close to the natural environment of cells in living organisms.In addition to being used in disease modeling and drug screening,spheroids have significant potential in tissue regeneration.The 3D bioprinting is an advanced biofabrication technique.It accurately deposits bioinks into predesigned 3D shapes to create complex tissue structures.Although 3D bioprinting is efficient,the time required for cells to develop into complex tissue structures can be lengthy.The 3D bioprinting of spheroids significantly reduces the time required for their development into large tissues/organs during later cultivation stages by printing them with high cell density.Combining spheroid fabrication and bioprinting technology should provide a new solution to many problems in regenerative medicine.This paper systematically elaborates and analyzes the spheroid fabrication methods and 3D bioprinting strategies by introducing spheroids as building blocks.Finally,we present the primary challenges faced by spheroid fabrication and 3D bioprinting with future requirements and some recommendations.

Accurate models and nutritional strategies for specific oxidative stress factors: Does the dose matter in swine production?

Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxidant strategies in relation to oxidative stress-induced pig production,it remains so far largely unsuccessful to develop accurate models and nutritional strategies for specific oxidative stress factors.Here,we discuss the dose and dose intensity of the causes of oxidative stress involving physiological,environmental and dietary factors,recent research models and the antioxidant strategies to provide theoretical guidance for future oxidative stress research in swine.

New Trends in Japan's“Indo-Pacific”Strategy

Introduced by the late Prime Minister Shinzo Abe and inherited and developed by Fumio Kishida,Japan's“Indo–Pacific”strategy has gradually taken shape.This strategy can be deemed a broad vision,covering a wide range of topics and an extensive network of partners,with a strong trend of pan-securitization.It is a comprehensive inter national st rateg y based on Japan's alliance policy and China containment strategy,following a global,security-oriented approach.Driven by considerations such as maintaining its economic status,realizing its long-cherished dream of becoming a political powerhouse,and containing China,Japan has stepped up its“Indo–Pacific”strategy,which may influence global development,undermine regional maritime security,and impede China's reunification process.Meanwhile,Japan's“Indo–Pacific”strategy faces the triple challenge of a strategic overdraft,the unstable economic foundations,and the weak external support.These constraints may not suffice to reverse the direction of Japan's“Indo–Pacific”strategy in the short term but will limit its effectiveness.

Practice of Infection Prevention and Control Strategies in Risk Departments during the COVID-19 Epidemic

Objective: To explore the practice and application of infection prevention and control strategies in risk departments during the COVID-19 epidemic, and to formulate the infection prevention and control measures to provide advice and guidance in risk departments. Methods: According to the latest plan of diagnosis and treatment, prevention and control issued by the National Health Commission, expert advice and consensus, combined with the actual situation in our hospital, a series of infection prevention and control measures of COVID-19 in risk department was formulated. Results: During the epidemic period, the prevention and control measures of nine risk departments including emergency operation, anesthesiology, endoscopy center, blood purification center, otolaryngology, stomatology, medical imaging department, medical cosmetology department and pulmonary function room were established from six aspects, including pre-examination and screening, medical technology control, personnel management, personal protection, environmental disinfection, medical waste disposal, etc. Conclusion: During the epidemic period, the infection prevention and control strategy of risk departments is one of the key links to control the spread of the epidemic, and risk departments must pay attention to and strictly implement various infection prevention and control measures.

The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’needs.Therefore,the Information-Centric Networking(ICN)came into being.From a technical point of view,ICN is a promising future network architecture.Researching and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of ICN.The current research on ICN pricing mechanism is focused on paid content.Therefore,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to analysis.In this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN entities.This solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each entity.Our extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

Staphylococcus aureus and biofilms:transmission, threats, and promising strategies in animal husbandry

Staphylococcus aureus(S. aureus) is a common pathogenic bacterium in animal husbandry that can cause diseases such as mastitis, skin infections, arthritis, and other ailments. The formation of biofilms threatens and exacerbates S. aureus infection by allowing the bacteria to adhere to pathological areas and livestock product surfaces, thus triggering animal health crises and safety issues with livestock products. To solve this problem, in this review, we provide a brief overview of the harm caused by S. aureus and its biofilms on livestock and animal byproducts(meat and dairy products). We also describe the ways in which S. aureus spreads in animals and the threats it poses to the livestock industry. The processes and molecular mechanisms involved in biofilm formation are then explained. Finally, we discuss strategies for the removal and eradication of S. aureus and biofilms in animal husbandry, including the use of antimicrobial peptides, plant extracts, nanoparticles, phages, and antibodies. These strategies to reduce the spread of S. aureus in animal husbandry help maintain livestock health and improve productivity to ensure the ecologically sustainable development of animal husbandry and the safety of livestock products.