The building materials choice and construction methods are critical to ensure the urban infrastructure’s safety, sustainability, and pliability. This study presents a comprehensive comparative seismic analysis of steel and reinforced cement concrete (RCC) frame structures for a residential building in Kabul, Afghanistan. Owing to the seismic vulnerability of the area and shifting construction trends, the performance of the two structural systems is compared using a 3D ETABS model for the most dominant seismic parameters. The study aims to enlighten planners, engineers and policy makers with evidenced-base facts to guide appropriate choice of structural systems that enhance sustainable city development. The key findings show that the Steel buildings, exhibit improved seismic performance due to their lightness, increased ductility, and stiffness-distributed uniformly. In addition, steel frames had significant cost benefits, with this study reporting up to 41.28% greater cost-effectiveness over RCC. The conclusion shows that, although both systems are feasible, steel frame buildings are more efficient and durable for seismic areas and Kabul city.
The explosion in digital medical data makes it crucial to design intelligent assistants capable of interrogating this information reliably, quickly and contextually. In this article, we propose a novel comparative approach between two forms of knowledge representation: traditional tabular data and semantic ontologies. Based on the same clinical dataset concerning diabetic patients, we have implemented a dual structuring: a tabular version and an RDF ontology modelled with Protégé. An intelligent assistant, interfaced with the GPT-4 API, was designed to query both formats. The originality of our contribution lies in the experimental parallelisation of these two data models, through a standardised series of 300 questions, classified according to three levels of increasing complexity. This methodology enables us to objectively assess the robustness, responsiveness and inference capacity of each approach. The results are unequivocal: the ontology systematically outperforms the tabular format, with exact response rates ranging from 97% to 100%, compared with 34% to 81% for the tabular format. In addition, the ontological approach shows better tolerance of ambiguous queries and stability in semantic interpretation. Over and above performance, this study highlights the potential of knowledge graphs as an architectural foundation for future medical decision support systems. It also paves the way for hybrid systems that combine the accessibility of tables with the semantic power of ontologies - a perspective that has so far been little explored in the context of connected healthcare.
This paper investigates the pyrolysis of five different oxygen-containing plastic wastes and evaluates the possibility of utilizing such plastics in transportation fuel production. Pyrolysis runs were performed in a batch reactor and the plastic waste types include polyethylene terephthalate (PET), polyoxymethylene (POM), polycarbonate (PC), polyvinyl butyral (PVB), and polyphenyl ether (PPE). Liquid products from PC, PVB, and PPE were further processed by atmospheric distillation to extract the 20-200 °C fractions. These fractions were analyzed by GC-MS to identify major compounds. PET and POM did not result in liquid products. Instead, solid deposits formed in the system, causing potential operational instability. Based on the results, three oxygen-containing plastic types were identified as promising candidates in liquid fuel production.
As I analyse the Intelligent Manufacturing Systems we can realise that the fundamental of the machining parts the main element is the holon/element. If we look at the logistical science the fundament is the supply chain. in mathematics the fundament is the mathematical formulas equations. In this article my main objective to analogize these 3 parts in an other objective [5][6].
This paper is based on the use of microcontroller systems to help optimize irrigation systems in order to improve crop production in Sahelian zones. In this paper, we implement an automatic device using sensors to monitor environmental data such as soil and air conditions in real time, microcontrollers to make irrigation decisions based on these data, and modules to store data from the sensors. Analysis of this data enables informed irrigation and crop management decisions to be made. This approach enables efficient irrigation management by precisely adjusting the amount of water supplied to crops, minimizing human intervention and thus reducing costs and environmental impacts while maximizing crop yields. The results obtained in this study show that the system works well, and justify the possibility of adjusting system parameters according to crop type.
