Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

Elaheh Janbezar, Hemayat Shekaari, Mohammed Taghi Zafarani-Moattar

Abstract This study addresses the challenge of achieving long-term colloidal stability in SiO2 nanofluids, a critical barrier for their practical applications, by investigating the stabilizing effects of surface-active ionic liquids (SAILs) on aqueous SiO2 nanoparticle dispersions. The purpose is to evaluate how SAILs specifically (2-hydroxyethyl)ammonium oleate (HEA-Ole), bis(2-hydroxyethyl)ammonium oleate (BHEA-Ole), and tris(2-hydroxyethyl)ammonium oleate (THEA-Ole) can enhance SiO2 stability beyond typical literature reports of less than 20 days. The stability was assessed through excess molar volume ( $$V_{m}^{E}$$ ), viscosity (η), density (ρ), DLS, zeta potential, surface tension, COSMO results, and visual observation over 60 days. The viscosity modeled by Eyring-mNRF and Eyring-NRTL, while density data were fitted with Redlich–Kister, polynomial, Ott, and PC-SAFT models. THEA-Ole demonstrated superior stabilization of SiO2, particularly after-critical micelle concentration (CMC), with minimal sedimentation, optimal dispersity via DLS, and a high zeta potential. Viscosity data aligned with Einstein, Batchelor, Brinkman, and Lundgren prediction models, $$V_{m}^{E}$$ and surface tension measurement indicated stable trends in THEA-Ole, and PC-SAFT showed the lowest ARD% for THEA-Ole nanofluids, confirming strong SiO2 interactions. THEA-Ole nanofluids provide exceptional SiO2 stability over 60 days, outperforming conventional surfactants and addressing key limitations in nanofluid dispersion for extended applications.

Sofia Tapias Montana, Ronnie de Souza Santos

This paper investigates how software professionals perceive the economic implications of diversity in software engineering teams. Motivated by a gap in software engineering research, which has largely emphasized socio-technical and process-related outcomes, we adopted a qualitative interview approach to capture practitioners' reasoning about diversity in relation to economic and market-oriented considerations. Based on interviews with ten software professionals, our analysis indicates that diversity is perceived as economically relevant through its associations with cost reduction and containment, revenue generation, time to market, process efficiency, innovation, and market alignment. Participants typically grounded these perceptions in concrete project experiences rather than abstract economic reasoning, framing diversity as a practical resource that supports project delivery, competitiveness, and organizational viability. Our findings provide preliminary empirical insights into how economic aspects of diversity are understood in software engineering practice.

Yu Zhang, Zhaohui Wang, Xiaofeng Luo et al.

We review recent results of net-proton multiplicity fluctuations from STAR experiment, aiming to locate the QCD critical point in high-energy nuclear collisions at RHIC. We show net-proton number cumulant and proton number factorial cumulant ratios up to fourth order using experimental data from RHIC BES-II Au+Au collisions in collider mode and fixed-target mode. The comparison is made between experimental data and non-critical model calculations from Lattice QCD, HRG, hydrodynamic simulations and transport model UrQMD. In addition, we discuss initial volume fluctuation effect, which plays significant role in fixed-target energies. Finally, an outlook on experimental research on the QCD critical point in future experiments will be presented.

Chen Cao, Jialin Wang, Qingli Wang et al.

To diagnose the electrical contact state of gas-insulated switchgear (GIS), the monitoring method based on variational mode decomposition (VMD) and Hilbert marginal spectrum energy entropy is proposed. The multi-physical field coupling model of GIS is established, and vibration signals under various states and operating currents are simulated. The GIS prototype and laboratory test platform are developed, and vibration tests are conducted under four different electrical contact states. Experimental results indicate that at the same contact state, with the current increases, the vibration amplitude of the GIS contact shows an increasing trend; under the same current, with the deterioration of the contact state, the vibration amplitude of the GIS contact shows an increasing trend. Further, the method of GIS contact state diagnosis based on VMD-Hilbert spectrum energy entropy is proposed. The online monitoring experiment is carried out in the substation. The results indicate that, aiming at the abnormal contact state of GIS, the energy entropy of the intrinsic mode function 6(IMF6) is 0.704, below 0.7368, while that of IMF7 is 0.2176, exceeding 0.187, which indicates a mechanical fault state. The conclusions show that the monitoring method can accurately identify the electrical contact state of GIS.

