Technological Advances Research Articles

Insights from “Advanced Technologies and Practices in the Built Environment and Cultural Heritage”

Insights from “Advanced Technologies and Practices in the Built Environment and Cultural Heritage”

Biomechanical and machine learning approaches to automating the identification of musical styles and emotions through human motion analysis

This study explores the intricate relationship between biomechanical movements and musical expression, focusing on the identification of musical styles and emotions. Violin performance is characterized by complex interactions between physical actions—such as bowing techniques, finger placements, and posture—and the resulting acoustic output. Recent advances in motion capture technology and sound analysis have enabled a more objective examination of these processes. However, the current literature frequently addresses biomechanics and acoustic features in isolation, lacking an integrated understanding of how physical movements translate into specific musical expressions. Machine Learning (ML), particularly Long Short-Term Memory (LSTM) networks, provides a promising avenue for bridging this gap. LSTM models are adept at capturing temporal dependencies in sequential data, making them suitable for analyzing the dynamic nature of violin performance. In this work, they have proposed a comprehensive model that combines biomechanical analysis with Mel-spectrogram-based LSTM modeling to automate the identification of musical styles and emotions in violin performances. Using motion capture systems, Inertial Measurement Units (IMUs), and high-fidelity audio recordings, we collected synchronized biomechanical and acoustic data from violinists performing various musical excerpts. The LSTM model was trained on this dataset to learn the intricate connections between physical movements and the acoustic features of each performance. Key findings from the study demonstrate the effectiveness of this integrated approach. The LSTM model achieved a validation accuracy of 92.5% in classifying musical styles and emotions, with precision, recall, and F1-score reaching 94.3%, 92.6%, and 93.4%, respectively, by the 100th epoch. The analysis also revealed strong correlations between specific biomechanical parameters, such as shoulder joint angle and bowing velocity, and acoustic features, like sound intensity and vibrato amplitude.

Into the Revolution of NanoFusion: Merging High Performance and Aesthetics by Nanomaterials in Textile Finishes

AbstractThe field of technical textiles has grown significantly during the last two decades, with a focus on functionality rather than aesthetics. However, the advancement of NanoFusion technology provides a novel potential to combine better functionality and aesthetic value in textile finishes. NanoFusion incorporates nanoparticles into textile treatments to improve waterproofing, stain resistance, durability, and breathability. This is performed without affecting the textile's visual appeal or aesthetics and may even improve them. This textile finishing revolution is expected to impact industries such as athletics, outdoor clothing, car upholstery, and luxury fashion. It offers cutting‐edge functionality while maintaining style and design integrity. Furthermore, the use of nanoparticle textile coatings opens up new opportunities for personalization and modification. Manufacturers and designers can now experiment with different color combinations, patterns, and textured finishes while maintaining performance characteristics. NanoFusion technology has the potential to transform the textile industry by providing hitherto unattainable levels of performance and aesthetics. This study reviews the current state of the art in nanofinishes for garment textiles, focusing on their many varieties, techniques, mechanisms, and applications. In addition, it addresses significant concerns such as sustainability and the environmental footprint, paving the way for a new era in textile manufacturing.

Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment

Objective. Vision restoration approaches, such as prosthetics and optogenetics, provide visual perception to blind individuals in clinical settings. Yet their effectiveness in daily life remains a challenge. Stereotyped quantitative tests used in clinical trials often fail to translate into practical, everyday applications. On the one hand, assessing real-life benefits during clinical trials is complicated by environmental complexity, reproducibility issues, and safety concerns. On the other hand, predicting behavioral benefits of restorative therapies in naturalistic environments may be a crucial step before starting clinical trials to minimize patient discomfort and unmet expectations.Approach. To address this, we leverage advancements in virtual reality technology to conduct a fully immersive and ecologically valid task within a physical artificial street environment. As a case study, we assess the impact of the visual field size in simulated artificial vision for common outdoor tasks.Main results. We show that a wide visual angle (45°) enhances participants' ability to navigate and solve tasks more effectively, safely, and efficiently. Moreover, it promotes their learning and generalization capability. Concurrently, it changes the visual exploration behavior and facilitates a more accurate mental representation of the environment. Further increasing the visual angle beyond this value does not yield significant additional improvements in most metrics.Significance. We present a methodology combining augmented reality with a naturalistic environment, enabling participants to perceive the world as patients with retinal implants would and to interact physically with it. Combining augmented reality in naturalistic environments is a valuable framework for low vision and vision restoration research.

