Sustainable management of water-agriculture-ecology nexus system under multiple uncertainties.

The shrinkage and ecological degradation of the Aral Sea resulting from the uncontrolled use of water resources and the unregulated expansion of agriculture activities call for sustainable management of water-agriculture-ecology (WAE) nexus from a basin perspective. However, managers face thorny challenges brought by multiple uncertainties in the management and planning processes. In this study, an interval stochastic fuzzy programming (ISF) method is developed for tackling multiple uncertainties presented as probability distributions, flexible variables and interval parameters. Then, an ISF-WAE model is formulated for Aral Sea Basin, which considers 108 planning scenarios that reflect different food-security and ecology-restoration requirements, as well as risk-response attitudes of decision maker over a long-term planning horizon (2021-2050). Results reveal that for Aral Sea Basin: (i) managers should set strict acreage benchmarks for cereal crops, in which wheat would account for a range of [29.1, 31.2] % of the total agricultural area; (ii) for promoting ecological restoration, the proportion of agricultural water allocation should decrease by a range of [12.7, 16.1] % during the planning horizon; (iii) due to low water requirement and high ecological value of grassland, it is recommended to expand grassland area to improve the sustainability of the Aral Sea Basin in the case of limited water resources.

[Efficacy of off-pump minimally invasive via a single left intercostal space incision compared with median sternotomy multi-vesselcoronary artery bypass grafting].

Objective: To compare the efficacy of off-pump minimally invasive cardiac surgery (MICS) via a single left intercostal space incision with median sternotomy multi-vesselcoronary artery bypass grafting (CABG). Methods: Patients who were diagnosed with multi-artery coronary artery disease (CAD) in the Ward 10 of the Department of Cardiac Surgery, Beijing Anzhen Hospital Affiliated to Capital Medical University and underwent CABG from July 2019 to January 2022 were retrospectively collected. All the patients were divided into MICS group and conventional CABG group according to the surgical methods. The perioperative outcomes were compared between thetwo groups, including intraoperative blood loss, postoperative 24 h thoracic drainage volume, ventilation duration, length of stay (LOS) in intensive care unit (ICU) and total LOS in hospital. Intraoperative blood flow of graft vesselswas measured by transit-time flow measurement (TTFM) after vascular anastomosis, and mean flow (MF) and pulsatile index (PI) were compared between the two groups. Results: A total of 444 patients were in the final analysis, with 351 males and 93 females, and the mean age of (62.0±8.9) years. There were 179 patients in MICS group and 265 cases in conventional CABG group, respectively. There were no statistically significant differences in the preoperative profiles between the two groups (all P>0.05) except that younger age [(60.7±9.3) years vs (62.8±8.5) years, P=0.017] and lower proportion of female [10.1% (18/179) vs 28.3% (75/265), P<0.001] were detected in MICS group. Likewise, there was no significant difference in the number of graft vessels between MICS group (3.18±0.74) and conventional CABG group (3.28±0.86) (P=0.234). Compared with those in conventional CABG group, patients in MICS group showed longer operation duration [ (5.10±1.09) h vs (4.33±0.86) h], fewer intraoperative blood loss [500 (200, 700) ml vs 700 (600, 900) ml], fewer postoperative 24 h thoracic drainage volume [300 (200, 400) ml vs 400 (250, 500) ml], shorter postoperative ventilation duration [15.0 (12.0, 17.0) h vs 16.5 (12.5, 19.0) h, P<0.001], LOS in ICU [18.0 (15.0, 20.0) h vs 20.0 (16.0, 23.0) h, P<0.001] and total LOS in hospital [(12.6±2.7) d vs (14.5±3.9) d, P<0.001]. MI and PI of graft vessels were similar between the two groups (both P>0.05). Moreover, there were no significant differences in major perioperative complications (i.e., repeat thoracotomy, incision infection, stroke) and mortality between the two groups (all P>0.05). Conclusion: MICS is an alternative treatment for patients with multi-vessel CAD with better perioperative outcomes compared with conventional CABG.

