THE CONSTRUCTION OF MULTITYPE CANONICAL MARKOV BRANCHING CHAINS IN RANDOM ENVIRONMENTS

The investigation for branching processes has a long history by their strong physics background, but only a few authors have investigated the branching processes in random environments. First of all, the author introduces the concepts of the multitype canonical Markov branching chain in random environment （CMBCRE） and multitype Markov branching chain in random environment （MBCRE） and proved that CMBCRE must be MBCRE, and any MBCRE must be equivalent to another CMBCRE in distribution. The main results of this article are the construction of CMBCRE and some of its probability properties.

Socioeconomic traits and the risk of Barrett’s esophagus and gastroesophageal reflux disease: A Mendelian randomization study

BACKGROUND Previous observational studies have shown that the prevalence of gastroesophageal reflux disease(GERD)and Barrett’s esophagus(BE)is associated with socioeconomic status.However,due to the methodological limitations of traditional observational studies,it is challenging to definitively establish causality.AIM To explore the causal relationship between the prevalence of these conditions and socioeconomic status using Mendelian randomization(MR).METHODS We initially screened single nucleotide polymorphisms(SNPs)to serve as proxies for eight socioeconomic status phenotypes for univariate MR analysis.The inverse variance weighted(IVW)method was used as the primary analytical method to estimate the causal relationship between the eight socioeconomic status phenotypes and the risk of GERD and BE.We then collected combinations of SNPs as composite proxies for the eight socioeconomic phenotypes to perform multivariate MR(MVMR)analyses based on the IVW MVMR model.Furthermore,a two-step MR mediation analysis was used to examine the potential mediation of the associations by body mass index,major depressive disorder(MDD),smoking,alcohol consumption,and sleep duration.RESULTS The study identified three socioeconomic statuses that had a significant impact on GERD.These included household income[odds ratio(OR):0.46;95% confidence interval(95%CI):0.31-0.70],education attainment(OR:0.23;95%CI:0.18-0.29),and the Townsend Deprivation Index at recruitment(OR:1.57;95%CI:1.04-2.37).These factors were found to independently and predominantly influence the genetic causal effect of GERD.Furthermore,the mediating effect of educational attainment on GERD was found to be mediated by MDD(proportion mediated:10.83%).Similarly,the effect of educational attainment on BE was mediated by MDD(proportion mediated:10.58%)and the number of cigarettes smoked per day(proportion mediated:3.50%).Additionally,the mediating effect of household income on GERD was observed to be mediated by sleep duration(proportion mediated:9.75%)CONCLUSION This MR study shed light on the link between socioeconomic status and GERD or BE,providing insights for the prevention of esophageal cancer and precancerous lesions.

Different effects of 24 dietary intakes on gastroesophageal reflux disease: A mendelian randomization

BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations are causal.METHODS To explore the relationship between dietary intake and the risk of GERD,we extracted appropriate single nucleotide polymorphisms from genome-wide asso-ciation study data on 24 dietary intakes.Three methods were adopted for data analysis:Inverse variance weighting,weighted median methods,and MR-Egger's method.The odds ratio(OR)and 95%confidence interval(CI)were used to eva-luate the causal association between dietary intake and GERD.RESULTS Our univariate Mendelian randomization(UVMR)results showed significant evidence that pork intake(OR,2.83;95%CI:1.76-4.55;P=1.84×10–5),beer intake(OR,2.70,95%CI:2.00-3.64;P=6.54×10–11),non-oily fish intake(OR,2.41;95%CI:1.49-3.91;P=3.59×10–4)have a protective effect on GERD.In addition,dried fruit intake(OR,0.37;95%CI:0.27-0.50;6.27×10–11),red wine intake(OR,0.34;95%CI:0.25-0.47;P=1.90×10-11),cheese intake(OR,0.46;95%CI:0.39-0.55;P=3.73×10-19),bread intake(OR,0.72;95%CI:0.56-0.92;P=0.0009)and cereal intake(OR,0.45;95%CI:0.36-0.57;P=2.07×10-11)were negatively associated with the risk of GERD.There was a suggestive asso-ciation for genetically predicted coffee intake(OR per one SD increase,1.22,95%CI:1.03-1.44;P=0.019).Multi-variate Mendelian randomization further confirmed that dried fruit intake,red wine intake,cheese intake,and cereal intake directly affected GERD.In contrast,the impact of pork intake,beer intake,non-oily fish intake,and bread intake on GERD was partly driven by the common risk factors for GERD.However,after adjusting for all four elements,there was no longer a suggestive association between coffee intake and GERD.CONCLUSION This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD,providing new insights for the treatment and prevention of GERD.

