The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this "digital thread" has the potential to drive innovation, the fragmented and inaccessible nature of existing datasets hinders method validation, limits reproducibility, and slows research progress. Unlike fields such as computer vision and natural language processing, which benefit from established benchmark ecosystems, engineering design research often relies on small, proprietary, or ad-hoc datasets. This paper addresses this challenge by proposing a systematic framework for a "Map of Datasets in EDSE." The framework is built upon a multi-dimensional taxonomy designed to classify engineering datasets by domain, lifecycle stage, data type, and format, enabling faceted discovery. An architecture for an interactive discovery tool is detailed and demonstrated through a working prototype, employing a knowledge graph data model to capture rich semantic relationships between datasets, tools, and publications. An analysis of the current data landscape reveals underrepresented areas ("data deserts") in early-stage design and system architecture, as well as relatively well-represented areas ("data oases") in predictive maintenance and autonomous systems. The paper identifies key challenges in curation and sustainability and proposes mitigation strategies, laying the groundwork for a dynamic, community-driven resource to accelerate data-centric engineering research.
Cultured meat is emerging as a sustainable alternative to conventional animal agriculture, with scaffolds playing a central role in supporting cellular attachment, growth, and tissue maturation. This review focuses on the development of gel-based hybrid biomaterials that meet the dual requirements of biocompatibility and food safety. We explore recent advances in the use of naturally derived gel-forming polymers such as gelatin, chitosan, cellulose, alginate, and plant-based proteins as the structural backbone for edible scaffolds. Particular attention is given to the integration of food-grade functional additives into hydrogel-based scaffolds. These include nanocellulose, dietary fibers, modified starches, polyphenols, and enzymatic crosslinkers such as transglutaminase, which enhance mechanical stability, rheological properties, and cell-guidance capabilities. Rather than focusing on fabrication methods or individual case studies, this review emphasizes the material-centric design strategies for building scalable, printable, and digestible gel scaffolds suitable for cultured meat production. By systemically evaluating the role of each component in structural reinforcement and biological interaction, this work provides a comprehensive frame work for designing next-generation edible scaffold systems. Nonetheless, the field continues to face challenges, including structural optimization, regulatory validation, and scale-up, which are critical for future implementation. Ultimately, hybrid gel-based scaffolds are positioned as a foundational technology for advancing the functionality, manufacturability, and consumer readiness of cultured meat products, distinguishing this work from previous reviews. Unlike previous reviews that have focused primarily on fabrication techniques or tissue engineering applications, this review provides a uniquely food-centric perspective by systematically evaluating the compositional design of hybrid hydrogel-based scaffolds with edibility, scalability, and consumer acceptance in mind. Through a comparative analysis of food-safe additives and naturally derived biopolymers, this review establishes a framework that bridges biomaterials science and food engineering to advance the practical realization of cultured meat products.
Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service availability. The development of conversational agents utilizing artificial intelligence (AI) techniques represents a significant advancement in Natural Language Processing (NLP). Numerous studies employ deep learning and NLP methodologies to construct sophisticated conversational agent systems. Additionally, developers and companies often utilize APIs provided by intent recognition services like Dialogflow and Amazon Lex to easily create conversational agents using graphical forms, which enhance conversational agent functionality. However, these APIs have limitations, such as potential dependency on specific NLP service providers and associated high costs. Besides, the lack of a specialized conversational agent development platform for the tourism domain poses a considerable challenge. To address these limitations, this work tackles critical gaps in conversational agent development tools by constructing a graphical Domain-Specific Language (DSL) and code generation templates for accelerating the development of conversational agents tailored to smart tourism’s needs. First, we provide a designed metamodel to define the abstract syntax of a DSL. Second, we implement the metamodel using the Eclipse Modeling Framework. Third, we develop a graphical interface that incorporates intuitive icons to simplify the creation of conversational agent models. Fourth, we define code generation templates to translate the graphical models into executable agent source code. Finally, we validate the proposed approach to demonstrate its effectiveness and applicability in real-world scenarios, reducing development time and avoiding the costs associated with NLP services.