Assessment of the effects of human activity and natural condition on the outflow of Syr Darya River: A stepwise-cluster factorial analysis method.

Water scarcity causes a series of eco-environmental problems, such as land salinization, biodiversity reduction and food crisis, which seriously restricts the sustainable development of the Aral Sea basin. In this study, a stepwise-cluster factorial analysis (SCFA) approach is proposed for assessing the effects of natural condition and human activity on the outflow of Syr Darya River (abbreviated as OSR) that has significant effects on the eco-environmental restoration of the Aral Sea. SCFA coupled stepwise cluster analysis and factorial analysis cannot only reflect the variability of outflow, but also identify the driving factors quantitatively. The results disclose that, in 1960-1991, the dominant factors (affecting the OSR) are upstream inflow (25.77%) > agricultural water use of Uzbekistan (7.21%) > industrial water use of Uzbekistan (4.53%) > agricultural water use of Kazakhstan (3.81%) > Precipitation (3.66%); interactions between upstream inflow and agricultural water use of Uzbekistan, Kazakhstan and Tajikistan and interactions between reservoir and evapotranspiration have the significant effects on the OSR. Results also indicate that, in 1992-2015, the dominant factors that affect the OSR are agricultural water use of Uzbekistan (23.31%) > agricultural water use of Kazakhstan (22.15%) > industrial water use of Uzbekistan (8.31%) > domestic water use of Kazakhstan (4.68%) > agricultural water use of Tajikistan (4.54%) > domestic water use of Uzbekistan (4.41%); the interactions between industrial water use and agricultural water use of Uzbekistan, Kazakhstan and Tajikistan and the interactions between reservoir and upstream inflow have the pivotal effects on OSR. In the future, when the agricultural water use of the basin decrease as 4% and the industry water use of Uzbekistan decrease as 2%, the OSR may recover to the middle level of 1970s. The results help identify the major factors affecting the outflow of Syr Darya River as well as seek an effective approach to restore the eco-environment of Aral Sea basin.

Impacts of climate variations on non-stationarity of streamflow over Canada.

With climate change, understanding and assessing the impact of climate variations on non-stationary changes of streamflow is of importance in the hydrologic and atmospheric sciences. In this study, tempo-spatial and scaling effects in the impacts of 18 climate variations on nonstationary streamflow for 279 watersheds across Canada are explored. Specifically, the change point and trends of streamflow are examined through Pettitt's test and Mann-Kendall test. Spatial patterns of correlations between the climate variations and flow rates over Canada, especially their non-stationarity, are investigated at seasonal and decadal scales. The patterns are also quantified by seven spatial classification algorithms under method uncertainty. A series of findings regarding the impacts are revealed. For instance, nonstationary changes of streamflow exist for approximately 9% of Canadian watersheds and most of them are located in Prairie Provinces and the eastern coast. The Atlantic Multidecadal Oscillation, Niño 12, Niño 3, Niño 4, and Niño 3.4 pose significant impacts on Canadian streamflow, which vary with watersheds and seasons. The impacts are closely associated with human activities, e.g., significant impacts of climate variations on populated-area streamflow over Canada. Different climatic variations have different time-varying effects on streamflow. All watersheds have obvious clustering characteristics and four spatial patterns are identified, which is insensitive with classification algorithm. These findings are conducive to understanding the hydrological impacts of atmospheric circulation and enhancing the reliability of hydrological prediction.

Development of an integrated multivariate trend-frequency analysis method: Spatial-temporal characteristics of climate extremes under global warming for Central Asia.