THE ANALYTICAL PROPERTIES FOR HOMOGENEOUS RANDOM TRANSITION FUNCTIONS

The concepts of Markov process in random environment and homogeneous random transition functions are introduced. The necessary and sufficient conditions for homogeneous random transition function are given. The main results in this article are the analytical properties, such as continuity, differentiability, random Kolmogorov backward equation and random Kolmogorov forward equation of homogeneous random transition functions.

THE ERGODICITY FOR BI-IMMIGRATION BIRTH AND DEATH PROCESSES IN RANDOM ENVIRONMENT

The concepts of bi-immigration birth and death density matrix in random environment and bi-immigration birth and death process in random environment are introduced. For any bi-immigration birth and death matrix in random environment Q（θ） with birth rate λ 〈 death rate μ, the following results are proved, （1） there is an unique q-process in random environment, P^-（θ＊（0）;t） = （p^-（θ^＊（0）;t,i,j）,i,j ≥ 0）, which is ergodic, that is, lim t→∞（θ^＊（0）;t,i,j） = π^-（θ^＊（0）;j） ≥0 does not depend on i ≥ 0 and ∑j≥0π （θ＊（0）;j） = 1, （2） there is a bi-immigration birth and death process in random enjvironment （X^＊ = {X^＊,t ≥ 0},ε^＊ = {εt,t ∈ （-∞, ∞）}） with random transition matrix P^-（θ^＊ （0）;t） such that X^＊ is a strictly stationary process.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

Can propensity score matching replace randomized controlled trials?

Randomized controlled trials(RCTs)have long been recognized as the gold standard for establishing causal relationships in clinical research.Despite that,various limitations of RCTs prevent its widespread implementation,ranging from the ethicality of withholding potentially-lifesaving treatment from a group to relatively poor external validity due to stringent inclusion criteria,amongst others.However,with the introduction of propensity score matching(PSM)as a retrospective statistical tool,new frontiers in establishing causation in clinical research were opened up.PSM predicts treatment effects using observational data from existing sources such as registries or electronic health records,to create a matched sample of participants who received or did not receive the intervention based on their propensity scores,which takes into account characteristics such as age,gender and comorbidities.Given its retrospective nature and its use of observational data from existing sources,PSM circumvents the aforementioned ethical issues faced by RCTs.Majority of RCTs exclude elderly,pregnant women and young children;thus,evidence of therapy efficacy is rarely proven by robust clinical research for this population.On the other hand,by matching study patient characteristics to that of the population of interest,including the elderly,pregnant women and young children,PSM allows for generalization of results to the wider population and hence greatly increases the external validity.Instead of replacing RCTs with PSM,the synergistic integration of PSM into RCTs stands to provide better research outcomes with both methods complementing each other.For example,in an RCT investigating the impact of mannitol on outcomes among participants of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial,the baseline characteristics of comorbidities and current medications between treatment and control arms were significantly different despite the randomization protocol.Therefore,PSM was incorporated in its analysis to create samples from the treatment and control arms that were matched in terms of these baseline characteristics,thus providing a fairer comparison for the impact of mannitol.This literature review reports the applications,advantages,and considerations of using PSM with RCTs,illustrating its utility in refining randomization,improving external validity,and accounting for non-compliance to protocol.Future research should consider integrating the use of PSM in RCTs to better generalize outcomes to target populations for clinical practice and thereby benefit a wider range of patients,while maintaining the robustness of randomization offered by RCTs.