Diagnostic Techniques for Infantile Subglottic Hemangiomas: A Scoping Review.

Infantile subglottic hemangioma (SGH) poses a risk of airway compromise if untreated. Traditionally, operative endoscopy (OH) diagnoses SGH, but since the discovery of beta-blockers' efficacy in treating infantile hemangiomas (IHs) in 2008, and advances in endoscopic technology, nonoperative methods have emerged. This review identifies endoscopic practices for diagnosing and monitoring infantile SGH during the oral beta-blocker treatment era. A comprehensive literature search in October 2022 and August 2023 covered PubMed, Embase, Cochrane Library, SCOPUS, and Web of Science. The search was limited to English-language studies published since 2008, considering this when propranolol was demonstrated as an effective treatment option for IH. The articles were screened for relevance based on predefined inclusion and exclusion criteria. After inclusion and exclusion criteria, sixty final studies were identified, describing 240 cases of infantile SGH. Most children were diagnosed using OE alone (73.3%; n = 176/240), 23.3% (n = 56/240) using office-based laryngoscopy procedures (OBPs) followed by OE, 3.3% using OBP alone (n = 8/240). There were no reported diagnostic endoscopy-related complications. Twenty-nine studies described using endoscopy plus diagnostic imaging to either confirm an SGH lesion, characterize the extent of disease spread, or rule out other causes of presenting symptoms. The proportion of infants diagnosed with OE alone decreased from 2008 to 2023. Operative endoscopy remains the SGH diagnostic standard, but OBP adoption is increasing. Further research is needed to determine the optimal SGH diagnosis and management approach. NA Laryngoscope, 2024.

Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions

The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about the potential and challenges of integrating AI into audiological practice. The PubMed, Cochrane, and Google Scholar databases were searched for articles published in English from 1990 to 2024 with the following query: “(audiology) AND (“artificial intelligence” OR “machine learning” OR “deep learning”)”. The PRISMA extension for scoping reviews (PRISMA-ScR) was followed. The database research yielded 1359 results, and the selection process led to the inclusion of 104 manuscripts. The integration of AI in audiology has evolved significantly over the succeeding decades, with 87.5% of manuscripts published in the last 4 years. Most types of AI were consistently used for specific purposes, such as logistic regression and other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) for automated audiometry and clinical predictions; convolutional neural networks for radiological image analysis; and large language models for automatic generation of diagnostic reports. Despite the advances in AI technologies, different ethical and professional challenges are still present, underscoring the need for larger, more diverse data collection and bioethics studies in the field of audiology.

CD137 Protein Expression Pattern Determines the Functional Role of Galectin-9 in Colorectal Cancer.

The rapid advancement of single-cell sequencing technology has generated extensive data, providing critical resources for colorectal cancer (CRC) research. This study conducts a detailed analysis of CRC single-cell sequencing data to develop a novel clinical prognostic tool and explore potential therapeutic targets for the LGALS9 gene. Using the Scissor algorithm, we created a CRC prognostic scoring system (SDRS) based on 13 key genes, with particular focus on LGALS9 and its protein, Galectin-9, in mice CRC model with altered CD137 expression. Our findings demonstrate that the SDRS accurately reflects clinical and pathological features of CRC patients, acting as an independent predictor of outcomes. LGALS9 expression is generally reduced in CRC tissues and is associated with poorer prognosis. We also observed a strong positive correlation between LGALS9 and CD137 expression, with CD137 showing significant variability in CRC tissues. In mouse models with CD137 overexpression, Galectin-9 treatment led to notable antitumor effects and increased infiltration of activated T cells. In contrast, in CD137-deficient models, Galectin-9 promoted tumor growth with limited T cell presence. These results suggest that the role of LGALS9 in CRC may depend on CD137 expression, highlighting the potential of LGALS9 as a therapeutic target. CD137 levels may serve as a key indicator for predicting the effectiveness of this treatment strategy.

