•A parsimonious approach was proposed for studying flood risks under climate change.•The method integrates ASD-KNN, CDEN, BNN, and KNN techniques.•Flood frequencies for a typical watershed in ...southeast China were investigated.
An integrated statistical and data-driven (ISD) framework was proposed for analyzing river flows and flood frequencies in the Duhe River Basin, China, under climate change. The proposed framework involved four major components: (i) a hybrid model based on ASD (Automated regression-based Statistical Downscaling tool) and KNN (K-nearest neighbor) was used for downscaling rainfall and CDEN (Conditional Density Estimate Network) was applied for downscaling minimum temperature and relative humidity from global circulation models (GCMs) to local weather stations; (ii) Bayesian neural network (BNN) was used for simulating monthly river flows based on projected weather information; (iii) KNN was applied for converting monthly flow to daily time series; (iv) Generalized Extreme Value (GEV) distribution was adopted for flood frequency analysis. In this study, the variables from CGCM3 A2 and HadCM3 A2 scenarios were employed as the large-scale predictors. The results indicated that the maximum monthly and annual runoffs would both increase under CGCM3 and HadCM3 A2 emission scenarios at the middle and end of this century. The flood risk in the study area would generally increase with a widening uncertainty range. Compared with traditional approaches, the proposed framework takes the full advantages of a series of statistical and data-driven methods and offers a parsimonious way of projecting flood risks under climatic change conditions.
Drought has become one of the most serious meteorological disasters for agricultural production in many areas around the world, and the situation could be worse under the impact of climate change. To ...facilitate better adaptation planning, this study proposed a drought assessment framework integrating downscaling method, drought index, copula technique, and bivariate frequency analysis, and applied it to investigate the change of the drought characteristics and drought risks from the past to the future in Huang-Huai-Hai River basin (HRB), North China. Drought was firstly defined by standardized precipitation evapotranspiration index (SPEI) based on 1497 observed grid data from 1979 to 2004. Then, we constructed the joint distribution of drought duration and severity based on copulas to detect and quantify the drought risks. To address the effect of climate change, similar calculation process was applied to the future climate data, which was downscaled using delta change method from representative concentration pathway (RCP 8.5) of 12 general circulation models (GCMs). The study results suggested that, under climate change condition, most irrigation districts over HRB would generally experience lower frequency of drought events but with extended duration; some districts would have more serious drought, but majority would experience similar or even lower level of severity. In light of the mean joint occurrence probability, the irrigation district at the south part of Huai River basin would likely experience the highest increase of drought risks in near future (by 0.86%) and distant future (by 0.76%), while most of other districts over HRB would face low risk of serious drought risks. The obtained results offer useful information to agricultural managers or water resources authorities who are interested in the development of effective long-term adaptation strategies for drought management.
An inexact double-sided fuzzy chance-constrained programming (IDFCCP) method was developed in this study and applied to an agricultural effluent control management problem. IDFCCP was formulated ...through incorporating interval linear programming (ILP) into a double-sided fuzzy chance-constrained programming (DFCCP) framework, and could be used to deal with uncertainties expressed as not only possibility distributions associated with both left- and right-hand-side components of constraints but also discrete intervals in the objective function. The study results indicated that IDFCCP allowed violation of system constraints at specified confidence levels, where each confidence level consisted of two reliability scenarios. This could lead to model solutions with high system benefits under acceptable risk magnitudes. Furthermore, the introduction of ILP allowed uncertain information presented as discrete intervals to be communicated into the optimization process, such that a variety of decision alternatives can be generated by adjusting the decision-variable values within their intervals. The proposed model could help decision makers establish various production patterns with cost-effective water quality management schemes under complex uncertainties, and gain in-depth insights into the trade-offs between system economy and reliability.
