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Ionizing radiation has the potential to cause operational disruptions and destroy microelectronic devices. This paper introduces and demonstrates a method of hardening microelectronic devices for sustained use in applications where exposure to ionizing radiation exists. By incorporating quantum structures below active regions of devices, gettering of charges created by ionizing radiation becomes possible. The gettering of electrons and holes forces recombination of carriers, thus eliminating photocurrent surges and trap filling which would otherwise disrupt device operation. Experimental results discussed here show a reduction in photocurrent of over two orders of magnitude when utilizing energy band engineering to create quantum structures for charge gettering. In this work, a nitride-based high electron mobility two-dimensional electron gas demonstrates the method. However, the theory utilized pertains not only to nitride-based devices, but transfers to other materials as well. [ABSTRACT FROM AUTHOR]

During the late 1960s, South Korean state engineers from construction agencies promoted large dam-building projects with the notion that their expertise would allow them to carve nature for the benefit of the nation. Hidden under this audacious declaration to manipulate nature was the precarious identitymaking of hydrological engineers from academia who contributed to rationalizing dam construction. This paper shows that the uncertain identity of hydrological engineers resonated with their position in a developing South Korea between the colonial legacy and the Cold War influx of Western knowledge. While working closely with state engineers, academic engineers had the distinct goal of establishing a unique Korean research program, overcoming both colonial river management and the Western methods on which it stood. This paper argues that carving nature ultimately concealed the haphazardness of the national water resources development plan as manifested in the tensions between state and academic engineers. [ABSTRACT FROM AUTHOR]

This paper, a first‐person account, describes a community psychology‐aligned intervention into a precalculus mathematics class at an Hispanic Serving Research Institution. The intervention was designed because the standard precalculus mathematics class had a high failure rate, especially for Latinx students, which was serving as a barrier for declaration of a Science, Technology, Engineering, or Mathematics major. The high failure rate indicates a structural problem that requires a structural intervention. The paper is coauthored with the teaching team, undergraduates who had taken the course, a graduate student who evaluated the class, and a community psychologist. We describe the ways that the new course, the College Math Academy, transformed the social environment through capacity building, providing access to valued resources for historically marginalized groups, facilitating opportunities to critique dominant power structures, prioritizing perspectives and experiences of people of color, and promoting understanding of how various social forces shape culture and values. The course also decentered white educational norms via adapting decoloniality and liberatory practices. In turn, each person describes their experience of the course. We draw on the first‐person accounts to show how they illustrate a transformative, decolonial, and liberatory social environment. We end with implications for how community psychologists can work in their universities to support structural change. Highlights: Changes to Precalculus class to better serve Latinx students.First person account of how structural course change shifted the classroom experience for students.Integration of a decolonial social enviornment intervention into a college math class. [ABSTRACT FROM AUTHOR]

At present, computer network technology is developing rapidly, and has been applied in many fields. Under this background, this paper analyzes the application of computer network technology in electronic information engineering, taking information warfare as an example. In this paper, the group decision algorithm was introduced into the fuzzy multi-objective decision algorithm, and the fuzzy multi-objective group decision algorithm was formed. The simulation showed that the fuzzy multi-objective group decision algorithm has the ability to deal with multi-ship and multi-target data. The sensitivity analysis algorithm of decision-making conclusion was given, and its algorithm was simulated. Through the data simulation and the sensitivity analysis of decision conclusion, it proved that the real time fuzzy multi-objective decision was feasible in theory. [ABSTRACT FROM AUTHOR]

