Reevaluating health metrics:Unraveling the limitations of disabilityadjusted life years as an indicator in disease burden assessment

In 1993,the World Bank released a global report on the efficacy of health promotion,introducing the disability-adjusted life years(DALY)as a novel indicator.The DALY,a composite metric incorporating temporal and qualitative data,is grounded in preferences regarding disability status.This review delineates the algorithm used to calculate the value of the proposed DALY synthetic indicator and elucidates key methodological challenges associated with its application.In contrast to the quality-adjusted life years approach,derived from multi-attribute utility theory,the DALY stands as an independent synthetic indicator that adopts the assumptions of the Time Trade Off utility technique to define Disability Weights.Claiming to rely on no mathematical or economic theory,DALY users appear to have exempted themselves from verifying whether this indicator meets the classical properties required of all indicators,notably content validity,reliability,specificity,and sensitivity.The DALY concept emerged primarily to facilitate comparisons of the health impacts of various diseases globally within the framework of the Global Burden of Disease initiative,leading to numerous publications in international literature.Despite widespread adoption,the DALY synthetic indicator has prompted significant methodological concerns since its inception,manifesting in inconsistent and non-reproducible results.Given the substantial diffusion of the DALY indicator and its critical role in health impact assessments,a reassessment is warranted.This reconsideration is imperative for enhancing the robustness and reliability of public health decisionmaking processes.

Accelerating Oxygen Electrocatalysis Kinetics on Metal-Organic Frameworks via Bond Length Optimization

Metal-organic frameworks(MOFs)have been developed as an ideal platform for exploration of the relationship between intrinsic structure and catalytic activity,but the limited catalytic activity and stability has hampered their practical use in water splitting.Herein,we develop a bond length adjustment strategy for optimizing naphthalene-based MOFs that synthesized by acid etching Co-naphthalenedicarboxylic acid-based MOFs(donated as AE-CoNDA)to serve as efficient catalyst for water splitting.AE-CoNDA exhibits a low overpotential of 260 mV to reach 10 mA cm^(−2)and a small Tafel slope of 62 mV dec^(−1)with excellent stability over 100 h.After integrated AE-CoNDA onto BiVO_(4),photocurrent density of 4.3 mA cm^(−2)is achieved at 1.23 V.Experimental investigations demonstrate that the stretched Co-O bond length was found to optimize the orbitals hybridization of Co 3d and O 2p,which accounts for the fast kinetics and high activity.Theoretical calculations reveal that the stretched Co-O bond length strengthens the adsorption of oxygen-contained intermediates at the Co active sites for highly efficient water splitting.

一种基于CatBoost优化的光伏阵列故障诊断模型

大部分光伏电站地处偏僻、地形复杂的区域,受到外界环境的影响,易发生各种故障.而传统的光伏阵列故障诊断方法存在精度不高以及光伏数据利用率低等问题.针对以上问题,本文先是通过引入Levy飞行策略和步长因子动态调整策略改进麻雀搜索算法(Sparrow Search Algorithm,SSA),降低SSA算法陷入局部最优的风险,提升SSA算法的寻优能力.然后采用改进的Levy步长调整麻雀搜索算法(Levy Adjustment Sparrow Search Algorithm,LASSA)对CatBoost模型关键超参数进行寻优,提出了一种基于CatBoost并以LASSA为优化策略的光伏阵列故障诊断模型LASSA-CatBoost,以实现光伏阵列的短路、开路、老化和阴影遮挡故障的精确诊断.实验结果表明,LASSA-CatBoost模型的故障诊断准确率为99.7%,相较于优化前的CatBoost模型,准确率提高了3.6%.与现有的光伏阵列故障诊断模型相比,LASSA-CatBoost模型的准确性和稳定性更高.

Research on Biometric Identification Method of Nuclear Cold Source Disaster Based on Deep Learning

In this paper, an improved Fast-R-CNN nuclear power cold source disaster biological image recognition algorithm is proposed to improve the safety operation of nuclear power plants. Firstly, the image data sets of the disaster-causing creatures hairy shrimp and jellyfish were established. Then, in order to solve the problems of low recognition accuracy and unrecognizable small entities in disaster biometrics, Gamma correction algorithm was used to optimize the image of the data set, improve the image quality and reduce the noise interference. Transposed convolution is introduced into the convolution layer to increase the recognition accuracy of small targets. The experimental results show that the recognition rate of this algorithm is 6.75%, 7.5%, 9.8% and 9.03% higher than that of ResNet-50, MobileNetv1, GoogleNet and VGG16, respectively. The actual test results show that the accuracy of this algorithm is obviously better than other algorithms, and the recognition efficiency is higher, which basically meets the preset requirements of this paper.