Temperature and precipitation are the two most critical climate variables and their extreme states have more severe impacts than average states on both human society and natural ecosystem. In this study, an integrated multivariate trend-frequency analysis (IMTFA) approach is developed for the risk assessment of climate extremes under the global warming. Through incorporating multiple time series analysis techniques (i.e., M-K test, Sen's slope estimator and Pettitt test) and copula function into a general framework, IMTFA is capable not only of analyzing the temporal trends and change points of extreme temperatures and precipitations, but also of quantifying their univariate and multivariate risks. IMTFA is applied to the Central Asia with considering a long-term (1881-2018) observation data. Our findings are: (i) significant wetting and warming trends were occurred in the Central Asia over past one hundred years, where 42.5%, 59.4% and 79.2% stations have change points for extreme precipitations, maximum and minimum temperatures, respectively; (ii) the occurrences of extreme climate events show obviously spatial heterogeneity, where the highest risks of meteorological drought, flood and frost events are occurred in the southwest, southeast and northeast regions, respectively; (iii) global warming significantly affects the intensities and frequencies of extreme precipitations and temperatures, and their univariate and multivariate risks are intensified in the most regions of Central Asia. The above findings can provide more valuable information for risk assessment and disaster adaptation of climate extremes in Central Asia.

Identifying optimal virtual water management strategy for Kazakhstan: A factorial ecologically-extended input-output model.

Virtual water is an important indicator measuring the amount of water needed from the perspective of consumption, which can help decision makers to identify desired system design and optimal management strategy against water resources shortage. In this study, a novel model named as factorial ecologically-extended input-output model (abbreviated as FEIOM) is developed for virtual water management. FEIOM integrates techniques of input-output model (IOM), ecological network analysis (ENA) and factorial analysis (FA) into a general framework. It is effective to evaluate the virtual water flows, reveal ecological inter-connections in virtual water system (VWS), and identify key water consumption sectors that have significant individual and interactive effects on VWS's performance. FEIOM is then applied to identifying optimal virtual water management strategies for Kazakhstan in Central Asia. The main findings are: (i) Kazakhstan is a net importer of virtual water (reaching up to 46.0 × 109 m3), demonstrating that the national economic structure is reasonable, which can abate the national water scarcity and improve its eco-environmental protection; (ii) the virtual water of agricultural sector is net exporter, where vegetables, fruits and nuts occupy 86% of the total agricultural exports; the massive export of water-intensive products further squeezes the water for other users; (iii) the key factors affecting the national VWS are agriculture > primary manufacturing > advanced manufacturing > services. Therefore, from solving water resources shortage and facilitating sustainable development perspectives, Kazakhstan should stimulate the domestic primary manufacturing productions and improve agriculture and advanced manufacturing water-use efficiencies.

A factorial Bayesian copula framework for partitioning uncertainties in multivariate risk inference.

In this study, a factorial Bayesian copula (FBC) method is proposed to quantify parameter uncertainties in copula-based models and then reveal their impacts on hydrologic risk inferences within a multivariate context. In detail, Bayesian inference and factorial analysis are integrated into copula-based multivariate risk models to (1) quantify parameter uncertainties, (ii) reveal their individual and interactive effects, and (iii) identify their detailed contributions to uncertain risk inferences. Streamflow observations at Xiangxi and Wei River basins is China are used to illustrate the applicability of FBC. The results indicate that imprecise parameters in marginal distributions and the dependence structure would lead to extensive uncertainties in predictive joint return periods and failure probabilities. Also, individual and interactive effects of parameters are well revealed through multilevel factorial analysis, and the detailed contributions of one parameter to different failure probabilities under different service time scenarios are identified.

A bi-level chance-constrained programming method for quantifying the effectiveness of water-trading to water-food-ecology nexus in Amu Darya River basin of Central Asia.

