bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Driver Readiness in Conditionally Automated Vehicles From Eye‐Tracking Data and Head Pose
Authors: Kazemi Mostafa , Rezaei Mahdi , Azarmi Mohsen
Published: February 2025

As automated driving technology advances, the role of the driver to resume control of the vehicle in conditionally automated vehicles becomes increasingly critical. In the SAE level 3 or partly automated vehicles, the driver needs to be available and ready to intervene when necessary. This makes it essential to evaluate their readiness accurately. This article presents a comprehensive analysis of driver readiness assessment by combining head pose features and eye‐tracking data. The study explores the effectiveness of predictive models in evaluating driver readiness, addressing the challenges of dataset limitations and limited ground truth labels. Machine learning techniques, including LSTM architectures, are utilised to model driver readiness based on the spatio‐temporal status of the driver's head pose and eye gaze. The experiments in this article revealed that a bidirectional LSTM architecture, combining both feature sets, achieves a mean absolute error of 0.363 on the DMD dataset, demonstrating superior performance in assessing driver readiness. The modular architecture of the proposed model also allows the integration of additional driver‐specific features, such as steering wheel activity, enhancing its adaptability and real‐world applicability.
Exploring the disc-jet scenario in 3C 273 using simultaneous XMM-Newton and NuSTAR observations
Authors: Pandey Ashwani , Mondal Santanu , Wiita Paul J.
Published: February 2025

The well-studied active galactic nucleus (AGN) 3C 273 displays characteristics of both jetted-AGNs and Seyfert galaxies, which makes it an excellent source to study the disc-jet connection in AGNs. We aim to investigate the disc-jet scenario in 3C 273 using broad-band (0.3--78 keV) X-ray spectra from XMM-Newton and NuSTAR We used simultaneous XMM-Newton and NuSTAR observations of 3C 273 carried out between 2012 and 2024. The 0.3--78 keV X-ray spectra were first fitted with a simple power law (PL) and then with the accretion-ejection-based model. The model accounts for emission from the jet, which extends up to the sonic surface. In this framework, a reflection hump above 10 keV can also arise due to the bulk motion Comptonization of coronal photons by the jet. We find that the simple PL did not provide a good fit, leaving significant residuals at energies below 1.5 keV. All the spectra were fitted well by the model. The weighted-averaged black hole mass of (7.77±0.30) times 10^8 M_⊙ obtained from the model is comparable with the previous estimates based on reverberation mapping observations and accretion disc models. The 0.3--78 keV X-ray emission of 3C 273 can be fit by the accretion-ejection-based model in which the corona and the jet on top of it make significant contributions to the X-ray flux. The Doppler boosting factor estimated from the jet flux ranges from 1.6 to 2.2, consistent with the lower limit from the literature.
Guidelines for non-LTE modelling of cyanopolyynes
Authors: Bop Cheikh T. , Lique François
Published: February 2025

Cyanopolyynes are abundant and widespread in cold molecular clouds. Their abundances are typically determined under the assumption of local thermodynamic equilibrium (LTE) or through non-LTE analysis based on approximate collisional rate coefficients. Here, we present the first quantum mechanical scattering data for HC_5N and HC_7N in collisions with helium. We used both close-coupling (CC) and coupled-states (CS) methods to compute excitation cross-sections. We then derived rate coefficients for the first energy levels of HC_5N and HC_7N. A comparative analysis between the CC and CS results reveals an agreement better than a factor of two for high-magnitude rate coefficients. However, we found that the derivation of approximate HC_5N and HC_7N rate coefficients from those of HCN and HC_3N using a size proportionality relationship, as has been previously done in the literature, leads to an overestimation of the collisional data by up to two orders of magnitude. To assess the sensitivity of cyanopolyyne line intensities to collisional rate coefficients, we compared LTE predictions with various non-LTE models using different rate coefficients. Under the typical physical conditions of cold molecular clouds, the LTE assumption and radiative transfer calculations based on approximate collisional rate coefficients strongly overestimate high-frequency line intensities, while the non-LTE models based on the HC_3N collisional rate coefficients as a proxy for HC_5N and HC_7N remain accurate within 10%. We therefore recommend revisiting the abundance estimates for HC_5N and HC_7N using the new rate coefficients. For HC_9N and HC_11N, adopting HC_7N collisional data in line modelling is expected to be highly accurate.
Application of Magnetic Coagulation Sedimentation Tank and Sand-adding High-efficiency Sedimentation Tank in Sewage Treatment
Authors: Shangguan Yufei , Qiu Binbin , Ma Zongkai , He Li
Published: February 2025

