Battery technology plays a crucial role across various sectors,powering devices from smartphones to electric vehicles and supporting grid-scale energy storage.To ensure their safety and efficiency,batteries must be evaluated under diverse operating conditions.Traditional modeling techniques,which often rely on first principles and atomic-level calculations,struggle with practical applications due to incomplete or noisy data.Furthermore,the complexity of battery dynamics,shaped by physical,chemical,and electrochemical interactions,presents substantial challenges for precise and efficient modeling.The Transformer model,originally designed for natural language processing,has proven effective in time-series analysis and forecasting.It adeptly handles the extensive,complex datasets produced during battery cycles,efficiently filtering out noise and identifying critical features without extensive preprocessing.This capability positions Transformers as potent tools for tackling the intricacies of battery data.This review explores the application of customized Transformers in battery state estimation,emphasizing crucial aspects such as charging,health assessment,lifetime prediction,and safety monitoring.It highlights the distinct advantages of Transformer-based models and addresses ongoing challenges and future opportunities in the field.By combining data-driven AI techniques with empirical insights from battery analysis,these pre-trained models can deliver precise diagnostics and comprehensive monitoring,enhancing performance metrics like health monitoring,anomaly detection,and early-warning systems.This integrated approach promises significant improvements in battery technology management and application.
[目的]从全球水平分析肺癌终生罹患风险和死亡风险。[方法]利用GLOBOCAN2022肺癌发病、死亡数据和联合国发布的人口和全死因数据,采用调整多原发癌的方法估计全球和不同地区肺癌终生罹患风险和死亡风险。[结果]全球肺癌终生罹患风险为3.59%[95%置信区间(confidence interval,CI):3.58%~3.59%],居不同癌种的第3位。终生罹患风险值存在明显的性别差异和地区差异,男性风险值为4.43%(95%CI:4.42%~4.44%),高于女性[2.71%(95%CI:2.70%~2.72%)],男女性别比为1.63∶1;全球不同人类发展指数(human development index,HDI)地区中,风险值随着HDI水平的升高而增加,超高HDI地区风险值为5.36%(95%CI:5.34%~5.37%),低HDI地区风险值为0.34%(95%CI:0.33%~0.34%);全球20个地区中,东亚地区终生罹患风险最高,为7.53%(95%CI:7.52%~7.55%);西非地区风险值最低,为0.16%(95%CI:0.16%~0.17%)。全球肺癌终生死亡风险为2.78%(95%CI:2.78%~2.78%),居不同癌种的第1位。终生死亡风险也存在明显的性别差异和地区差异,男性风险值[3.64%(95%CI:3.63%~3.64%)]高于女性[1.89%(95%CI:1.89%~1.90%)],男女性别比为1.93∶1;全球不同HDI水平地区中,风险值随着HDI水平的升高而增加,超高HDI地区风险值为3.98%(95%CI:3.97%~3.99%),低HDI地区风险值为0.31%(95%CI:0.31%~0.31%);全球20个地区中,死亡风险最高的为密克罗尼西亚联邦/波利尼西亚[5.80%(95%CI:4.98%~6.62%)],死亡风险最低的为西非[0.15%(95%CI:0.15%~0.16%)]。中国肺癌终生罹患风险和死亡风险分别为7.54%(95%CI:7.52%~7.56%)和5.88%(95%CI:5.87%~5.90%),均居所有癌种的第1位。[结论]全球和不同地区肺癌终生罹患风险和死亡风险仍然较高,风险值随着HDI水平的增加而升高,中国肺癌终生罹患风险和死亡风险均高于全球水平,提示基于肺癌相关危险因素和筛查与早诊早治的综合防控措施仍需不断加强,从而降低肺癌疾病负担。
Stimulated emission and lasing of GaN-based laser diodes(LDs)were reported at 1995[1]and 1996[2],right after the breakthrough of p-type doping[3−5],material quality[6]and the invention of high-brightness GaN-based LEDs[7,8].However,it took much longer time for GaN-based LDs to achieve high power,high wall plug efficiency,and long lifetime.Until 2019,Nichia reported blue LDs with these performances[9],which open wide applications with GaN-based blue LDs.
Lei HuSiyi HuangZhi LiuTengfeng DuanSi WuDan WangHui YangJun WangJianping Liu
Multicolor microscopy and super-resolution optical microscopy are two widely used techniques that greatly enhance the ability to distinguish and resolve structures in cellular imaging.These methods have individually transformed cellular imaging by allowing detailed visualization of cellular and subcellular structures,as well as organelle interactions.However,integrating multicolor and super-resolution microscopy into a single method remains challenging due to issues like spectral overlap,crosstalk,photobleaching,phototoxicity,and technical complexity.These challenges arise from the conflicting requirements of using different fluorophores for multicolor labeling and fluorophores with specific properties for super-resolution imaging.We propose a novel multicolor super-resolution imaging method called phasor-based fluorescence spatiotemporal modulation(Phasor-FSTM).This method uses time-resolved detection to acquire spatiotemporal data from encoded photons,employs phasor analysis to simultaneously separate multiple components,and applies fluorescence modulation to create super-resolution images.Phasor-FSTM enables the identification of multiple structural components with greater spatial accuracy on an enhanced laser scanning confocal microscope using a single-wavelength laser.To demonstrate the capabilities of Phasor-FSTM,we performed two-color to four-color super-resolution imaging at a resolution of~λ/5 and observed the interactions of organelles in live cells during continuous imaging for a duration of over 20 min.Our method stands out for its simplicity and adaptability,seamlessly fitting into existing laser scanning microscopes without requiring multiple laser lines for excitation,which also provides a new avenue for other super-resolution imaging technologies based on different principles to build multi-color imaging systems with the requirement of a lower budget.
Several process parameters affect product reliability.Traditional reliability improvement methods primarily focus on maximizing product lifetime,often overlooking the variation in product lifetime.Manufacturers,however,aim to produce products with minimal variations in their performance.Robust parameter design offers an effective strategy to help manufacturers enhance product reliability while reducing process variations.In practice,reliability experiments frequently involve constrained randomization due to the selection of specific experimental protocols.This study proposes a framework to achieve robust product reliability under a constrained randomization experiment.To consider random effects,we develop a Bayesian method-based Weibull non-linear mixed model for the lifetime response.Important factors are identified according to Bayesian posterior credible intervals.Subsequently,we propose an integrated multi-objective optimization model to determine the optimal factor levels.This model simultaneously considers minimizing the total costs of the manufacturer,maximizing the product lifetime,and minimizing the lifetime variance.An industrial thermostat experiment is conducted to validate the proposed method.Compared to existing approaches,the proposed method demonstrates superior performance in reducing variance and total cost,particularly for long warranty periods.Finally,we discuss the practical implications of the optimal solutions for manufacturers,finding that variations remain tolerable within a certain range.
Shanshan LvYichen ZhaoSen LiGuodong WangXueqing Wang
