A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Permeability Logging:A Breakthrough from 0 to1

On March 3,2024,the prototype permeability logging instrument independently developed in China successfully completed its first downhole test in Ren 91 standard well in PetroChina Huabei Oilfield.In the open hole section at a depth of 3925 metres and at a temperature of 148℃,the device collected high-quality permeability logging data.This marks a key technological breakthrough from 0 to 1 in permeability logging,and lays the foundation for the next step in developing a complete set of permeability logging equipment.

Three decades and beyond:Breeding,biotech breakthroughs and future of China's GM insect-resistant cotton

Cotton(Gossypium spp.)is a pivotal crop in the global textile industry,providing essential natural fibers.Additionally,cottonseed offers significant value as a source of oil and as feed for livestock(Huang et al.2021;Wen et al.2023).The sector,dependent on cotton,features a comprehensive value chain extending from the processing of fibers to the production of finished textiles,and it employs tens of millions of individuals(Dorward et al.1970).

Early identification of scientific breakthroughs through outlier analysis based on research entities

Purpose:To address the“anomalies”that occur when scientific breakthroughs emerge,this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers,aiming to achieve early identification of scientific breakthroughs in papers.Design/methodology/approach:This study utilizes semantic technology to extract research entities from the titles and abstracts of papers to represent each paper’s research content.Outlier detection methods are then employed to measure and analyze the anomalies in breakthrough papers during their early stages.The development and evolution process are traced using literature time tags.Finally,a case study is conducted using the key publications of the 2021 Nobel Prize laureates in Physiology or Medicine.Findings:Through manual analysis of all identified outlier papers,the effectiveness of the proposed method for early identifying potential scientific breakthroughs is verified.Research limitations:The study’s applicability has only been empirically tested in the biomedical field.More data from various fields are needed to validate the robustness and generalizability of the method.Practical implications:This study provides a valuable supplement to current methods for early identification of scientific breakthroughs,effectively supporting technological intelligence decision-making and services.Originality/value:The study introduces a novel approach to early identification of scientific breakthroughs by leveraging outlier analysis of research entities,offering a more sensitive,precise,and fine-grained alternative method compared to traditional citation-based evaluations,which enhances the ability to identify nascent breakthrough innovations.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Analytical Determination of Size and Location of Roadside Horizontal Sightline Offsets for Compound Curves

AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines have analytical models for determining the extent of clearance, known as the horizontal sightline offset or clearance offset, for simple curves. Researchers in the past have developed analytical models for clearance offsets for spiraled and reverse curves. Very few researchers developed analytical models for available sight distances for compound curves. Still missing are models for horizontal sightline offsets and locations of the offsets for compound curves. The objective of this paper is to present development of analytical models and charts for determining horizontal sightline offsets and their locations for compound curves. The paper considers curves whose component arcs are individually shorter than stopping sight distance. The resulting models and the charts have been verified with accurate values determined using graphical methods. The models and the charts will find application in geometric design of highway compound curves.

Using Pearson’s System of Curves to Approximate the Distributions of the Difference between Two Correlated Estimates of Signal-to-Noise Ratios: The Cases of Bivariate Normal and Bivariate Lognormal Distributions

Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.

Big Fish, Big Market Controversies and breakthroughs in salmon farming in China

On August 28,salmon industry insiders and consumers shared insights and analysis on the salmon market and consumption at the 7th Global Salmon Industry Development Summit.An important component of the 18th Shanghai International Fisheries Expo,the event attracted more than100 salmon farming companies from around the globe to exchange views on the current situation and future development of the industry.

Blasts Of Progress Xinjiang Bayi Iron and Steel's carbon reduction breakthroughs

Facing dual challenges of climate change and energy crisis,the global iron and steel industry has been seeking to balance efficiency with energy conservation and environmental protection.Could the realities of blast furnace operation possibly align with low-carbon circular development within China's iron and steel industry?Hydrogen-rich carbon circulating oxygen blast furnace (HyCROF)technology is gaining traction in the Chinese metallurgical industry.