Magnetic coagulation sedimentation tank and sand-adding high-efficiency sedimentation tank are more and more widely used in the upgrading of sewage plants, industrial wastewater treatment and river water treatment, which are on the basis of ordinary high-density sedimentation tanks, the addition of magnetic powder and micro-sand as the core of flocculation to strengthen the flocculation process. This paper discusses the development history, research direction and application results of magnetic coagulation sedimentation tank and sand-adding high-efficiency sedimentation tank, and summarises the advantages and disadvantages of the two in engineering applications. In the case of the same footprint and treatment effect, compared with the magnetic coagulation and sedimentation tank, the sand-adding high-efficiency sedimentation tank is more adaptable, less difficult to operate and maintain, and more economical in operating costs.
Impact of Dissolved Oxygen Limiting Strategies on the Simultaneous Partial Nitrification, Anammox and Denitrification (SNAD) Process
Authors: Xia Zhouzhenyang , Luo Jiajun , Liu Zhifan , Ou Menglin , Fu Haiyan
Published: February 2025

The effect of dissolved oxygen (DO) limitation strategies on the nitrogen removal performance of the SNAD system under high DO damage was explored. Nitrogen removal efficiency (NRE) decreased rapidly in a high DO environment (2.0-3.0 mg/L). The NRE temporarily recovered to 87.32% after the DO limiting strategy was adopted. However, the NRE decreased to 59.35% with the rapid increase in nitrate concentration and the average anaerobic ammonia oxidation rate decreased to 1.37 mg-TN/(gVSS-h). In order to suppress the gradually increasing nitrate concentration, DO was further limited to 0.3-1.0 mg/L. This strategy effectively stabilised the nitrate concentration and achieved the recovery of anammox bacteria (AnAOB) activity, but could not stably restore the system denitrification performance. At the same time, the pH in the system dropped below 7, which hindered the restoration of the nitrogen removal efficacy. The DO limitation strategy can temporarily restore AnAOB activity. Achieving stable nitrogen removal may require synergistic adjustments of alkalinity and hydraulic retention time, among other strategies.
Spatiotemporal Patterns and Influencing Factors of Ecosystem Services in Shandong Province
Authors: Guo Liangjie , Wang Junyue , Zhai Yongbo , Zuo Yanlei , Liu Wei
Published: February 2025

Ecosystem services (ESs) are essential for human survival and development and serve as key indicators in evaluating ecological civilization progress. This study investigated the spatiotemporal patterns of ESs in Shandong Province from 2000 to 2020, using the Geographical Detector model to assess the impact of diverse influencing factors. The results showd that: (1) From 2000 to 2020, grain production (GP), soil conservation (SC), and carbon sequestration (CS) showed a fluctuating increase of 39.92%, 106.88%, and 32.21%, respectively. Water yield (WY) remained relatively stable, while habitat quality (HQ) declined rapidly after 2010. (2) Land use types and elevation demonstrated high explanatory power regarding the spatial heterogeneity of each ES, with population density also having a significant impact on all services except SC. Precipitation emerged as the strongest explanatory factor for water conservation. Furthermore, all pairwise interactions between factors exhibited a bi-factor enhancement in 2020, indicating a substantial role of multi-factor interactions in ES dynamics. This study provides essential insights to support decision-making, addressing the challenges ESs face and promoting the sustainable, high-quality development of Shandong’s socio-ecological-economic system.
Comparison of Coastal Resilience Policies: A Perspective on Effective Global Governance Strategies
Authors: Dong Weiwei , Lin Guilan
Published: February 2025

Coastal areas are key ecosystems that concentrate global biodiversity and are particularly vulnerable to the impacts of climate change. Countries around the world have developed diverse policies to address coastal resilience challenges, responding to threats from sea level rise, extreme weather events, and coastal development. This paper provides a comparative analysis of coastal resilience governance policies across different countries and regions, summarizing successful governance practices. The study reveals that developed countries like the Netherlands and the United States have effectively enhanced disaster resilience and ecological protection by combining hard engineering measures with nature-based solutions. In contrast, countries such as Japan and Indonesia have focused more on community participation and nature-based solutions, demonstrating the advantages of low-cost and sustainable governance. Successful policy tools exhibit several common characteristics, including the integration of engineering measures with nature-based solutions, broad community involvement, multi-level collaborative governance, and adaptive management. Moreover, the study highlights the challenges and prerequisites of cross-regional policy transfer. This paper provides feasible recommendations for policymakers to enhance the adaptability and resilience of coastal areas in response to the long-term risks posed by climate change.
Research on Zero Carbon Sports Building Technology Strategy in Regions with Hot Summers and Cold Winters
Authors: Ding Yunxia , Qiu Xilan , Cai Jinxing
Published: February 2025

