Search Results (39)

Given the climate change observed in the past few decades, sustainable development and the use of renewable energy sources are urgent. In this scenario, hydrogen production through electrolyzers is a promising renewable source and energy vector because of its ultralow greenhouse emissions and high energy content. Hydrogen can be used in a variety of applications, from transportation to electricity generation, contributing to the diversification of the energy matrix. In this context, this paper presents an autonomous isolated DC microgrid system for generating and storing electrical energy to be exclusively used for feeding an electrolyzer hydrogen production plant, which has been retrofitted for green hydrogen production. Experimental verification was performed at Itaipu Parquetec, which consists of an alkaline electrolysis unit directly integrated with a battery energy storage system and renewable sources (e.g., photovoltaic and wind) by using an isolated DC microgrid concept based on DC/DC and AC/DC converters. Experimental results revealed that the new electrolyzer DC microgrid increases the system’s overall efficiency in comparison to the legacy thyristor-based power supply system by 26%, and it autonomously controls the energy supply to the electrolyzer under optimized conditions with an extremely low output current ripple. Another advantage of the proposed DC microgrid is its ability to properly manage the startup and shutdown process of the electrolyzer plant under power generation outages. This paper is the result of activities carried out under the R&D project of ANEEL program No. PD-10381-0221/2021, entitled “Multiport DC-DC Converter and IoT System for Intelligent Energy Management”, which was conducted in partnership with CTG-Brazil. Full article

Sustainable path-planning algorithms are essential for executing complex user-defined missions by mobile robots. Addressing various scenarios with a unified criterion during the design phase is often impractical due to the potential for unforeseen situations. Therefore, it is important to incorporate the concept of adaptive autonomy for path planning. This approach allows the system to autonomously select the best path-planning strategy. The technique utilizes dynamic programming with an adaptive memory size, leveraging a cellular decomposition technique to divide the map into convex cells. The path is divided into three segments: the first segment connects the starting point to the center of the starting cell, the second segment connects the center of the goal cell to the goal point, and the third segment connects the center of the starting cell to the center of the goal cell. Since each cell is convex, internal path planning simply requires a straight line between two points within a cell. Path planning uses an improved $A^{\ast }$ (I-$A^{\ast }$) algorithm, which evaluates the feasibility of a direct path to the goal from the current position during execution. When a direct path is discovered, the algorithm promptly returns and saves it in memory. The memory size is proportional to the square of the total number of cells, and it stores paths between the centers of cells. By storing and reusing previously calculated paths, this method significantly reduces redundant computation and supports long-term sustainability in mobile robot deployments. The final phase of the path-planning process involves pruning, which eliminates unnecessary waypoints. This approach obviates the need for repetitive path planning across different scenarios thanks to its compact memory size. As a result, paths can be swiftly retrieved from memory when needed, enabling efficient and prompt navigation. Simulation results indicate that this algorithm consistently outperforms other algorithms in finding the shortest path quickly. Full article

Advanced air defense methods are essential to address the growing complexity of aerial threats. The increasing number of targets necessitates better defensive coordination, and a promising strategy involves the use of interceptors together to protect a specific area. This task fundamentally depends on accurately predicting their kinematic envelopes, or reachable sets. This paper presents a novel approach to determine the boundaries of reachable sets for aerodynamic interceptors, accounting for energy loss from drag, energy gain from thrust, variable acceleration limits, and autopilot dynamics. The devised numerical method approximates reachable sets for nonlinear problems using a constrained model predictive programming concept. Results demonstrate that explicitly accounting for input constraints, such as acceleration limits, significantly impacts the shape and area of the reachable boundaries. Furthermore, a sensitivity analysis was conducted to demonstrate the impact of parameter variations on the reachable set. Revealing the reachable set’s sensitivity to variations in thrust and drag coefficients, this analysis serves as a framework for considering parameter uncertainty and enables the evaluation of these effects prior to embedding the reachability boundaries into an offline database for guidance applications. The resulting boundaries, representing minimum and maximum ranges for various initial parameters, can be stored offline, allowing interceptors to estimate their own or allied platforms’ kinematic capabilities for cooperative strategies. Full article