Familial hypercholesterolemia:Current limitations and future breakthroughs

Familial hypercholesterolemia(FH)is characterized by elevated low-density lipoprotein cholesterol levels due to genetic mutations,presenting with xanthomas,corneal arch,and severe cardiovascular diseases.Early identification,diagnosis,and treatment are crucial to prevent severe complications like acute myocardial infarction.Statins are the primary treatment,supplemented by Ezetimibe and proprotein convertase subtilisin/kexin type 9 inhibitors,though their effectiveness can be limited in severe cases.Over 90%of FH cases remain undiagnosed,and current treatments are often inadequate,underscoring the need for improved diagnostic and management systems.Future strategies include advancements in gene testing,precision medicine,and novel drugs,along with gene therapy approaches like AAV-mediated gene therapy and clustered regularly interspaced short palindromic repeats.Lifestyle modifications,including health education,dietary control,and regular exercise,are essential for managing FH and preventing related diseases.Research into FH-related gene mutations,especially LDLR,is critical for accurate diagnosis and effective treatment.

Sensitive Information Security Based on Elliptic Curves

The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.

Review on Service Curves of Typical Scheduling Algorithms

In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.

The Effectiveness of the Havriliak-Negami Model in Predicting the Master Curves of the Asphalt Blends with SBS Triblock Copolymer and Organic-Montmorillonite at Different Temperatures and Frequencies

The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theory (LVE). The HN parameters, α, β, G0, G∞and τHN were determined by solving the HN equation across various temperatures and frequencies. The HN model successfully predicted the rheological behavior of the asphalt and its blends within the temperature range of 25˚C - 40˚C. However, deviations occurred between 40˚C - 75˚C, where the glass transition temperature Tg of the asphalt components and the SBS polymer are located, rendering the HN model ineffective for predicting the dynamic viscoelastic properties of composites containing OMMt under these conditions. Yet, the prediction error of the HN model dropped to 2.28% - 2.81% for asphalt and its mixtures at 100˚C, a temperature exceeding the Tg values of both polymer and asphalt, where the mixtures exhibited a liquid-like behavior. The exponent α and the relaxation time increased with temperature across all systems. Incorporating OMMt clay into the asphalt blends significantly enhanced the relaxation dynamics of the resulting composites.

Gaussian Distance Weighted Algorithm for Geometric Characteristics of Three-Dimensional Discrete Curves

Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.

Suggestions on Improving China’s Breakthrough Therapy Designation System

Objective To analyze the characteristics of breakthrough therapy designation(BTD)and its implementation in China,and to provide reference for the optimization of BTD system.Methods A comparative research method was used to study the content and implementation effect of BTD system in China and the relevant policies and implementation of the same procedures of drug regulatory authorities in the United States,Japan and the European Union.Then,the differences in policies and implementation results among these countries were analyzed to provide suggestions for the implementation and optimization of this system in China.Results and Conclusion China’s BTD system is implemented late and a small number of drugs has been approved.At the same time,there are problems such as insufficient guidance and communication from the agency to applicants,a broad application condition,single review mode,and lack of full-time personnel.Both the agencies and the applicants have limited experience due to the short implementation time of BTD system in China.There are still some problems despite we have learned a lot from the experience of other drug regulatory agencies.Therefore,based on our national conditions,we should strengthen the guidance of evaluation agency to applicants,optimize the eligibility criteria of BTD system,introduce the rolling review,and increase the number of professional liaisons,which can accelerate the development and marketing process of drugs with obvious clinical value,and finally to address unmet medical need.

A Review of the Research on the Influencing Factors of Enterprise Key Core Technology Breakthrough

The breakthrough of key core technology is a theoretical and practical strategic issue to realize the rise of the country.This paper analyzes the concept of key core technology and its breakthrough and analyzes its characteristics.Based on the perspective of participants,this paper summarizes the influencing factors of key core technology breakthroughs in enterprises:internal and external enterprises,universities and scientific research institutions,and government.This paper expands the relevant research on key core technology breakthroughs and provides inspiration for enterprises to carry out key core technology research and breakthrough practices.

Magnetic Field Curves and Magnetic Equipotential Surfaces around Crossing Electrical Wires Replacing Classical Magnetic Field Lines

This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with the new concept of magnetic equipotential surface to magnetic field curves around crossing wires. Cases of single, double, and triple wires are described. Subsequent article will be conducted for more general scenarios where wires are neither infinite nor parallel.