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

Ultrafast Response and Threshold Adjustable Intelligent Thermoelectric Systems for Next‑Generation Self‑Powered Remote IoT Fire Warning

Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

On calculating glacial isostatic adjustment

Modeling the earth's fluid and elastic response to the melting of the glaciers of the last ice age is the most direct way to infer the earth's radial viscosity profile.Here,we compare two methods for calculating the viscoelastic response to surface loading.In one,the elastic equation of motion is converted to a viscoelastic equation using the Correspondence Principle.In the other,elastic deformation is added to the viscous flow as isostatic adjustment proceeds.The two modeling methods predict adjustment histories that are different enough to potentially impact the interpretation of the observed glacial isostatic adjustment(GIA).The differences arise from buoyancy and whether fluid displacements are subjected to hydrostatic pre-stress.The methods agree if they use the same equations and boundary conditions.The origin of the differences is determined by varying the boundary conditions and pre-stress application.

The effect of the carbon components on the performance of carbonbased transition metal electrocatalysts for the hydrogen evolution reaction

The hydrogen evolution reaction(HER)is a promising way to produce hydrogen,and the use of non-precious metals with an excellent electrochemical performance is vital for this.Carbon-based transition metal catalysts have high activity and stability,which are important in reducing the cost of hydrogen production and promoting the development of the hydrogen production industry.However,there is a lack of discussion regarding the effect of carbon components on the performance of these electrocatalysts.This review of the literature discusses the choice of the carbon components in these catalysts and their impact on catalytic performance,including electronic structure control by heteroatom doping,morphology adjustment,and the influence of self-supporting materials.It not only analyzes the progress in HER,but also provides guidance for synthesizing high-performance carbon-based transition metal catalysts.

Adjustment mechanism of blasting dynamic-static action in the water decoupling charge

Water decoupling charge blasting excels in rock breaking,relying on its uniform pressure transmission and low energy dissipation.The water decoupling coefficients can adjust the contributions of the stress wave and quasi-static pressure.However,the quantitative relationship between the two contributions is unclear,and it is difficult to provide reasonable theoretical support for the design of water decoupling blasting.In this study,a theoretical model of blasting fracturing partitioning is established.The mechanical mechanism and determination method of the optimal decoupling coefficient are obtained.The reliability is verified through model experiments and a field test.The results show that with the increasing of decoupling coefficient,the rock breaking ability of blasting dynamic action decreases,while quasi-static action increases and then decreases.The ability of quasi-static action to wedge into cracks changes due to the spatial adjustment of the blast hole and crushed zone.The quasi-static action plays a leading role in the fracturing range,determining an optimal decoupling coefficient.The optimal water decoupling coefficient is not a fixed value,which can be obtained by the proposed theoretical model.Compared with the theoretical results,the maximum error in the model experiment results is 8.03%,and the error in the field test result is 3.04%.

Early clinical outcome with lens position adjustment following implantable collamer lens surgery

AIM:To observe early clinical outcome with lens position adjustment following the implantable collamer lens(ICL)surgery.METHODS:Sixty patients were selected for this retrospective study.One eye from each patient received Toric ICL for astigmatism correction,and the other received non-astigmatic ICL surgery using horizontal position.Patients with higher postoperative arch height were selected,and their non-astigmatic eye clinical outcome were observed after ICL surgery at 1wk,1,and 3mo.The clinical measurements included uncorrected visual acuity(UCVA),intraocular pressure(IOP),refractive state,corneal endothelium cell count,and arch height.Three months later,the ICL in each patient’s non-astigmatic eye was adjusted to the vertical from the horizontal position.The results were compared before and 1wk,1,and 3mo after adjustment.RESULTS:UCVA and IOP were significantly reduced 1wk after position adjustment compared to 1wk after ICL implantation(P<0.05).The patients demonstrated significantly reduced arch height and corneal endothelium cell count 1wk,1,and 3mo after adjusting position compared to 1wk,1,and 3mo after ICL implantation(P<0.05).However,there was no significant difference in refraction between 1wk,1,and 3mo after ICL implantation and position adjustment(P>0.05).CONCLUSION:Early positioning adjustment postphakic ICL implantation can benefit patients with adjusted arch height or higher IOP.Despite the good clinical effects,the doctors should pay attention to the potential for adverse effects on UCVA and corneal endothelium cells following early position adjustment after posterior chamber phakic ICL implantation.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

Adaptive linear active disturbance-rejection control strategy reduces the impulse current of compressed air energy storage connected to the grid