The presence of kimberlites in the Democratic Republic of Congo has been known since buttgenbach reported a typical ‘yellow ground’ in Katanga as early as 1908, and prospecting work before and after 1914 had already identified twenty-four pipes in the province. In eastern Kasai, the local Kimberlite, which crosses the entire Precambrian (Socle and its overburden) as well as the sandstone Mesozoic and is covered by the Tertiary, is found in two groups, namely the Northern Group, also known as the Bakwanga Kimberlites, and the Southern Group, known as the Bakwa-Kalonji Kimberlites. With the same age, dated to the Cretaceous and quantified at 71.3 million years, a comparative scientific study of the two groups of kimberlites in East Kasai is of interest in order to gain an insight into the primitive magmatism that created them. To this end, we have set ourselves the objective of taking stock of geochemical knowledge of the Bakwanga and Bakwa-Kalonji kimberlite massifs (accessible to our sampling) in order to better interpret and compare, from a petrological point of view, the genesis, composition and nature of these kimberlite intrusions.Based on our studies, we found that the Kimberlitic formations studied (Bakwanga and Tshibwe Kimberlite) are all characteristic of ultrabasic (or silica-undersaturated), mafic and not ultramafic, hyperalkaline, ultrapotassic, volatile-rich (H2O and CO2) magmatism of the lamproite or orangite group, showing clear crustal alteration or contamination and originating in the upper mantle. These two groups differ in terms of the lithology of the host rock (limestone and/or dolomite for the northern group and sandstone for the southern group). In terms of the proportion of xenoliths in the respective kimberlites, there is a total absence of sedimentary xenoliths, particularly limestone and dolomite, and incidentally sandstone, in the southern kimberlites. Gabbro-dioritic xenoliths are more abundant in the southern group than in the north, and xenoliths from basement rocks are more abundant and dominant in the north than in the south.)
Ultrafiltration is a key technology for treating dairy wastewater; however, its efficiency is often hindered by critical challenges such as membrane fouling and concentration polarization. To mitigate these issues, one effective approach involves optimizing operational parameters to enhance system performance and longevity. In this study the influence of key operational parameters on the performance of a lab-scale low-pressure ultrafiltration membrane system for treating dairy wastewater model were investigated. The optimization focused on three critical factors: transmembrane pressure (TMP), stirring speed, and membrane molecular weight cut-off (MWCO). Key performance metrics, including permeate flux, membrane retention efficiency, and total, reversible, and irreversible membrane resistances, were analyzed. The results showed that the optimal conditions were identified using a 20 kDa polyethersulfone membrane, with a TMP of 0.3 MPa and a stirring speed of 400 rpm. Statistical analysis was conducted to further refine and validate the optimization of these parameters.
The article presents the 2024 ranking of Hungarian researchers in the field of Scientometrics. The ranking is presented primarily according to the h-index of researchers. Researchers with matching h-index are ranked by the number of citations. The ranking list includes 12 researchers. The h-index can be determined from Web of Science, Scopus, Google Scholar, the Hungarian Scientific Works Repository and the programs Tud-O-Méter, Publish or Perish. The ranking is edited using the Google Scholar web database.
The growing demand for accurate, real-time indoor positioning in healthcare environments has led to the exploration of alternative localization technologies beyond traditional GPS. Hospitals face the challenge of tracking mobile diagnostic equipment and coordinating personnel under tight operational constraints. This paper presents a practical implementation of an indoor positioning system (IPS) within an outpatient medical facility in Hungary, designed to track the movement of a shared mobile ultrasound device. Three technologies were investigated: Wi-Fi (using RSSI fingerprinting), Bluetooth Low Energy (BLE) beacons, and Ultra-Wideband (UWB) with ToF-based trilateration. All solutions were implemented using ESP32 microcontrollers, supported by custom Arduino code and MATLAB for data analysis. Results show significant differences in accuracy and reliability, with UWB proving superior for precision-demanding medical use cases.
The future of augmented reality (AR) application development is being shaped by emerging trends and expanding opportunities across various industries. In this study, key advancements in AR technology, including artificial intelligence integration, cloud computing, and 5G connectivity, are examined. The increasing adoption of AR in sectors such as healthcare, education, retail, and manufacturing are highlighted, emphasizing its role in enhancing user experiences and operational efficiency. The challenges related to hardware limitations, data security, and user privacy are also discussed. A review of current development frameworks and platforms is conducted, showcasing the evolution of AR tools and their impact on accessibility for developers. The shift toward web-based and cross-platform AR solutions is explored, demonstrating the growing demand for seamless and scalable applications. Additionally, opportunities for innovation in AR content creation, user interaction, and enterprise applications are identified. Through an analysis of these trends, it is concluded that AR development will continue to evolve, driven by advancements in computing power, sensor technology, and user demand. It is suggested that collaboration between researchers, developers, and businesses will play a crucial role in overcoming existing barriers and unlocking the full potential of AR applications in the future.