Issues of water scarcity, food crisis, and ecological degradation pose great challenges to the sustainable development of Central Asia. In this study, a bi-level chance-constrained programming (BCCP) method is developed for planning water-food-ecology (WFE) nexus system of the Amu Darya River basin, where the efficiency of water-trading mechanism and the impact of uncertain water-availability are examined. This is the first attempt for planning WFE nexus system by incorporating chance-constrained programming (CCP) within a bi-level optimization framework. BCCP can reflect the risk of violating probabilistic constraint under uncertainty as well as balance the tradeoff between two-level decision makers in the WFE nexus system. Under trading scheme, multiple scenarios in association with different food demand, ecological-water requirement, and water availability are examined. Major findings are: (i) compared with that under non-trading, system benefits would increase [3.9, 20.4]% under trading scenarios, disclosing that water trading is an effective mechanism for the study basin; (ii) when food demand increases 10.5%, water allocated to ecological use would decrease [0.9, 2.7]% under all scenarios, revealing that agriculture can squeeze ecological water; (iii) both system benefit and water allocation would increase with p level, implying there is a tradeoff between system benefit and system-failure risk. These findings can gain insight into the interaction between two-level stakeholders and objectives as well as provide decision support for WFE nexus synergetic management.

Effluent trading planning and its application in water quality management: A factor-interaction perspective.

In this study, a Bayesian risk-induced interval stochastic modeling framework (BRISF) is proposed for planning effluent trading program among point and nonpoint sources as well as identifying interactions of important trading factors under system risk. BRISF incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian inference with random walk Metropolis algorithm (RWM), and constraint-violation risk-based two-stage stochastic programming (CRTSP) within a general framework. Bayesian inference is employed for uncertainty analysis of SWAT model parameters and uncertain prediction of nutrient loadings; this process provides the random inputs for optimization process. CRTSP is capable of dealing with multiple uncertainties in modeling effluent trading program as well as system risk of environmental allowance violation. BRISF is applied to a real case of Xiangxihe watershed in China for water quality management. Solutions for optimal trading scheme corresponding to different risk levels are generated. Thousands of scenarios are examined to analyze the individual and interactive effects of trading ratios and treatment rates on trading system. Comparison between cross-industry and intra-industry effluent trading scheme is also conducted. It is proved that cross-industry trading would bring about higher benefit with reduced pollution loading; cross-industry effluent trading scheme would be recommended to achieve optimal water quality management and system benefit.

Ultrasound-guided high-intensity focused ultrasound treatment for abdominal wall endometriosis: a retrospective study.

OBJECTIVE: To evaluate the safety and efficacy of ultrasound-guided high-intensity focused ultrasound (USgHIFU) for treating abdominal wall endometrioses (AWE). DESIGN: A retrospective study. SETTING: Department of Obstetrics and Gynaecology in China. POPULATION: Patients with abdominal wall endometriosis. METHODS: From August 2010 to April 2014, 32 patients with AWE were treated with USgHIFU in our hospital. USgHIFU treatment was performed with the Model JC-200 High Intensity Focused Ultrasound Tumor Therapeutic System. The symptom relief and the adverse effects were evaluated after USgHIFU ablation. MAIN OUTCOME MEASURES: USgHIFU as a new treatment option for patients with AWE. RESULTS: Contrast-enhanced ultrasound showed that all lesions were successfully ablated with USgHIFU. The follow-up results showed that the average volume of AWE lesions at 6 months after USgHIFU was significantly smaller than that before treatment (2.80 ± 0.12 versus 1.33 ± 0.31 cm3 ). The pain scores at 6 months after treatment were significantly lower than those before treatment (6.80 ± 2.64 versus 1.80 ± 0.3). The non-perfused volume (indicative of successful ablation) was measured in all patients immediately after treatment, ranging from 0.9 to 2.1 cm3 (median: 1.6 cm3 ), and the fractional ablation ranged from 87% to 100% (median: 94%). Local oedema was observed in these patients, lasting for 1-3 days only. No severe complications occurred during the follow-up period. CONCLUSIONS: Based on our study, USgHIFU ablation is a safe and effective method for treating AWE. TWEETABLE ABSTRACT: As a non-invasive treatment technique, HIFU could be used to treat abdominal wall endometriosis.

A comparison of the cost-utility of ultrasound-guided high-intensity focused ultrasound and hysterectomy for adenomyosis: a retrospective study.