With the arrival of the era of all-people sports and the rapid development of sports venue construction, under the background of “carbon peaking and carbon neutrality”, green and low-carbon construction of sports venues is imperative, and it is urgent to build a suitable and mature zero carbon technology system. In this thesis, a research is conducted on canonical zero carbon sports venues both domestically and internationally, summarizing the application and adaptive forms of zero carbon technology in sports buildings, as well as difficulties in implementation from actual engineering cases. Then, starting from the functional features of sports venues, the focus of energy conservation and emission reduction of sports buildings is clarified through comparative analysis, the appropriate low-carbon technology path for sports buildings in regions with hot summers and cold winters is refined, and its effectiveness is verified by the analysis on a typical actual case, by which the zero carbon strategy concept of “source reduction first, passive design priority, ontology focus, efficiency improvement as the core, and energy enhancement as the wing” is further proposed and refined into 20 key technologies and implementation points, thus constructing a zero carbon sports venue technology system with climate adaptability, and providing technical guidance for the construction of zero carbon sports venues.
Renewable Energy Development in Funafuti: Photovoltaic System Design and Economic Performance
Authors: Zhuang Yuan
Published: February 2025

Funafuti, the capital of Tuvalu, currently depends heavily on imported fossil fuels for its electricity generation, rendering the energy supply both expensive and environmentally unsustainable. However, the territory’s abundant solar resources offer a promising pathway toward cleaner, renewable energy sources. This research investigates the design and economic evaluation of a photovoltaic (PV) energy system for Funafuti, with the aim of reducing dependence on fossil fuels and promoting renewable energy adoption. The study utilizes HelioScope for PV system design and HOMER Pro for system integration and economic analysis. The findings suggest that while a 100% renewable energy system can significantly lower emissions, it is the judicious integration of storage that is pivotal to achieving economic viability The most cost-effective system configuration substantially reduces the net present cost (NPC) and operational expenses when compared to fossil fuel-based systems, thereby emphasizing the critical role of storage in bolstering both energy security and economic efficiency. The lowest-cost system configuration significantly reduces the net present cost (NPC) and operational costs compared to fossil fuel-based systems, highlighting the critical role of storage in enhancing both energy reliability and cost-effectiveness.
Evaluation of the Application and Development Potential of Distributed PV in Industrial Parks–Take the 180MW Distributed Photovoltaic Project as an Example
Authors: Long Yetian , Lu Shuming , Chen Shuaiming , Chen Chen , Chen Guanghua , Shan Xianjin , Hu Yuanyuan
Published: February 2025

As one of the main sources of global greenhouse gas emissions, realizing the goal of “carbon peak, carbon neutrality” has become a major problem to be solved urgently. The application of distributed photovoltaic technology, as one of the effective ways to promote the realization of carbon peak and carbon neutrality in industrial parks, is particularly critical. This paper analyzes the application status of distributed photovoltaic in industrial parks in depth, and focuses on the application scenarios and technical standards of related technologies. Taking the 180MW distributed photovoltaic project as an example, the engineering benefits and development potential of the project are analyzed in detail, and the problems of distributed photovoltaic in the industrial park are pointed out. Through this analysis, we aim to realize the green aluminum industry and clean energy industry integration collaborative win-win development, power cloud aluminum construction “national environment friendly enterprise”, for more similar to aluminum industrial park in promoting distributed photovoltaic applications provide useful reference and reference, in order to promote the development of industrial park green low carbon.
Some Fixed-Point Theorems on Quasi M-Metric Spaces
Authors: Darojad Rofiud , Indrati Christiana Rini
Published: February 2025

In this paper, it will be discussed a metric that is constructed based on a quasi M-metric and a new definition of Cauchy sequences in quasi M-metric spaces. The discussion will be continued by giving a relationship between completeness in the quasi M-metric space and the constructed metric space. Furthermore, it will be developed some fixed-point theorems on quasi M-metric spaces.
Analytical Solution of Generalised Mandel’s Problem
Authors: Mahdiyasa Adilan W. , Justica Alma , Prastoro Tarasinta
Published: February 2025

Mandel’s problem considers the time-dependent deformation of a fully saturated rectangular porous material with drainage at the lateral sides and steady load from the top and bottom. It plays a major role in the fields of geomechanics and hydrogeology. This paper presents analytical solutions to Mandel’s problem with compressible fluid and solid particles. The governing equations are developed based on the equation of equilibrium and the conservation of mass both for fluid and solid constituents. The analytical solution is obtained by applying the Laplace transform to the proposed governing equation with the pore pressure becoming the main variable. The result can serve as a benchmarking and calibration tool for both modelling and experimental data. To show the application of the proposed analytical solution, we perform simulations to study the influence of solid compressibility on the pore pressure distribution. We found that the pore pressure is significantly affected not only by the permeability but also the compressibility of the solid particles. Therefore, compared to the classical analytical solution of Mandel’s problem, in which the fluid and solid particles are incompressible, our analytical solution offers more general results and provides a deeper understanding of the mechanical behaviour of a porous material.
Dynamical System Modeling in Asset and Liability Management
Authors: Tandy Marvin , Budhi Marcus Wono Setya
Published: February 2025