Background: Digital‐first assessments leverage the affordances of technology in all elements of the assessment process: from design and development to score reporting and evaluation to create test taker‐centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and technologies of a test security framework (part of a larger ecosystem; Burstein et al., 2021) that can be used to create systems that protect the integrity of test scores. Methods: We use the Duolingo English Test to exemplify the processes and technologies that are presented. This includes methods for actively detecting and deterring malicious behaviour (e.g., a custom desktop app). It also includes methods for passively detecting and deterring malicious behaviour (e.g., a large item bank created through automatic generation methods). We describe the certification process that each test administration undergoes, which includes both automated and human review. Additionally, we describe our quality assurance dashboard which leverages psychometric data mining techniques to monitor test quality and inform decisions about item pool maintenance. Results and Conclusions: As assessment developers transition to online delivery and to a design approach that places the test taker at the centre, it becomes increasingly important to take advantage of the tools and methodological advances in different fields (e.g., engineering, machine learning, psychometrics). These tools and methods are essential to maintaining the security of assessments so that the score reliability is sustained and the interpretations and uses of test scores remain valid. Lay Description: What is known about this topic?: As more and more testing programmes transition to test taker‐centric administrations, effective measures to prevent cheating and protect content are critical to ensure the validity and integrity of scores.Two of the most common forms of cheating in online testing are (a) having someone other than the person who has registered take the test, and (b) stealing content and providing it to others to assist them in achieving a higher score. What does this paper add?: In designing a test taker‐centric digital‐first assessment, a test security framework must inform decisions from end‐to‐end (i.e., registration, onboarding, communications regarding test taker behaviours, test preparation and practice, test administration, and post‐administrative activities including scoring).Security is safeguarded through active and passive design methods; active methods include having test takers attest that they will follow the rules governing testing and informing them that they will be videoed during testing; passive methods include a computer adaptive design that limits item exposure and test overlap rates, development of a large item pool using automated item generation, and applying artificial intelligence to review test administration videos to flag unauthorized behaviours for human review. Implications: With more educational and assessment programmes transitioning to online digital models, the paper presents a comprehensive review of security issues and identifies an integrated approach for preventing cheating and other unauthorized behaviours. [ABSTRACT FROM AUTHOR]

Many subsurface engineering applications require accurate knowledge of the in-situ state of stress for their safe design and operation. Existing methods to meet this need primarily include field measurements for estimating one or more of the principal stresses from a borehole, or optimization methods for constructing a 3D geomechanical model in terms of geophysical measurements. These methods, however, often contain considerable uncertainty in estimating the state of stress. In this paper, we build on a Bayesian approach to quantify uncertainty in stress estimations for subsurface engineering applications. This approach can provide an estimate of the 3D distribution of stress throughout the volume of interest and provide an estimate of the uncertainty arising from the stress measurement, the rheology parameters, and a paucity of measurements. The value of this approach is demonstrated using stress measurements from the In Salah carbon storage site, which was one of the world's first industrial carbon capture and storage projects. This demonstration shows the application of this Bayesian approach for estimating the initial state of stress for In Salah and quantifying the uncertainty in the estimated stress. Also, an assessment of a maximum injection pressure to prevent geomechanical risks from CO2 injection pressures is provided in terms of the probability distribution of the minimum principal stress quantified by the approach. With the In Salah case study, this paper demonstrates that using the Bayesian approach can provide additional insights for site explorations and/or project operations to make informed-site decisions for subsurface engineering applications. Highlights: This study proposes a Bayesian approach to quantify uncertainty in estimates of initial 3D stress distributions arising from different sources. The approach provides the joint probability of the two horizontal principal stresses, instead of only the mean stress state of each. Adding regional geologic information and stress-related informative priors can reduce uncertainty in estimates of stress and modeling parameters. The approach helps make more reliable geomechanical decisions for subsurface engineering applications compared to a deterministic method. [ABSTRACT FROM AUTHOR]

In recent years significant progress has been made in structural application of glass elements in building industry. However, the issues related to computer modelling of glass panes, as well as analytical procedures allowing for taking into account the bonding action of PVB foil are not widely known in the engineering environment. In this paper results of numerical study of laminated glass plates are presented. The scope of the research covers over 40 cases of panes. Narrow (characterized by edge length ab > 2) and square (a/b = 1) panes made of two or three layer laminated glass have been taken into account. The paper deals mainly with point supported glass. However, selected results for linearly supported plates have been included as well for comparison. For each considered case an advanced computational model have been developed within the environment of Abaqus software. Pointwise supports have been modelled using methods of various complexity. The obtained results have been compared with the results of standard calculations using Wolfel-Bennison and Galuppi-Royer-Carfagni hypotheses. The analytical procedures proposed by CEN have been applied as well. As a result, recommendations for static calculations of laminated glass panes have been formulated. The computational procedure based on the hypothesis presented by L. Galuppi and G. Royer-Carfagni should be considered the most universal. The remaining methods may be applied only in limited scope. In order to estimate maximum principal stress in the support zone an advanced computer model has to be used. The support may be modelled in an exact or simplified manner. [ABSTRACT FROM AUTHOR]

