A“Going Concern”and the Need to Fully Integrate Economics in the Business School Curriculum

In response to the recommendation by the American Assembly of Collegiate Schools of Business(AACSB,2002),which urged business schools to embark on interdisciplinary programs to facilitate boundary-spanning teaching and learning,many colleges have conducted one form of curriculum integration or the other.Many of these team-taught course integrations,however,concentrate on core business courses without reaching out to related courses in other disciplines.Moreover,due to some factors,the informational contents of management disclosures in annual reports and audit unqualified opinions may not align with the future viability of an enterprise.Using a“going concern concept”,this paper demonstrates how the addition of economics in business school curriculum integration could produce well-rounded business graduates.Economics concepts could unambiguously support the tests that cast doubts on firms’ability to continue operations.

Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

The quantization algorithm compresses the original network by reducing the numerical bit width of the model,which improves the computation speed. Because different layers have different redundancy and sensitivity to databit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determinethe optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantizationcan effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In thispaper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bitwidth is proposed, and reinforcement learning is used to automatically predict the mixed precision that meets theconstraints of hardware resources. In the state-space design, the standard deviation of weights is used to measurethe distribution difference of data, the execution speed feedback of simulated neural network accelerator inferenceis used as the environment to limit the action space of the agent, and the accuracy of the quantization model afterretraining is used as the reward function to guide the agent to carry out deep reinforcement learning training. Theexperimental results show that the proposed method obtains a suitable model layer-by-layer quantization strategyunder the condition that the computational resources are satisfied, and themodel accuracy is effectively improved.The proposed method has strong intelligence and certain universality and has strong application potential in thefield of mixed precision quantization and embedded neural network model deployment.

Neoadjuvant treatment of rectal cancer: Where we are and where we are going

Locally advanced rectal cancer requires a multidisciplinary approach based on total neoadjuvant treatment with radiotherapy(RT)and chemotherapy(ChT),followed by deferred surgery.Currently,alternatives to the standard total neoadjuvant therapy(TNT)are being explored,such as new ChT regimens or the introduction of immunotherapy.With standard TNT,up to a third of patients may achieve a complete pathological response(CPR),potentially avoiding surgery.However,as of now,we lack predictive markers of response that would allow us to define criteria for a conservative organ strategy.The presence of muta-tions,genes,or new imaging tests is helping to define these criteria.An example of this is the diffusion coefficient in the diffusion-weighted sequence of magnetic resonance imaging and the integration of this imaging technique into RT treatment.This allows for the monitoring of the evolution of this coefficient over successive RT sessions,helping to determine which patients will achieve CPR or those who may require intensification of neoadjuvant therapy.

Strategies for Video Producers to Tell Their Good Stories Under the 5W Model of Communication

In recent years,with the rise of video media such as YouTube and Tik Tok,the short video creation industry has emerged.How to spread China's excellent culture and how to“tell a good Chinese story”have become a hot concern.Using the 5W Model of Communication as a framework for analysis,this paper selects Chinese short videos with high popularity on YouTube as the object of the study.Studies found that the success of these videos was associated with five factors in the process of communication,which are communication main forces,communication content,communication channels,communication audience,and audience effects.Through theoretical and data analysis,the study concluded five strategies in video production to help promote Intercultural communication.

Impact of Sedation Protocols on Elderly Patients Undergoing Mechanical Ventilation and Off-Line Weaning

The proportion of elderly patients in intensive care is increasing, and a significant proportion of them require mechanical ventilation. How to implement safe and effective mechanical ventilation for elderly patients, and when appropriate off-line is an important issue in the field of critical care medicine. Appropriate sedation can improve patient outcomes, but excessive sedation may lead to prolonged mechanical ventilation and increase the risk of complications. Elderly patients should be closely monitored and evaluated on an individual basis while offline, and the sedation regimen should be dynamically adjusted. This requires the healthcare team to consider the patient’s sedation needs, disease status, and pharmacodynamics and pharmacokinetics of the drug to arrive at the best strategy. Although the current research has provided valuable insights and strategies for sedation and off-line management, there are still many problems to be further explored and solved.

