STEADY-STATE AND IDLE OPTIMIZA-TION OF INTERNAL COMBUSTION ENGINE CONTROL STRATEGIES FOR HYBRID ELECTRIC VEHICLES

A novel steady-state optimization （SSO） of internal combustion engine （ICE） strategy is proposed to maximize the efficiency of the overall powertrain for hybrid electric vehicles, in which the ICE efficiency, the efficiencies of the electric motor （EM） and the energy storage device are all explicitly taken into account. In addition, a novel idle optimization of ICE strategy is implemented to obtain the optimal idle operating point of the ICE and corresponding optimal parking generation power of the EM using the view of the novel SSO of ICE strategy. Simulations results show that potential fuel economy improvement is achieved relative to the conventional one which only optimized the ICE efficiency by the novel SSO of ICE strategy, and fuel consumption per voltage increment decreases a lot during the parking charge by the novel idle optimization of ICE strategy.

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.

Semi-analytical steady-state response prediction for multi-dimensional quasi-Hamiltonian systems

The majority of nonlinear stochastic systems can be expressed as the quasi-Hamiltonian systems in science and engineering. Moreover, the corresponding Hamiltonian system offers two concepts of integrability and resonance that can fully describe the global relationship among the degrees-of-freedom(DOFs) of the system. In this work, an effective and promising approximate semi-analytical method is proposed for the steady-state response of multi-dimensional quasi-Hamiltonian systems. To be specific, the trial solution of the reduced Fokker–Plank–Kolmogorov(FPK) equation is obtained by using radial basis function(RBF) neural networks. Then, the residual generated by substituting the trial solution into the reduced FPK equation is considered, and a loss function is constructed by combining random sampling technique. The unknown weight coefficients are optimized by minimizing the loss function through the Lagrange multiplier method. Moreover, an efficient sampling strategy is employed to promote the implementation of algorithms. Finally, two numerical examples are studied in detail, and all the semi-analytical solutions are compared with Monte Carlo simulations(MCS) results. The results indicate that the complex nonlinear dynamic features of the system response can be captured through the proposed scheme accurately.

A Posteriori Stabilized Sixth-Order Finite Volume Scheme with Adaptive Stencil Construction:Basics for the 1D Steady-State Hyperbolic Equations

We propose an adaptive stencil construction for high-order accurate finite volume schemes a posteriori stabilized devoted to solve one-dimensional steady-state hyperbolic equations.High accuracy(up to the sixth-order presently)is achieved,thanks to polynomial recon-structions while stability is provided with an a posteriori MOOD method which controls the cell polynomial degree for eliminating non-physical oscillations in the vicinity of dis-continuities.We supplemented this scheme with a stencil construction allowing to reduce even further the numerical dissipation.The stencil is shifted away from troubles(shocks,discontinuities,etc.)leading to less oscillating polynomial reconstructions.Experimented on linear,Burgers',and Euler equations,we demonstrate that the adaptive stencil technique manages to retrieve smooth solutions with optimal order of accuracy but also irregular ones without spurious oscillations.Moreover,we numerically show that the approach allows to reduce the dissipation still maintaining the essentially non-oscillatory behavior.

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.

Secondary steady-state and time-periodic flows from a basic flow with square array of odd number of vortices

In a magnetohydrodynamic(MHD)driven fluid cell,a plane non-parallel flow in a square domain satisfying a free-slip boundary condition is examined.The energy dissipation of the flow is controlled by the viscosity and linear friction.The latter arises from the influence of the Hartmann bottom boundary layer in a three-dimensional(3D)MHD experiment in a square bottomed cell.The basic flow in this fluid system is a square eddy flow exhibiting a network of N~2 vortices rotating alternately in clockwise and anticlockwise directions.When N is odd,the instability of the flow gives rise to secondary steady-state flows and secondary time-periodic flows,exhibiting similar characteristics to those observed when N=3.For this reason,this study focuses on the instability of the square eddy flow of nine vortices.It is shown that there exist eight bi-critical values corresponding to the existence of eight neutral eigenfunction spaces.Especially,there exist non-real neutral eigenfunctions,which produce secondary time-periodic flows exhibiting vortices merging in an oscillatory manner.This Hopf bifurcation phenomenon has not been observed in earlier investigations.

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.

High-Intensity Interval Training v/s Steady-State Cardio in Rehabilitation of Neurological Patients

Neuropathy is nerve damage that can cause chronic neuropathic pain, which is challenging to cure and has a significant financial burden. Exercise therapies, including High-Intensity Interval Training (HIIT) and steady-state cardio, are being explored as potential treatments for neuropathic pain. This systematic review compares the effectiveness of HIIT and steady-state cardio for improving function in neurological patients. This article provides an overview of the systematic review conducted on the effects of exercise on neuropathic patients, with a focus on high-intensity interval training (HIIT) and steady-state cardio. The authors conducted a comprehensive search of various databases, identified relevant studies based on predetermined inclusion criteria, and used the EPPI automation application to process the data. The final selection of studies was based on validity and relevance, with redundant articles removed. The article reviews four studies that compare high-intensity interval training (HIIT) to moderate-intensity continuous training (MICT) on various health outcomes. The studies found that HIIT can improve aerobic fitness, cerebral blood flow, and brain function in stroke patients;lower diastolic blood pressure more than MICT and improve insulin sensitivity and skeletal muscle mitochondrial content in obese individuals, potentially helping with the prevention and management of type 2 diabetes. In people with multiple sclerosis, acute exercise can decrease the plasma neurofilament light chain while increasing the flow of the kynurenine pathway. The available clinical and preclinical data suggest that further study on high-intensity interval training (HIIT) and its potential to alleviate neuropathic pain is justified. Randomized controlled trials are needed to investigate the type, intensity, frequency, and duration of exercise, which could lead to consensus and specific HIIT-based advice for patients with neuropathies.