OBJECTIVE: To evaluate cost-effectiveness of ultrasound-guided high-intensity focused ultrasound (USgHIFU) and open hysterectomy for adenomyosis. DESIGN: A retrospective analysis. SETTING: Gynaecological department in a single centre in China. POPULATION: Patients with symptomatic adenomyosis. MAIN OUTCOME MEASURES: Cost difference between patients with adenomyosis treated with USgHIFU and open hysterectomy. METHODS: Three hundred and sixty-eight patients with adenomyosis were retrospectively reviewed. Among them, 302 patients were treated with USgHIFU and 66 patients with open hysterectomy. All of them had 1-, 3-, 6- and 12-month follow ups. The patients' quality of life (QOL) was evaluated and the utility scores were obtained from a rating scale to conduct a cost-utility analysis (CUA). RESULTS: No significant differences were found at any follow-up time point in the QOL between the two groups (P > 0.05). After treatment, the QOL scores significantly increased in both groups (P < 0.05): the quality adjusted life year (QALY) for patients treated with USgHIFU was USUS$5256.48, whereas it was USUS$7510.03 for patients treated with open hysterectomy. Both incremental cost and sensitivity analysis showed that USgHIFU was less costly than open hysterectomy. CONCLUSIONS: The QOL of patients with adenomyosis can be significantly improved by either USgHIFU or open hysterectomy, but USgHIFU is less costly. TWEETABLE ABSTRACT: USgHIFU can safely be used to treat patients with adenomyosis and significantly improved the quality of life of patients after treatment. The cost of USgHIFU is less than that of surgical treatment.

Scenario analysis of carbon emissions' anti-driving effect on Qingdao's energy structure adjustment with an optimization model, Part II: Energy system planning and management.

In this study, an inexact multistage stochastic mixed-integer programming (IMSMP) method was developed for supporting regional-scale energy system planning (EPS) associated with multiple uncertainties presented as discrete intervals, probability distributions and their combinations. An IMSMP-based energy system planning (IMSMP-ESP) model was formulated for Qingdao to demonstrate its applicability. Solutions which can provide optimal patterns of energy resources generation, conversion, transmission, allocation and facility capacity expansion schemes have been obtained. The results can help local decision makers generate cost-effective energy system management schemes and gain a comprehensive tradeoff between economic objectives and environmental requirements. Moreover, taking the CO2 emissions scenarios mentioned in Part I into consideration, the anti-driving effect of carbon emissions on energy structure adjustment was studied based on the developed model and scenario analysis. Several suggestions can be concluded from the results: (a) to ensure the smooth realization of low-carbon and sustainable development, appropriate price control and fiscal subsidy on high-cost energy resources should be considered by the decision-makers; (b) compared with coal, natural gas utilization should be strongly encouraged in order to insure that Qingdao could reach the carbon discharges peak value in 2020; (c) to guarantee Qingdao's power supply security in the future, the construction of new power plants should be emphasised instead of enhancing the transmission capacity of grid infrastructure.

Andrographolide radiosensitizes human esophageal cancer cell line ECA109 to radiation in vitro.

To explore the radiosensitivity of andrographolide on esophageal cancer cell line ECA109. The inhibition effects of andrographolide were measured using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium (MTT) assay. Clonogenic survival assay was used to evaluate the effects of andrographolide on the radiosensitivity of esophageal cancer cells. Immunofluorescence was employed to examine Bax expression. The changes in cell cycle distribution and apoptosis were assayed using flow cytometry. The expression of NF-κb/Cleaved-Caspase3/Bax/Bcl-2 was measured using Western blot analysis. DNA damage was detected via γ-H2AX foci counting. With a clear dose and time effects, andrographolide was found to inhibit the proliferation of esophageal cell line ECA109. The results of the clonogenic survival assay show that andrographolide could markedly enhance radiosensitivity (P < 0.05) with a sensitizing enhancement ratio of 1.28. Andrographolide caused a dose-dependent increase in Cleaved-Caspase3/Bax protein expression and a decrease in Bcl-2/NF-κb expression. Apoptosis in andrographolide-treated ECA-109 increased significantly compared with the apoptosis in the simple drug and radiation combined with drug groups (P < 0.001; P < 0.05). Moreover, compared with the independent radiation group, the andrographolide combined with radiation group increased the number of DNA double chain breaks. Andrographolide can increase the radiosensitivity of esophageal cell line ECA109. This result may be associated with the decrease in the NF-κb level and the induced apoptosis of esophageal cancer cells.