THE BRANCHING CHAIN WITH DRIFT IN SPACE-TIME RANDOM ENVIRONMENT(I):MODEL,MARKOV PROPERTY,MOMENTS

There are three parts in this article. In Section 1, we establish the model of branching chain with drift in space-time random environment （BCDSTRE）, i.e., the coupling of branching chain and random walk. In Section 2, we prove that any BCDSTRE must be a Markov chain in time random environment when we consider the distribution of the particles in space as a random element. In Section 3, we calculate the first-order moments and the second-order moments of BCDSTRE.

THE EXISTENCE AND MOMENTS OF CANONICAL BRANCHING CHAIN IN RANDOM ENVIRONMENT

The concepts of branching chain in random environmnet and canonical branching chain in random environment are introduced. Moreover the existence of these chains is proved. Finally the exact formulas of mathematical expectation and variance of branching chain in random environment are also given.

ON MARKOV CHAINS IN SPACE-TIME RANDOM ENVIRONMENTS

In Section 1, the authors establish the models of two kinds of Markov chains in space-time random environments (MCSTRE and MCSTRE(+)) with abstract state space. In Section 2, the authors construct a MCSTRE and a MCSTRE(+) by an initial distribution Φ and a random Markov kernel (RMK) p(γ). In Section 3, the authors es-tablish several equivalence theorems on MCSTRE and MCSTRE(+). Finally, the authors give two very important examples of MCMSTRE, the random walk in spce-time random environment and the Markov br...

Theoretical and experimental study of a bi-stable piezoelectric energy harvester under hybrid galloping and band-limited random excitations

In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating.For this purpose,the effects of the wind speed and random excitation level are investigated with the stochastic averaging method(SAM)based on the energy envelope.The results of the analytical prediction are verified with the Monte-Carlo method(MCM).The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester(BEH)realize the performance enhancement for a weak base excitation.However,as the strength of the wind increases to a particular level,the influence of the random base excitation on the dynamic responses is weakened,and the system exhibits a periodic galloping response.A comparison between a BEH and a linear energy harvester(LEH)indicates that the BEH demonstrates inferior performance for high-speed wind.Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation.The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds.However,as the speed of the incoming wind is up to a particular level,the disadvantage of the BEH becomes clear and evident.

An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.

Immune cell signatures and causal association with irritable bowel syndrome:A mendelian randomization study

BACKGROUND The mucosal barrier's immune-brain interactions,pivotal for neural development and function,are increasingly recognized for their potential causal and therapeutic relevance to irritable bowel syndrome(IBS).Prior studies linking immune inflammation with IBS have been inconsistent.To further elucidate this relationship,we conducted a Mendelian randomization(MR)analysis of 731 immune cell markers to dissect the influence of various immune phenotypes on IBS.Our goal was to deepen our understanding of the disrupted brain-gut axis in IBS and to identify novel therapeutic targets.AIM To leverage publicly available data to perform MR analysis on 731 immune cell markers and explore their impact on IBS.We aimed to uncover immunophenotypic associations with IBS that could inform future drug development and therapeutic strategies.METHODS We performed a comprehensive two-sample MR analysis to evaluate the causal relationship between immune cell markers and IBS.By utilizing genetic data from public databases,we examined the causal associations between 731 immune cell markers,encompassing median fluorescence intensity,relative cell abundance,absolute cell count,and morphological parameters,with IBS susceptibility.Sensitivity analyses were conducted to validate our findings and address potential heterogeneity and pleiotropy.RESULTS Bidirectional false discovery rate correction indicated no significant influence of IBS on immunophenotypes.However,our analysis revealed a causal impact of IBS on 30 out of 731 immune phenotypes(P<0.05).Nine immune phenotypes demonstrated a protective effect against IBS[inverse variance weighting(IVW)<0.05,odd ratio(OR)<1],while 21 others were associated with an increased risk of IBS onset(IVW≥0.05,OR≥1).CONCLUSION Our findings underscore a substantial genetic correlation between immune cell phenotypes and IBS,providing valuable insights into the pathophysiology of the condition.These results pave the way for the development of more precise biomarkers and targeted therapies for IBS.Furthermore,this research enriches our comprehension of immune cell roles in IBS pathogenesis,offering a foundation for more effective,personalized treatment approaches.These advancements hold promise for improving IBS patient quality of life and reducing the disease burden on individuals and their families.