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.

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.

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.

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.

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.

Solvation strategies in various electrolytes for advanced zinc metal anode

Aqueous zinc-ion batteries(AZIBs),known for their high safety,low cost,and environmental friendliness,have a wide range of potential applications in large-scale energy storage systems.However,the notorious dendrite growth and severe side reactions on the anode have significantly hindered their further practical development.Recent studies have shown that the solvation chemistry in the electrolyte is not only closely related to the barriers to the commercialization of AZIBs,but have also sparked a number of valuable ideas to address the challenges of AZIBs.Therefore,we systematically summarize and discuss the regulatory mechanisms of solvation chemistry in various types of electrolytes and the influence of the solvation environment on battery performance.The challenges and future directions for solvation strategies based on the electrolyte environment are proposed to improve their performance and expand their application in AZIBs.

The component-activity interrelationship of cobalt-based bifunctional electrocatalysts for overall water splitting:Strategies and performance

Cobalt-based electrocatalysts take advantage of potentially harmonizable microstructure and flexible coupling effects compared to commercial noble metal-based catalytic materials.However,conventional water electrolysis systems based on cobalt-based monofunctional hydrogen evolution reaction(HER)or oxygen evolution reaction(OER)catalysts have certain shortcomings in terms of resource utilization and universality.In contrast,cobalt-based bifunctional catalysts(CBCs)have attracted much attention in recent years for overall water splitting systems because of their practicality and reduced preparation cost of electrolyzer.This review aims to address the latest development in CBCs for total hydrolysis.The main modification strategies of CBCs are systematically classified in water electrolysis to provide an overview of how to regulate their morphology and electronic configuration.Then,the catalytic performance of CBCs in total-hydrolysis is summarized according to the types of cobalt-based phosphides,sulfides and oxides,and the mechanism of strengthened electrocatalytic ability is emphasized through combining experiments and theoretical calculations.Future efforts are finally suggested to focus on exploring the dynamic conversion of reaction intermediates and building near-industrial CBCs,designing advanced CBC materials through micro-modulation,and addressing commercial applications.

Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players usually move in three-dimensional space with a three-degree-of-freedom control. In this paper,we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game, in which the pursuer follows a three-degree-of-freedom control, and the evader moves freely. First, we describe the pursuer's three-degree-of-freedom control and the evader's relative coordinate. We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs(HJBI) method, which divides the pursuit-evasion process into the navigation and acceleration phases. Besides, we analyze the maximum allowable speed for the pursuer to capture the evader successfully and provide the strategy with which the evader can escape when the pursuer's speed exceeds the threshold. We further conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.

Machine learning solution for regional landslide susceptibility based on fault zone division strategy

Landslide susceptibility assessment is an essential tool for disaster prevention and management. In areas with multiple fault zones, the impact of fault zone on slope stability cannot be disregarded. This study performed qualitative analysis of fault zones and proposed a zoning method to assess the landslide susceptibility in Chengkou County, Chongqing Municipality, China. The region within a distance of 1 km from the faults was designated as sub-zone A, while the remaining area was labeled as sub-zone B. To accomplish the assessment, a dataset comprising 388 historical landslides and 388 non-landslide points was used to train the random forest model. 10-fold cross-validation was utilized to select the training and testing datasets for the model. The results of the models were analyzed and discussed, with a focus on model performance and prediction uncertainty. By implementing the proposed division strategy based on fault zone, the accuracy, precision, recall, F-score, and AUC of both two sub-zones surpassed those of the whole region. In comparison to the results obtained for the whole region, sub-zone B exhibited an increase in AUC by 6.15%, while sub-zone A demonstrated a corresponding increase of 1.66%. Moreover, the results of 100 random realizations indicated that the division strategy has little effect on the prediction uncertainty. This study introduces a novel approach to enhance the prediction accuracy of the landslide susceptibility mapping model in areas with multiple fault zones.

Factors influencing willingness to participate in ophthalmic clinical trials and strategies for effective recruitment

AIM:To explore the factors influencing individuals’willingness to participate in ophthalmic clinical trials.METHODS:A questionnaire survey was conducted from January to April 2021 among patients and their family members at Zhongshan Ophthalmic Center,Sun Yat-sen University,in Guangzhou,China.The survey gathered data on respondents’willingness,demographic and socioeconomic profiles,as well as their reasons and concerns regarding engagement in clinical trials.RESULTS:Of the 1078 residents surveyed(mean age 31.2±13.1y;65.8%females)in Guangzhou,749(69.5%)expressed a willingness to participate in future ophthalmic clinical trials.Specific characteristics associated with greater willingness included a younger age,lower annual income,higher education,prior participation experience,previous ophthalmic treatment,and a better understanding of clinical trials.With the exception of age,these characteristics were significantly linked to a higher willingness.The primary barrier to participation,expressed by 64.8%of those willing and 54.4%of those unwilling,was“Uncertain efficacy”.In terms of motivations,the willing group ranked“Better therapeutic benefits”(35.0%),“Professional monitoring”(34.3%),and“Trust in healthcare professionals”(33.1%)as their top three reasons,whereas the unwilling participants indicated“Full comprehension of the protocol”(46.2%)as the key facilitator.CONCLUSION:This study reveals a substantial willingness to participate in ophthalmic clinical trials and demonstrates the predictive role of demographic and socioeconomic factors.Variations in motivators and concerns between willing and unwilling participants highlight the significance of tailored recruitment strategies.Importantly,the need for and trust in healthcare professionals stand out as powerful motivations,underscoring the importance of enhancing physician-patient relationships,adopting patient-centered communication approaches,and addressing individualized needs to improve accrual rates.