Sustained release of vascular endothelial growth factor A and basic fibroblast growth factor from nanofiber membranes reduces oxygen/glucose deprivation-induced injury to neurovascular units

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective effects.However,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently increased.In this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning techniques.We found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 month.This 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose deprivation.Furthermore,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved caspase-3.Therefore,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance:Subsea Christmas Tree System as A Case Study

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Predictive maintenance and its applications in civil engineering structures:A review

Structural health monitoring and performance prediction are crucial for smart disaster mitigation and intelligent management of structures throughout their lifespan.Recent advancements in predictive maintenance strategies within the industrial manufacturing industry have inspired similar innovations in civil engineering,aiming to improve structural performance evaluation,damage diagnosis,and capacity prediction.This review delves into the framework of predictive maintenance and examines various existing solutions,focusing on critical areas such as data acquisition,condition monitoring,damage prognosis,and maintenance planning.Results from real-world applications of predictive maintenance in civil engineering,covering high-rise structures,deep foundation pits,and other infrastructure,are presented.The challenges of implementing predictive maintenance in civil engineering structures under current technology,such as model interpretability of data-driven methods and standards for predictive maintenance,are explored.Future research prospects within this area are also discussed.

Risk Factors for Mortality in Acute Kidney Injury in Intensive Care Units in Togo

Context: Acute kidney injury (AKI) in intensive care unit (ICU) is common and associated with very high mortality. In Togo, a tropical country with limited resources and only one nephrology department in the north, acute kidney injury seems to be a real tragedy with high mortality. Aims: to determine risk factors for mortality in acute kidney injury in the intensive care units. Methods and Material: We made a multicentric cross sectional study during 6 months in the four referral centers in northern Togo. Univariate and multivariate logistic regression was used to identify factors associated with mortality. Data were analyzed using RStudio 2023.04.1. Results: A total of 12.6% of patients admitted to intensive care had presented with AKI. The mean age was 49.6 ± 17.9. The sex ratio (M/F) was 2.1. Community-acquired AKI was in the majority (67.7%). Oligo anuria was the most frequent functional sign (38.4%). In our series, 81.6% of patients were in KDIGO stages 2 to 3. AKI was organic in 56.2% of cases. Mortality was 44.3%. In multivariate analysis, the main factors predictive of death were: respiratory distress (OR = 2.36;p Conclusions: Acute kidney injury in intensive care is common in northern Togo, and mortality is high. Identification of associated factors should help anticipate prognosis.

Impact of Safety-Maintenance Practices on the Overall Performance of an Industry

The study aims to evaluate how safety-maintenance practices affect the mechanical engineering industry’s overall performance in Ghana. The study used a descriptive survey design technique to ascertain the type of maintenance engineering that was practiced in Ghanaian mechanical engineering workshops at the time of the study. In the mechanical engineering workshops, respondents provided both qualitative and quantitative data using a variety of data collecting instruments, with the quantitative approach being more common. The study employed Kumasi, Tamale, and Accra’s mechanical engineering workshops as a case study. The number of mechanical engineering workshop enterprises that made up the sample size for the questionnaire administration was sixty (60), chosen at random from the AGI membership registry. Primary data was gathered using interview guides and questionnaires. To analyse the data, descriptive statistics were employed. According to the study’s findings, mechanical engineering companies combined different maintenance techniques in order to best fit their organisational culture and equipment. Preventive shut-down, with a mean score of 4.78 and RII = 0.98, placing first (1st) in the Likert rating order, is the most frequently used maintenance system by respondents. The maintenance procedures employed by mechanical engineering organisations were influenced not only by their equipment and organisational culture but also by other factors such as cost, personnel expertise and external partnerships.

One memristor–one electrolyte-gated transistor-based high energy-efficient dropout neuronal units

Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.

Exploration of Operation and Maintenance Management Mode and Innovation Mechanism of Pilot Base of Chemical Park

Based on the current situation of the operation and maintenance management of the pilot base in many chemical parks in China,this paper conducts an in-depth exploration of the operation and maintenance management and innovation mode of the pilot base from the aspects of the evaluation of the pilot project entering the park,safety and environmental protection supervision,pilot mode,and industrialization mode of the pilot test results,so as to provide solutions for accelerating the process and industrialization of the pilot project and realizing the innovation value of the pilot base.