Exploring Pedagogical Ideologies and Strategies for College English Writing Instruction from a Generative Artificial Intelligence Perspective

This study,drawing on the commonalities between generative artificial intelligence and foreign language writing instruction,outlines the core ideology of digital humanities-based college English writing instruction,including auxiliary use of generative artificial intelligence tools,primary focus on humanistic education,and the re-production of knowledge,aiming to foster students’critical thinking,collaborative skills,and creativity.Building on this foundation,the study delves into generative artificial intelligence tools applicable to different stages of process-genre writing and their strategic applications.The use of generative artificial intelligence tools is beneficial for students to present,discuss,and share writing content,encouraging them to enhance their writing,collaboration,critical thinking,and creative abilities through deep interaction with model essays and creative discourses.

On the Strategic Paths of the Going Global Strategy of Chinese Literature

The going global strategy of Chinese literature is a vital part of the going global strategy of Chinese culture. In recent years,the Chinese government has launched and strongly supported a series of activities and projects to promote this strategy,but little effect has been produced. Starting from analyzing the predicament and reasons of the current strategy,the essay suggests four strategic paths: enhancing the overall strength of the country to promote the international influence of Chinese culture,strengthening cultural awareness and cultural introspection,integrating the nationality and cosmopolitan of literature and establishing a market-oriented literary translation mechanism.

GO掺杂对TA1钛合金等离子体电解氧化涂层硬度和耐磨性能的影响

本研究在掺杂氧化石墨烯(简称“CO”)的硅酸盐电解液中对TA1钛合金进行等离子体电解氧化处理,旨在获得较高硬度的等离子体电解氧化陶瓷涂层(PEO)。通过表征涂层的物相组成、表面与截面形貌、粗糙度、显微硬度、摩擦因数以及结合力等参数,分析了CO浓度对涂层性能的影响。研究结果表明,CO参与涂层的形成过程,能够有效地减小微孔和裂纹尺寸,表面粗糙度降低。涂层厚度虽然略有降低,但致密性显著增加。与未掺杂GO的PEO涂层相比,当GO掺杂量为0.6g·L^(-1)时掺杂GO的PEO涂层显微硬度提升18.54%,摩擦系数降低84%,临界载荷强度提高32.59%。

静电组装低感度CL-20@GO核壳复合材料的制备及性能研究

为降低六硝基六氮杂异伍兹烷(CL-20)的机械感度,提高其综合性能,以3-氨丙基三乙氧基硅烷(APS)为改性剂对CL-20改性,以氧化石墨烯(GO)为包覆材料,利用静电自组装方法对改性CL-20炸药进行表面包覆,制备得到CL-20@GO核壳复合材料;采用水接触角测试、扫描电子显微镜(SEM)和X射线光电子能谱(XPS)等对样品进行形貌表征;利用差示扫描量热仪(DSC)测试其热性能,并测试了其机械感度。结果表明,经质量分数5%的APS溶液改性的CL-20成功引入氨基基团,亲水性效果最佳;GO层包覆改性CL-20完整,致密性强;与原料CL-20相比,CL-20@GO核壳复合材料的活化能提高了63.0kJ/mol,撞击感度(H 50)由13.0cm提升至23.5cm,摩擦感度由100%降至24%,表明采用静电自组装的GO涂层可以明显降低CL-20的感度。

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.

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.

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.

Multi-Strategy Boosted Spider Monkey Optimization Algorithm for Feature Selection

To solve the problem of slow convergence and easy to get into the local optimum of the spider monkey optimization algorithm,this paper presents a new algorithm based on multi-strategy(ISMO).First,the initial population is generated by a refracted opposition-based learning strategy to enhance diversity and ergodicity.Second,this paper introduces a non-linear adaptive dynamic weight factor to improve convergence efficiency.Then,using the crisscross strategy,using the horizontal crossover to enhance the global search and vertical crossover to keep the diversity of the population to avoid being trapped in the local optimum.At last,we adopt a Gauss-Cauchy mutation strategy to improve the stability of the algorithm by mutation of the optimal individuals.Therefore,the application of ISMO is validated by ten benchmark functions and feature selection.It is proved that the proposed method can resolve the problem of feature selection.

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.

A Dynamic Maintenance Strategy for Multi-Component Systems Using a Genetic Algorithm

In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.