A fuzzy parameterized probabilistic analysis (FPPA) method was developed in this study to assess risks associated with environmental pollution-control problems. FPPA integrated environmental ...transport modeling, fuzzy transformation, probabilistic risk assessment, fuzzy risk quantification into a general risk assessment framework, and was capable of handling uncertainties expressed as fuzzy-parameterized stochastic distributions. The proposed method was applied to two environmental pollution problems, with one being about the point-source pollution in a river system with uncertain water quality parameters and the other being concerned with groundwater contaminant plume from waste landfill site with poorly known contaminant physical properties. The study results indicated that the complex uncertain features had significant impacts on modeling and risk-assessment outputs; the degree of impacts of modeling parameters were highly dependent on the level of imprecision of these parameters. The results also implied that FPPA was capable of addressing vagueness or imprecision associated with probabilistic risk evaluation, and help generate risk outputs that could be elucidated under different possibilistic levels. The proposed method could be used by environmental managers to evaluate trade-offs involving risks and costs, as well as identify management solutions that sufficiently hedge against dual uncertainties.
A new spin-dependent deflection mechanism is revealed by considering the spin-correlated radiation-reaction force during laser-electron collision. We found that such deflection originates from the ...non-zero work done by the radiation-reaction force along the laser polarization direction in each half-period, which is larger/smaller for spin-anti-paralleled/spin-paralleled electrons. The resulted anti-symmetric deflection is further accumulated when the spin-projection onto the laser magnetic field is reversed in adjacent half-periods. The discovered mechanism dominates over the Stern-Gerlach deflection for electrons of several hundreds of MeV and 10 PW-level laser peak power. The results provide a new perspective to study the strong-field QED physics in quantum radiation-reaction regime and an approach to leverage the study of radiation-dominated and strong-field QED physics via particle spins.
Using a total of 11.0 fb^{-1} of e^{+}e^{-} collision data with center-of-mass energies between 4.009 and 4.6 GeV and collected with the BESIII detector at BEPCII, we measure fifteen exclusive cross ...sections and effective form factors for the process e^{+}e^{-}→Ξ^{-}Ξover ¯^{+} by means of a single baryon-tag method. After performing a fit to the dressed cross section of e^{+}e^{-}→Ξ^{-}Ξover ¯^{+}, no significant ψ(4230) or ψ(4260) resonance is observed in the Ξ^{-}Ξover ¯^{+} final states, and upper limits at the 90% confidence level on Γ_{ee}B for the processes ψ(4230)/ψ(4260)→Ξ^{-}Ξover ¯^{+} are determined. In addition, an excited Ξ baryon at 1820 MeV/c^{2} is observed with a statistical significance of 6.2-6.5σ by including the systematic uncertainty, and the mass and width are measured to be M=(1825.5±4.7±4.7) MeV/c^{2} and Γ=(17.0±15.0±7.9) MeV, which confirms the existence of the J^{P}=3/2^{-} state Ξ(1820).
This meta-analysis aims to access the efficacy of nasal saline irrigation in the treatment of allergic rhinitis (AR) in adults and children.
Two authors independently searched databases up to ...December 2018. Differences in efficacy between saline irrigation and other treatments were compared. Subgroup analyses of discrepancy in effects between children and adults were performed.
(1) Saline irrigation vs. no irrigation, in both children and adults groups, saline irrigation showed significant efficacy. (2) Saline+medication vs. medication, in children group, there was no statistical difference of efficacy between saline+medication and medication; in adults group, efficacy of saline+medicine was superior to that of medication. (3) Saline irrigation vs. medication, in children group, there was no statistical difference between efficacy of saline irrigation and medication; in adults group, efficacy of medication was superior to that of saline irrigation. (4) Hypertonic saline vs. isotonic saline, for children, efficacy of hypertonic saline was superior to that of isotonic saline. Additionally, no adults reported adverse events in all trials. Adverse effects were reported during the first nasal irrigation in 20 children, and one child withdrew due to adverse reactions.
