Supportive care in transplantation: A patient-centered care model to better support kidney transplant candidates and recipients

Kidney transplantation(KT),although the best treatment option for eligible patients,entails maintaining and adhering to a life-long treatment regimen of medications,lifestyle changes,self-care,and appointments.Many patients experience uncertain outcome trajectories increasing their vulnerability and symptom burden and generating complex care needs.Even when transplants are successful,for some patients the adjustment to life post-transplant can be challenging and psychological difficulties,economic challenges and social isola-tion have been reported.About 50%of patients lose their transplant within 10 years and must return to dialysis or pursue another transplant or conservative care.This paper documents the complicated journey patients undertake before and after KT and outlines some initiatives aimed at improving patient-centered care in transplantation.A more cohesive approach to care that borrows its philosophical approach from the established field of supportive oncology may improve patient experiences and outcomes.We propose the"supportive care in transplantation"care model to operationalize a patient-centered approach in transplantation.This model can build on other ongoing initiatives of other scholars and researchers and can help advance patient-centered care through the entire care continuum of kidney transplant recipients and candidates.Multi-dimensionality,multi-disciplinarity and evidence-based approaches are proposed as other key tenets of this care model.We conclude by proposing the potential advantages of this approach to patients and healthcare systems.Core Tip:Kidney transplant recipients and candidates face several uncertainties in their care journey and have several expressed unmet healthcare needs.We recommend a structured and comprehensive approach to transplant care across the entire continuum of a transplant patient’s journey similar to what has been developed in the field of oncology.The supportive care in transplantation model can operationalize patient-centered care and build on the efforts of other researchers in the field.We postulate that such a model would significantly improve care delivery and patients’experiences and outcomes and potentially decrease healthcare utilization and cost.INTRODUCTION Patients with kidney failure benefit from(KT)[1,2],and experience improved survival rates when compared with dialysis[3-6].KT studies,using validated instruments,have also consistently demonstrated that kidney transplant recipients(KTRs)experience better health-related quality of life and several improvements in other disease-specific domains when compared with dialysis[7].In countries where dialysis is out of reach for many,the diagnosis of kidney failure would be futile without KT[8].Thus,increasing KT has been a priority for the nephrology and transplant communities.This priority has been reflected in recent global trends:Of the 79 countries where data were available,the International Society of Nephrology’s Global Kidney Atlas reported that the prevalence of KTRs in 2023 was 279 per million population which represented an increase of 9.4%from the data published four years prior[8].Despite this growth,KT can be a challenging journey for many patients and it is sometimes regarded as a‘cure’,which does not conform with the reality that many patients experience[9-13].KTRs must maintain a life-long treatment regimen of medications,lifestyle changes,self-care and medical appointments[14-17].As poignantly stated by a young female transplant recipient,“I thought everything would change once I got my kidney.I thought I would be healthy again”but after experiencing multiple side effects of immunosuppressive medications and graft loss,she stated,“I am just a different kind of patient now”[18].Indeed,a significant proportion of patients experience graft failure and return to dialysis;it is estimated that over 50%return to dialysis within 10 years of KT[19-23].Patients are often not prepared for this outcome and report several psychosocial and physical ramifications of graft failure[24,25].Overall,high symptom burden,adverse effects of immunosuppressants,risk of graft rejection or failure and mortality,contribute to complex needs,vulnerability and uncertainties for patients,increasing their care needs and treatment burden[26-30].In this paper,we highlight the complex journey that KTRs and candidates undertake that can generate varied outcome trajectories and complex healthcare needs.We highlight the need for a comprehensive patient-centered approach to care and conclude with a proposal for a“supportive care in transplantation”care model.

Impact of COVID-19 on liver transplant recipients: A nationwide cohort study evaluating hospitalization, transplant rejection, and inpatient mortality