Internet terminology in modern German: semantics and structure

Abstract The article presents an in-depth analysis of the formation of terminology in the professional language of the Internet in German and offers predictions about its future development, in line with the evolution of this area of knowledge. Drawing from a corpus of about 8,000 terms and term combinations, the authors explore the dynamics of German Internet terminology, propose a timeline for the emergence of these terms in relation to advancements in science and technology, and identify key methods of term formation along with their semantic characteristics. The primary source of expansion in German Internet terminology comes from Anglo-American borrowings, which, during their adaptation into German, have undergone structural and semantic assimilation. The main methods of term formation within the examined terminology are compounding (with a predominance of binary structures), derivation, and abbreviation. German Internet terminology is characterized by synonymy and polysemy, reflecting the dynamic nature of network technology development. A distinctive feature of this terminology is the formal redundancy in expressing a single concept, leading to the formation of synonymous sets. The uniqueness of the semantic paradigm of these terms lies in the extralinguistic factors that influence terminological synonymy, polysemy, and the broader system of structural relations in German Internet terminology.

Cross-comparison of gut metagenomic profiling strategies.

The rapid advancements in sequencing technologies and bioinformatics have enabled metagenomic research of complex microbial systems, but reliable results depend on consistent laboratory and bioinformatics approaches. Current efforts to identify best practices often focus on optimizing specific steps, making it challenging to understand the influence of each stage on microbial population analysis and compare data across studies. This study evaluated DNA extraction, library construction methodologies, sequencing platforms, and computational approaches using a dog stool sample, two synthetic microbial community mixtures, and various sequencing data sources. Our work, the most comprehensive evaluation of metagenomic methods to date. We developed a software tool, termed minitax, which provides consistent results across the range of platforms and methodologies. Our findings showed that the Zymo Research Quick-DNA HMW MagBead Kit, Illumina DNA Prep library preparation method, and the minitax bioinformatics tool were the most effective for high-quality microbial diversity analysis. However, the effectiveness of pipelines or method combinations is sample-specific, making it difficult to identify a universally optimal approach. Therefore, employing multiple approaches is crucial for obtaining reliable outcomes in microbial systems.

Data-Driven Day-Ahead Dispatch Method for Grid-Tied Distributed Batteries Considering Conflict Between Service Interests

The rapid advancement of battery technology has drawn attention to the effective dispatch of distributed battery storage systems. Batteries offer significant benefits in flexible energy supply and grid support, but maximising their cost-effectiveness remains a challenge. A key issue is balancing conflicts between intentional network services, such as energy arbitrage to reduce the overall electricity costs, and unintentional services, like fault-induced unintentional islanding. This paper presents a novel dispatch methodology that addresses these conflicts by considering both energy arbitrage and unintentional islanding services. First, demand profiles are clustered to reduce uncertainty, and uncertainty sets for photovoltaic (PV) generation and demand are derived. The dispatch strategy is originally formulated as a robust optimal power flow problem, accounting for both economic benefits and risks from unresponsive islanding requests, alongside energy loss reduction to prevent a battery-induced artificial peak. Last, this paper updates the objective function for adapting possible long-run competition changes. The IEEE 33-bus system is utilised to validate the methodology. Case studies show that, by considering the reserve for possible islanding requests, a battery with limited capacity will start to discharge after a demand drop from the peak, leading to the profit dropping from USD 185/day (without reserving capacity) to USD 21/day. It also finds that low-resolution dynamic pricing would be more appropriate for accommodating battery systems. This finding offers valuable guidance for pricing strategies.

A Multi-Scale Approach to Early Fire Detection in Smart Homes

In recent years, advancements in smart home technologies have underscored the need for the development of early fire and smoke detection systems to enhance safety and security. Traditional fire detection methods relying on thermal or smoke sensors exhibit limitations in terms of response time and environmental adaptability. To address these issues, this paper introduces the multi-scale information transformer–DETR (MITI-DETR) model, which incorporates multi-scale feature extraction and transformer-based attention mechanisms, tailored specifically for fire detection in smart homes. MITI-DETR achieves a precision of 99.00%, a recall of 99.50%, and a mean average precision (mAP) of 99.00% on a custom dataset designed to reflect diverse lighting and spatial conditions in smart homes. Extensive experiments demonstrate that MITI-DETR outperforms state-of-the-art models in terms of these metrics, especially under challenging environmental conditions. This work provides a robust solution for early fire detection in smart homes, combining high accuracy with real-time deployment feasibility.

