Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

User Preference Aware Hierarchical Edge-User Cooperative Caching Strategy

The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.

Deep Learning Social Network Access Control Model Based on User Preferences

A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.

Pregnancy Preferences in Females of Reproductive Age with Sickle Cell Disease at Laquintinie Hospital: A Cross-Sectional Analysis

Introduction: Females with sickle cell disease (SCD), despite having a delayed pubertal development, are subject to many worries relating to their abilities to conceive, their capacity to maintain a maternofetal-risk-free pregnancy till term and give birth to healthy children without sickle cell disease. Knowing that unplanned pregnancies are more likely to increase maternofetal morbidity and mortality, we sought out to explore the pregnancy preferences in female patients with sickle cell disease to promote healthy conception and childbirth in this vulnerable population. Methodology: We conducted a cross-sectional study involving female patients of child-bearing age with sickle cell disease followed at Laquintinie Hospital Douala or who were members of a local sickle cell association. Pregnancy preferences were determined using the Desire to Avoid Pregnancy (DAP) scale. Factors associated with pregnancy preferences were determined using multivariable linear regression model. Threshold for significance was set at p Results: Seventy-seven patients were included with a mean age of 24.71 ± 5.53 years. Forty patients (51.95%) had one sexual partner and thirteen women (32.5%) used contraceptive methods. Most patients (46.0%) responded “Strongly Agree” or “Agree” to the statement “it would be a good thing for me if I became pregnant in the next 3 months”. The mean DAP score was 1.63 ± 0.91 [1.28 ± 0.82 in those who had a sexual partner and 1.99 ± 0.86 in those who had no sexual partner]. Factors that were positively associated with DAP score were students (b = 0.32, 95% CI [0.21, 0.95], p = 0.003), monthly income ≥ 100,000 FCFA (b = 0.24, 95% CI [0.07, 0.81], p = 0.022), and not having a sexual partner (b = 0.26, 95% CI [0.11, 0.85], p = 0.012). Conclusion: Most female patients with SCD have a low desire to avoid pregnancy. This is especially true for patients who are not students, have a partner and have a low monthly income.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

Adaptive Successive POI Recommendation via Trajectory Sequences Processing and Long Short-Term Preference Learning

Point-of-interest(POI)recommendations in location-based social networks(LBSNs)have developed rapidly by incorporating feature information and deep learning methods.However,most studies have failed to accurately reflect different users’preferences,in particular,the short-term preferences of inactive users.To better learn user preferences,in this study,we propose a long-short-term-preference-based adaptive successive POI recommendation(LSTP-ASR)method by combining trajectory sequence processing,long short-term preference learning,and spatiotemporal context.First,the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window.Subsequently,an adaptive filling strategy is used to expand the recent check-in sequences of users with inactive check-in behavior using those of similar active users.We further propose an adaptive learning model to accurately extract long short-term preferences of users to establish an efficient successive POI recommendation system.A spatiotemporal-context-based recurrent neural network and temporal-context-based long short-term memory network are used to model the users’recent and historical checkin trajectory sequences,respectively.Extensive experiments on the Foursquare and Gowalla datasets reveal that the proposed method outperforms several other baseline methods in terms of three evaluation metrics.More specifically,LSTP-ASR outperforms the previously best baseline method(RTPM)with a 17.15%and 20.62%average improvement on the Foursquare and Gowalla datasets in terms of the Fβmetric,respectively.