Insurance companies must ensure a balance between the profits generated from their investment and the liabilities they owe to policyholders. This is widely known as asset and liability management (ALM). One important element of ALM involves forecasting the long-term financial status of the company. Therefore, a discrete time dynamical system is developed to illustrate the fluctuations in the financial components of an insurance company. Subsequently, simulations are conducted based on the constructed model for cases both with and without mortality. The model takes into account varying premium amounts and durations, a stochastic capital market, a dynamic management strategy, as well as mechanisms for establishing reserves. The financial components arising in the model are calculated recursively, allowing for easier and more efficient simulations.
Variation in extreme rainfall in indonesia associated with four propagation types of madden-julian oscillation
Authors: Setiabudi Dendi , Suwarman Rusmawan , Abdillah Muhammad Rais
Published: February 2025

The impact of the MJO on extreme daily rainfall (xMJO ≥ xc), namely the 95th extreme, is known by quantifying the difference in probability of extreme daily rainfall during the MJO versus NDJFMA (△PMJO) events. MJO has four propagation characteristics. In this study, the differences in the 95th extreme probability is the impact of the characteristics of each type of MJO propagation which are different from each other. MJO identification is by using a band-pass filter frequency against the daily average Outgoing Longwave Radiation and certain criteria. MJO identified according to certain criteria from the band-pass filter will be grouped based on the similarity of propagation types using the k-mean clustering method. In addition, a regional probability matrix of the 95th extreme probability difference is created. The positive (negative) difference in daily rainfall and the probability of the 95th extreme follows the propagation of the active phase (inactive phases) of each MJO type. The regional probability of a positive 95th extreme probability difference or positive probability (negative probability) also has the same or follows the propagation of active phase (inactive phases) for each MJO type from west to east, just like the similarity of the pattern of bulk difference daily rainfall and 95th extreme probability.
The entombed lives – the experience of sibling abortion under China’s One-Child Policy
Authors: Liu Ying
Published: February 2025

Drawing on the author’s own experience, this paper explores the rarely researched experience of sibling abortion under China’s One-Child Policy through a psychodynamic lens. The author uses writing as a method of inquiry to delve into the emotional impact of losing a younger brother to abortion due to the One-Child Policy and to dialogue with relevant psychodynamic literature on loss and grief. The main body of this paper consists of three separate yet interrelated sections. In the first section, drawing on the concept of The Dead Mother, the author explores the possible impact of her mother’s bereavement of a second child on the author’s emotional life in her formative years. The second section draws on psychodynamic literature on melancholia to understand how the lost life of an aborted brother is kept alive in the author’s psyche and the ambivalence this brings to the author’s psychical world. The third section is an analysis of the first two sections, constructing an understanding of the missing psychosocial elements in the first two sections. This paper gives voice to the longing and mourning brought by sibling abortion under the One-Child Policy, presenting the author’s process of trying to understand such experiences and attempt to understand the personal and the psychical under the influence of the political.
An enhanced crow search algorithm based on the disturbance method for engineering design problems
Authors: Fan Yuqi , Peng Zhihong , Wang Yaping , Gao Bingwei , Li Shengbiao
Published: February 2025

To address the shortcomings of the basic crow search algorithm (CSA), an enhanced crow search algorithm based on the disturbance method (DMCSA) is proposed. The basic CSA has slightly weak exploration and development abilities. The fixed flight length causes the basic CSA to conduct intensive searches in small areas, and it cannot conduct comprehensive and broad searches in the entire search space. The trigonometric function updating strategy is adopted to obtain a random walk model, so the global search ability is strong in DMCSA. In addition, the disturbance searching operation is adopted for detailed local search in DMCSA, as it can simultaneously balance convergence and diversity in the search space. Finally, this paper tests basic functions and multimodal functions and also provides iteration numbers, box plots, search paths, radar charts, the Wilcoxon rank sum test, graphs, and confidence intervals to comprehensively show different aspects of the performance of DMCSA in different functions. The experimental results show that the DMCSA efficiency reached 100% for all the high-dimensional functions. Among the two-dimensional functions, the worst-case function efficiency was 40%, and more than 60% efficiency was reached for all the other functions. For DMCSA application, this paper uses three engineering design problems to show different efficiencies. All results show that the DMCSA has excellent balance, good accuracy, wide exploration, and a high iteration speed.
A combat game model between hierarchical networks
Authors: Chen Hao , Liu Zhixin
Published: February 2025