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic has posed a major public health concern worldwide.Patients with comorbid conditions are at risk of adverse outcomes following COVID-19.Solid organ transplant recipients with concurrent immunosuppression and comorbidities are more susceptible to a severe COVID-19 infection.It could lead to higher rates of inpatient complications and mortality in this patient population.However,studies on COVID-19 outcomes in liver transplant(LT)recipients have yielded inconsistent findings.AIM To evaluate the impact of the COVID-19 pandemic on hospital-related outcomes among LT recipients in the United States.METHODS We conducted a retrospective cohort study using the 2019–2020 National Inpatient Sample database.Patients with primary LT hospitalizations and a secondary COVID-19 diagnosis were identified using the International Classi-fication of Diseases,Tenth Revision coding system.The primary outcomes included trends in LT hospitalizations before and during the COVID-19 pandemic.Secondary outcomes included comparative trends in inpatient mortality and transplant rejection in LT recipients.RESULTS A total of 15720 hospitalized LT recipients were included.Approximately 0.8% of patients had a secondary diagnosis of COVID-19 infection.In both cohorts,the median admission age was 57 years.The linear trends for LT hospitalizations did not differ significantly before and during the pandemic(P=0.84).The frequency of in-hospital mortality for LT recipients increased from 1.7% to 4.4% between January 2019 and December 2020.Compared to the pre-pandemic period,a higher association was noted between LT recipients and in-hospital mortality during the pandemic,with an odds ratio(OR)of 1.69[95% confidence interval(CI):1.55-1.84),P<0.001].The frequency of transplant rejections among hospitalized LT recipients increased from 0.2%to 3.6% between January 2019 and December 2020.LT hospitalizations during the COVID-19 pandemic had a higher association with transplant rejection than before the pandemic[OR:1.53(95%CI:1.26-1.85),P<0.001].CONCLUSION The hospitalization rates for LT recipients were comparable before and during the pandemic.Inpatient mortality and transplant rejection rates for hospitalized LT recipients were increased during the COVID-19 pandemic.

Optimizing growth in pediatric renal transplant recipients: An update

Growth retardation is a significant complication observed in pediatric renal transplant recipients,originating from a multifactorial etiology.Factors contributing to growth impairment encompass pre-transplant conditions such as primary kidney disease,malnutrition,quality of care,growth deficits at the time of transplantation,dialysis adequacy,and the use of recombinant human growth hormone.Additionally,elements related to the renal transplant itself,such as living donors,corticosteroid usage,and graft functioning,further compound the challenge.Although renal transplantation is the preferred renal replacement therapy,its impact on achieving final height and normal growth in children remains uncertain.The consequences of growth delay extend beyond the physi-ological realm,negatively influencing the quality of life and social conditions of pediatric renal transplant recipients,and ultimately affecting their educational and employment outcomes.Despite advancements in graft survival rates,growth retardation remains a formidable clinical concern among children undergoing renal transplantation.Major risk factors for delayed final adult height include young age at transplantation,pre-existing short stature,and the use of specific immunosuppressive drugs,particularly steroids.Effective management of growth retardation necessitates early intervention,commencing even before transplantation.Strategies involving the administration of recombinant growth hormone both pre-and post-transplant,along with protocols aimed at minimizing steroid usage,are important for achieving catch-up growth.This review provides a comprehensive outline of the multifaceted nature of growth retardation in pediatric renal transplant recipients,emphasizing the importance of early and targeted interventions to mitigate its impact on the long-term well-being of these children from birth to adolescence.INTRODUCTION Children with chronic kidney disease(CKD)endure frequent hospitalizations and ongoing treatment,which significantly affect their quality of life.One of the most noticeable effects of CKD in children is poor growth,with stunted height being a common sign of chronic malnutrition.Growth assessment involves regularly measuring weight and height/length and comparing these against z-score charts,along with other anthropometric indicators like head circumference and mid-upper arm circumference.Data from the North American Pediatric Renal Trials and Collaborative Studies(NAPRTCS)registry shows that over 35%of children enrolled had stunted growth at the time of admission,with growth impairment being more severe in younger children(58%in those aged under 1 year,compared to 22%in those aged over 12 years).Additionally,the same data revealed that growth impairment worsens as the severity of the disease increases.Although recent advances in science have enabled better outcomes for children with CKD,in resource-limited settings,numerous children are still deprived of achieving optimal growth owing to the disease and its related factors.Stunting is a key indicator of chronic growth impairment in children.A study by Wong et al[1]in the United States Renal Data System found that each SD decrease in height among children with stage V CKD is linked to a 14%increase in the risk of death[1].Similarly,research by Furth et al[2]using data from the NAPRTCS indicated that children with a height standard deviation score(SDS)of-2.5 face a relative hazard of death of 2.07.Stunting also correlates with increased hospitalizations.A study in the United States followed 1112 pediatric patients with end-stage renal disease from 1990 to 1995.It showed that children with severe or moderate growth failure had higher hospitalization rates compared to those with normal growth.Specifically,the relative risk for hospitalization was 1.14(95%CI:1.1-1.2)for those with moderate growth failure and 1.24(95%CI:1.2-1.3)for those with severe growth failure,even after adjusting for age,sex,race,cause,and duration of end-stage renal disease,and treatment type[2](dialysis or transplant).The growth of a child significantly affects his/her psychological and overall well-being as an adult.Short children are often embarrassed by peers,and it has been observed that height influences employment status,with unemployment being more prevalent among stunted individuals.Further,marital opportunities can be fewer among stunted individuals[3].Hence,all measures to achieve adequate growth should be attempted in children with CKD,regardless of whether they undergo transplantation.