The Origin of the Flat Rotation Curves in Spiral Galaxies: The Hidden Roles of Glitching SMDEOs and Emission of Gravitational Waves

Supermassive DEOs (SMDEOs) are cosmologically evolved objects made of irreducible incompressible supranuclear dense superfluids: The state we consider to govern the matter inside the cores of massive neutron stars. These cores are practically trapped in false vacua, rendering their detection by outside observers impossible. Based on massive parallel computations and theoretical investigations, we show that SMDEOs at the centres of spiral galaxies that are surrounded by massive rotating torii of normal matter may serve as powerful sources for gravitational waves carrying away roughly 1042 erg/s. Due to the extensive cooling by GWs, the SMDEO-Torus systems undergo glitching, through which both rotational and gravitational energies are abruptly ejected into the ambient media, during which the topologies of the embedding spacetimes change from curved into flatter ones, thereby triggering a burst gravitational energy of order 1059 erg. Also, the effects of glitches found to alter the force balance of objects in the Lagrangian-L1 region between the central SMDEO-Torus system and the bulge, enforcing the enclosed objects to develop violent motions, that may explain the origin of the rotational curve irregularities observed in the innermost part of spiral galaxies. Our study shows that the generated GWs at the centres of galaxies, which traverse billions of objects during their outward propagations throughout the entire galaxy, lose energy due to repeatedly squeezing and stretching the objects. Here, we find that these interactions may serve as damping processes that give rise to the formation of collective forces f∝m(r)/r, that point outward, endowing the objects with the observed flat rotation curves. Our approach predicts a correlation between the baryonic mass and the rotation velocities in galaxies, which is in line with the Tully-Fisher relation. The here-presented self-consistent approach explains nicely the observed rotation curves without invoking dark matter or modifying Newtonian gravitation in the low-field approximation.

新质生产力的运行机理、生成逻辑与模式建构——基于生产力与生产关系辩证统一的视角

新质生产力是创新发挥主导作用,摆脱传统经济增长方式、生产力发展路径,具有高科技、高效能、高质量特征,符合新发展理念的先进生产力质态。纵观三次科技革命变革生产力的历程,新质生产力的产生和发展是生产力与生产关系相互作用的结果,具有生产力与生产关系的双重内涵和发展要求。新质生产力以新型劳动者、新型劳动资料、新型劳动对象及其组合模式和新型生产关系为架构要素与发展基础,其生成逻辑与运行机理是由技术革命性突破引发,在催生新型生产力要素、新型要素组合模式的基础上促使与新质生产力相适应的新型生产关系变革形成,新型生产关系的反作用促进新质生产力进一步生成的过程。发展新质生产力要以实施创新驱动战略、加快产业深度转型、构建要素生态系统和全面深化改革为基本模式和关键路径。亟须加快实现高水平科技自立自强,加快技术革命性创新;促进产业深度转型,构建现代化产业体系;促进生产要素创新配置,构建新质生产要素系统;全面深化改革,加快建立健全与新质生产力相适应的新型生产关系,促进新质生产力加快形成发展。

Time-temperature-property curves for quench sensitivity of 6063 aluminum alloy

The quench sensitivity of 6063 alloy was investigated via constructing time-temperature-property（TTP） curves by interrupted quenching technique and transmission electron microscopy（TEM） analysis.The results show that the quench sensitivity of 6063 alloy is lower than that of 6061 or 6082 alloy,and the critical temperature ranges from 300 to 410℃ with the nose temperature of about 360℃.From TEM analysis,heterogeneous precipitate β-Mg2Si is prior to nucleate on the（AlxFeySiz） dispersoids in the critical temperature range,and grows up most rapidly at the nose temperature of 360℃.The heterogeneous precipitation leads to a low concentration of solute,which consequently reduces the amount of the strengthening phase β＇＇ after aging.In the large-scale industrial production of 6063 alloy,the cooling rate during quenching should be enhanced as high as possible in the quenching sensitive temperature range（410-300℃） to suppress the heterogeneous precipitation to get optimal mechanical properties,and it should be slowed down properly from the solution temperature to 410℃ and below 300℃ to reduce the residual stress.