Causal associations between gastroesophageal reflux disease and essential hypertension: A bidirectional Mendelian randomization study

BACKGROUND Clinical studies have reported that patients with gastroesophageal reflux disease(GERD)have a higher prevalence of hypertension.AIM To performed a bidirectional Mendelian randomization(MR)analysis to investi-gate the causal link between GERD and essential hypertension.METHODS Eligible single nucleotide polymorphisms(SNPs)were selected,and weighted median,inverse variance weighted(IVW)as well as MR egger(MR-Egger)re-gression were used to examine the potential causal association between GERD and hypertension.The MR-Pleiotropy RESidual Sum and Outlier analysis was used to detect and attempt to reduce horizontal pleiotropy by removing outliers SNPs.The MR-Egger intercept test,Cochran’s Q test and“leave-one-out”sen-sitivity analysis were performed to evaluate the horizontal pleiotropy,heterogen-eities,and stability of single instrumental variable.RESULTS IVW analysis exhibited an increased risk of hypertension(OR=1.46,95%CI:1.33-1.59,P=2.14E-16)in GERD patients.And the same result was obtained in replication practice(OR=1.002,95%CI:1.0008-1.003,P=0.000498).Meanwhile,the IVW analysis showed an increased risk of systolic blood pressure(β=0.78,95%CI:0.11-1.44,P=0.021)and hypertensive heart disease(OR=1.68,95%CI:1.36-2.08,P=0.0000016)in GERD patients.Moreover,we found an decreased risk of Barrett's esophagus(OR=0.91,95%CI:0.83-0.99,P=0.043)in essential hypertension patients.CONCLUSION We found that GERD would increase the risk of essential hypertension,which provided a novel prevent and therapeutic perspectives of essential hypertension.

Genetically predicted fatty liver disease and risk of psychiatric disorders: A mendelian randomization study

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)and alcohol-related liver disease(Ar-LD)constitute the primary forms of chronic liver disease,and their incidence is progressively increasing with changes in lifestyle habits.Earlier studies have do-cumented a correlation between the occurrence and development of prevalent mental disorders and fatty liver.AIM To investigate the correlation between fatty liver and mental disorders,thus ne-cessitating the implementation of a mendelian randomization(MR)study to elu-cidate this association.METHODS Data on NAFLD and ArLD were retrieved from the genome-wide association studies catalog,while information on mental disorders,including Alzheimer's disease,schizophrenia,anxiety disorder,attention deficit hyperactivity disorder(ADHD),bipolar disorder,major depressive disorder,multiple personality dis-order,obsessive-compulsive disorder(OCD),post-traumatic stress disorder(PTSD),and schizophrenia was acquired from the psychiatric genomics consor-tium.A two-sample MR method was applied to investigate mediators in signifi-cant associations.RESULTS After excluding weak instrumental variables,a causal relationship was identified between fatty liver disease and the occurrence and development of some psychia-tric disorders.Specifically,the findings indicated that ArLD was associated with a significantly elevated risk of developing ADHD(OR:5.81,95%CI:5.59-6.03,P<0.01),bipolar disorder(OR:5.73,95%CI:5.42-6.05,P=0.03),OCD(OR:6.42,95%CI:5.60-7.36,P<0.01),and PTSD(OR:5.66,95%CI:5.33-6.01,P<0.01).Meanwhile,NAFLD significantly increased the risk of developing bipolar disorder(OR:55.08,95%CI:3.59-845.51,P<0.01),OCD(OR:61.50,95%CI:6.69-565.45,P<0.01),and PTSD(OR:52.09,95%CI:4.24-639.32,P<0.01).CONCLUSION Associations were found between genetic predisposition to fatty liver disease and an increased risk of a broad range of psychiatric disorders,namely bipolar disorder,OCD,and PTSD,highlighting the significance of preven-tive measures against psychiatric disorders in patients with fatty liver disease.

