Marcio Luis Munhoz Amorim, Oswaldo Hideo Ando Junior, Mario Gazziro
et al.
This paper presents Nexus, a proof-of-concept low-cost, modular, and reprogrammable multichannel data logger aimed at validating the architectural feasibility of an open and scalable acquisition platform for scientific instrumentation. The system was conceived to address common limitations of commercial data loggers, such as high cost, restricted configurability, and limited autonomy, by relying exclusively on widely available components and open hardware/software resources, thereby facilitating reproducibility and adoption in resource-constrained academic and industrial environments. The proposed architecture supports up to six interchangeable acquisition modules, enabling the integration of up to 20 analog channels with heterogeneous resolutions (24-bit, 12-bit, and 10-bit ADCs), as well as digital acquisition through multiple communication interfaces, including I2C (two independent buses), SPI (two buses), and UART (three interfaces). Quantitative validation was performed using representative acquisition configurations, including a 24-bit ADS1256 stage operating at sampling rates of up to 30 kSPS, 12-bit microcontroller-based stages operating at approximately 1 kSPS, and 10-bit operating at 100 SPS, consistent with stable real-time acquisition and visualization under proof-of-concept constraints. SPI communication was configured with an effective clock frequency of 2 MHz, ensuring deterministic data transfer across the tested acquisition modules. A hybrid data management strategy is implemented, combining high-capacity local storage via USB 3.0 solid-state drives, optional cloud synchronization, and a 7-inch touchscreen human–machine interface based on Raspberry Pi OS for system control and visualization. Power continuity is addressed through an integrated smart uninterruptible power supply, which provides telemetry, automatic source switching, and limited backup operation during power interruptions. As a proof of concept, the system was functionally validated through architectural and interface-level tests, demonstrating stable communication across all supported protocols and reliable acquisition of synthetic and biosignal-like waveforms. The results confirm the feasibility of the proposed modular architecture and its ability to integrate heterogeneous acquisition, storage, and interface subsystems within a unified open-source platform. While not intended as a finalized commercial product, Nexus establishes a validated foundation for future developments in modular data logging, embedded intelligence, and application-specific instrumentation.
Rafael Achury, Robin Heinen, Sebastian T. Meyer
et al.
Smart farming (SF), the use of advanced technologies such as sensors, the Internet of Things (IoT), artificial intelligence (AI), data analytics, and automation, holds great promise for increasing agricultural sustainability as it enables a reduction of inputs while maintaining yield. A general assumption is that biodiversity will benefit from reduced synthetic inputs. We argue that biodiversity benefits will not come automatically, especially within agricultural fields. Rather, technological developments need to embrace ecological targets during future innovations. Done right, with a new framework that integrates ecological and agronomic objectives in decision-making algorithms, SF could restore biodiversity in agricultural landscapes of the Global North, and preserve it in the Global South, while closing the yield gap. However, making agriculture more biodiversity-friendly through SF requires a more interdisciplinary research by scientists, targeted research funding schemes, incentives for the application of these technologies, and supporting strong national and international policies that drive widespread and equitable adoption.
Muhammad Shoaib Farooq, Junaid Nasir Qureshi, Fatima Ahmed
et al.
Revolutionizing distributed agile software testing, we propose BCTestingPlus, a groundbreaking blockchain-based platform. In the traditional distributed agile software testing lifecycle, software testing has suffered from a lack of trust, traceability, and security in communication and collaboration. Furthermore, developers’ failure to complete unit testing has been a significant bottleneck, causing delays and contributing to project failures. Introducing BCTestingPlus, a transformative blockchain-based architecture engineered to overcome these challenges. This framework integrates blockchain technology to establish an inherently transparent and secure environment for software testing. BCTestingPlus operates on a private Ethereum blockchain network, offering superior control and privacy. By implementing smart contracts on this network, BCTestingPlus ensures secure payment verification and efficient acceptance testing. Crucially, it aligns development and testing teams toward shared objectives and guarantees equitable compensation for their efforts. The experimental results and findings conclusively show that this innovative approach demonstrates that BCTestingPlus significantly enhances transparency, bolsters trust, streamlines coordination, accelerates testing, and secures communication channels for all parties involved in the distributed agile software testing lifecycle. It delivers robust security for both development and testing teams, ultimately transforming the efficiency and reliability of distributed agile software testing.
Engineering machinery, tools, and implements, Technological innovations. Automation
Zuolong Ye, Alexander A. Hernandez, Yulin Chen
et al.