Christoph Treude, Margaret-Anne Storey

The adoption of large language models (LLMs) and autonomous agents in software engineering marks an enduring paradigm shift. These systems create new opportunities for tool design, workflow orchestration, and empirical observation, while fundamentally reshaping the roles of developers and the artifacts they produce. Although traditional empirical methods remain central to software engineering research, the rapid evolution of AI introduces new data modalities, alters causal assumptions, and challenges foundational constructs such as "developer", "artifact", and "interaction". As humans and AI agents increasingly co-create, the boundaries between social and technical actors blur, and the reproducibility of findings becomes contingent on model updates and prompt contexts. This vision paper examines how the integration of LLMs into software engineering disrupts established research paradigms. We discuss how it transforms the phenomena we study, the methods and theories we rely on, the data we analyze, and the threats to validity that arise in dynamic AI-mediated environments. Our aim is to help the empirical software engineering community adapt its questions, instruments, and validation standards to a future in which AI systems are not merely tools, but active collaborators shaping software engineering and its study.

Joshua Owotogbe, Indika Kumara, Dario Di Nucci et al.

Chaos engineering aims to improve the resilience of software systems by intentionally injecting faults to identify and address system weaknesses that cause outages in production environments. Although many tools for chaos engineering exist, their practical adoption is not yet explored. This study examines 971 GitHub repositories that incorporate 10 popular chaos engineering tools to identify patterns and trends in their use. The analysis reveals that Toxiproxy and Chaos Mesh are the most frequently used, showing consistent growth since 2016 and reflecting increasing adoption in cloud-native development. The release of new chaos engineering tools peaked in 2018, followed by a shift toward refinement and integration, with Chaos Mesh and LitmusChaos leading in ongoing development activity. Software development is the most frequent application (58.0%), followed by unclassified purposes (16.2%), teaching (10.3%), learning (9.9%), and research (5.7%). Development-focused repositories tend to have higher activity, particularly for Toxiproxy and Chaos Mesh, highlighting their industrial relevance. Fault injection scenarios mainly address network disruptions (40.9%) and instance termination (32.7%), while application-level faults remain underrepresented (3.0%), highlighting for future exploration.

Ruijing Li, Peng Gao, Mengyan Dai et al.

Preclinical research has established X-ray-induced photodynamic therapy (X-PDT) as a highly acknowledged antitumor therapy. X-rays play an important role in the X-PDT process. It is crucial to understand the impact of both the total dose and dose fractionation on the effectiveness of X-PDT. For the first time, a systematic study has been conducted on the effects of radiation dose and dose fractionation mode on the efficacy of X-PDT deeply. In vitro and in vivo results showed that there is an optimum dose threshold for the anti-tumor efficacy of X-PDT within the range of 0–6 Gy radiation dose. Additionally, the anti-tumor effect of a single exposure mode is significantly superior to that of a hyperfractionated radiation mode in 4T1 tumor-bearing mice. Notably, X-PDT significantly inhibited the invasion and migration of tumor cells and significantly inhibited lung metastasis of breast cancer. These new findings are significant for the clinical application of X-PDT and offer valuable insights for the development of future X-PDT radiation plans.