Inter-network combat between hierarchical systems plays an essential role in shaping the landscape of everyone’s surroundings, influencing fields such as sports tournaments, business competitions, military conflicts, and trade wars. In response, this study proposes a hierarchical combat game model to analyze the dynamics of leader–follower networks engaged in adversarial interactions. Within this model, leaders are motivated by the collective goals, framing the strategic dilemmas faced by followers, who must balance adherence to leadership strategies against minimizing personal risk. Utilizing the leader–follower game as a theoretical framework, the study investigates the impact of leader characteristics on overall success, measured by the winning percentage (WP). The key findings reveal that increasing the number of leaders consistently enhances WP, with the effect being more pronounced in larger populations. However, higher aspiration level and rationality among leaders may impede their chances of winning the game. Additionally, the analysis uncovers strong correlations between the differences in the number of surviving followers, differences in payoffs, and differences in the proportion of followers adopting the Attack strategy, highlighting critical factors that drive success in combat scenarios. Furthermore, our investigation into follower dynamics reveals that the side making the first sacrifice often wins.
Distributed OPGW abnormal vibration monitoring and forewarning based on LSTM
Authors: Bu Tianlong , Kou Hanpeng , Zhang Dapei , Feng Zhenhua , Law Helen , Wang Bin
Published: February 2025

Analyzing and predicting abnormal vibrations in optical fiber composite overhead ground wire (OPGW) transmission lines accurately is a challenging task. This paper proposes a distributed monitoring and forewarning method for OPGW abnormal vibrations using the long short-term memory (LSTM) algorithm, leveraging the regularity of abnormal vibrations related to climatic conditions. A distributed fiber Bragg grating array is employed to acquire monitoring signals, followed by the derivation of LSTM prediction steps. We effectively capture the long-term dependence of OPGW abnormal vibration signals by introducing cell state and gating mechanisms. In addition, the abnormal vibration forewarning method is analyzed by correlating predicted data with historical data. Experimental results in Hulunbuir demonstrate that the LSTM algorithm performs well in predictions over a 22-h period, evidenced by a root mean square error of 0.8729 and a determination coefficient (R2) of 0.9938 for the fitting curve with actual results. This performance surpasses that of the traditional GA-BP algorithm, facilitating effective abnormal vibration forewarning. This method holds significant potential for widespread application in the field of OPGW abnormal vibration engineering.
Weighing unequal parameter importance and measurement expense in adaptive quantum sensing
Authors: Kelley M. , McMichael R. D.
Published: February 2025

A large class of experiments consists of measuring the parameters of physical models. In these experiments, the goal is to learn about these parameters as accurately and, often, quickly as possible. Adaptive experiment design works by yielding instrument control to Bayesian-based algorithms that alter instrument settings based on potential information gain about the parameters. By actively learning from data in real-time where to measure instead of determining instrument settings a priori, striking improvements in experiment efficiency are possible. Here, two new algorithms that improve upon previous implementations of adaptive experiment design are introduced. The first algorithm focuses on learning the model parameters that matter the most. The second algorithm considers the expense of a measurement and prioritizes information that can be gained at a lower cost. We demonstrate the remarkable improvement in efficiency and sensitivity that these algorithms provide for quantum sensing, specifically magnetometry, with nitrogen-vacancy centers in diamond. Most notably, we find an almost fivefold improvement in magnetic field sensitivity.
Optical sensing of nanoparticles employing porous silicon thin films
Authors: Riven Vered , Zemmour Chalom , Naor Tom , Sagi Roey , Banin Uri , Asscher Micha , Benny Ofra , Jaiswal Jyoti , Sa’ar Amir
Published: February 2025

With the increasing consumption of nanomaterials in a variety of applications, our environment becomes more and more exposed to different kinds of (possibly toxic) nanomaterials having variable sizes and shapes, raising up the requirement to sense and monitor the presence of nanomaterials. Here, we propose and demonstrate a porous-silicon based optical sensing platform, capable of sensing nanoparticles of a given distribution of sizes and shapes, but independent of their chemical, mechanical, or electrical properties. A white light optical interference technique has been utilized to transduce nanoparticles trapped in the porous matrix into an optical signal. We have found an unusual optical sensing response that substantially increases the sensing bandwidth of the porous-silicon based optical sensor, which follows a Hill-equation type behavior that is characterized by a logarithmic response at low nanoparticle's concentration and saturation at high concentrations. These universal characteristics of the sensors are explained by the anomalous and limited diffusion of the nanoparticles via a quasi-1D geometry of the pore's matrix. Very low concentration of nanoparticles, of the order of few μg/ml, has been measured by this sensing technique.
Currere
Authors: Garcia Maria , Masterson Jessica
Published: February 2025

In this chapter we discuss how currere can support research in Applied Linguistics
(AL). We examine studies where currere or a similar approach has been used as a research method in
Applied Linguistics. Citing these studies, we discuss how they can be used as examples for future
currere-based AL research. Following that discussion, we also provide guidance about
considerations that researchers should be aware of before choosing currere as their research
approach. This discussion will help guide AL researchers in using currere in the different stages of a
currere-based AL research project. Lastly, we address affordances, limitations, and ethical
considerations of using currere in AL research, especially within studies that examine power dynamics
used within language. Additionally, we provide guidance on how to use currere in studies where there
is a larger group of participants.
When children don’t learn to read
Authors: Jack-Malik Sandra , Kuhnke Janet L.
Published: February 2025