The general objective of this work is to determine the efficiency of the flow of hydrocarbons in the Tshiende 07 Well. To do this, we have set ourselves the following specific objectives: To carry out a study of the performance of Tshiende 07 wells; Calculate the productivity index of the Tshiende 07 well; Calculate the maximum flow rate in the Tshiende 07 well; Draw the Inflow Performance Relationship (IPR) curve; Determine the hydraulic parameters of the flow of hydrocarbons in a well; Draw the Tubing Performance Relationship (TPR) curve; Apply nodal analysis in the TS-07 well. As we have developed the different mathematical approaches for the optimization of the flow of hydrocarbons in a producing well, we exploited the Poettman-Carpenter mathematical approach, and since iterative calculations of this approach are tedious, we used the Poettmann-carpenter BH-xls software to know the evolution of the pressure in the tubing as a function of depth and Botthom Oil Nodal BH-xls to draw the Tubing Performance Relationship (TPR) curve and to determine the operating points between the curve IPR and TPR during nodal analysis.
This logistics case review delves into Laos’ various waste management problems highlighting different aspects of garbage collection and handling from an operational standpoint. This study involves an integrated approach taking into consideration both peer reviewed journal articles and results of primary research, as well as practical suggestions that are highly relevant to the country’s social-economic context as well as environmental conditions. The findings of this research improve comprehension of the main threats facing Laos and suggest environmentally friendly approaches for mitigation of adverse consequences of inadequate waste management.
The integration of smart technology into heating systems has led to increased efficiency and remote management capabilities. However, these advancements also introduce security vulnerabilities, especially in critical infrastructure. This paper explores the development of an IoT-based heating control system utilizing MQTT, ESP8266 microcontrollers, and Node-RED for centralized management. The study examines system design, identifies potential security threats, and proposes strategies to mitigate risks. Additionally, real-world case studies illustrate how cybersecurity weaknesses have impacted similar IoT applications in critical infrastructure, reinforcing the importance of implementing robust security measures.
The laboratory tests necessary for oil and gas production were carried out under realistic conditions. Due to ever deeper drilling, this can mean a pressure of up to 1000-2000 bar, and a temperature of 200-300 °C. The creation of these conditions is carried out with target machines, which are usually partially automated measuring devices. In addition to creating extreme environmental properties, other substances are often present during the measurement, such as mercury or hydrogen, justifying that the equipment can be controlled remotely with an IT system. In addition to the remote control and supervision of the measurement, the connected IT system also monitors it. The article deals with the communication solutions of the IT system of target machines used in the gas and oil industry.
In order to fill the glaring gaps in the geological data for the Mbanga region and surrounding area, in the Province of Kongo-Central in DR Congo, geological investigations were carried out in the field over a three-week period. The results obtained, coupled with those from the laboratory, led to the identification of eight different lithofacies in the study area, namely: metaryolites, sericite schists and biotitose schists, all with grey to greenish grey facies. This work consists of a detailed petrographic study to identify the different facies of the West Congo Supergroup belonging to the Mayumbian Group and the Zadinian Group. The geology of the Mbanga sector and its surroundings is made up of metamorphic layers of volcanic and sedimentary origin. The various rock formations in our study area are grouped into two West Congo Supergroup groups; the metarhyolite formation belongs to the Tshela/Seke-Banza Group (Mayumbian) and the others belong to the Matadi Group (Zadinian).