The name ‘Malvasia’ and its various spellings has historically been associated with a type of sweet and/or aromatic wine. However, a definitive association with a specific grape variety remains unconfirmed. In fact, up to 413 different grape variety names (cultivar name (synonym name) and/or first name) are related to the term “Malvasia”. The question arises: are all of these truly Malvasia? To answer this question, our research group presents a hypothesis. We worked with 43 genetic profiles that various scientific groups have published over decades and that are stored in the world’s largest grape database, the Vitis International Variety Catalogue (VIVC). The known molecular profiles were obtained using the SSR (Simple Sequence Repeats) or microsatellite technique. Various population structure programs were applied, information on the possible origin or area where each of the varieties was mostly grown was used, and historical information was used to explain the results obtained. Therefore, it can be concluded that the current varieties best positioned to define the concept of grape and/or wine variety “Malvasia” would be (1) Malvasia Dubrovacka, Malvasia bianca lunga, and Malvasia del Cilento, by genetic proximity; (2) Malvasia volcanica, Malvasia babosa, Malvasia nera di Basilicata, Malvasia nera di Brindisi, Vitovska, Pelena, Prunesta (false), and Lagorthi, by crosses; and (3) Malvasia di Sardegna Rosada, by mutation. The rest of the candidate varieties to be part of the ‘Malvasia’ family are dismissed because they result from crosses with members of the Muscat family or crosses with other varieties (known or unknown) that, in any case, are not related historically, genetically, or geographically (with the exception of Malvasia istriana and Malvasia Župska) to the hypothetical members of the ‘Malvasia’ family. Full article

Background/Objectives: The surveillance of viral strain evolution is needed during prophylactic HPV vaccination programs against cervical cancer and necessitates safely archiving and storing cervical samples while maintaining the long-term stability of HPV DNA to carry out molecular diagnosis. The present proof-of-concept study aimed to assess DNA stability for HPV molecular detection from veils resuspended in a universal transport medium (UTM) and conserved at different temperatures after long-term storage. Methods: The detection and quantification of HPV DNA were evaluated in female genital secretions self-collected using veils and conserved in Cyt-All^® UTM at −30 °C, +4 °C, and +25 °C after long-term 27-month storage. Results: A slight degradation of the ubiquitous single-copy cellular DNA TOP3 gene was assessed using multiplex real-time PCR (BMRT Human Papillomavirus Genotyping Real Time PCR Kit, Bioperfectus Technologies Co., Ltd., Taizhou, Jiangsu, China) at positive temperatures (+4 °C and +25 °C) but not at a frozen temperature (−30 °C) after 27 months of storage. Nevertheless, HPV DNA preservation was sufficient at the three storage temperatures to detect and quantify HPV DNA, with a similar rate of HPV detection, a similar level of cumulative HPV viral loads, high sensitivity and specificity, and perfect concordance in HPV genotype detection after the long period of 27 months of storage. Finally, the conservation of genital samples for a prolonged period in the Cyt-All^® medium, even at room temperature, allows for the detection and quantification of any HPV and HR-HPV with high accuracy. Conclusions: The combination of veil-based self-sampling of female genital secretions and their elution and conservation in UTM may be used in the field to carry out longitudinal molecular epidemiology surveys of circulating HPV. Full article