Aiming at the problems such as service homogenization and ambiguous stage intervention in current university innovation and entrepreneurship incubation platforms, this research constructs a four-stage incubation model of "seedling selection - seedling planting - seedling cultivation - seedling transplantation". Grounded in the resource-based theory, life cycle theory, and service-dominant logic, this study uses 130 projects from the incubation platform of Guangzhou Vocational and Technical University of Science and Technology as samples and conducts empirical tests through methods such as multiple linear regression and hierarchical regression. The results indicate that the core service elements in each stage (for example, the precision of creative screening in the seedling selection stage and the technical resource support in the seedling planting stage) have a significantly positive impact on the outputs of the corresponding stage (such as the passing rate and the prototype iteration speed). The stage assessment mechanism plays a positive moderating role in the service transmission effect. This model has increased the three-year survival rate of projects by nearly 20 percentage points. This research offers references for improving the theory of university incubation and enhancing the practical effectiveness.
Mohammad Hossein Modirrousta, Mahdi Aliyari Shoorehdeli, Mostafa Yari
Abstract In industrial and real‐world systems, recognising errors and adopting the best approaches are gaining relevance. The authors’ goal is to identify artificial intelligence apps that provide the most reliable and valuable data‐based fault detection techniques. A system for fault identification is presented based on reinforcement learning and proximal policy optimisation (PPO). Due to the lack of fault data, one of the key issues with the standard policy is its inability to recognise fault classes; this issue was resolved by modifying the cost equation. Using improved PPO, the authors can improve performance, address data imbalances, and forecast possible failures more accurately. The approach utilises policy‐based optimisation, which offers several advantages. Firstly, it directly optimises the advantage quantity, and secondly, it ensures the stability of function approximation. The authors have studied two different turbines in Iran and collected data from them separately when a fault occurred. To demonstrate the efficiency of our algorithm, the authors have included the third and fourth datasets as cyber attack benchmarks. When the authors’ proposed policy is adopted, all evaluation metrics will improve by 3%–4% as compared to the previous policy in the first benchmark, between 20% and 55% in the second benchmark, between 6% and 14% in the third benchmark, and between 4% and 5% in the fourth benchmark, with improved results and prediction times compared to existing studies.
The issue of climate change, greenhouse gas emissions, global warming, and their effect on nature and the ecosystem has raised serious concerns. The desire to sustain economic growth and development while keeping a check on the environmental footprints is one of the leading challenges the contemporary world is currently facing. To ensure sustained growth, there is a need for technologies and solutions that has the potential to meet industrial needs without compromising the environment. Cleantech offers a possibility to address these needs in a sustainable and environmentally friendly manner. Cleantech, being an umbrella term, is often confused and misunderstood, in terms of its definition and scope. This study seeks to explore what cleantech actually is, how this sector came into prominence, what are the driving factors behind its surge, and what kind of socio-economic, technical, and regulatory prerequisites are necessary for the advancement of this sector.
Innovative technologies are increasingly determining the competitive advantage of enterprises. They also form the basis for modern manufacturing processes, enabling them to meet the needs of society. Awareness of the need for technological development has become widespread, which has been confirmed by international and national programs, scientific and research activities, as well as emerging institutions. Considering the increasing demand for innovative technologies and the developed market, it appears important to use specific methods and tools for the effective analysis and selection of technologies. This paper presents a proposal to use multi-attribute decision-making methods during technology assessment and selection. The proposed concept combines an S-life-cycle analysis (S-LCA), which determines the performance of a technology, the method of Technology Readiness Levels (TRL), which examines the technological maturity, and the TOPSIS method, which allows for developing a technology ranking. To verify this approach, the example of a ranking and selection of the best road technology in Poland is presented, considering the proposed set of criteria and sub-criteria. In the technology assessment, the criteria for innovation, competitiveness, and usefulness of this technology were used in addition to S-LSA and TRL methods.
Martina Crapolicchio, Henrique de Carvalho, Karim Chaitani
et al.
This article investigates the sustainability in the Italian hospitality sector and the reasons why its infrastructure lacks on energetic and thermal efficiency despite the numerous solutions present in the market. The study is performed based on bibliographical research and a survey conducted with hotel managers and hotel real estate owners. It draws compelling conclusions about the main drivers to innovation and restructuring in the sector.
When planting our human print in a new technology-driven world we should ask, remembering Neil Armstrong in 1969, “after many small steps for AI researchers, will it result in a giant leap in the unknown for mankind?” An “Artificial Intelligence-first” world is being preached all over the media by many responsible players in economic and scientific communities.