A copula-based chance-constrained waste management planning method: An application to the city of Regina, Saskatchewan, Canada.

UNLABELLED: This study proposes a copula-based chance-constrained waste management planning (CCWMP) method. The method can effectively reflect the interactions between random parameters of the waste management planning systems, and thus can help analyze the influences of their interactions on the entire systems. In particular, a joint distribution function is established using preestimated marginal distributions of random variables and an optimal copula selected from widely used Gaussian, Student's t, Clayton, Frank, Gumbel, and Ali-Mikhail-Haq copulas. Then a set of joint probabilistic constraints in the chance-constrained programming problems is converted into individual probabilistic constraints using the joint distribution function. Further, this method is applied to residential solid waste management in the city of Regina in Canada for demonstrating its applicability. Nine scenarios based on different joint and marginal probability levels are considered within a multiperiod and multizone context to effectively reflect dynamic, uncertain, and interactive characteristics of the solid waste management systems in the city. The results provide many decision alternatives under these scenarios, including cost-effective and environmentally friendly decision schemes. Moreover, the results indicate that even though the effect of the joint probability levels on the system costs is more significant than that of the marginal probability levels, the effect of marginal probability levels is notable, and there exists a trade-off between the total system cost and the constraint-violation risk. Therefore, the results obtained from the present study would be useful to support the city's long-term solid waste management planning and formulate local policies and regulation concerning the city's waste generation and management. IMPLICATIONS: The CCWMP method not only can solve chance-constrained problems with unknown probability distributions of random variables in the right-hand sides of constraints, but also can effectively reflect the interactions between the random parameters and thus help analyze the influences of their interactions on the entire systems. The results obtained through applying this method to the city of Regina in Canada can provide many decision alternatives under different joint probability levels and marginal probability levels, and would be useful to support the city's long-term solid waste management planning.

A fractional-factorial probabilistic-possibilistic optimization framework for planning water resources management systems with multi-level parametric interactions.

In this study, a multi-level factorial-vertex fuzzy-stochastic programming (MFFP) approach is developed for optimization of water resources systems under probabilistic and possibilistic uncertainties. MFFP is capable of tackling fuzzy parameters at various combinations of α-cut levels, reflecting distinct attitudes of decision makers towards fuzzy parameters in the fuzzy discretization process based on the α-cut concept. The potential interactions among fuzzy parameters can be explored through a multi-level factorial analysis. A water resources management problem with fuzzy and random features is used to demonstrate the applicability of the proposed methodology. The results indicate that useful solutions can be obtained for the optimal allocation of water resources under fuzziness and randomness. They can help decision makers to identify desired water allocation schemes with maximized total net benefits. A variety of decision alternatives can also be generated under different scenarios of water management policies. The findings from the factorial experiment reveal the interactions among design factors (fuzzy parameters) and their curvature effects on the total net benefit, which are helpful in uncovering the valuable information hidden beneath the parameter interactions affecting system performance. A comparison between MFFP and the vertex method is also conducted to demonstrate the merits of the proposed methodology.

An integrated simulation and optimization approach for managing human health risks of atmospheric pollutants by coal-fired power plants.