Children who learn to read fluently are more likely to experience academic success. Many
youngsters however fail to meet literacy, learning outcomes. This chapter describes a study involving children in
grade three, labelled as struggling readers. Using narrative inquiry as the research methodology, we worked in
partnership with the principal and classroom teacher to co-design a study including a structured literacy
intervention. Narrative inquiry methodology was utilized because it supports the collection of rich data (stories).
Using the narrative inquiry framework of commonplaces: temporality, sociality and place, the research was designed,
lived out, analyzed, and reported. The methodology also provided a framework for dealing with ethical challenges
encountered. Our goal was to come alongside children, families and teachers through time to deepen understandings of
how they experienced learning to read and reading remediation. We were interested in understanding efforts to shift
away from struggling reader identity stories. Included is an overall narrative of the study and participant and
researcher stories. Furthermore, researcher and participant artwork and artifacts are embedded because they provide
nuances beyond words on the page. We attended a First Nation’s in-community school, two mornings per week over
five-months. Our plan had been to conduct the research over a two-year period, following the children from grade three
to four. The plan, however, was interrupted by the global pandemic and related restrictions on school access.
Pivoting physics labs online
Authors: Varney C N , Seals S R , Wade A
Published: February 2025

The COVID-19 pandemic forced introductory lab courses to shift to an online format. This implementation involved a shift in emphasis in learning goals towards transferable lab skills and involved a range of activities, including PhET simulations, video data collection, analysis of data sets, and open-ended free response conceptual questions. In this study, we examined student perceptions of aspects of the online lab activities and learning outcomes. We find that synchronous attendance is more likely to produce positive learning outcomes and that activities associated with data analysis are perceived to be more difficult. We discuss structural flaws with the learning management systems that can exacerbate student perceptions.
Modeling of microstructure and microsegregation evolution in solidification of ternary alloys
Authors: Yu Qiannan , Hu Mengdan , Wu Jinyi , Sun Dongke
Published: February 2025

The microstructure formed during solidification has a significant impact on the mechanical properties of materials. In this study, a two-dimensional (2D) cellular automaton (CA)-finite difference (FD)-CALPHAD model was developed to simulate the formation of microstructure and solute segregation in the solidification processes of ternary alloys. In the model, dendritic growth is simulated using the CA technique, while solute diffusion is solved by the FD method, and the CALPHAD method is employed to calculate thermodynamic phase equilibrium during solidification. The CA-FD-CALPHAD coupled model is capable of reproducing the evolution of continuous nucleation and growth of grains as well as the evolution of the microstructure and solute distribution during solidification of ternary alloys. In this study, Al-Zn-Mg ternary alloy is taken as an example to simulate the growth of equiaxed and columnar grains and the columnar-to-equiaxed transition (CET) under different solidification conditions. The simulation results are compared with experimental data from the literature, showing a good agreement. Besides, the study also investigates the evolution of temperature and multicomponent solute fields during solidification and the effects of alloy composition and cooling rate on the microstructure morphology. The results reveal that the initial alloy composition and cooling rate significantly affect dendritic morphology and solute segregation. Higher initial alloy concentrations promote the growth of side branches in equiaxed grains, leading to more pronounced solute segregation between dendrites. As the cooling rate increases, the average grain size of the equiaxed grains decreases accordingly. Additionally, a higher cooling rate accelerates the columnar-to-equiaxed transition, leading to a finer grain structure.
Design and Preparation of Amorphous Carbon Nanotubes Reinforced Copper
Authors: Ren Xiaona , Wu Wentao , Chen Zhipei , Ge Changchun
Published: February 2025

Carbon nanotubes (CNTs) reinforced copper (CNTs/Cu) is one of the most promising and extensively researched materials for replacing traditional Cu-based materials in high-load and high-current applications, particularly within the aerospace industry. Amorphous carbon nanotubes (aCNTs) are a type of carbon nanotubes characterized by the presence of mesopores distributed across their amorphous sidewalls, facilitating connectivity between the hollow core and the external environment. Therefore, we propose utilizing aCNTs as a reinforcing agent for Cu. The mesoporous structure of aCNTs facilitates the interpenetration of Cu into the aCNTs, thereby maintaining the continuity of the matrix properties. Experimental results demonstrate that Cu effectively penetrates the mesoporous sidewalls of aCNTs. Both pure Cu and aCNTs-reinforced Cu exhibit comparable electrical conductivity, while the hardness of the aCNTs/Cu composite is significantly enhanced. Additionally, both the density and porosity of aCNTs/Cu are lower than those of pure Cu, and the introduction of aCNTs helps to reduce the sintering temperature.
Development of the mental models of wave and particle as basis for wave-particle duality
Authors: Ockhorst Rutger , Pols Freek
Published: February 2025