We present an automatic approach for generating learning problems for teaching introductory programming in different programming languages. The current implementation allows input and output in the three most popular programming languages for teaching introductory programming courses: C++, Java, and Python. The generator stores learning problems using the “meaning tree”, a language-independent representation of a syntax tree. During this study, we generated a bank of 1,428,899 learning problems focused on the order of expression evaluation. They were generated in about 16 h. The learning problems were classified for further use with the used concepts, possible domain-rule violations, and required skills; they covered a wide range of difficulties and topics. The problems were validated by automatically solving them in an intelligent tutoring system that recorded the actual skills used and violations made. The generated problems were favorably assessed by 10 experts: teachers and teaching assistants in introductory programming courses. They noted that the problems are ready for use without further manual improvement and that the classification system is flexible enough to receive problems with desirable properties. The proposed approach combines the advantages of different state-of-the-art methods. It combines the diversity of learning problems generated by restricted randomization and large language models with full correctness and a natural look of template-based problems, which makes it a good fit for large-scale learning problem generation. Full article

The age of pervasive computing has initiated a boom in the development of adaptive context-aware learning environments (ACALEs), i.e., systems that are capable of detecting a learner’s context and providing adaptive learning services based on this context. Many of the existing educational systems were developed as standalone applications for specific or a small range of adaptive educational scenarios. It would be extremely helpful for developers and educators to have a unified framework that provides an infrastructure for the development of ACALEs. In this study, we propose Lightlore—an adaptation framework that enables the development of different types of ACELEs for a wide range of learning scenarios in formal and informal settings. We first used scenario-based design (SBD) as the design methodology for creating a conceptual model of Lightlore. Educational scenarios were adopted from the results of a previous literature review. We then developed a proof-of-concept implementation of Lightlore, with a hypermedia system for learning data structures that uses the adaptation service of Lightlore. This implementation is essentially an adaptation infrastructure and a programming API for creating new (or transforming existing) adaptive and context-aware educational services. It exploits the experience API (xAPI), a modern e-learning standard and learning record store, thus making coupling with existing learning environments easier. We expect that diverse types of users will benefit from using Lightlore, such as learners, educators, learning environment developers, and researchers on educational technologies. Full article

With recent advancements, large language models (LLMs) such as ChatGPT and Bard have shown the potential to disrupt many industries, from customer service to healthcare. Traditionally, humans interact with geospatial data through software (e.g., ArcGIS 10.3) and programming languages (e.g., Python). As a pioneer study, we explore the possibility of using an LLM as an interface to interact with geospatial datasets through natural language. To achieve this, we also propose a framework to (1) train an LLM to understand the datasets, (2) generate geospatial SQL queries based on a natural language question, (3) send the SQL query to the backend database, (4) parse the database response back to human language. As a proof of concept, a case study was conducted on real-world data to evaluate its performance on various queries. The results show that LLMs can be accurate in generating SQL code for most cases, including spatial joins, although there is still room for improvement. As all geospatial data can be stored in a spatial database, we hope that this framework can serve as a proxy to improve the efficiency of spatial data analyses and unlock the possibility of automated geospatial analytics. Full article

With nearly half of the world’s population being at risk of infection, dengue virus represents a major global health issue. The use of dengue antigen rapid diagnostic tests (Ag-RDTs) represents an alternative to PCR methods for the diagnosis of acute infections since they display excellent sensitivities and specificities and can be performed outside the laboratory. The high genetic diversity of the dengue virus genome represents a challenge for vaccine development, and the progressive expansion of this virus into previously nonendemic regions justifies the implementation of a genomic surveillance program. In this proof-of-concept study, we show the feasibility of sequencing dengue virus genomes directly from positive Ag-RDT (Standard Q Dengue Duo Test assay, n = 7) cassettes stored up to 31 days at room temperature after testing. For 5 of the 7 samples, a high number of reads were obtained allowing phylogenetic analyses to be carried out to determine not only the serotypes (dengue 1, 2, 3 and 4 were detected) but also the genotypes. Furthermore, in one sample, our unbiased metagenomic next-generation sequencing approach made it possible to detect epizootic hemorrhagic disease virus sequences, an arthropod-transmitted virus in ruminants. To conclude, as such an approach requires no cold storage or freezing of samples, dengue Ag-RDTs represent a very pragmatic and robust alternative for the genomic surveillance of dengue virus. Full article