Study on the Alignment Between Talent Training Directions and Employment Market Demands in the Landscape Architecture Industry

Currently,talent training in Chinese universities for landscape architecture is mainly divided into three directions:“landscape planning and design,”“landscape construction management,”and“landscape plant planting and maintenance.”However,with the background of the slowing urbanization process and the widespread demand for composite talents in society,it remains to be verified whether the traditional three major talent training directions in landscape architecture align with the job demands in the current construction market.Based on a survey and analysis of over 300 industry practitioners,this study found a clear trend of merging the three major employment directions into“landscape design and construction”and“landscape plant planting and maintenance.”This presents new requirements and directions for the skill training of landscape architecture majors in universities and provides insights into the alignment between talent training and employment demands in other industries.

Diagnosis,treatment protocols,and outcomes of liver transplant recipients infected with COVID-19

Several cases of fatal pneumonia during November 2019 were linked initially to severe acute respiratory syndrome coronavirus 2,which the World Health Organization later designated as coronavirus disease 2019(COVID-19).The World Health Organization declared COVID-19 as a pandemic on March 11,2020.In the general population,COVID-19 severity can range from asymptomatic/mild symptoms to seriously ill.Its mortality rate could be as high as 49%.The Centers for Disease Control and Prevention have acknowledged that people with specific underlying medical conditions,among those who need immunosuppression after solid organ transplantation(SOT),are at an increased risk of developing severe illness from COVID-19.Liver transplantation is the second most prevalent SOT globally.Due to their immunosuppressed state,liver transplant(LT)recipients are more susceptible to serious infections.Therefore,comorbidities and prolonged immunosuppression among SOT recipients enhance the likelihood of severe COVID-19.It is crucial to comprehend the clinical picture,immunosuppressive management,prognosis,and prophylaxis of COVID-19 infection because it may pose a danger to transplant recipients.This review described the clinical and laboratory findings of COVID-19 in LT recipients and the risk factors for severe disease in this population group.In the following sections,we discussed current COVID-19 therapy choices,reviewed standard practice in modifying immunosuppressant regimens,and outlined the safety and efficacy of currently licensed drugs for inpatient and outpatient management.Additionally,we explored the clinical outcomes of COVID-19 in LT recipients and mentioned the efficacy and safety of vaccination use.

Cryptococcosis in kidney transplant recipients:Current understanding and practices

Cryptococcosis is the third most commonly occurring invasive fungal disease in solid organ transplant recipients(SOT).It is caused by encapsulated yeast,Cryptococcus species,predominantly Cryptococcus neoformans and Cryptococcus gattii.Though kidney transplant recipients are at the lowest risk of cryptococcosis when compared to other solid organ transplant recipients such as lung,liver or heart,still this opportunistic infection causes significant morbidity and mortality in this subset of patients.Mortality rates with cryptococcosis range from 10%-25%,while it can be as high as 50%in SOT recipients with central nervous system involvement.The main aim of diagnosis is to find out if there is any involvement of the central nervous system in disseminated disease or whether there is only localized pulmonary involvement as it has implications for both prognostication and treatment.Detection of cryptococcal antigen(CrAg)in cerebrospinal fluid or plasma is a highly recommended test as it is more sensitive and specific than India ink and fungal cultures.The CrAg lateral flow assay is the single point of care test that can rapidly detect cryptococcal polysaccharide capsule.Treatment of cryptococcosis is challenging in kidney transplant recipients.Apart from the reduction or optimization of immunosuppression,lipid formulations of amphotericin B are preferred as induction antifungal agents.Consolidation and maintenance are done with fluconazole;carefully monitoring its interactions with calcineurin inhibitors.This review further discusses in depth the evolving developments in the epidemiology,pathogenesis,diagnostic assays,and management approach of cryptococcosis in kidney transplant recipients.

Research on design methodology for railway freight service combination plans to meet diverse demands

Purpose–Facing the diverse needs of large-scale customers,based on available railway service resources and service capabilities,this paper aims to research the design method of railway freight service portfolio,select optimal service solutions and provide customers with comprehensive and customized freight services.Design/methodology/approach–Based on the characteristics of railway freight services throughout the entire process,the service system is decomposed into independent units of service functions,and a railway freight service combination model is constructed with the goal of minimizing response time,service cost and service time.A model solving algorithm based on adaptive genetic algorithm is proposed.Findings–Using the computational model,an empirical analysis was conducted on the entire process freight service plan for starch sold from Xi’an to Chengdu as an example.The results showed that the proposed optimization model and algorithm can effectively guide the design of freight plans and provide technical support for real-time response to customers’diversified entire process freight service needs.Originality/value–With the continuous optimization and upgrading of railway freight source structure,customer demands are becoming increasingly diverse and personalized.Studying and designing a reasonable railway freight service plan throughout the entire process is of great significance for timely response to customer needs,improving service efficiency and reducing design costs.