Saline irrigation can significantly improve symptoms of AR in children and adults. Saline irrigation can serve as a safe adjunctive treatment to medication of AR in adults. Saline irrigation can be an alternative therapy for children and pregnant women with AR. Efficacy of hypertonic saline may be better than that of isotonic saline in treating AR of children.
ABSTRACT
A coupled K‐nearest neighbour (KNN) and Bayesian neural network (BNN) model was developed for downscaling daily rainfall at a single site. The KNN was used for classification of dry/wet day ...and rainfall typing based on rainfall magnitude. The BNN was applied for prediction of rainfall amount. The proposed method was applied to rainfall downscaling at Singapore Island. The Climate Forecast System Reanalysis (CFSR) data were used for providing large‐scale predictors at a high spatial resolution; 31‐years daily rainfall record at two typical weather stations on the island was used as predictand. The performance of KNN–BNN was compared with two classical downscaling tools including automated statistical downscaling tool (ASD) and generalized linear model (GLM). The study results indicated that, the proposed model performed equally good or better than both ASD and GLM, in terms of prediction of basic statistical indicators (i.e. mean, SD, probability of wet days, 90th percentile rainfall amount, and maximum rainfall); it notably outperformed others in generating narrower uncertainty intervals for all indicators, especially for monthly mean and maximum rainfall. It was also demonstrated that separation of yearly data into monthly or seasonal could considerably enhance the performance of KNN–BNN.
ABSTRACT
GW190814 was reported during LIGO’s and Virgo’s third observing run with the most asymmetric component masses (an ∼23 M⊙ black hole and an ∼2.6 M⊙ compact object). Under the assumption that ...this event is a binary black hole (BBH) merger formed through the isolated binary evolution channel, we reanalyse the publicly released data of GW190814 with the modified astrophysical priors on the effective spin χeff, and further explore its formation history using detailed binary modelling. We show that GW190814 is likely to have been formed through the classical common envelope channel. Our findings show that the properties inferred using the modified astrophysical priors are consistent with those inferred by the uniform priors. With the newly inferred properties of GW190814, we perform detailed binary evolution of the immediate progenitor of the BBH (namely a close binary system composed of a BH and a helium star) in a large parameter space, taking into account mass-loss, internal differential rotation, supernova kicks, and tidal interactions between the helium star and the BH companion. Our findings show that GW190814-like events could be formed in limited initial conditions just after the common envelope phase: an ∼23 M⊙ BH and a helium star of MZamsHe ∼ 8.5 M⊙ at solar metallicity (∼ 7.5 M⊙ at 10 per cent solar metallicity) with an initial orbital period at around 1.0 d. Additionally, the inferred low spin of the secondary indicates that the required metallicity for reproducing GW190814-like events should not be too low (e.g. Z ≳ 0.1 Z⊙).
Planning for water quality management systems is complicated by a variety of uncertainties and nonlinearities, where difficulties in formulating and solving the resulting inexact nonlinear ...optimization problems exist. With the purpose of tackling such difficulties, this paper presents the development of an interval-fuzzy nonlinear programming (IFNP) model for water quality management under uncertainty. Methods of interval and fuzzy programming were integrated within a general framework to address uncertainties in the left- and right-hand sides of the nonlinear constraints. Uncertainties in water quality, pollutant loading, and the system objective were reflected through the developed IFNP model. The method of piecewise linearization was developed for dealing with the nonlinearity of the objective function. A case study for water quality management planning in the Changsha section of the Xiangjiang River was then conducted for demonstrating applicability of the developed IFNP model. The results demonstrated that the accuracy of solutions through linearized method normally rises positively with the increase of linearization levels. It was also indicated that the proposed linearization method was effective in dealing with IFNP problems; uncertainties can be communicated into optimization process and generate reliable solutions for decision variables and objectives; the decision alternatives can be obtained by adjusting different combinations of the decision variables within their solution intervals. It also suggested that the linearized method should be used under detailed error analysis in tackling IFNP problems.
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