Linear programming formulations of forest ecosystem management (FEM) problems proposed in the 1960s have been adapted and improved upon over the years. Generating management alternatives for forest planning is a key step in building these models. Global forests are diverse, and a variety of models have been developed to simulate management alternatives. This paper describes iGen, a forest prescription generator that employs a rule-based system (AI-RBS), an AI technique that is often used for expert systems. iGen was designed with the goal of being able to generate management alternatives for virtually any FEM problem. The prescription generator is not designed for, adapted to, focused on—and ideally not limited to—any specific region, landscape, forest condition, projection method, or yield function. Instead, it aims to maximize generality, enabling it to address a broad range of FEM problems. The goal is that practitioners and researchers who do not have and do not want to develop their own alternative generator can use iGen as a prescription generator for their problem instances. For those who choose to develop their own alternative generators, we hope that the concepts and algorithms we propose in this paper will be useful in designing their own systems. iGen’s flexibility can be attributed to three key features. First, users can define the state variable vector for management units according to the available data, models (production functions), and objectives of their problem instance. Second, users also define the types of interventions that can be applied to each type of management unit and create a rule base describing the conditions under which each intervention can be applied. Finally, users specify the equations of motion that determine how the state vector for each management unit will be updated over time, depending on which, if any, interventions are applied. Other than this basic structure, virtually everything in an iGen problem instance is user-defined. iGen uses these key elements to simulate all possible management prescriptions for each management unit and stores the resulting information in a database that is structured to efficiently store the output data from these simulations and to facilitate the generation of optimization models for ultimately determining the Pareto frontier for a given FEM problem. This article introduces iGen, illustrating its concepts, structure, and algorithms through two FEM example problems with contrasting forest management practices: natural regeneration with shelterwood harvests and plantation/coppice. For data and iGen source programs, visit github.com/SilvanaNobre/iGenPaper. Full article

Equilibrium propagation (EP) has been proposed recently as a new neural network training algorithm based on a local learning concept, where only local information is used to calculate the weight update of the neural network. Despite the advantages of local learning, numerical iteration for solving the EP dynamic equations makes the EP algorithm less practical for realizing edge intelligence hardware. Some analog circuits have been suggested to solve the EP dynamic equations physically, not numerically, using the original EP algorithm. However, there are still a few problems in terms of circuit implementation: for example, the need for storing the free-phase solution and the lack of essential peripheral circuits for calculating and updating synaptic weights. Therefore, in this paper, a new analog circuit technique is proposed to realize the EP algorithm in practical and implementable hardware. This work has two major contributions in achieving this objective. First, the free-phase and nudge-phase solutions are calculated by the proposed analog circuits simultaneously, not at different times. With this process, analog voltage memories or digital memories with converting circuits between digital and analog domains for storing the free-phase solution temporarily can be eliminated in the proposed EP circuit. Second, a simple EP learning rule relying on a fixed amount of conductance change per programming pulse is newly proposed and implemented in peripheral circuits. The modified EP learning rule can make the weight update circuit practical and implementable without requiring the use of a complicated program verification scheme. The proposed memristor conductance update circuit is simulated and verified for training synaptic weights on memristor crossbars. The simulation results showed that the proposed EP circuit could be used for realizing on-device learning in edge intelligence hardware. Full article

In the wide scenario of heritage documentation and conservation, the multi-scale nature of digital models is able to twin the real object, as well as to store information and record investigation results, in order to detect and analyse deformation and materials deterioration, especially from a structural point of view. The contribution proposes an integrated approach for the generation of an n-D enriched model, also called a digital twin, able to support the interdisciplinary investigation process conducted on the site and following the processing of the collected data. Particularly for 20th Century concrete heritage, an integrated approach is required in order to adapt the more consolidated approaches to a new conception of the spaces, where structure and architecture are often coincident. The research plans to present the documentation process for the halls of Torino Esposizioni (Turin, Italy), built in the mid-twentieth century and designed by Pier Luigi Nervi. The HBIM paradigm is explored and expanded in order to fulfil the multi-source data requirements and adapt the consolidated reverse modelling processes based on scan-to-BIM solutions. The most relevant contributions of the research reside in the study of the chances of using and adapting the characteristics of the IFC (Industry Foundation Classes) standard to the archiving needs of the diagnostic investigations results so that the digital twin model can meet the requirements of replicability in the context of the architectural heritage and interoperability with respect to the subsequent intervention phases envisaged by the conservation plan. Another crucial innovation is a proposal of a scan-to-BIM process improved by an automated approach performed by VPL (Visual Programming Languages) contribution. Finally, an online visualisation tool enables the HBIM cognitive system to be accessible and shareable by stakeholders involved in the general conservation process. Full article