Alexandros Gazis, Ioannis Papadongonas, Athanasios Andriopoulos
et al.
This article provides a comprehensive overview of sensors commonly used in low-cost, low-power systems, focusing on key concepts such as Internet of Things (IoT), Big Data, and smart sensor technologies. It outlines the evolving roles of sensors, emphasizing their characteristics, technological advancements, and the transition toward "smart sensors" with integrated processing capabilities. The article also explores the growing importance of mini-computing devices in educational environments. These devices provide cost-effective and energy-efficient solutions for system monitoring, prototype validation, and real-world application development. By interfacing with wireless sensor networks and IoT systems, mini-computers enable students and researchers to design, test, and deploy sensor-based systems with minimal resource requirements. Furthermore, this article examines the most widely used sensors, detailing their properties and modes of operation to help readers understand how sensor systems function. The aim of this study is to provide an overview of the most suitable sensors for various applications by explaining their uses and operations in simple terms. This clarity will assist researchers in selecting the appropriate sensors for educational and research purposes or understanding why specific sensors were chosen, along with their capabilities and possible limitations. Ultimately, this research seeks to equip future engineers with the knowledge and tools needed to integrate cutting-edge sensor networks, IoT, and Big Data technologies into scalable, real-world solutions.
Hashini Gunatilake, John Grundy, Rashina Hoda
et al.
Empathy, defined as the ability to understand and share others' perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.
Harsh Abhinandan, Aditya Dhanraj, Aryan Katoch
et al.
Unmanned Aerial Vehicles (UAVs) or drones have witnessed a spectacular surge in applications for military, commercial, and civilian purposes. However, their potential for flight is always limited by the finite power budget of their onboard power supplies. The limited flight time problem has led to intensive research into new sources of power and innovative charging strategies to enable protracted, autonomous flight. This paper gives a comparative summary of the current state-of-the-art in UAV power and refuelling technology. The paper begins with an analysis of the variety of energy sources, from classical batteries to fuel cells and hybrid systems, based on their relative advantages and disadvantages in energy density, weight, and safety. Subsequently, the review explores a spectrum of replenishment options, from simple manual battery swapping to sophisticated high-tech automatic docking stations and smart contact-based charging pads. Most of the review is dedicated to the newer technology of wireless power transfer, which involves near-field (inductive, capacitive) and far-field (laser, microwave) technology. The article also delves into the most important power electronic converter topologies, battery management systems, and control approaches that form the core of these charging systems. Finally, it recapitulates the most significant challenges in technical, economic, and social aspects for promising avenues of future research. The comprehensive review is a valuable guide for researchers, engineers, and policymakers striving to enhance UAV operational performance.
Diana Robinson, Christian Cabrera, Andrew D. Gordon
et al.
What if end users could own the software development lifecycle from conception to deployment using only requirements expressed in language, images, video or audio? We explore this idea, building on the capabilities that generative Artificial Intelligence brings to software generation and maintenance techniques. How could designing software in this way better serve end users? What are the implications of this process for the future of end-user software engineering and the software development lifecycle? We discuss the research needed to bridge the gap between where we are today and these imagined systems of the future.
Shivani Nanda, Marc‐Antoine Jacques, Wen Wang
et al.
Abstract Metabolism is controlled to ensure organismal development and homeostasis. Several mechanisms regulate metabolism, including allosteric control and transcriptional regulation of metabolic enzymes and transporters. So far, metabolism regulation has mostly been described for individual genes and pathways, and the extent of transcriptional regulation of the entire metabolic network remains largely unknown. Here, we find that three‐quarters of all metabolic genes are transcriptionally regulated in the nematode Caenorhabditis elegans. We find that many annotated metabolic pathways are coexpressed, and we use gene expression data and the iCEL1314 metabolic network model to define coregulated subpathways in an unbiased manner. Using a large gene expression compendium, we determine the conditions where subpathways exhibit strong coexpression. Finally, we develop “WormClust,” a web application that enables a gene‐by‐gene query of genes to view their association with metabolic (sub)‐pathways. Overall, this study sheds light on the ubiquity of transcriptional regulation of metabolism and provides a blueprint for similar studies in other organisms, including humans.