一种基于KMeans与Random Forest的异常温升捕捉方法

针对线路老化、线路过载的火灾频发问题,分析了线路老化、线路过载与异常温升之间的关联性,以电流值、线缆温度作为输入,利用KMeans聚类算法划分可能存在异常温升的区间,通过Random Forest算法识别线路过载问题,可以提前通知用户整改线路,预防火灾的发生。

Python语言random库经典案例教学

Python是一种计算生态语言,也是开源的语言,具有丰富和强大的类库,语法简洁、清晰明了。随着物联网、大数据、人工智能等技术的兴起,Python位于PYPL全球编程语言排行榜的榜首,成为受人们欢迎的编程语言。主要阐述利用Python的random库解决一些实际问题,既提高学习者的兴趣和积极性,又能提高学习者利用所学知识分析和处理实际问题的能力。

OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

How completely are randomized controlled trials of non-pharmacological interventions following concussion reported? A systematic review

Purpose:The study aimed to examine the reporting completeness of randomized controlled trials(RCTs)of non-pharmacological interventions following concussion.Methods:We searched MEDLINE,Embase,PsycInfo,CINAHL,and Web of Science up to May 2022.Two reviewers independently screened studies and assessed reporting completeness using the Template for Intervention Description and Replication(TIDieR),Consensus on Exercise Reporting Template(CERT),and international Consensus on Therapeutic Exercise aNd Training(i-CONTENT)checklists.Additional information was sought my study authors where reporting was incomplete.Risk of bias(ROB)was assessed with the Cochrane ROB-2 Tool.RCTs examining non-pharmacological interventions following concussion.Results:We included 89 RCTs(n=53 high ROB)examining 11 different interventions for concussion:sub-symptom threshold aerobic exercise,cervicovestibular therapy,physical/cognitive rest,vision therapy,education,psychotherapy,hyperbaric oxygen therapy,transcranial magnetic stimulation,blue light therapy,osteopathic manipulation,and head/neck cooling.Median scores were:TIDieR 9/12(75%;interquartile range(IQR)=5;range:5-12),CERT 17/19(89%;IQR=2;range:10-19),and i-CONTENT 6/7(86%;IQR=1;range:5-7).Percentage of studies completely reporting all items was TIDieR 35%(31/89),CERT 24%(5/21),and i-CONTENT 10%(2/21).Studies were more completely reported after publication of TIDieR(t_(87)=2.08;p=0.04)and CERT(t_(19)=2.72;p=0.01).Reporting completeness was not strongly associated with journal impact factor(TIDieR:rs=0.27;p=0.01;CERT:r_(s)=-0.44;p=0.06;i-CONTENT:r_(s)=-0.17;p=0.48)or ROB(TIDieR:rs=0.11;p=0.31;CERT:rs=0.04;p=0.86;i-CONTENT:rs=0.12;p=0.60).Conclusion:RCTs of non-pharmacological interventions following concussion demonstrate moderate to good reporting completeness,but are often missing key components,particularly modifications,motivational strategies,and qualified supervisor.Reporting completeness improved after TIDieR and CERT publication,but publication in highly cited journals and low ROB do not guarantee reporting completeness.

Efficacy of a Nutritional Cream Intervention to Treat Depression in Rescuers:A Randomized Controlled Trial

Objective To explore the effectiveness of a nutritional intervention in rescuers who screened positive for depression.Methods A randomized controlled trial design was employed.From June to August,2022,4,460 rescuers were screened using the Self-Rating Depression Scale(SDS),and 1,615 positive cases were identified.Thirty-one volunteers were recruited and randomly divided into a nutritional intervention group and a control group.The intervention group received health education and nutritional intervention(a compound paste therapy primarily composed of red roses and Seville orange flowers),while the control group received psychological education.SDS scores were assessed before and after the intervention.Results There was a statistically significant decline in SDS scores in the nutritional intervention group after the intervention(P<0.05).Furthermore,the SDS scores of the intervention group were significantly lower than those of the control group,both before and after the intervention(P<0.05).No severe adverse reactions were observed during safety evaluation.Conclusion The nutritional intervention effectively reduced the depression scores in rescuers.Early nutritional intervention is recommended for rescuers who initially screen positive for depression.