Surgeon preferences in the treatment of thumb carpometacarpal osteoarthritis

BACKGROUND Primary thumb carpometacarpal(CMC)osteoarthritis is one of the most common conditions encountered by hand surgeons.Of the vast number of operations that have been proposed,none have demonstrated results significantly superior to trapeziectomy alone.AIM The purpose of our study was to determine why surgeons opt for their technique in treating CMC arthritis.METHODS A cross-sectional survey of active members of the American Society for Surgery of the Hand was conducted to evaluate the reasons behind their preferred technique in the treatment of isolated thumb CMC arthritis.Surgeons were contacted by email once and provided with a link to a de-identified survey consisting of 5 treatment questions and 5 demographic questions.RESULTS Of 950 responses were received.40.5%of surgeons preferred trapeziectomy+ligament reconstruction tendon interposition(LRTI),followed by trapeziectomy+suspensionplasty(28.2%),suture button suspension(5.9%),trapeziectomy alone(4.6%),prosthetic arthroplasty(3.2%),arthrodesis(1.1%),and other(6.6%).Proponents of trapeziectomy+LRTI cited familiarity(73.2%),exposure during fellowship(48.8%)and less proximal migration(60%)to be the main reasons affecting their decision.Surgeons who preferred trapeziectomy+suspensionplasty most reported simplicity(74.9%),fewer complications(45.3%),less proximal migration(43.8%),and avoidance of autogenous tissue harvest(42.7%).Advocates of suture button suspension cited avoidance of autogenous tissue harvest(80.4%),shorter immobilization(76.8%),and quicker recovery(73.2%)with their technique.Advocates of trapeziectomy alone cited simplicity(97.7%),fewer complications(86.4%),and avoidance of autogenous tissue harvest(59.1%).In their comments,45%of surgeons choosing trapeziectomy alone cited evidence as an additional rationale.Advocates of prosthetic arthroplasty cited improved pinch strength(83.3%)and improved range of motion(63.3%),while those preferring arthrodesis cited better pinch strength(90%)and frequently in their comments,durability.Of the surgeons who preferred a technique other than LRTI,41.8%reported they had tried LRTI in the past,citing complexity of the procedure,flexor carpi radialis harvest,and longer operative time as reasons for moving on.CONCLUSION Our study provides an update on current treatment trends and offers new insight into the reasons behind surgeons'decision making in the management of thumb carpometacarpal osteoarthritis.Despite strong Level 1 evidence supporting the use of trapeziectomy alone,our findings demonstrate that most surgeons continue to supplement trapeziectomy with other techniques such as LRTI or suspensionplasty.Several factors including familiarity,personal experience(Level 4 evidence),and comfort may be more influential than Level 1 evidence in determining the techniques in a surgeon's armamentarium.Further prospective studies are needed to determine the optimal technique for surgical management of Eaton stages II-IV CMC arthritis and how these studies will affect surgeons’choice.

Oviposition Site Preference and Its Effects on Subsequent Development of Variegated Grasshopper (Zonocerus variegatus L.) under Laboratory Conditions

Female grasshoppers can affect the fitness of their offspring through their selection of oviposition site. Knowledge of soil type on oviposition, and its effects on subsequent development can provide guidelines for habitat manipulations that reduce the harmful effects of these pests on farmers fields. The influence of soil types on the oviposition site preference of variegated grasshopper (Zonocerus variegatus L.) reared some cassava (Manihot esculenta Crantz) varieties, was investigated in a cage trial carried out at the Bio factory laboratory, School of Agriculture and Food Sciences, Njala University, Sierra Leone during 2022/2023. The treatments comprised three soil types (Sandy, Loamy and Clay), each with three replications laid out in a randomized complete block design (RCBD) in wooden cages. Data were collected on the following development parameters including, Net reproductive growth ratio (R0), Generation time (Tc), Intrinsic rate of increase (rm), Finite rate of increase (), Doubling time (Dt), and overall survivorship. Findings revealed that, Z. variegatus L. preferred sandy soil in which, on average, most eggs were deposited (338, 6.62 4.40), followed by loamy soil, 286 (5.53 3.96), and then, clayey soil, 200 (3.91 3.85);though, the differences were not significant. This study established that Z. variegatus deposited more eggs in sandy soil > loamy soil > clayey soil, respectively;and subsequent survivorship of the immature unto mature adult insect, revealed a similar order. This indicates that the sandy soil is the most preferred substrate for oviposition and subsequent development into adult insects.

Response of Distribution Range Against Climate Change and Habitat Preference of Four National Protected Diploderma Species in Tibetan Plateau