Nature- and society-inspired metaheuristic algorithms have recently become the most promising technological model. To solve more complex optimization problems and complicated engineering applications, this paper proposes a new people duality psychological tendency and feedback mechanism-based Inherited Optimization Algorithm(IOA), which is inspired by people showing positive-negative duality cognitive tendency and adaptive feedback behavior when selecting information resources with different identity attributes. The IOA algorithm contains the symmetric two exploration phases. The exploitation phase adaptively regulates the dualistic psychological balance of people in inheriting the information resources with better existence value through a feedback regulation mechanism controlled by the profitability awareness to increase population diversity. This paper qualitatively and quantitatively evaluates the optimization performance of IOA on 84 benchmarks, including swarm convergence behavior, effectiveness, convergence, robustness, and significance. The scalability of the IOA is investigated using the CEC2017 suites. The algorithm performance in solving constrained optimization is verified on 8 engineering problems. All statistical results of the IOA are compared with the most promising 12 metaheuristics, which shows that the absolute computational efficiency of IOA on four types of functions is 95%, 96.67%, 80.95%, and 76.92%, respectively, the average rank (rank sum ratio) of IOA is 1.08 (1.19%) among the 13 algorithms, ranking first. The Wilcoxon signed rank test results on the CEC2017 suites show that IOA contains 1437 significance indicators out of 1440 comparisons, with the proportion of significant differences 99.79%, which suggests the proposed IOA maintains efficient search efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Main principles and methods for measuring acoustic cavitation are discussed. • Acoustic wave and system parameters affecting US process efficiency are discussed. • US for agri-food applications improved product quality and extraction efficiency. • US can be combined with conventional agri-food processes to improve operations. • Innovative designs for large-scale US assisted food processing are described. Acoustic cavitation, an intriguing phenomenon resulting from the interaction of sound waves with a liquid medium, has emerged as a promising avenue in agri-food processing, offering opportunities to enhance established processes improving primary production of ingredients and further food processing. This comprehensive review provides an in-depth analysis of the mechanisms, design considerations, challenges and scale-up strategies associated with acoustic cavitation for agri-food applications. The paper starts by elucidating the fundamental principles of acoustic cavitation and its measurement, delving then into the diverse effects of different parameters associated with, the acoustic wave, mechanical design and operation of the ultrasonic system, along with those related to the food matrix. The technological advancements achieved in the design and set-up of ultrasonic reactors addressing limitations during scale up are also discussed. The design, engineering and mathematical modelling of ultrasonic equipment tailored for agri-food applications are explored, along with strategies to maximize cavitation intensity and efficiency in the application of brining, freezing, drying, emulsification, filtration and extraction. Advanced US equipment, such as multi-transducers (tubular resonator, FLOW:WAVE®) and larger processing surface areas through innovative designing (Barbell horn, CascatrodesTM), are one of the most promising strategies to ensure consistency of US operations at industrial scale. This review paper aims to provide valuable insights into harnessing acoustic cavitation's potential for up-scaling applications in food processing via critical examination of current research and advancements, while identifying future directions and opportunities for further research and innovation. [ABSTRACT FROM AUTHOR]

There is a pressing requirement to design a simple battery thermal model that balances simulation accuracy regarding battery thermal characteristics and engineering application feasibility. The paper carries out the experimental study and model characterization of thermoelectric coupling characteristics of ternary lithium batteries with different shapes under ambient temperature conditions. The paper designs a characterization method of the battery thermoelectric coupling model. It conducts experiments to analyze the battery's charging and discharging characteristics and extracts essential modeling parameters. It reveals the differences in the modeling parameters of ternary lithium batteries with different shapes and constructs the thermoelectric coupling models of the square and 21700 cylindrical ternary lithium battery respectively. At the same time, the paper applies the model to carry out the simulation and experimental verification of the battery thermal behavior. The experimental data monitored by the infrared thermal imager and temperature sensors are compared with the simulation results. The errors are less than 5 %. It can provide a reference for related researches and engineering applications of battery thermal behavior and thermal management. • Designing a model characterization method for batteries with different shapes. • Revealing differences in modeling parameters of batteries with different shapes. • Constructing a simpler battery thermal model with low calculation volume. • Balancing the accuracy of simulation with the feasibility of applications. [ABSTRACT FROM AUTHOR]