Risk stratification of renal transplant recipients using routine parameters: Implication of learning from SARS-CoV-2 into transplant follow-up program

BACKGROUND Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is a global pandemic that is associated with a high risk of morbidity and mortality among recipients of solid organ transplantation.In the course of acute SARS-CoV-2 infection,various laboratory markers have been identified as predictors for high risk of mortality.AIM To risk stratify renal transplant recipients(RTxR)using general demographic parameters,comorbidities and routine laboratory markers for the severity of the disease and its outcomes.We believe that learning about these routinely monitored parameters can help us plan better strategies for the RTxR follow-up program.METHODS This present study includes RTxR who acquired SARS-CoV-2 infection from March 2020 to February 2021.We recorded the basic demographics,comorbidities and routine laboratory markers.We investigated the impact of SARS-CoV-2 infection on RTxRs and risk-stratified the progression of disease severity and outcomes in terms of recovery or mortality.RESULTS From 505 RTxRs in our renal transplant follow-up program,29(7.75%)RTxRs had PCR-positive SARS-CoV-2 infection.We recorded 8 deaths from SARS-CoV-2 infection giving an overall mortality rate of 1.6%but a significant 27.6%mortality in SARS-CoV-2 positive recipients.Age more than 68 years,non-Caucasian ethnicity and male gender were associated with a significant drop in survival probability;P≤0.001.<0.001 and<0.0001 respectively.87.5%of the deceased were diabetic;P≤0.0.0001.Estimated glomerular filtration rate of less than 26 mL/min/1.73 m2,serum albumin less than 20 g/L,Hemoglobin less than 9.6 g/L and serum calcium less than 1.70 mmol/L were all associated with significantly increased risk of mortality;P=0.0128,<0.001,<0.0001 and 0.0061 respectively.CONCLUSION This study has identified some routinely used modifiable parameters in predicting a higher risk of mortality and morbidity.This knowledge can be used in RTxR follow-up programs by addressing these parameters early to help reduce the morbidity and mortality in RTxRs.

Recipient artery dissection during extracranial-intracranial bypass surgery:Two case reports

BACKGROUND Superficial temporal artery to middle cerebral artery(STA-MCA)bypass is a valuable treatment for preventing ischemia and hemorrhage in occlusive cerebrovascular disease.Anastomosis site dissection is rarely reported among the various bypass-related complications.CASE SUMMARY In this case report,we describe two patients,who were 63-and 59-years-old with middle cerebral artery occlusion treated by STA-MCA bypass.During bypass surgery,the recipient M4 artery intima was dissected.We sacrificed the dissecting portion,and no complications occurred during the follow-up period.Postoperative brain imaging revealed improved brain perfusion.We report rare cases of recipient artery dissection located in the extracranial to intracranial bypass site,and we suggest atherosclerotic changes in the recipient artery and insufficient puncture as the causes.CONCLUSION Appropriate recipient artery selection is critical,and if dissection occurs,it is essential to sacrifice the dissecting portion quickly.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

Vickrey-Clark-Groves-based Method for Eradicating Deceptive Behaviors in Demand Response Transactions

Demand response transactions between electric con-sumers,load aggregators,and the distribution network manag-er based on the"combination of price and incentive"are feasi-ble and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggrega-tors from taking illegitimate interests through deceptive behav-iors in the demand response transactions.Firstly,a demand re-sponse transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and val-idate the proposed method.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.

Vehicle routing optimization algorithm based on time windows and dynamic demand

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

Demand and Analysis of Clinical Research Curriculum in Medical Universities

Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,medical students at medical universities in Shaanxi Province were surveyed using online questionnaires.The survey covered their demographic information,awareness of their major,understanding of clinical research,and preferences for curriculum content.Results:A total of 341 valid questionnaires were analyzed.Medical students demonstrated a strong awareness of their majors but a relatively low awareness of clinical research.There was significant demand for clinical research courses,with preferences for professionally oriented(81.8%),market-oriented(100%),theoretically and practically integrated teaching(78.6%),and application-focused(73.0%)courses.Conclusion:Medical colleges and universities should align clinical research curricula with the actual needs of medical students and clinical practice.Reforms in curriculum design and teaching methods are essential to better prepare students for careers in public health.