Understanding the spatial distribution and habitat preference for rare and endangered species are essential for effective conservation practice.We examined the spatial distribution and habitat preference of four Diploderma species(Diploderma drukdaypo,D.laeviventre,D.batangense,and D.vela),which are endemic to the Qinghai-Tibet Plateau and are currently under state protection.We used the ensembles of small models(ESM)approach and predicted potential distribution ranges of the species in current and two future climate scenarios(SSP126 and SSP585).The degree of overlap between the predicted distribution ranges and existing natural reserves was further analyzed.Habitat preference was examined using a paired quadrat method.Our results predicted that D.drukdaypo has a current distribution range of 600 km^(2),which would decrease to 50 km^(2)and 55 km^(2)under the SSP126 and SSP585 respectively.For D.laeviventre,the current distribution range is 817 km^(2),with minimum changes in the two future climate scenarios(774 km^(2)and 902 km^(2)).For D.batangense,the current distribution range is 875 km^(2),which would expand to 1522 km^(2)and 3340 km^(2)in the two future climate scenarios.Similarly for D.vela,the current distribution range is 1369 km^(2),which would change to 1825 km^(2)and 2043 km^(2)respectively under the two future climate scenarios.The effect of protection of current nature reserves are likely low for those species;we found no overlap(D.drukdaypo,D.laeviventre)or little overlap(D.batangense 2.04%–3.56%,D.vela 15.52%–16.87%)between the currently designated protection area and distribution range under current and future climate scenarios.For habitat preference,stones appear to be the critical habitat element for those species although different species had different stone requirements.Taken together,we provided critical information on potential distribution ranges and habitat preference for four endangered Diploderma species,and confirmed the inadequacy of current nature reserves.The establishment of new or expansion of existing nature reserves is urgent for the conservation of those species.

The role of time preferences in contract breach:Evidence from Chinese poultry farmers participating in contract farming

Farmers’contract breach behavior is cited as one of the major stumbling blocks in the sustainable expansion of contract farming in many developing countries.This paper examines farmers’contract breach decisions from the perspective of time preferences.The empirical analysis is based on a household survey and economic field experiments of poultry households participating in contract farming conducted in Jiangsu Province,China.A discounted utility model and a maximum likelihood technique are applied to estimate farmers’time preferences and the effect of time preferences on contract breach in the production and sales phases are explored with a bivariate probit model.The results show that,on average,the poultry farmers in the sample are generally present biased and impatient regarding future utility.The regression results show that farmers with a higher preference for the present and a higher discount rate are more likely to breach contracts,and time preferences play a greater role in the production phase than in the sales phase.When considering heterogeneity,specific investments and transaction costs promote contract stability only for farmers with a low degree of impatience.Moreover,compared with large-scale farmers,small-scale farmers’contract breach decisions are more significantly affected by their time preferences.These results have implications for contract stability policies and other issues that are impacted by the linking of behavioral preferences to agricultural decisions.

Consumers’experiences and preferences for plant-based meat food:Evidence from a choice experiment in four cities of China

This paper examined consumers’experiences in and preferences for plant-based meat(PBM)food and their respective correlates,based on data from an online survey of 579 consumers in four major cities in China in early 2021.We first described consumers’experiences in consuming and purchasing PBM food and their correlates,and then analyzed consumer preferences using hypothetical choice experiment.The experiment offered consumers various options to purchase burgers made from PBM or animal-based meat(ABM),combined with different countries of origin(COO),taste labels,and prices.Our data showed that respondents hold overall positive attitudes toward PBM food;85 and 82%of respondents reported experience in eating and purchasing PBM food,respectively.More than half of them ate PBM food because they wanted to try new food(58%),or were interested in healthy food(56%).Income,religion,and dietary restrictions were significantly correlated with consumers’experiences in PBM food consumption.Results from the Random Parameter Logit Model based on the hypothetical choice experiment data showed that 79%of respondents chose PBM burgers and were willing to pay an average of 88 CNY for a PBM burger.We also found that 99.8 and 83%of respondents are willing to buy burgers made in China and those with a taste label,with a willingness to pay(WTP)of 208 and 120 CNY,respectively.The heterogeneity test revealed that females and those with at least a bachelor’s degree,higher income,religious beliefs,and dietary restrictions are more likely to buy PBM burgers than their counterparts.

Farmers’risk preference and fertilizer use

This study examines the role of farmers’risk attitudes toward fertilizer use in cotton production in China.Contradicting previous studies,this paper theoretically shows that the relationship between farmers’risk aversion and fertilizer use is not always monotonic.Field survey data were collected to test this relationship using the Cobb–Douglas production function.Results suggest that when the elasticity of fertilizer use and the probability of achieving the desired effects from fertilizer use are high,risk-averse farmers apply more fertilizer than risk-taking farmers.Conversely,when the elasticity of fertilizer use and the probability of achieving the desired effects are low,risk-taking farmers apply more fertilizer than risk-neutral or risk-averse farmers.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Validity and Reliability of the Preference for and Tolerance of the Intensity of Exercise Questionnaire among Chinese College Students

