Closed-loop supply chain network equilibrium strategy model with environmental protection objectives

With the increasing popularity of ecological civilization and sustainable development,enterprises should consider environmental protection measures in their operations in addition to pursue their economic interests.This paper establsihes a closed-loop supply chain network model composed of multiple suppliers,manufacturers,retailers,recyclers,and demand markets—regarding their dual goals of the profit maximization and the minimization of carbon emissions.The conditions necessary for establishing overall equilibrium and an equilibrium model of the entire closed-loop supply chain network are determined by applying variational inequality and dual theory.A modified projection contraction algorithm is used to design a model-solving program.Finally,using numerical examples,the paper conducts a comparative static analysis on important parameters such as the weight coefficients of environmental protection objectives and consumers'awareness of low-carbon environmental protection and attains some beneficial enlightenment on management.The results indicate that when the environmental protection objectives of a certain type of enterprise increases,both the economic benefits and environmental protection performance will improve;when the environmental protection objectives of all enterprises increases simultaneously,environmental protection performance improves significantly,but the changes in economic benefits of different enterprises are inconsistent and profit coordination is more complex.Although consumers’awareness of low-carbon preference could improve environmental performance,it reduces the overall profits of network members and the entire closed-loop supply chain network as a whole.The above conclusions can be used as a reference for the government in designing low-carbon environmental protection policy and in closed-loop supply chain research.

Chinese Stroke Association guidelines for clinical management of ischaemic cerebrovascular diseases:executive summary and 2023 update

Background China is one of the countries with the highest burden of stroke.Implementing multidimensional management guidelines will help clinicians practise evidence-based care,improve patient outcomes and alleviate societal burdens.This update of the 2019 edition will provide the latest comprehensive recommendations for the diagnosis and treatment of ischaemic cerebrovascular diseases.Methods We conducted a comprehensive search on MEDLINE(via PubMed)up to 31 August 2023.The writing team established the recommendations through multiple rounds of online and offline discussions.Each recommendation was graded using the evidence grading algorithm developed by the Chinese Stroke Association(CSA).The draft was reviewed and finalised by the CSA Stroke Guidelines Writing Committee.Results This update included revisions of 15 existing recommendations and 136 new recommendations in the following areas of stroke care:emergency assessment and diagnosis of ischaemic cerebrovascular disease,acute-phase reperfusion therapy,evaluation of underlying mechanisms,antithrombotic therapy,prevention and treatment of complications,and risk factor management.Conclusions This guideline updated the recommendations for the clinical management of ischaemic cerebrovascular disease from 2019.

Childhood strokes in China describing clinical characteristics, risk factors and performance indicators: a case-series study

Aim To investigate clinical characteristics,risk factors(RFs),neurologic deficits and medical care provided in children who had a stroke in China.Methods We conducted a retrospective case-series study using the medical records of children aged 1 month to 18 years with arterial ischaemic stroke(AIS)or haemorrhagic stroke(HS)(with the entry codes I60,I61,I62,I63(ICD-10)),who were admitted to different hospitals in Beijing,between January 2018 and December 2018.We obtained the following information from the charts:demographic characteristics,clinical presentations,RFs for paediatric stroke,laboratory examination,neuroimaging records and neurologic sequelae.Results We identified 312 first admissions for stroke(172 AIS and 140 HS).The mean age at onset was 8.6±3.9 years for patients who had an AIS and 8(5–13)years for patients who had an HS.There were more males than females in both groups(AIS:59.88%vs 40.12%;HS:52.14%vs 47.86%).A known aetiology was identified in 92.44%and 86.43%of patients who had an AIS and HS,respectively.The leading cause of AIS was cerebrovascular diseases including moyamoya(68.6%),while that for HS was arteriovenous malformation(51.43%).The most common initial clinical presentation was hemiplegia(86.05%)in patients who had an AIS and headache(67.86%)in patients who had an HS.The use of healthcare,including acute treatment(antithrombotic in 17.44%,anticoagulant in 5.23%)and secondary prevention(antithrombotic in 6.39%,anticoagulant in 1.16%),varied and was significantly lower among patients who had an AIS.The most common complications were epilepsy(22.09%)and pneumonia(4.65%)in patients who had an AIS and epilepsy(17.14%)and hydrocephalus(12.14%)in patients who had an HS.Neurological deficits occurred in 62.8%of patients who had an AIS and 72.86%of patients who had an HS.Conclusion Cerebral arteriopathy was a major RF for both AIS and HS in children living in China.Large epidemiological studies are required to identify RFs to prevent stroke as well as appropriate interventions.

Determination of Elastoplastic Properties of 2024 Aluminum Alloy Using Deep Learning and Instrumented Nanoindentation Experiment

The instrumented nanoindentation technique has been widely used to measure the tensile properties of various materials,for its simple specimen preparation and nearly nondestructive testing processes.In this paper,a novel inverse method is established for measuring the elastoplastic properties of Al 2024 alloy.The grid indentation experiments are performed on Al 2024 material.The obtained experimental load–displacement(P–h)data exhibit obvious scatter characteristics.The artificial neural network(ANN)model with tunable hyper-parameters is adopted to establish the forward relationship between elastoplastic parameters and indentation load–displacement snapshot.An objective function for quantifying the error norm between predicted and experimental P–h snapshots is established.The parameter identification problem is solved using the“interior-point”constraint optimization algorithm..The identified material properties show good agreement with the tensile data,and the error values are−8.66%for elastic modulus,1.08%for yield stress,and 6.90%for hardening exponent.The sensitivity of numerical results to experimental uncertainty is analyzed,and the error bound of experimental data is determined.The results of sensitivity analysis indicate that the proposed inverse method in the work is very effective and reliable.