Kathiresan Subramanian, Kagne Suresh

The administration of rural effluent is essential due to the scarcity of resources and infrastructure, which exacerbates health hazards and environmental degradation. Decentralised wastewater treatment (DWT) is a system that reduces the transportation costs and environmental impact by recycling wastewater for agricultural and other purposes. This study suggests a single system DWT technique that integrates natural and artificial systems to enhance rural sustainability. The system employs an Anaerobic Baffled Reactor (ABR) for the initial decomposition of organic matter, a solar-powered disinfection device, and constructed wetlands (CW) for the secondary treatment and nutrient removal. The system is cost-effective and simple to deploy by utilizing renewable energy and local components. The system satisfied local environmental criteria by reducing biochemical oxygen demand (BOD) by 85 %, total suspended solids (TSS) by 90 %, and infections by 99.9 %, as demonstrated by a pilot study conducted in a rural community. Users and administrators were impressed by the system's simplicity and ease of maintenance. Sustainability and ownership were enhanced through community involvement in design and execution. The results indicate that this DWT technique, considered a scalable and adaptive wastewater management solution, has the potential to enhance the quality of water and the health of rural environments. To enhance the sustainability and effectiveness of the system, future research will expand the number of system components and examine alternative applications, such as nitrogen recovery and greywater recycling. This study demonstrates that rural communities may address wastewater treatment challenges by employing a decentralized approach that capitalizes on community engagement and local resources. This strategy also has a positive impact on public health and the environment over time.

Egor Klimov, Muhammad Umair Ahmed, Nikolai Sviridov et al.

Bus factor (BF) is a metric that tracks knowledge distribution in a project. It is the minimal number of engineers that have to leave for a project to stall. Despite the fact that there are several algorithms for calculating the bus factor, only a few tools allow easy calculation of bus factor and convenient analysis of results for projects hosted on Git-based providers. We introduce Bus Factor Explorer, a web application that provides an interface and an API to compute, export, and explore the Bus Factor metric via treemap visualization, simulation mode, and chart editor. It supports repositories hosted on GitHub and enables functionality to search repositories in the interface and process many repositories at the same time. Our tool allows users to identify the files and subsystems at risk of stalling in the event of developer turnover by analyzing the VCS history. The application and its source code are publicly available on GitHub at https://github.com/JetBrains-Research/bus-factor-explorer. The demonstration video can be found on YouTube: https://youtu.be/uIoV79N14z8

Vadim Sidorov, Andrii Chub, Dmitri Vinnikov et al.

This paper introduces the novel concept of a highly versatile smart power electronic interface for fast deployment of residential dc microgrids. The proposed approach has bidirectional power flow control capabilities, wide operating voltage range, and high efficiency resulting from the topology morphing control utilization. This enables universal compatibility with the majority of the commercial 60- and 72-cell photovoltaic modules, as well as the efficient charge/discharge control of the 24 V and 48 V battery energy storages using the same hardware platform. The proposed concept features fully autonomous operation where switching between the photovoltaic and battery interfacing modes is automatically done using the input source identification algorithm. Moreover, the proposed universal interface converter employs droop control and solid-state protection, making it fully compatible with the emerging standards and requirements for power electronic systems used in dc microgrid environments. A 350 W prototype was developed and tested in the residential 350 V dc microgrid with droop control to validate the proposed concept experimentally.

Renxi Gong, Cheng Zhao

There exists the problems of output voltage zero-point drift and high even harmonic content of the three-phase Cuk liftable voltage photovoltaic (PV) inverter when it adopts the conventional carrier modulation method. In view of these, a new optimized Phase-Shifted Pulse Width Modulation (PSPWM) strategy is proposed. Firstly, the optimal zero-sequence component is determined based on the inverter topology and control objectives. Next, the zero-sequence component is injected into the sinusoidal signal and used as the new modulating signal so that the carrier pulse width modulation is equivalent to the space vector pulse width modulation. Finally, the carrier and modulating waveforms are blended in a superior manner, and a new logical operation is applied to generate the required switching drive signals for the control of the inverter switching tubes. In order to verify the effectiveness of the strategy, simulation and experimental platforms were constructed, and numerous simulations and experiments were done. The results show that the modulation strategy can solve the output voltage zero drift problem effectively, and suppress the even harmonics effectively, meanwhile, the harmonics are mainly concentrated near the primary frequency, which significantly reduces the total harmonic content and greatly improves the output voltage waveform. In addition, the modulation can be achieved by reducing one carrier signal, thus simplifying the modulation process and the design of the digital signal system.