This paper presents the design and construction of vacuum preloading incorporated with electroosmosis (VPE) engineering application for the treatment of soft soil on complex terrain for sluice foundation excavation in order to reduce the amount of cement used in construction. Monitoring was conducted during the VPE treatment and laboratory geotechnical tests were carried out once the treatment came to an end. Results show that the electrification mode has a significant influence on electric energy consumption. Stepped-up voltage helped in saving electric energy while electrode conversion consumed a lot of electric energy. The dispersion of soil parameters became larger after VPE treatment. The stability of physical parameters is better than the mechanical parameters, and the latter is better than the deformation parameters. Soil water content has a linear relationship with density and compression coefficient. The given linear fitting equations can help in simplifying the calculation and acquisition of these indexes. Although the mean values of the soil index parameters slightly improved, their coefficient of variation (COV) significantly increased. These locations with improved index parameters scattering in the construction site ensured that the subsequent construction tasks such as pit slope and excavation were successfully realized in this area. [ABSTRACT FROM AUTHOR]

Concrete infrastructure repair remains a formidable challenge. The application of engineering geopolymer composites (EGCs) as a repair material in the field of rapid structural repair can ensure the safety of structural facilities and prolong their service life. However, the interfacial bonding performance of existing concrete with EGCs is still unclear. The purpose of this paper is to explore a kind of EGC with good mechanical properties, and to evaluate the bonding performance of EGCs with existing concrete using a tensile bonding test and single shear bonding test. At the same time, X-ray diffraction (XRD) and Scanning electron microscopy (SEM) were adopted to study the microstructure. The results showed that the bond strength increased with the increase in interface roughness. For polyvinyl alcohol (PVA)-fiber-reinforced EGCs, the bond strength increased with the increase in FA content (0–40%). However, with the change of FA content (20–60%), the bond strength of polyethylene (PE) fiber-reinforced EGCs have little change. The bond strength of PVA-fiber-reinforced EGCs increased with the increase in water–binder ratio (0.30–0.34), while that of PE-fiber-reinforced EGCs decreased. The bond–slip model of EGCs with existing concrete was established based on the test results. XRD studies showed that when the FA content was 20–40%, the content of C-S-H gels was high and the reaction was sufficient. SEM studies showed that when the FA content was 20%, the PE fiber–matrix bonding was weakened to a certain extent, so the ductility of EGC was improved. Besides, with the increase in the water–binder ratio (0.30–0.34), the reaction products of the PE-fiber-reinforced EGC matrix gradually decreased. [ABSTRACT FROM AUTHOR]

The inherent weakly damped resonant modes of the piezoelectric nanopositioning platform and the presence of model uncertainty seriously affect the performance of the system. A structured H∞ design is used in this paper to solve the accuracy and robustness problems respectively using a two-loop control structure. The multiple performance requirements of the system are constituted into an H∞ optimization matrix containing multi-dimensional performance diagonal decoupling outputs, and an inner damping controller d is set according to the damping of the resonant modes; the second-order robust feedback controller is preset in the inner loop to improve the robustness of the system; the tracking controller is connected in series in the outer loop to achieve high accuracy scanning; finally, the structured H∞ controller is designed to meet the multiple performance requirements. To verify the effectiveness of the proposed structured H∞ control, simulation comparison experiments are done with the integral resonant control (IRC) and H∞ controller. The results demonstrate that the designed structured H∞ controller achieves higher tracking accuracy compared to the IRC and H∞ controllers under grating input signals of 5, 10, and 20 Hz. Moreover, it has good robustness under 600g and 1000g loads and high frequency disturbances close to the resonant frequency of the system, meeting multiple performance requirements. Compared with the traditional H∞ control, yet with lower complexity and transparency, which is more suitable for engineering practice applications. [ABSTRACT FROM AUTHOR]

The cutting process finite element simulation technology is a numerical method to simulate the cutting process, which can investigate various physical mechanisms caused by material removal during the cutting process. It has significant advantages in optimizing cutting parameters, improving machining quality, and reducing research costs. The significantly investigate objective is how to make the finite element simulation of cutting process more consistent with actual cutting process, so numerous research on finite element simulation technology for cutting has been carried out both domestically and internationally, and the relevant achievements have been applied in engineering. This paper provides an overview of the basic principles, advantages, and development trends of geometric simulation and physical simulation in cutting process finite element simulation. It systematically summarizes the development of constitutive models and mesh partitioning by domestic and foreign scholars to improve the accuracy and efficiency of cutting machining finite element simulation. On this foundation, the research progress of the combination of geometric and physical simulation methods is summarized. Finally, the important issues and future development trends of finite element simulation technology for cutting machining are envisioned. [ABSTRACT FROM AUTHOR]