Exploring Work-Related Stress and Coping Strategies among Omani Nurses Working in Tertiary Governmental Hospitals at Muscat: A Cross-Sectional Study

Introduction: Work-related stress has become a global issue in the nursing workplace, with about 9.20% - 68.0% of nurses globally experiencing stress. Conversely, work-related stress ranges between 20% and 40% in nursing. Other researchers noted that 35.1% of nurses globally experienced elevated stress levels. Stress can damage well-being and lead to coping, which can, directly and indirectly, improve well-being through a perceived state. Nurses need coping mechanisms to manage their stress levels and maintain stability. Coping mechanisms can vary greatly depending on a nurse’s culture and background. Numerous findings indicate that managing stress is more critical than the cause of stress and that the more successful a stress-management approach, the less damage stress brings. Objective: In response to this, it is necessary to explore Omani nurses’ stress level and their coping strategies working in tertiary governmental hospitals in Muscat. Methods: The sample size for this study was 383 Omani nurses, with a 100% response rate. This study used a descriptive cross-sectional design from 15 October 2020 to 30 November 2020. Samples were selected through proportionate population sampling (PPS) from the five selected tertiary hospitals. Data were collected by self-administered questionnaires using a perceived stress scale and Ways of Coping. A simple random sample within a stratum (each hospital admitting ward) was done to identify the study participants. The sample size for this study was 383 Omani nurses, with a 100% response rate. Results: About 83.3% of participants had a moderate perceived level of stress with an overall mean perceived stress level of 18.46 ± 4.52. The most common sources of perceived stress are feeling nervous and “stressed” in the last month (2.30 ± 0.95). According to the ways of coping strategies, nurses seemed to be resorting to more “planful problem” (mean = 11.04) and least was seeking social support (mean = 9.67). Conclusion: This study highlighted the work-related stress level of staff nurses, explored their ways of coping and determined the relationship between work-related stress levels and methods of coping. The key finding of this study was that the frequency of stress reported by nurses was high enough to suggest that their stress levels were significant, given the demanding nature of their profession that requires maximum attention. Additionally, nurses seemed to resort to more planful problem-solving mechanisms to deal with their stressful situations than other coping strategies.

New Developments in US Arctic Strategy and Their Implications for Arctic Governance

With the increasing strategic relevance of the Arctic region in the international system,the United States,as the global hegemon and also an Arctic country,has gradually viewed the region as an important arena to address its alleged security threats and conduct major-power competition.

Strategy dominance mechanism of autonomous collaboration in unmanned swarm within the framework of public goods game

The key advantage of unmanned swarm operation is its autonomous cooperation. How to improve the proportion of cooperators is one of the key issues of autonomous collaboration in unmanned swarm operations. This work proposes a strategy dominance mechanism of autonomous collaboration in unmanned swarm within the framework of public goods game. It starts with the requirement analysis of autonomous collaboration in unmanned swarm;and an aspiration-driven multiplayer evolutionary game model is established based on the requirement. Then the average abundance function and strategy dominance condition of the model are constructed by theoretical derivation. Furthermore, the evolutionary mechanism of parameter adjustment in swarm cooperation is revealed via simulation,and the influences of the multiplication factor r, aspiration levelα, threshold m and other parameters on the strategy dominance conditions were simulated for both linear and threshold public goods games(PGGs) to determine the strategy dominance characteristics;Finally, deliberate proposals are suggested to provide a meaningful exploration in the actual control of unmanned swarm cooperation.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

TEOS-GO掺杂的银基离子聚合物金属复合材料的制备及其致动性能

离子聚合物金属复合材料(IPMC)是一种新型的电驱动软材料,具有质量轻、驱动电压低的优点,但也存在输出力较小、驱动时间短的缺点,限制了其应用前景。提出了一种在基膜内掺杂硅酸乙酯-氧化石墨烯(TEOS-GO)以提高保水性和驱动能力的银基IPMC,通过对纯Nafion IPMC与TEOS-GO/Nafion IPMC致动器的含水量、尖端位移、输出力和稳定性等参数的测试,证实优化后IPMC的驱动性能有明显的提升。实验结果表明,掺杂质量分数1.5%TEOS-GO的IPMC在3 V直流电压下,尖端位移达到16.579 mm,相当于纯Nafion IPMC的3.37倍;输出力最高达到0.439 gf(1 gf=9.8 mN),是纯Nafion IPMC的5倍。这种改进方式弥补了IPMC用于致动器的缺点,为今后的发展开拓了前景。