Renewable energy resources require energy storage techniques to curb problems with intermittency. One potential solution is the use of phase change materials (PCMs) in latent heat thermal energy storage (LHTES) systems. Despite the high energy storage density of PCMs, their thermal response rate is restricted by low thermal conductivity. The topic of heat transfer enhancement techniques for increasing thermal performance of LHTES systems has mainly focused on passive heat transfer enhancement techniques with less attention towards active methods. Active heat transfer enhancement techniques require external power supplied to the system. In this paper, recent advances in active heat transfer enhancement techniques within LHTES systems are reviewed, including mechanical aids, vibration, jet impingement, injection, and external fields. The pertinent findings related to the field are summarized in relation to the charging and discharging processes of PCMs. Suggestions for future research are proposed, and the importance of additional energy input for storage is discussed.
Christian Fiedler, Michael Herty, Sebastian Trimpe
Mean field limits are an important tool in the context of large-scale dynamical systems, in particular, when studying multiagent and interacting particle systems. While the continuous-time theory is well-developed, few works have considered mean field limits for deterministic discrete-time systems, which are relevant for the analysis and control of large-scale discrete-time multiagent system. We prove existence results for the mean field limit of very general discrete-time control systems, for which we utilize kernel mean embeddings. These results are then applied in a typical optimal control setup, where we establish the mean field limit of the relaxed dynamic programming principle. Our results can serve as a rigorous foundation for many applications of mean field approaches for discrete-time dynamical systems.
Noise radars, as well as certain types of quantum radar, can be understood in terms of a correlation coefficient which characterizes their detection performance. Although most results in the noise radar literature are stated in terms of the signal-to-noise ratio (SNR), we show that it is possible to carry out performance prediction in terms of the correlation coefficient. To this end, we derive the range dependence of the correlation coefficient under the assumption that all external noise is additive white Gaussian noise. We then combine our result with a previously-derived expression for the receiver operating characteristic (ROC) curve of a coherent noise radar, showing that we can obtain ROC curves for varying ranges. A comparison with corresponding results for a conventional radar employing coherent integration shows that our results are sensible. The aim of our work is to show that the correlation coefficient is a viable adjunct to SNR in understanding noise radar performance.
Stephanie O. Sangalang, Allen Lemuel G. Lemence, Zheina J. Ottong
et al.
Abstract Background The impacts of multicomponent school water, sanitation, and hygiene (WaSH) interventions on children’s health are unclear. We conducted a cluster-randomized controlled trial to test the effects of a school WaSH intervention on children’s malnutrition, dehydration, health literacy (HL), and handwashing (HW) in Metro Manila, Philippines. Methods The trial lasted from June 2017 to March 2018 and included children, in grades 5, 6, 7, and 10, from 15 schools. At baseline 756 children were enrolled. Seventy-eight children in two clusters were purposively assigned to the control group (CG); 13 clusters were randomly assigned to one of three intervention groups: low-intensity health education (LIHE; two schools, n = 116 children), medium-intensity health education (MIHE; seven schools, n = 356 children), and high-intensity health education (HIHE; four schools, n = 206 children). The intervention consisted of health education (HE), WaSH policy workshops, provision of hygiene supplies, and WaSH facilities repairs. Outcomes were: height-for-age and body mass index-for-age Z scores (HAZ, BAZ); stunting, undernutrition, overnutrition, dehydration prevalence; HL and HW scores. We used anthropometry to measure children’s physical growth, urine test strips to measure dehydration, questionnaires to measure HL, and observation to measure HW practice. The same measurements were used during baseline and endline. We used multilevel mixed-effects logistic and linear regression models to assess intervention effects. Results None of the interventions reduced undernutrition prevalence or improved HAZ, BAZ, or overall HL scores. Low-intensity HE reduced stunting (adjusted odds ratio [aOR] 0.95; 95% CI 0.93 to 0.96), while low- (aOR 0.57; 95% CI 0.34 to 0.96) and high-intensity HE (aOR 0.63; 95% CI 0.42 to 0.93) reduced overnutrition. Medium- (adjusted incidence rate ratio [aIRR] 0.02; 95% CI 0.01 to 0.04) and high-intensity HE (aIRR 0.01; 95% CI 0.00 to 0.16) reduced severe dehydration. Medium- (aOR 3.18; 95% CI 1.34 to 7.55) and high-intensity HE (aOR 3.89; 95% CI 3.74 to 4.05) increased observed HW after using the toilet/urinal. Conclusion Increasing the intensity of HE reduced prevalence of stunting, overnutrition, and severe dehydration and increased prevalence of observed HW. Data may be relevant for school WaSH interventions in the Global South. Interventions may have been more effective if adherence was higher, exposure to interventions longer, parents/caregivers were more involved, or household WaSH was addressed. Trial registration number DRKS00021623.