Accelerating the charge transfer (CT) capability of photocatalysts is an efficient way to improve the overall photocatalytic performance, yet the precise regulation of CT in photocatalyst systems is still lacking. In this paper, a series of hybrid photocatalysts composed of graphitic carbon nitride (CN) and various viologens (V) were prepared for the photocatalytic hydrogen evolution (PHE) from water splitting under visible-light irradiation. Considering the fixed energy structure of CN , the different electron-withdrawing substituents were introduced to engineer the band structure of V delicately and modulate the CT process between CN and V. It was shown that all the hybrid photocatalysts CN-x%V y exhibited higher photocatalytic performance, of which CN–1%V 3 , possessing the strongest electron withdrawing group (-NO 2), demonstrated the best PHE performance (3572.3 μmol g−1 h−1), exceeding 29 times over the unmodified CN. It was proposed that the introduction of V can optimize the interfacial photogenerated electron transfer (CN → V →Pt) of the whole photocatalytic system effectively. We highlighted the V as an efficient chemical segment to modify semiconductors toward enhanced activity due to the following unique characteristics: (i) the unique redox ability, (ii) the easy synthetic methods for controlling the band structures precisely, and (iii) the inherent positively charged feature. This work provides a deep understanding of CT for the rational design of high-performance photocatalysts through band engineering. [Display omitted] • Hybrid photocatalysts CN-x%V y composed of g -C 3 N 4 (CN) and viologens (V) were prepared. • The photocatalytic performance of CN-x%V y catalysts was dependent on the band engineering of V. • Charge transfer of CN-x%V y catalysts was precisely regulated. • CN–1%V 3 exhibited a 29 times higher photocatalytic H 2 evolution rate than the unmodified CN. [ABSTRACT FROM AUTHOR]

Probing the stress state using a high density of measurement points is time intensive and presents a limitation for what is experimentally feasible. Alternatively, individual strain fields used for determining stresses can be reconstructed from a subset of points using a Gaussian process regression (GPR). Results presented in this paper evidence that determining stresses from reconstructed strain fields is a viable approach for reducing the number of measurements needed to fully sample a component's stress state. The approach was demonstrated by reconstructing the stress fields in wire-arc additively manufactured walls fabricated using either a mild steel or low-temperature transition feedstock. Effects of errors in individual GP reconstructed strain maps and how these errors propagate to the final stress maps were assessed. Implications of the initial sampling approach and how localized strains affect convergence are explored to give guidance on how best to implement a dynamic sampling experiment. [ABSTRACT FROM AUTHOR]

Locomotion prediction for human welfare has gained tremendous interest in the past few years. Multimodal locomotion prediction is composed of small activities of daily living and an efficient approach to providing support for healthcare, but the complexities of motion signals along with video processing make it challenging for researchers in terms of achieving a good accuracy rate. The multimodal internet of things (IoT)-based locomotion classification has helped in solving these challenges. In this paper, we proposed a novel multimodal IoT-based locomotion classification technique using three benchmarked datasets. These datasets contain at least three types of data, such as data from physical motion, ambient, and vision-based sensors. The raw data has been filtered through different techniques for each sensor type. Then, the ambient and physical motion-based sensor data have been windowed, and a skeleton model has been retrieved from the vision-based data. Further, the features have been extracted and optimized using state-of-the-art methodologies. Lastly, experiments performed verified that the proposed locomotion classification system is superior when compared to other conventional approaches, particularly when considering multimodal data. The novel multimodal IoT-based locomotion classification system has achieved an accuracy rate of 87.67% and 86.71% over the HWU-USP and Opportunity++ datasets, respectively. The mean accuracy rate of 87.0% is higher than the traditional methods proposed in the literature. [ABSTRACT FROM AUTHOR]