A. Makowski, M. C. Barton, P. Magierski et al.

We discuss the possible manifestation of pairing dynamics in nuclear collisions beyond the standard quasi-static treatment of pairing correlations. These involve solitonic excitations induced by pairing phase difference of colliding nuclei and pairing dynamic enhancement in the di-nuclear system formed by merging nuclei.

Lorenz Graf-Vlachy

Background: Risk-taking is prevalent in a host of activities performed by software engineers on a daily basis, yet there is scant research on it. Aims and Method: We study if software engineers' risk-taking is affected by framing effects and by software engineers' personality. To this end, we perform a survey experiment with 124 software engineers. Results: We find that framing substantially affects their risk-taking. None of the "Big Five" personality traits are related to risk-taking in software engineers after correcting for multiple testing. Conclusions: Software engineers and their managers must be aware of framing effects and account for them properly.

Boyang Zhou, Chunming Wu, Qiang Yang et al.

In a modern electric power transmission grid, the phasor measurement unit requires a reliable transport of its sampled statistics with a low end-to-end failure rate (EEFR) to ensure the accuracy of the grid state estimation. However, EEFR can be deteriorated by packet losses due to multiple link disruptions in the primary forwarding path (PP). To address that, we investigate a novel disruption resilient transport protocol (DRTP) enabling hop-by-hop retransmission utilizing the redundant subpaths (RSPs) available for the PP to increase reliability. It addresses the new distributed collaboration issue under multiple link failures to avoid cache mismatching. These have not been considered by the existing approaches. The DRTP was evaluated in the ndnSIM simulator through both the typical and general routes that are constructed from real transmission grids. The numerical results demonstrate that it has a significant advantage in reducing the EEFR with a low end-to-end delivery time under serious link disruptions.

Mohammad Javad Rezaei-Hosseinabadi, Meysam Bayat, Bahram Nadi et al.

Granular column is an attractive mitigation method which is widely used in geotechnical engineering to enhance the bearing capacity, reduce settlement and accelerate consolidation. Utilisation of industrial wastes such as steel slag in soil stabilization can be an environment-friendly and cost-effective extraction technique to the disposal of solid waste materials. Previous studies investigated the bearing capacity and settlement of ground improved with granular columns with or without the geosynthetic encasement. However, very limited number of studies have investigated the response of ordinary stone columns without encasement and geosynthetic encased steel slag columns under lateral loading. In this paper, the lateral load capacity of steel slag granular column-soil composites has been investigated. For this purpose, a series of large direct shear tests were performed on the column-soil composites with the steel slag column and the ordinary stone column with or without the geosynthetic encasement. The effect of type of column materials (steel slag and sand), column diameter, number of columns, columns arrangement, and geosynthetic encasement on the shear strength parameters of column-soil composites have been studied. The experimental results show the effectiveness of using the steel slag columns to improve the lateral load-bearing performance of soil.

Zheng Li, Austen Rainer

Background: Academic search engines (i.e., digital libraries and indexers) play an increasingly important role in systematic reviews however these engines do not seem to effectively support such reviews, e.g., researchers confront usability issues with the engines when conducting their searches. Aims: To investigate whether the usability issues are bugs (i.e., faults in the search engines) or constraints, and to provide recommendations to search-engine providers and researchers on how to tackle these issues. Method: Using snowball-sampling from tertiary studies, we identify a set of 621 secondary studies in software engineering. By physically re-attempting the searches for all of these 621 studies, we effectively conduct regression testing for 42 search engines. Results: We identify 13 bugs for eight engines, and also identify other constraints. We provide recommendations for tackling these issues. Conclusions: There is still a considerable gap between the search-needs of researchers and the usability of academic search engines. It is not clear whether search-engine developers are aware of this gap. Also, the evaluation, by academics, of academic search engines has not kept pace with the development, by search-engine providers, of those search engines. Thus, the gap between evaluation and development makes it harder to properly understand the gap between the search-needs of researchers and search-features of the search engines.

Richard M. Ñope-Giraldo, Luis A. Illapuma-Ccallo, Jose Cornejo et al.