Mediating role of social support in dysphoria,despondency,and quality of life in patients undergoing maintenance hemodialysis

BACKGROUND Dysphoria and despondency are prevalent psychological issues in patients undergoing Maintenance Hemodialysis(MHD)that significantly affect their quality of life(QOL).High levels of social support can significantly improve the physical and mental well-being of patients undergoing MHD.Currently,there is limited research on how social support mediates the relationship between dysphoria,despondency,and overall QOL in patients undergoing MHD.It is imperative to investigate this mediating effect to mitigate dysphoria and despondency in patients undergoing MHD,ultimately enhancing their overall QOL.AIM To investigate the mediating role of social support in relationships between dysphoria,despondency,and QOL among patients undergoing MHD.METHODS Participants comprised 289 patients undergoing MHD,who were selected using a random sampling approach.The Social Support Rating Scale,Self-Rating Anxiety Scale,Self-Rating Depression Scale,and QOL Scale were administered.Correlation analysis was performed to examine the associations between social support,dysphoria,despondency,and QOL in patients undergoing MHD.To assess the mediating impact of social support on dysphoria,despondency,and QOL in patients undergoing MHD,a bootstrap method was applied.RESULTS Significant correlations among social support,dysphoria,despondency,and quality in patients undergoing MHD were observed(all P<0.01).Dysphoria and despondency negatively correlated with social support and QOL(P<0.01).Dysphoria and despondency had negative predictive impacts on the QOL of patients undergoing MHD(P<0.05).The direct effect of dysphoria on QOL was statistically significant(P<0.05).Social support mediated the relationship between dysphoria and QOL,and this mediating effect was significant(P<0.05).Similarly,the direct effect of despondency on QOL was significant(P<0.05).Moreover,social support played a mediating role between despondency and QOL,with a significant mediating effect(P<0.05).CONCLUSION These findings suggest that social support plays a significant mediating role in the relationship between dysphoria,despondency,and QOL in patients undergoing MHD.

Hounsfield units in assessing bone mineral density in ankylosing spondylitis patients with cervical fracture-dislocation

BACKGROUND Cervical spine fracture-dislocations in patients with ankylosing spondylitis(AS)are mostly unstable and require surgery.However,osteoporosis,one of the comorbidities for AS,could lead to detrimental prognoses.There are few accurate assessments of bone mineral density in AS patients.AIM To analyze Hounsfield units(HUs)for assessing bone mineral density in AS patients with cervical fracture-dislocation.METHODS The HUs from C2 to C7 of 51 patients obtained from computed tomography(CT)scans and three-dimensional reconstruction of the cervical spine were independently assessed by two trained spinal surgeons and statistically analyzed.Inter-reader reliability and agreement were assessed by interclass correlation coefficient.RESULTS The HUs decreased gradually from C2 to C7.The mean values of the left and right levels were significantly higher than those in the middle.Among the 51 patients,25 patients(49.02%)may be diagnosed with osteoporosis,and 16 patients(31.37%)may be diagnosed with osteopenia.CONCLUSION The HUs obtained by cervical spine CT are feasible for assessing bone mineral density with excellent agreement in AS patients with cervical fracture-dislocation.

Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

Azacitidine maintenance therapy for blastic plasmacytoid dendritic cell neoplasm allograft: A case report

BACKGROUND Blastic plasmacytoid dendritic cell neoplasm(BPDCN)is a rare,highly invasive malignant neoplasm.There is no universally accepted standard of care because of its rarity and the dearth of prospective research.It is still challenging for some patients to achieve persistent clinical remission or cure,despite the success of allogeneic hematopoietic stem cell transplantation(allo-HSCT),indicating that there is still a significant recurrence rate.We report a case of prevention of BPDCN allograft recurrence by azacitidine maintenance therapy and review the relevant literature.CASE SUMMARY We report a 41-year-old man with BPDCN who was admitted to hospital due to skin sclerosis for>5 mo’duration.BPDCN was diagnosed by combined clinical assessment and laboratory examinations.Following diagnosis,the patients underwent induction consolidation chemotherapy to achieve the first complete remission,followed by bridging allo-HSCT.Post-transplantation,azacitidine(75 mg/m2 for 7 d)was administered as maintenance therapy,with repeat administration every 4–6 wk and appropriate extension of the chemotherapy cycle.After 10 cycles,the patient has been disease free for 26 mo after transplantation.Regular assessments of bone marrow morphology,minimal residual disease,full donor chimerism,Epstein–Barr virus,and cytomegalovirus all yielded normal results with no abnormalities detected.CONCLUSION Azacitidine may be a safe and effective maintenance treatment for BPDCN following transplantation because there were no overt adverse events during the course of treatment.

Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped robots.Among various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large payloads.As the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight design.Inspired by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an LLU.We propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston rod.In addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the LLU.The mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah muscle.The mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

Analysis of current status of and barriers to exercise participation among patients on maintenance hemodialysis

Objective:The objective of this study was to analyze the current status of barriers to exercise participation(EP)among patients on maintenance hemodialysis(MHD).Materials and Methods:A cross-sectional study was conducted on 277 outpatients undergoing MHD in 2 tertiary first-class hospitals in Beijing from February 2023 to June 2023 who were selected using convenience sampling method.The data of patients on MHD were collected using the general information questionnaire,Physical Activity Rating Scale,Exercise Benefits/Barriers Scale(EBBS),and Exercise Self-Efficacy Scale(ESES).The relationship between EP and barriers to EP was analyzed through univariate and multivariate linear regression models.Results:Patients on MHD had a low exercise volume score of 13.71±0.68 points and a medium EBBS score of 63.36±0.40 points.Multivariate logistic analysis showed that exercise volume was significantly related to the following four aspects,including low monthly household income per capita(odds ratio[OR]=86.741,95%confidence interval[CI][1.164-6.465],P=0.042),primary underlying disease of diabetic nephropathy(OR=45.993,95%CI[1.353-1.564],P=0.033),the belief that“fatigue in lower extremities hinders exercise”(OR=4.697,95%CI[1.127-19.585],P=0.034),and the belief that“physical exercise bringing optimistic and positive life attitude”(OR=0.074,95%CI[0.007-0.830],P=0.035).Conclusions:Since patients on MHD had low physical exercise volume,the health-care provider should pay more attention on the controllable factors that affect the EP of patients on MHD.Therefore,feasible and effective intervention measures can be formulated based on ESES in clinical nursing.

A Maintenance Service Improvement Approach Based on Queue Networks: Application

The quest to increase the performance of production systems that have become complex leads to the transfer to the maintenance function of the responsibility of guaranteeing the availability of such systems. Also, we will never stop saying that maintenance must integrate into all of the company’s initiatives, to affirm its role, which is to ensure greater availability and sustainability of the means of production. The objective of this paper is to evaluate the reliability and availability of a system without knowing the distribution law of the operating times. Among the methods for evaluating dependability criteria (Fault Trees, Petri Nets, etc.), we are interested in queues that have the advantage of taking into account functional dependencies, thus allowing a quantified optimization of maintenance. Indeed, queues make it possible to model parallel or sequential processes, implementing operations taking place at the same time or one after the other, meeting the needs of modeling production systems. The main result of this paper is the study of the influence of availability on the reliability of a multi-state production system.

Improvement of the nutritional support management system for patients in intensive care units

BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.

Translation Theory and Techniques in Optometry Literature: A Case Study of the “Optoform 80 Installation and Maintenance Manual”

Translation of specialized documents in optometry presents unique challenges,requiring a deep understanding of the professional context,terminology,and adherence to specific translation styles.This paper delves into the translation theory and techniques employed in the English-to-Chinese translation of the“Optoform 80 Installation and Maintenance Manual”,serving as a case study.Emphasizing Nida’s theory of functional equivalence,the paper explores the complexities of translating professional optometry literature,focusing on key points and common issues in translating installation and maintenance manuals for optometric devices.Special attention is given to the translation of professional terminology,employing methods such as addition,omission,conversion,and repetition.The translation process aims to meet specific requirements,ensuring accuracy and coherence while aligning with Chinese language conventions.The paper also analyzes translation methods and techniques concerning terminology,prepositions,conjunctions,and handling parallel elements based on practical insights from the Optoform 80 Manual.