To ensure that large precision instruments and equipment are in the best working condition, it is necessary to provide a suitable working environment for them. At this time, there is a high requirement for the vibration of the foundation at the location. Measuring the foundation vibration parameters, analyzing the foundation vibration state, and taking necessary damping measures during the construction process to provide basis are the premise of equipment installation and normal work. Combined with an application example, this paper briefly introduces the general situation of a project blasting, and obtains the basic characteristic parameters such as the peak velocity of ground motion and the time of arrival during the blasting operation; Based on the basic principle of regression analysis, the relationship between the peak velocity and the distance between the detonation centers and the charge weight is obtained by fitting the Sadovsky formula. [ABSTRACT FROM AUTHOR]

Accommodation cabin is a living place for operators, and it should play a role in alleviating the fatigue and stress. This paper focuses on the problem of monotony and lack of emotional care in the design of accommodation, and develops a design system to meet the emotional needs of operators based on Kansei Engineering. First, the key design elements affecting emotional comfort are extracted and the virtual reality experimental platform is established. Second, the affective factors are extracted, constituting the semantic space. Third, the mapping relationship between affective factors and design elements is established. Finally, the design system of accommodation cabin based on the emotional needs is developed. The system can output and evaluate the design scheme through virtual reality technology, so it makes the design process more intuitive and efficient. It has a certain reference value for improving the comfort experience of operators and the design level of accommodation cabin. [ABSTRACT FROM AUTHOR]

Practical engineering problems are often involved multiple computationally expensive objectives. A promising strategy to alleviate the computational cost is the variable-fidelity metamodel-based multi-objective Bayesian optimization approach. However, the existing approaches are under the assumption of independent correlations across the multiple objectives by constructing a variable-fidelity metamodel for each objective, which may lose some useful information in a way. To facilitate the usage of the variable-fidelity metamodel-based multi-objective Bayesian optimization approach, a multi-objective Bayesian optimization approach based on variable-fidelity multi-output (VFMO) metamodeling is proposed in this paper. A variable-fidelity multi-output metamodeling approach is developed to model the multiple objectives jointly, which can capture the latent correlations across the multiple objectives and further enhance the optimization. Furthermore, a weighted expected hypervolume improvement acquisition function based on the VFMO metamodeling approach (VFMO-WEHVI) is proposed for multi-objective optimization. The weight coefficients are adaptively determined according to the information from the current metamodel, which allows a better tradeoff between global exploration and local exploitation. Moreover, the probability of feasibility is introduced to deal with multi-objective optimization problems with constraints. The effectiveness of the proposed approach is demonstrated using five analytical benchmark examples and the multi-objective optimization of a metamaterial vibration isolator. Results indicate that the proposed VFMO-WEHVI approach has the best overall performance compared with the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Metaheuristic algorithms have been widely studied and shown to be suitable for solving various engineering optimization problems. This paper presents a novel variant of the whale optimization algorithm known as multi-cohort whale optimization algorithm to solve engineering optimization problems. The new algorithm improves the existing whale optimization by dividing the population in to cohorts and introduces a separate exploration procedure for each cohort. Also, a new boundary update procedure for the search space is introduced. In addition to this, opposition-based initialization and elitism are employed to aid quick convergence of the algorithm. The proposed algorithm is compared with whale optimization algorithm variants and other metaheuristic algorithms for different numerical optimization problems. Statistical analysis is performed to ensure the significance of the proposed algorithm. In addition to this, the proposed and existing algorithms are studied based on three engineering optimization problems. The analyses show that the proposed algorithm achieves 53.75% improvement in average fitness when compared to the original whale optimization algorithm. [ABSTRACT FROM AUTHOR]

The analysis of cumulative fatigue damage is an important factor in predicting the life of composite elements and structures that are exposed to field load histories. A method for predicting the fatigue life of composite laminates under varying loads is suggested in this paper. A new theory of cumulative fatigue damage is introduced grounded on the Continuum Damage Mechanics approach that links the damage rate to cyclic loading through the damage function. A new damage function is examined with respect to hyperbolic isodamage curves and remaining life characteristics. The nonlinear damage accumulation rule that is presented in this study utilizes only one material property and overcomes the limitations of other rules while maintaining implementation simplicity. The benefits of the proposed model and its correlation with other relevant techniques are demonstrated, and a broad range of independent fatigue data from the literature is used for comparison to investigate its performance and validate its reliability. [ABSTRACT FROM AUTHOR]