This letter states our belief in AI potentialities, including its major and decisive role in computer science and engineering, while warning against the current hyping of its near future. Although quite excited by several recent interesting revelations about the future of AI, we here argue in favor of a more cautious interpretation of the current and future AI-based systems potential outreach.
We also include some personal perspectives on simple remedies to preventing recognized possible dangers. We advocate a set of practices and principles that may prevent the development of AI-based systems prone to be misused.
Accountable “Data curators”, appropriate Software Engineering specification methods, the inclusion, when needed, of the “human in the loop”, software agents with emotion-like states might be important factors leading to more secure AI-based systems.
Moreover, to inseminate ART in Artificial Intelligence, ART standing for Accountability, Responsibility and Transparency, becomes also mandatory for trustworthy AI-based systems.
This letter is an abbreviation of a more substantial article to be published in IJCA journal.
Gilbert Audira, Bonifasius Putera Sampurna, Stevhen Juniardi
et al.
The measurement of multiple behavior endpoints in zebrafish can provide informative clues within neurobehavioral field. However, multiple behavior evaluations usually require complicated and costly instrumental settings. Here, we reported a versatile setting that applied ten acrylic tanks arranging into five vertical layers and two horizontal columns to perform multiple behavior assays simultaneously, such as the novel tank diving test, mirror-biting test, social interaction, shoaling, and predator escape assay. In total, ten behavioral performance were collected in a single video, and the XY coordination of fish locomotion can be tracked by using open source software of idTracker and ImageJ. We validated our setting by examining zebrafish behavioral changes after exposure to low dose ethanol (EtOH) for 96 h. Fish were observed staying longer time at bottom of the tank, less mirror biting interest, higher freezing time, less fear in predator test, and tight shoaling behaviors which indicated the anxiogenic effect was induced by low dosage exposure of EtOH in zebrafish. In conclusion, the setting in this study provided a simple, versatile and cost-effective way to assess multiple behavioral endpoints in zebrafish with high reliability and reproducibility for the first time.
Engineering machinery, tools, and implements, Technological innovations. Automation
Rogério Navarro Correia de Siqueira, Pâmela Fernandes de Oliveira
Nanostructured oxides with interesting magnetic properties, such as the spinel Al2
MnO4
, can be synthesized
through thermal decomposition of nitrate solution followed by thermal treatment under a reducing atmosphere. The
present work can be understood as a study of the synthesis of Al2
MnO4
samples based on the H2
reduction of Al and Mn
oxide mixtures, including a discussion of the effect of some important process variables over the kinetic behavior of the
system, such as temperature and thermal treatment time. For the temperature range considered (1,073 K to 1,173 K)
both the total reduction of manganese oxides to MnO, as well as the formation of spinel structures could be verified. At
the beginning of the formation process, the spinel shows considerable cationic disorder (non-stoichiometric structure).
The structure then evolves to the equilibrium stoichiometric form for higher process temperature and time.
Materials of engineering and construction. Mechanics of materials, Mining engineering. Metallurgy
Vinícius Lopes Vieira Martins, Felipe Pereira Vasconcelos, Juno Gallego
Yield strength of Nb-Ti-V microalloyed steel has been investigated as a function of its microstructure obtained after
industrial rolling on a hot strip mill. Optical (OM) and transmission electron microscopy (TEM) were used to reveal the
ferrite grain structure, fine carbonitride precipitation and dislocation substructures. It was found that the effects of solid
solution and grain size hardening were not sufficient to justify the results of tensile testing. Additional strengthening was
attributed to carbonitride precipitation in austenite, interphase precipitation during transformation, and the formation of
dislocations. All contributions of these microstructural features on mechanical property were estimated from empirical
models available from literature. A global effect of both austenite and interphase carbonitride precipitation hardening was
proposed. It was verified that yield strength calculated from cumulative effect of different strengthening mechanisms has
presented good fitting with experimental tensile test.
Materials of engineering and construction. Mechanics of materials, Mining engineering. Metallurgy
Patrick Cohendet was previously dean of the Faculty of Economics at Strasbourg University (1982–1985), vice president of the University of Strasbourg (1991–1992), member of the Conseil des Applications de l’Académie des Sciences in Paris (1994–2002), and chairman of the International Business Department at HEC Montréal (2007–2008). He was also visiting professor at the University of Virginia, and the University of Tokyo. His research interests include the theory of the firm, economics of innovation, economics of knowledge, economics of creativity and knowledge management.