The merits of compressed air energy storage(CAES)include large power generation capacity,long service life,and environmental safety.When a CAES plant is switched to the grid-connected mode and participates in grid regulation,using the traditional control mode with low accuracy can result in excess grid-connected impulse current and junction voltage.This occurs because the CAES output voltage does not match the frequency,amplitude,and phase of the power grid voltage.Therefore,an adaptive linear active disturbance-rejection control(A-LADRC)strategy was proposed.Based on the LADRC strategy,which is more accurate than the traditional proportional integral controller,the proposed controller is enhanced to allow adaptive adjustment of bandwidth parameters,resulting in improved accuracy and response speed.The problem of large impulse current when CAES is switched to the grid-connected mode is addressed,and the frequency fluctuation is reduced.Finally,the effectiveness of the proposed strategy in reducing the impact of CAES on the grid connection was verified using a hardware-in-the-loop simulation platform.The influence of the k value in the adaptive-adjustment formula on the A-LADRC was analyzed through simulation.The anti-interference performance of the control was verified by increasing and decreasing the load during the presynchronization process.

Perioperative chemotherapy improves survival of patients with locally advanced diffuse gastric cancer

BACKGROUND Whether patients with diffuse gastric cancer,which is insensitive to chemo-therapy,can benefit from neoadjuvant or adjuvant chemotherapy has long been controversial.AIM To investigate whether perioperative chemotherapy can improve survival of patients with locally advanced diffuse gastric cancer.METHODS A total of 2684 patients with locally advanced diffuse gastric cancer from 18 population-based cancer registries in the United States were analyzed.RESULTS Compared with surgery alone,perioperative chemotherapy improved the prognosis of patients with locally advanced gastric cancer.Before stabilized inverse probability of treatment weighting(IPTW),the median overall survival(OS)times were 40.0 months and 13.0 months(P<0.001),respectively.After IPTW,the median OS times were 33.0 months and 17.0 months(P<0.001),respectively.Neoadjuvant chemotherapy did not improve the prognosis of patients with locally advanced gastric cancer compared with adjuvant chemotherapy after IPTW.After IPTW,the median OS times were 38.0 months in the neoadjuvant chemotherapy group and 42.0 months in the adjuvant chemotherapy group(P=0.472).CONCLUSION Patients with diffuse gastric cancer can benefit from perioperative chemotherapy.There was no significant difference in survival between patients who received neoadjuvant chemotherapy and those who received adjuvant chemotherapy.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

Assessment of Operational Performance in a Power Generation/Selling Integrated Company Using a Dynamic Proportional Adjustment Coefficient

Currently,the operational performance assessment system in the power market primarily focuses on power generation and electricity retail companies,lacking a system tailored to the operational characteristics of power generation/selling integrated companies.Therefore,this article proposes an assessment index system for assessing the operational performance of a power generation/selling integrated company,encompassing three dimensions:basic capacity,development potential,and external environment.A dynamic proportional adjustment coefficient is designed,along with a subjective and objective weighting model for assessment indexes based on a combined weightingmethod.Subsequently,the operational performance of an integrated company is assessed using extension theory.The results in the case study demonstrate the feasibility and effectiveness of the proposed dynamic proportional adjustment coefficient.

Ground target localization of unmanned aerial vehicle based on scene matching

In order to improve target localization precision,accuracy,execution efficiency,and application range of the unmanned aerial vehicle(UAV)based on scene matching,a ground target localization method for unmanned aerial vehicle based on scene matching(GTLUAVSM)is proposed.The sugges-ted approach entails completing scene matching through a feature matching algorithm.Then,multi-sensor registration is optimized by robust estimation based on homologous registration.Finally,basemap generation and model solution are utilized to improve basemap correspondence and accom-plish aerial image positioning.Theoretical evidence and experimental verification demonstrate that GTLUAVSM can improve localization accuracy,speed,and precision while minimizing reliance on task equipment.

Differential pressure difference based altitude control of a stratospheric satellite

An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to balance the platform gravity.The two-way blower inflates and deflates the ballonet to regulate the buoyancy.Altitude adjustment is achieved by tracking the differential pressure difference(DPD),and a threshold switching strategy is used to achieve blower flow control.The vertical acceleration regulation ability is decided not only by the blower flow rate,but also by the designed margin of pressure difference(MPD).Pressure difference is a slow-varying variable compared with altitude,and it is adopted as the control variable.The response speed of the actuator to disturbance can be delayed,and the overshoot caused by the large inertia of the platform is inhibited.This method can maintain a high tracking accuracy and reduce the complexity of model calculation,thus improving the robustness of controller design.