UNLABELLED: This research developed a simulation-aided nonlinear programming model (SNPM). This model incorporated the consideration of pollutant dispersion modeling, and the management of coal blending and the related human health risks within a general modeling framework In SNPM, the simulation effort (i.e., California puff [CALPUFF]) was used to forecast the fate of air pollutants for quantifying the health risk under various conditions, while the optimization studies were to identify the optimal coal blending strategies from a number of alternatives. To solve the model, a surrogate-based indirect search approach was proposed, where the support vector regression (SVR) was used to create a set of easy-to-use and rapid-response surrogates for identifying the function relationships between coal-blending operating conditions and health risks. Through replacing the CALPUFF and the corresponding hazard quotient equation with the surrogates, the computation efficiency could be improved. The developed SNPM was applied to minimize the human health risk associated with air pollutants discharged from Gaojing and Shijingshan power plants in the west of Beijing. Solution results indicated that it could be used for reducing the health risk of the public in the vicinity of the two power plants, identifying desired coal blending strategies for decision makers, and considering a proper balance between coal purchase cost and human health risk. IMPLICATIONS: A simulation-aided nonlinear programming model (SNPM) is developed. It integrates the advantages of CALPUFF and nonlinear programming model. To solve the model, a surrogate-based indirect search approach based on the combination of support vector regression and genetic algorithm is proposed. SNPM is applied to reduce the health risk caused by air pollutants discharged from Gaojing and Shijingshan power plants in the west of Beijing. Solution results indicate that it is useful for generating coal blending schemes, reducing the health risk of the public, reflecting the trade-offbetween coal purchase cost and health risk.

A factorial-analysis-based Bayesian neural network method for quantifying China's CO2 emissions under dual-carbon target.

Energy-structure transformation and CO2-emission reduction are becoming particularly urgent for China and many other countries. Development of effective methods that are capable of quantifying and predicting CO2 emissions to achieve carbon neutrality is desired. This study advances a factorial-analysis-based Bayesian neural network (abbreviated as FABNN) method to reflect the complex relationship between inputs and outputs as well as reveal the individual and interactive effects of multiple factors affecting CO2 emissions. FABNN is then applied to analyzing CO2 emissions of China (abbreviated as CEC), where multiple factors involve in energy (e.g., the consumption of natural gas, CONG), economic (e.g., Gross domestic product, GDP) and social (e.g., the rate of urbanization, ROU) aspects are investigated and 512 scenarios are designed to achieve the national dual carbon targets (i.e., carbon peak before 2030 and carbon neutrality by 2060). Comparing to the conventional machine learning methods, FABNN performs better in calibration and validation results, indicating that FABNN is suitable for CEC simulation and prediction. Results disclose that the top three factors affecting CEC under the dual­carbon target are GDP, CONG, and ROU; energy, economic and social contributions are 43.5 %, 34.6 % and 21.9 %, respectively. CEC reaches its carbon peak during 2027-2032 and achieve carbon neutrality during 2053-2057 under all scenarios. Under the optimal scenario (S195), the CO2-emission reduction potential is about 772.2 million tonnes and the consumptions of coal, petroleum and natural gas can be respectively reduced by 3.1 %, 9.9 % and 23.0 % compared to the worst scenario (S466). The results can provide solid support for national energy-structure transformation and CO2-emission reduction to achieve carbon-peak and carbon-neutrality targets.

[Analysis on the use of HIV post-exposure prophylaxis and related factors in men who have sex with men in Qingdao].