The green technology innovation system is a fundamental method for China to achieve its goals of carbon peak and carbon neutrality. Clarifying the relationship between two-way foreign direct investment (FDI) synergy and regional green technology innovation is key to the green transformation and sustainable development of regional innovation systems. Based on panel data from 30 provinces in China from 2009 to 2020, a threshold-panel-regression technique is used. Command-controlled environmental regulation (CER), market-incentive environmental regulation (MER), and public-participation environmental regulation (PER) are taken as threshold variables, and the threshold effect of two-way FDI synergy on regional green technology innovation under heterogeneous environmental regulation is empirically explored. The results show the following. (i) The effects of two-way FDI synergy on regional green technology innovation exhibit significant threshold characteristics with heterogeneous environmental regulation as a double threshold. (ii) As the threshold values of CER and PER increase, the promoting effect of two-way FDI synergy on regional green technology innovation first increases and then decreases. (iii) As the MER threshold value increases, the promoting effect of two-way FDI synergy on regional green technology innovation continues to increase. (iv) Under the medium-threshold condition of PER, the promoting effect of two-way FDI synergy reaches its greatest value. (v) The intensity of intellectual property protection, the number of regional innovation institutions, and the level of transportation infrastructure all have significant positive effects on regional green technology innovation, and the number of regional innovation institutions exhibits the greatest promoting effect. This study provides new insights into two-way FDI synergy and methods to promote green technology innovation, and these findings can help the government formulate future policies and strategies to promote regional green technology innovation.
Ion Sococol, Petru Mihai, Tudor-Cristian Petrescu
et al.
In the first part of the current study, the effectiveness of the transversal cross-section reduction method for RC beams in marginal areas (by means of mechanical drilling) was validated. The said method “encourages” the formation of plastic hinges at the beam ends and, at the same time, allows for taking into account the bending stiffness of RC slabs, which is exerted upon the RC beams. In these conditions, the second part of the current research study (i.e., the current manuscript) highlights the real mode of reducing the lateral stiffness of the slabs upon the RC beams. These elements form a common body, together with the beam–column frame node. The same method as in the first part of the study—“weakening” the plates in the corner area through vertical drilling, without affecting the integrity of the reinforcing elements—was used. The analytical MR RC frame model, studied by means of the comparative method, highlights the efficiency of the transversal cross-section reduction method for RC slabs. Basically, the directing of the plastic deformations from the weakened slab areas towards the marginal areas of the reinforced concrete beams takes place. The beams rotate as far as the weakened slab areas allow its plastic deformation, thus being possible to observe the partial conservation effect of the beam–column frame joint. Furthermore, for the analytical model with the maximum number of vertical holes in the corner areas of the concrete plate, minimal plastic deformations are recorded for the marginal areas of the concrete columns. A partial conservation of the formation mechanism of the “beam-slab-frame node” common rigid block is also noted. Consequently, the dissipation of the seismic energy is made in a partially controlled and directed manner, in the “desired” areas, according to the “Strong Columns—Weak Beams” (SCWB) ductile mechanism of the lateral behavior to seismic actions for reinforced concrete frame structures. The mechanism is specified in current design norms for RC frame systems. The effectiveness of the method for reducing the transversal section of the RC plates in the corner areas by means of transversal drilling is highlighted and validated from the perspective of the local and global ductile seismic response of reinforced concrete frame structures. A significant reduction in the bending stiffness of the slabs upon the beams and a real development of the plastic hinges in the marginal areas of the beams (together with partial implications and plastic deformations) were observed.