The whole population of Feutap still collects drinking water from two protected springs, some 1 km away from this small rural agglomeration. For many generations, the only improvement has been the protection of the springs during the 1980s. The resulting high incidence of gastrointestinal infections continues to hinder the socioeconomic development of this mountain community. This dynamic wherein “poverty begets disease, and disease begets poverty” seems endless given the number of water improvement programs and other health-focused campaigns in rural areas of Cameroon since the 1960s. Fortunately, the hydrographic regime of Feutap and its geographical situation enable the implementation of the Kilimanjaro Concept (KC), wherein rainwater is quantitatively harvested, partly infiltrated, and largely stored to (i) meet the whole-year water needs of the population, (ii) create new ecosystems, and (iii) enable irrigated agriculture. This communication prepares the implementation of the KC in Feutap, including the creation of irrigation ponds for agriculture and small farm animals (e.g., goats and sheep). The view is promoted that Feutap is a potential viable space in which life and work are possible, using the existing rainfall and the few natural springs in a sustainable manner. The presented concept can be extended to other hilly small communities with similar hydraulic regimes. Full article

Often, solar power parks are built in remote areas where the provider’s internet connection using the GSM network is insufficient. In addition, in order to monitor the parameters of each solar module, a very dense arrangement of IoT components would be required, as a result of which the speed of the external network would not be sufficient. In solving this problem, a hybrid data transmission network (there are no universal hybrid network concepts proposed in the literature for monitoring the operating parameters of a solar power park) was designed and tested for the monitoring system of the working parameters (voltage, current, etc.) of the solar power plant. This network consists of RF modules, RS458 modules communicating with a twisted pair cable, a GSM module, etc. PIC series microcontrollers with original programming code written in the C language were used to ensure the operation of the monitoring system and the hybrid data network. The data of the operating parameters of the solar power plant are stored centrally on a server, in a MySQL database. The central server has the ability to display data not only on the graphical output device, but also to transmit it to mobile devices using the Android operating system. During the testing of this network, observations of the working parameters of the 870 W solar power plant were made. Observations lead to the conclusion that such a network can be fully used in solar power parks as an alternative to the GSM network. Analyzing the data, it was found that the efficiency of bifacial type batteries is about 15–20% higher than that of traditional, silicon-based solar batteries. The voltammetric characteristics of a bifacial type battery, a new silicon battery and a 10-year-old battery basically match, which means that the silicon active material of all types of batteries has a similar alloying degree and the same internal resistance. Full article

This article provides a detailed analysis of the transfer of a key cluster of ideas from mathematical logic to computing. We demonstrate the impact of certain of Turing’s logico-philosophical concepts from the mid-1930s on the emergence of the modern electronic computer—and so, in consequence, Turing’s impact on the direction of modern philosophy, via the computational turn. We explain why both Turing and von Neumann saw the problem of developing the electronic computer as a problem in logic, and we describe their joint journey from logic to electronic computation. While much has been written about Turing’s and von Neumann’s individual contributions to the development of the computer, this article investigates less well-known terrain: their interactions and mutual influences. Along the way we argue against ‘logic skeptics’ and ‘Turing skeptics’, who claim that neither logic nor Turing played any significant role in the creation of the modern computer. Full article