Wave-particle duality is included in many secondary school and university physics curricula as a concept central to quantum physics. The very term wave-particle duality suggests that a firm grasp of the individual classical concepts of wave and particle is crucial to studying quantum mechanics successfully. This raises the question whether students’ mental models of these concepts are sufficiently addressed and developed prior to the teaching of wave-particle duality. We explored Dutch upper secondary school students’ mental models of waves and particles using a short questionnaire. It was administered to a total of 147 students from two different groups. One group consisted of secondary school students prior to receiving formal education in introductory quantum mechanics while students from the other group had recently completed the Dutch national curriculum for pre-university education, which includes wave-particle duality. Our findings support the notion that students model classical particles and waves as mutually exclusive phenomena. Mental models of wave-particle duality, which require mixing the two classical models, appear to be only superficially developed. Our findings open avenues for future research on students’ mental models of waves and particles as basis for wave-particle duality.
Physics Kaleidoscope: From simple tools to inspirative physics education
Authors: Juhásová Antónia
Published: February 2025

It is a challenge to engage and develop the talents of lower secondary school students who have minimal knowledge of physics but are interested in why and how the world around them works. By making physical toys and conducting simple experiments with readily available materials, students are introduced to selected physical phenomena through play. In the physics club, we discuss physical principle and look for answers to curious questions. A great advantage for the pupils is that they can present their own toys and explain their physical nature to their parents and siblings. Every year, new exhibits are added to the physics club gallery, which motivates the followers. This paper is not a research study but has a focus as an innovative programme for motivating students to learn Physics.
Interdisciplinary Lesson Study in Italian High School focused on energy transformations
Authors: Giuseppina Adesso Maria , Capone Roberto , Fiore Oriana
Published: February 2025

This research focuses on the educational experiment of Interdisciplinary Lesson Study, carried out with 15-year-old students in Italy on the energy transformations. The teaching was carried out following the IBSE model of 5E and involving teachers from several disciplines. The theoretical lens used to read the data is the Lotman’s idea of Semiosphere revisited in the educational context. It seems that collaborative teaching processes make teachers aware that asymmetry between disciplines can be an engine of knowledge. Moreover, these processes can also improve teaching disciplinary actions.
School - University collaboration to train teachers on new topics and new tools in physics education
Authors: Serio Marina , Piccione Andrea , Marino Tommaso , Marocchi D , Alessandra Massa Anna , Rinaudo Marta , Luca Ruggiero Matteo , Scalzo Gabriele
Published: February 2025

In-service teacher training must ensure professional development based on both disciplinary and pedagogical research, taking advantage of collaboration between different training and institutional agencies. In this article we will talk about a collaborative experience among different training partners, to increase teachers’ interest in new tools and learning environments. We use different kinds of training sessions to introduce innovative didactic methodologies for teaching and learning involving both university research staff and secondary school teachers. The training project has planned a series of five meetings, divided into a seminar and a laboratorial part on the following topics: new didactic technologies, weather data processing, space missions, image processing, and modern physics. The laboratorial workshops were centered on applications that can be integrated into civic education and dual training. The meetings, followed by a hundred teachers, formed a design basis for the initial teacher training courses that will be activated from 2024 by the Italian Universities.
Using a Mn-incorporated FeOOH co-catalyst for improved water oxidation activity for BiVO4 photoelectrodes
Authors: Xue Kehui , Yu Lianqing
Published: February 2025

The commercial development of photoelectrochemical (PEC) devices for the conversion of solar power into sustainable fuels is contingent upon the development of efficacious photoelectrodes. However, sluggish surface water oxidation kinetics of BiVO4 constrained the overall PEC water splitting efficiencies. Herein, we reported a Mn-incorporated FeOOH co-catalyst loaded BiVO4 photoelectrode (Mn:FeOOH/BiVO4). The combination of Mn and FeOOH on BiVO4 can boost the carrier transfer efficiency. And it can also promote the interfacial reaction kinetics. A preeminent current density of 3.88 mA·cm−2 at 1.23 VRHE was recorded on Mn:FeOOH/BiVO4 composite photoanode. A ηsurface of 81.9% and a ηbulk of 77.3% are reached at 1.23 VRHE. This work can be an inspiration for the reasonable design of highly efficient photoelectrodes for the feasible harvesting of solar power.
Effect of Electrolyte on Carbon Dioxide Reduction of Silver Electrocatalyst
Authors: Chen Hongyu , Xing Zheyuan , Wang Zhaojie , Lu Xiaoqing , Wei Baojun
Published: February 2025