We aim to analyze the behaviour of a finite-time stochastic system, whose model is not available, in the context of more rare and harmful outcomes. Standard estimators are not effective in making predictions about such outcomes due to their rarity. Instead, we use Extreme Value Theory (EVT), the theory of the long-term behaviour of normalized maxima of random variables. We quantify risk using the upper-semideviation $ρ(Y) = E(\max\{Y - μ,0\})$ of an integrable random variable $Y$ with mean $μ= E(Y)$. $ρ(Y)$ is the risk-aware part of the common mean-upper-semideviation functional $μ+ λρ(Y)$ with $λ\in [0,1]$. To assess more rare and harmful outcomes, we propose an EVT-based estimator for $ρ(Y)$ in a given fraction of the worst cases. We show that our estimator enjoys a closed-form representation in terms of the popular conditional value-at-risk functional. In experiments, we illustrate the extrapolation power of our estimator using a small number of i.i.d. samples ($<$50). Our approach is useful for estimating the risk of finite-time systems when models are inaccessible and data collection is expensive. The numerical complexity does not grow with the size of the state space.
By seamlessly integrating everyday objects and by changing the way we interact with our surroundings, Internet of Things (IoT) is drastically improving the life quality of households and enhancing the productivity of businesses. Given the unique IoT characteristics, IoT applications have emerged distinctively from the mainstream application types. Inspired by the outlook of a programmable world, we further foresee an IoT-native trend in designing, developing, deploying, and maintaining software systems. However, although the challenges of IoT software projects are frequently discussed, addressing those challenges are still in the "crossing the chasm" period. By participating in a few various IoT projects, we gradually distilled three fundamental principles for engineering IoT-native software systems, such as just enough, just in time, and just for "me". These principles target the challenges that are associated with the most typical features of IoT environments, ranging from resource limits to technology heterogeneity of IoT devices. We expect this research to trigger dedicated efforts, techniques and theories for the topic IoT-native software engineering.
Intrauterine adhesions (IUAs) refer to the repair disorder after endometrial injury and may lead to uterine infertility, recurrent miscarriage, abnormal menstrual bleeding, and other obstetric complications. It is a pressing public health issue among women of childbearing age. Presently, there are limited clinical treatments for IUA, and there is no sufficient evidence that these treatment modalities can effectively promote regeneration after severe endometrial injury or improve pregnancy outcome. The inhibitory pathological micro-environment is the main factor hindering the repair of endometrial damaged tissues. To address this, tissue engineering and regenerative medicine have been achieving promising developments. Particularly, biomaterials have been used to load stem cells or therapeutic factors or construct an in situ delivery system as a treatment strategy for endometrial injury repair. This article comprehensively discusses the characteristics of various bio-scaffold materials and their application as stem cell or therapeutic factor delivery systems constructed for uterine tissue regeneration.
Due to the mismatch of main circuit parameters and the negative impedance characteristics of inverter-motor system under specific operating conditions, urban rail transit traction system is prone to DC-link voltage oscillation. In order to solve this problem, this paper establishes a characteristic equation model of traction system, and analyzes the influence of DC-link filter parameters on system stability. For inverter-motor drive system, it proposes an oscillation suppression method based on impedance reconstruction. By compensating d axis and q axis reference voltage signal of controller, negative impedance characteristic of the inverter-motor system is improved so that the system is stable. Simulation and hardware-in-the-loop experiment results show that the suppression strategy can effectively suppress the oscillation and improve the stability of system.
Control engineering systems. Automatic machinery (General), Technology