The rising prevalence of physical inactivity is in all age groups(e.g.,in college students)a major public health issue as not meeting the recommended minimum amount of regular physical activity is linked to adverse health events.Vice versa,there is mounting evidence that achieving the recommended amount of regular physical activity is a vital element to prevent chronic diseases,but there is often an insufficient adherence to planned and structured forms of physical activity(i.e.,physical exercises).In this context,there is a large body of evidence indicating that exercise adherence is,among other factors,influenced by exercise-related affective responses.The Preference for and Tolerance of the Intensity of Exer-cise Questionnaire(PRETIE-Q)has been developed to measure these affective responses(e.g.,to specific exercise inten-sities).So far,no validated Chinese version of the PRETIE-Q has been available in the literature.To address this gap in literature,the present study developed and validated a Chinese version of the PRETIE-Q in a large sample of Chinese college students.Data from a total of 1117 college students were collected for analyses concerning factorial validity and construct validity.The re-test reliability was established using a sample of 150 randomly selected participants.In addition,the level of regular physical activity(PA),cardiorespiratoryfitness(CRF),and resilience were used to examine possible links with two domains(preference and tolerance)of the PRETIE-Q.Our results showed that a Chinese version of the PRETIE-Q has a goodfit and reliability(Cronbach’sαof 0.72 to 0.85 for preference and tolerance,respectively;ICC:r=0.72 of preference and r=0.67 of tolerance;fit indices:χ^(2)=21.612,df=19,p>0.05,TLI=0.997,CFI=0.998,RMSEA=0.016,SRMR=0.024).Secondly,positive associations of intensity-tolerance with PA,CRF,and resilience were observed.In summary,this study indicates that the Chinese version of the PRETIE-Q has sound psychometric properties and can be used in Chinese college students.The adapted version of the PRETIE-Q paves the way for further research on exer-cise-related affective responses in Chinese-speaking samples,although the generalizability of ourfindings needs to be established for other cohorts such as adolescents and older people with and without chronic diseases.

Hypoxia tolerance in fish depends on catabolic preference between lipids and carbohydrates

Hypoxia is a common environmental stress factor in aquatic organisms,which varies among fish species.However,the mechanisms underlying the ability of fish species to tolerate hypoxia are not well known.Here,we showed that hypoxia response in different fish species was affected by lipid catabolism and preference for lipid or carbohydrate energy sources.Activation of biochemical lipid catabolism through peroxisome proliferator-activated receptor alpha(Pparα)or increasing mitochondrial fat oxidation in tilapia decreased tolerance to acute hypoxia by increasing oxygen consumption and oxidative damage and reducing carbohydrate catabolism as an energy source.Conversely,lipid catabolism inhibition by suppressing entry of lipids into mitochondria in tilapia or individually knocking out three key genes of lipid catabolism in zebrafish increased tolerance to acute hypoxia by decreasing oxygen consumption and oxidative damage and promoting carbohydrate catabolism.However,anaerobic glycolysis suppression eliminated lipid catabolism inhibition-promoted hypoxia tolerance in adipose triglyceride lipase(atgl)mutant zebrafish.Using 14 fish species with different trophic levels and taxonomic status,the fish preferentially using lipids for energy were more intolerant to acute hypoxia than those preferentially using carbohydrates.Our study shows that hypoxia tolerance in fish depends on catabolic preference for lipids or carbohydrates,which can be modified by regulating lipid catabolism.

基于LDSCR-at-Risk的PPP项目可融资性评价

通过分析传统的偿债备付率适用性及政府和社会资本合作(PPP)项目的特点,认为传统的偿债备付率不适合于PPP项目可融资性评价。因此,为了评价中长期债务的可融资性,提出了“平准化偿债备付率”(LDSCR),即在借款偿还期内,各年可用于还本付息的资金折现到起始点的现值与贷款金额的比值;进一步提出“风险下的平准化偿债备付率”(LDSCR-at-Risk),即在给定的置信度下的平准化偿债备付率。运用蒙特卡洛仿真进行验证,结果表明:LDSCR-at-Risk可用于PPP项目的可融资性评价,且在可以评价具有风险的PPP项目可融资性的同时,还避免了如何确定项目的最低偿债备付率的问题,从而促进PPP项目融资的发展。