Antennas with broadband radiation and small-size are highly required in wireless communication system. The trade-off relation between bandwidth and size became a difficulty when it comes to miniaturized antenna design. A method of realizing antenna miniaturization and bandwidth enhancement at the same time is needed. Monopole antennas are the most common used one in the devices of Internet of Things, Internet of Vehicles, and wireless access points et al. In this paper, a wideband low-profile top-loaded patch monopole antenna based on surface current engineering is proposed. The topology combines a center-fed circular patch with inductive vias. The patch is designed with patterns, which consists of four concentric annular rings and some strips in radial direction. In this way, three resonances are generated, and the pattern is optimized to bring three resonances close to each other. The number of the strips is specially designed to bring three resonances close to each other. By loading the inductive vias on the outermost rings, connecting to the ground, the resonance at low frequencies can be enhanced, as a consequence of the optimized impedance matching. The field distribution is analyzed to verify the operation principle. A prototype is fabricated, and the measured results agree well with the simulated ones. The relative −10 dB bandwidth is 69% and the omnidirectional radiation pattern is stable in the operating band. The antenna achieves a rather wideband radiation while maintaining a low profile. The method of antenna miniaturization and bandwidth enhancement based on surface current engineering paves the way for antenna design in low-profile ultra-wideband applications. [ABSTRACT FROM AUTHOR]

For engineering applications, an innovative design can be developed by reusing and modifying existing models with similar features and manufacturing properties, and accurately searching CAD models has become a valuable knowledge acquisition technique in product design. Although there are many retrieval technologies, most methods focus on the global shape of models. In this paper, a CAD model retrieval framework based on local feature segmentation is proposed, offering users a free-form way to choose any subpart as a query from a given model. First, a novel model segmentation method based on the vertex-neighbor extension is proposed to divide a target CAD model into overlapping local features. The chosen subpart with arbitrary boundaries is also successfully described for retrieval by combining local features. Then, a composite descriptor considering both shapes and attribute characteristics is established, which is proved effective for distinguishing local features. Finally, the problem of matching free-form queries to CAD models in the dataset is transformed into descriptor set measurement and is implemented using the bag-of-word algorithm. The proposed model retrieval approach outperforms many existing approaches in matching performance and provides a user-friendly query mode. [Display omitted] • Solve the partial CAD models retrieval (B-rep) to support engineering reuse. • Introduce a innovative model segmentation method to generate local features. • Apply the bag-of-word algorithm to measure the similarity. • Allow arbitrary queries acquiring from free-form interaction with the CAD system. [ABSTRACT FROM AUTHOR]

Background: The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives: This study explores computer and software engineering students' learning practices, wherein online platforms are used as resources for both curricular learning activities and students' interest‐driven learning. Methods: The learning practices of 73 students were examined using a mixed‐methods design and a conceptualization of practices accounting for the context and purpose of their enactment. The dataset includes students' self‐reports on domain‐specific learning activities, three‐month‐long web‐browsing history of multiple platforms and stimulated‐recall interviews. The data were analysed through latent class and thematic analyses. Results and Conclusion: Five distinct patterns were found in the use of online platforms. These patterns show that different types of platforms were used purposely and in combination during curricular and interest‐driven activities aimed at learning software development. Moreover, students' purposes were driven by both the need to progress in their learning activities and the development of their interest in software development. The findings highlight the complexity of students' learning with online platforms, which develop quite extensively beyond curricular boundaries. Implications: The findings stress the need to recognize that undergraduate students' learning practices involve multiple online platforms and activities beyond the formal curriculum and that these play a key role in developing students' interests in learning software development. Moreover, our findings indicate the importance of taking into account the way students' learning practices unfold within platforms and how these relate to domain‐specific practices. Lay Description: What is already known about this topic?: Online platforms are mostly used by teaching staff in undergraduate education to support student learning during formal curricular tasks.Research knowledge is limited mostly to specific features of social networking platforms, such as Facebook Groups or instant messaging technologies.Students informally use interest‐driven activities and both social and domain‐specific platforms to support their learning.Research on students' interest in using massive open online courses suggested that students' learning is motivated by academic success, prospective economic opportunities, and personal interests. What this paper adds?: Students combine various types of online platforms purposely (e.g., search engines or Q&A sites), many of which are domain‐specific (e.g., Stack Overflow).Students use online platforms informally during work on curricular tasks to, for example, collaborate, solve problems, and understand concepts or methods.Domain‐specific (e.g., software engineering) platforms are used during other study‐related leisure and entrepreneurial activities.Online platforms play a key role in how students develop their interests in learning. Through them, students connect not only with other students but also with professionals, companies, and information about them. Implications of study findings for practitioners: Curriculum developers and faculty should consider preparing students to use disparate types of online platforms beyond what is included in the curriculum.Curriculum developers should also consider other activities beyond the classroom that are study‐related and meaningful for students and their learning. [ABSTRACT FROM AUTHOR]