Objective: To understand the use of post-exposure prophylaxis (PEP) and analyze related factors among men who have sex with men (MSM) in Qingdao, and provide a reference for the AIDS prevention and control in this population. Methods: A cross-sectional survey conducted from April 2022 to February 2023. Relying on MSM social groups in Qingdao, a snowball sampling method was applied to recruit research subjects who met the inclusion criteria of age ≥18 years old, having had homosexual anal or oral sex in the past six months, and HIV-negative or infection status unknown. The sample size was estimated at 566. Data on demographic characteristics, sexual behavior characteristics, PEP use, and others of the research subjects was collected through on-site questionnaires. The logistic regression model was used to analyze the factors associated with using PEP. Results: A total of 811 participants were recruited, mainly aged 25-34 (53.6%, 435/811), unmarried (74.7%, 606/811), with an average monthly income of ≥5 000 yuan (52.2%, 423/811), and having lived in Qingdao for ≥10 years (75.6%, 613/811). The proportion of those who knew the HIV status of their sexual partners in the last six months was 67.1% (544/811), and those with HIV-positive partners were 3.6% (29/811). In the last six months, the proportion of participants who had group sex (86.4%, 701/811), unprotected anal sex (98.2%, 796/811), and use of club drugs (80.3%, 651/811) was high. Moreover, 28.4% (230/811) had used PEP. The multivariate logistic regression analysis showed that the factors related to the use of PEP included divorced or widowed (aOR=5.46,95%CI:1.96-15.17), average monthly income ≥5 000 yuan (aOR=2.04,95%CI:1.44-2.89), same-sex sexual orientation (aOR=0.40,95%CI:0.22-0.71), having HIV-positive sexual partners in the last six months (aOR=2.54,95%CI:1.13-5.71) and having been tested for HIV ≥3 times in the last six months (aOR=1.46,95%CI:1.04-2.06). Conclusions: The prevalence of risk behaviors among MSM in Qingdao was high, and the use of PEP was low. In the future, it is essential to increase HIV/AIDS prevention education among MSM, promote MSM to know the HIV status of their sexual partners, and reduce the prevalence of risk behaviors among this population. Additionally, explore medical insurance reimbursement plans for PEP to reduce utilization costs and promote the use of PEP by MSM after HIV exposure occurs as soon as possible.

A coupled factorial-analysis-based interval programming approach and its application to air quality management.

UNLABELLED: In this study, a coupled factorial-analysis-based interval programming (CFA-IP) approach is developed through incorporating factorial analysis within an interval-parameter linear programming framework. CFA-IP can tackle uncertainties presented as intervals that exist in the objective function and the left- and right-hand sides of constraints, as well as robustly reflect interval information in the solutions for the objective-function value and decision variables. Moreover CFA-IP has the advantage of investigating the potential interactions among input parameters and their influences on lower- and upper-bound solutions, which is meaningful for supporting an in-depth analysis of uncertainty. A regional air quality management problem is studied to demonstrate applicability of the proposed CFA-IP approach. The results indicate that useful solutions have been generated for planning the air quality management practices. They can help decision makers identify desired pollution mitigation strategies with minimized total cost and maximized environmental efficiency, as well as screen out dominant parameters and explore the valuable information that may be veiled beneath their interrelationships. IMPLICATIONS: The CFA-IP approach can not only tackle uncertainties presented as intervals that exist in the objective function and the left- and right-hand sides of constraints, but also investigate their interactive effects on model outputs, which is meaningful for supporting an in-depth analysis of uncertainty. Thus CFA-IP would be applicable to air quality management problems under uncertainty. The results obtained from CFA-IP can help decision makers identify desired pollution mitigation strategies, as well as investigate the potential interactions among factors and analyze their consequent effects on modeling results.

A two-stage mixed-integer fuzzy programming with interval-valued membership functions approach for flood-diversion planning.

Flood disasters have been extremely severe in recent decades, and they account for about one third of all natural catastrophes throughout the world. In this study, a two-stage mixed-integer fuzzy programming with interval-valued membership functions (TMFP-IMF) approach is developed for flood-diversion planning under uncertainty. TMFP-IMF integrates the fuzzy flexible programming, two-stage stochastic programming, and integer programming within a general framework. A concept of interval-valued fuzzy membership function is introduced to address complexities of system uncertainties. TMFP-IMF can not only deal with uncertainties expressed as fuzzy sets and probability distributions, but also incorporate pre-regulated water-diversion policies directly into its optimization process. TMFP-IMF is applied to a hypothetical case study of flood-diversion planning for demonstrating its applicability. Results indicate that reasonable solutions can be generated for binary and continuous variables. A variety of flood-diversion and capacity-expansion schemes can be obtained under four scenarios, which enable decision makers (DMs) to identify the most desired one based on their perceptions and attitudes towards the objective-function value and constraints.