The critical situation of COVID-19 widespread in Perú from the beginning of year 2020, has been maximized by the avoidance of social distancing reflected in crowded public places where most people go without any personal protective equipment (PPEs) leading to higher risk of virus transmission. Therefore, an innovative research has been conducted in 2020 under the supervision of the Mechatronic Engineering Laboratory at Ricardo Palma University and Bioastronautics & Space Mechatronics Research Group, resulting in the proposed project named “ROHNI-1” medical robot, as Social Humanoid Machine, that is going to be located at the entrance of a wholesale-supermarket. It is composed by 3 wheels in the chassis-base and 2 anthropomorphic arms of 4 DOF each. In order to perform an efficient human-machine interaction, it can develop 3 functions such as Detection of mask, Disinfection of hands and Monitoring of vital signs. This study presents a mechatronics conceptual design using the software SolidWorks 2020 for 3D mechanical systems development, Proteus 8 for electrical and electronics circuit technical schematics, and also, Matlab 2020a for kinematic motion testing of the robotic arms. In conclusion, favourable simulation results were achieved; the robot manufacturing is expected to be ready by 2021, and due to frugal-innovation engineering analysis, it is planned to be donated to Latin American countries working with supermarket-chains.

Lei Chen, Shangbin Li

To address the problem that the traditional human motion attitude detection process is easy to ignore the data calibration, which leads to the problems of long running time, low accuracy and poor detection effect, a human motion target attitude detection algorithm based on semi-supervised learning in the Internet of things environment is proposed. Firstly, human motion target images are collected using the Internet of things (IoT), human motion attitude features are extracted based on the eight-star model, and multi-features are fused to form image blocks of 17-dimensional feature vectors. Then, random fern classifiers are optimized and semi-supervised learning is used to calculate a large number of uncalibrated data in time domain, spatial domain and data. The classifier is trained to complete image block classification. Finally, the classifier parameters are updated iteratively to complete the attitude detection of human motion target. The results show that the proposed algorithm has high accuracy in human motion attitude extraction and multi-feature fusion, and has a high correct classification rate for different feature poses, as high as 92.5%. The average F value of human motion attitude detection is 0.95, the overlap ratio is high and the time is short. The overall performance is good.

Yuda Lin, Liang Jin, Kaizhi Huang et al.

Abstract This paper studies multi‐antenna covert communication exploiting a public communication link over the wireless fading channel. In particular, a relatively practical covert communication scenario is considered for the first time, where a warden with radiometer may improve its detection accuracy by jointly detecting uplink covert pilot and downlink covert communication. To this end, a joint covert communication system, jointly considering uplink covert pilot, imperfect channel state information issue and downlink covert communication, is proposed and further studied. Specifically, the detection performance of warden and the covertness performance of system are comprehensively studied, respectively. Afterwards, an optimization problem for covert capacity is formulated to maximize overall performance. Then, with our analysis and simplification, an optimal power allocation algorithm is designed for covert capacity accordingly. Our examination shows a win‐win situation has been achieved in the proposed system, that is, covert communication would rarely affect the normal communication of public link and occupy its communication resources. Interestingly enough, we analytically find an invariance property of downlink covert communication that covertness performance is not impacted by noise levels or warden's position. Based on this extraordinary finding, we conclude that the downlink covert communication system can perfectly combat with a powerful warden adopting power trend test method, while the joint covert communication system may resist that through a pilot deception scheme.

Marian Daun, Jennifer Brings, Marcel Goger et al.

The use of conceptual models to foster requirements engineering has been proposed and evaluated as beneficial for several decades. For instance, goal-oriented requirements engineering or the specification of scenarios are commonly done using conceptual models. Bringing such model-based requirements engineering approaches into industrial practice typically requires industrial training. In this paper, we report lessons learned from a training program for teaching industry professionals model-based requirements engineering. Particularly, we as educators and learners report experiences from designing the training program, conducting the actual training, and applying the instructed material in our day-to-day work. From these findings we provide guidelines for educators designing requirements engineering courses for industry professionals.