CO2 geological storage projects are an essential tool for China to achieve the double carbon target of energy savings and emission reductions. In order to safely and effectively control the implementation of injection projects and monitor the dynamics of CO2 injection, multi-dimensional and multi-disciplinary monitoring tools are required. Among them, microseismic monitoring is a key technology for predicting reservoir dynamics and reflecting reservoir geomechanical behavior. Such monitoring has been carried out previously for reservoirs in other countries, but experimental projects are also gradually being developed in China. In this paper, we focus on the research and analysis results of microseismic monitoring of carbon storage projects in various work areas. For different reservoir conditions, we explore combinations of the monitoring implementation methods in China, comparing the differences in each work area. We propose a joint well and ground microseismic monitoring method and a multi-spatial and multi-physical field coupling research system for use in the implementation of domestic demo projects for the future research and development of microseismic monitoring of carbon storage projects. The monitoring program can meet the requirements for certain periodic repeated or continuous observations and can intelligently assess the risk and handle the alert behavior. The foundation is laid for the development of the future microseismic monitoring technology to achieve the goal of developing cost-controllable, permanent, and real-time monitoring equipment. The application of the monitoring system in China has been effective, and this experience can contribute to the development of injection engineering in the future. [ABSTRACT FROM AUTHOR]

This paper draws on data from the National Science Foundation (NSF) ADVANCE-funded LATTICE program (Launching Academics on the Tenure-Track: an Intentional Community in Engineering) to examine how a diverse group of women worked across social and professional identities to support early-career women in academic engineering. We used ethnography to elucidate the social dynamics and power relations involved in forming a coherent group identity for the LATTICE leadership team, and the boundaries we negotiated in running the LATTICE program. We identify the processes and behaviors through which we made boundaries between members salient yet porous to build a coherent community across various dimensions of difference. We offer three actionable strategies that impact change agents' engagement and the group's coherence across multiple dimensions of difference: (1) intentionally creating a socio-emotional culture in our group, one that spans across group members' personal and professional identities; (2) validating other group members' perspectives, and (3) striving to build consensus using storytelling. These strategies of the LATTICE leadership team provide guidelines for others who work across intersecting dimensions of difference. [ABSTRACT FROM AUTHOR]

RAPOC (Rosseland and Planck Opacity Converter) is a Python 3 code that calculates Rosseland and Planck mean opacities (RPMs) from wavelength-dependent opacities for a given temperature, pressure, and wavelength range. In addition to being user-friendly and rapid, RAPOC can interpolate between discrete data points, making it flexible and widely applicable to the astrophysical and Earth-sciences fields, as well as in engineering. RAPOC uses ExoMol, DACE, or any user defined input data, provided that it is in a readable format. In this paper, we present the RAPOC code and compare its calculated Rosseland and Planck mean opacities with other values in the literature. RAPOC is open-source and available on Pypi and GitHub. [ABSTRACT FROM AUTHOR]

This article aims to expand our knowledge on interdisciplinary design education by focusing on team development, which has remained a less explored aspect of interdisciplinary collaboration so far. An interdisciplinary design studio course, Collaborative Design, for food engineering and industrial design students in higher education provides the research context. The empirical basis of the paper comes from interviews with students on their experiences of interdisciplinary collaboration in the course, and the educator's observation notes. Drawing on these data, this article critically reflects on how and to what extent the teaching materials, methods and strategies incorporated into the course design guided and supported students' transition through the four stages of becoming a performing interdisciplinary team. The article concludes with four suggestions for design educators. First, encountering new ways of thinking, talking and doing that make sense for both disciplines engages students in interdisciplinary collaboration. Second, humour and positive social relations play an important role in team success in all stages of team development. Third, using the first weeks of the course to reveal the disciplinary differences and potential issues that would lead to conflicts through class discussions and warm-up activities facilitates a smooth transition from forming to norming. Fourth, adequate representation of each discipline should be ensured both in the design problem and solution, and among the tutors. [ABSTRACT FROM AUTHOR]