Xanthan is microbial polysaccharide with outstanding rheological properties, non-toxic nature, biodegradability, and biocompatibility. This biopolymer is widely used in food, biomedical, pharmaceutical, petrochemical, chemical and textile industry. Industrial xanthan production is generally conducted by aerobic submerged cultivation of Xanthomonas campestris strains on the media with glucose or sucrose under optimal conditions. Results from previous research indicate that xanthan can be successfully produced on media containing crude glycerol from biodiesel industry by different Xanthomonas species. The aim of this study was to examine the course of xanthan biosynthesis by the reference strain X. campestris ATCC 13951 in lab-scale bioreactor on medium containing crude glycerol generated in domestic biodiesel factory. The bioprocess was monitored by the analysis of cultivation medium samples taken in predetermined time intervals, and its success was estimated based on the xanthan concentration in the medium, separated biopolymer average molecular weight and degree of nutrients conversion. At the end of bioprocess, cultivation medium contained 12.34 g/L of xanthan with the average molecular weight of 3.04∙105 g/mol. Within this study, the achieved degree of glycerol, total nitrogen and total phosphorous conversion were 75.91%, 53.27% and 38.96%, respectively.
Nowadays, the fitness industry has become a growing industry alongside the nutritional supplements industry within the food industry. Small and large companies are fighting for consumers. They offer products tailored to different training goals, whether sold online or offline. Companies are developing their marketing strategies by observing consumer preferences and habits. But do we need supplementation? Are the products on the market safe? What do we even mean by a food supplement? Is it a good idea to buy supplements that are in line with the latest trends? In this study we will show whether or not supplementation is really necessary for athletes and what determines whether it is.
In the realm of electronics, the foundational passive components—resistors, inductors, and capacitors—are well-established. However, in 1971, Leon Chua introduced a theoretical fourth element, the memristor, identified by its distinctive characteristic of memristance and its manifestation in a pinched hysteresis loop. This intriguing property suggests potential applications beyond conventional electronics, particularly in modelling hysteresis phenomena across various domains. This paper delves into the exploration of memristance as a mathematical framework for simulating hysteresis in electrical and mechanical systems. We commence by elucidating the theoretical underpinnings of memristance and its hysteresis behaviour, followed by a comprehensive overview of existing hysteresis models. Subsequently, we propose a novel approach that leverages the memristor model to offer enhanced insights and predictive capabilities for hysteresis in these systems. Through analytical examination and simulation studies, we demonstrate the versatility and applicability of the memristor model, underscoring its potential as a universal tool for hysteresis modelling. This research not only broadens the understanding of memristive properties but also opens new avenues for cross-disciplinary applications, ranging from electronic circuit design to mechanical system analysis.
Integration of artificial intelligence (AI) into agriculture has the potential to revolutionise agriculture, but it also presents challenges and risks that must be carefully managed. AI can improve planning, streamline work processes, and improve decision making in crop cultivation and animal husbandry, ultimately leading to higher returns for farmers. However, lack of training and high implementation costs can make it difficult for some farmers to adopt AI, creating a competitive disadvantage and concentrating agricultural resources. Additionally, AI may contribute to unemployment among those with lower skill levels and poses cybersecurity risks that need continuous monitoring. Legal concerns also arise with respect to data ownership and usage rights, with questions about who can access and utilise collected data. Farmers often have to rely on AI systems as "black boxes", with limited understanding of how they work. If these systems fail and cause damage, accountability becomes an important issue. It is crucial to assess the drawbacks and risks of AI implementation in agriculture and educate farmers about these risks to prevent significant damage. Managing these risks effectively and ensuring data accuracy and security are essential in the global adoption of AI in agriculture.
The virtualization systems enable the examination of the system's virtual elements by manufacturers, thus allowing them to be analysed and designed where real-world changes are necessary. Unnecessary planning is reduced by virtual reality, which allows engineers to experiment with changes before the final solution is created. Realistic and risky simulations occurring in the manufacturing environment, such as chemical spills, hazardous machinery, and noisy surroundings, can be simulated through virtual reality training programs without exposing workers to actual danger. In the event of an inevitable occurrence, employees will have usable experience and are more likely to respond appropriately to the situation. The paper presents and describes some of the most important Logistics 4.0 technologies: Internet of Things, robotics and automation, augmented reality, 3D printing and automatic guided vehicles. The aim of this paper is to describe the concept of Logistics 4.0, define its significance, components and technologies using augmented reality.