Large amounts of CO2 have disrupted the natural carbon cycle. CO2 reduction reaction (CO2RR) is an effective strategy to reduce high concentration of CO2. Currently, the design of cathode catalyst is widespread to promote CO2RR. However, the effect of electrolyte on the catalytic reaction is fuzzy. Hence, silver nanoparticles (Ag NPs) synthesized conveniently by a one-pot method was used to study the effects of different electrolytes on activity and selectivity in CO2RR. 0.1 M NaHCO3, KHCO3 and KCl as electrolytes were applied into CO2RR. Efficient CO2RR performances are exposed to three electrolytes. The results show that the 0.1 M KHCO3 is the optimal choice with the maximum catalytic activity and CO selectivity over 80%, which is better than many of the reports. Meanwhile, high concentration of KHCO3 enhances the activity but poisons the active site with the weaken selectivity. This research affords a direction for acquainting oneself with the electrolyte and CO2RR to exploit the new energy.
Spikes in UK wildfire emissions driven by peatland fires in dry years
Authors: Baker Sarah J , Perry Matthew C , Betts Richard A , Schoenecker Johanna , Pellegrini Adam F A
Published: February 2025

Wildfires on peatlands can nearly double global fire-driven carbon emissions, requiring centuries to re-sequester carbon (C) losses. Peatland fires require sufficiently hot, dry conditions and/or drainage for the peat to burn. Although these conditions have historically been infrequent, the warming and drying climate could increase the potential for wildfires and subsequent emissions. Here, we evaluate how climate change impacts peatland fire emissions by using the United Kingdom as a case study—where peatlands store an estimated 3.2 PgC. We use a fire emission model to quantify fire-driven C emissions using high-resolution land-surface data and fire-weather indices. Between 2001 and 2021, we estimate 0.8 TgC has been emitted from fires on peatlands, which can contribute up to 90% of total annual UK fire-driven C emissions. Consequently, protecting peatlands from fires in the UK would be a cost-effective way to slow climate change by avoiding future emissions. Peatland emissions spike during prominent dry years, implicating the inter-annual climate as a dominant driver of year-to-year variability. Integrating future climate projections suggests that a 2 °C global warming level could increase fire-driven C emissions in peatlands by over 60% solely via increased burn depths. Our findings are likely a bellwether for other temperate peatlands where climate change is leading to drier conditions, which increase burn depths and C emissions.
Research on the performance of the air processing system for commercial vehicles based on a multidimensional co-simulation
Authors: He Shuilong , Xiao Fei , Wang Jiahan , Tang Tao , Li Jun , Chen Chongshan
Published: February 2025

The air processing system plays a crucial role in the safe operation of vehicles. However, due to the complex spatial layout of the air processing system in commercial vehicles and the combined effects of its parameters, accurately characterizing and evaluating its performance remains highly challenging. This paper proposes a multidimensional co-simulation approach for the air processing system of commercial vehicles. Firstly, a three-dimensional (3D) pipe model is constructed to simulate the gas flow within the pipes of the air processing system. Secondly, a one-dimensional (1D) pipe model is established as a bridge for the multidimensional co-simulation. The 1D and 3D models can achieve strong coupling through data interaction. Subsequently, a co-simulation model of the complete air processing system is built. Finally, the co-simulation model is validated, and research and analysis are conducted on the factors affecting the performance of the air processing system in commercial vehicles based on the validated model. The validation results indicate that the co-simulation model exhibits high accuracy. Compared with the traditional 1D model, the co-simulation model not only has the similar fast-simulation capability but also reduces the error in temperature simulation by approximately 7%. The research findings show that increasing the inner diameter and length of the pipes can decrease the inlet temperature of the air processing unit, and increasing the pressure difference of unloading and regeneration control can enhance the system's regeneration rate. This study provides engineering reference value for enhancing the stability and safety of vehicle braking systems.
Retrieval Augmented Medical Diagnosis System
Authors: Johnson Ethan Thomas , Bande Jathin Koushal , Thomas Johnson
Published: February 2025

Subjective variability in human interpretation of diagnostic imaging presents significant clinical limitations, potentially resulting in diagnostic errors and increased healthcare costs. While artificial intelligence algorithms offer promising solutions to reduce interpreter subjectivity, they frequently demonstrate poor generalizability across different healthcare settings. To address these issues, we introduce Retrieval Augmented Medical Diagnosis System (RAMDS), which integrates an AI classification model with a similar image model. This approach retrieves historical cases and their diagnoses to provide context for the AI predictions. By weighing similar image diagnoses alongside AI predictions, RAMDS produces a final weighted prediction, aiding physicians in understanding the diagnosis process. Moreover, RAMDS does not require complete retraining when applied to new datasets; rather, it simply necessitates re-calibration of the weighing system. When RAMDS fine-tuned for negative predictive value was evaluated on breast ultrasounds for cancer classification, RAMDS improved sensitivity by 21% and negative predictive value by 9% compared to ResNet-34. Offering enhanced metrics, explainability, and adaptability, RAMDS represents a notable advancement in medical AI. RAMDS is a new approach in medical AI that has the potential for pan-pathological uses, though further research is needed to optimize its performance and integrate multimodal data.