A Review on Modular Multi-level Converter Based HVDC Systems

Modular Multilevel Converters (MMCs) have emerged as a promising technology for High Voltage Direct Current (HVDC) transmission systems, offering several advantages such as reduced harmonic distortion, high voltage capability and modularity. This paper presents a comprehensive review of MMC-based HVDC systems, focusing on their applications, control strategies and challenges. The paper begins by discussing the basic principles and structure of MMCs, highlighting their modular design and operation. The paper delves into the control strategies employed in MMC-HVDC systems, emphasizing the importance of coordinated control between the AC and DC sides to ensure stable and efficient operation. Furthermore, the paper addresses the challenges associated with MMC-HVDC systems, such as fault ride-through capability, harmonic interactions and grid integration. It highlights recent advancements in control techniques and technologies that are being developed to address these challenges. The paper provides a valuable overview of MMC-based HVDC systems, highlighting their potential benefits and the ongoing research efforts to overcome their challenges. As the demand for renewable energy sources and long-distance power transmission increases, MMC-HVDC systems are poised to play a crucial role in shaping the future of the power grid

Influence of (ultra-)processing methods on aquatic proteins and product quality.

Aquatic products are a high-quality source of protein for humans, and the changes in protein during aquatic product processing are crucial for nutritional value, product performance, and consumer health. With the advancement of science and technology, aquatic product processing methods have become increasingly diverse. In addition to traditional methods such as thermal processing (steaming, roasting, and frying) and pickling, emerging non-thermal processing technologies, such as high pressure, ultrasound, and irradiation, are also being applied. During (ultra-)processing, aquatic products undergo complex biochemical reactions, among which protein oxidation significantly affects the quality of aquatic products. Protein oxidation can alter the molecular structure of proteins, thereby changing their functional properties and ultimately impacting product quality. This paper primarily explored the effects of protein changes under different processing methods on aquatic product quality and human health, as well as techniques for controlling protein oxidation. It aims to provide a theoretical basis for selecting appropriate processing methods, improving aquatic product quality, and controlling protein oxidation in aquatic products, and to offer scientific guidance for practical production.

Digital humanists in the modern international business world—Bulgarian context

Digital humanists play a crucial role in the modern international business world by combining the principles of regular employees with the advancements of digital technologies to address a variety of challenges and opportunities. They are specific labour forces that are driving digital transformation and innovation in the modern international business world. This article presents some key impacts the digital humanists have on global business practices and strategies particularly in the area of international business. Using the advantages, the digital era in which we live provides, digital humanists are becoming part of the international workforce but in a different and non-standard way. The main purpose of this article is to highlight some of the main characteristics of this modern workforce, the advantages and disadvantages of such an approach. It should be noted that the article is part of a scientific research dedicated to the changes in the international human resource management due to the technology developments and digitalization of the international business. The main research methods used are literature summary and analysis, comparative analysis, focus group interviews.

Masterbatch Natural Rubber—Innovative Asphalt Cement Additive for Sustainable Flexural Pavements

The mechanical performance of Masterbatch Natural Rubber (MNR)-modified asphalt concrete (MNR-AC) was investigated and is presented in this paper. When compared to conventional asphalt concrete (AC), MNR-AC exhibits significantly superior performance across key mechanical parameters, including Marshall stability, indirect tensile strength (ITS), resilient modulus (IT Mr), indirect tensile fatigue life (ITFL), and rutting resistance. The most pronounced enhancements are observed at the optimal dry rubber to asphalt cement (r/b) ratio of 3%, at which MNR-AC demonstrates peak performance in all evaluated tests. The fatigue distress models for MNR-AC and AC reveal distinct logarithmic relationships, with an intersection point occurring at an r/b ratio of approximately 3%. This suggests that MNR-AC with an r/b ratio of 3% or less exhibits a markedly superior fatigue life compared to conventional AC under equivalent applied-stress conditions. MNR offers significant practical advantages over liquid natural rubber, including more consistent mixing, and simplified storage and transportation, positioning it as a promising and sustainable advancement in pavement material technology.

High‐Performance Supercapacitor Electrodes Based on Porosity‐Controllable Carbon Paper by Centrifugal Spinning

Carbon paper is widely utilized in supercapacitors primarily for its notable attributes, including high specific surface area, commendable electrical conductivity, and excellent chemical stability. Then investigate the effect of carbon paper with different porosities as supercapacitor substrates on the electrochemical performance of electrodes. Meanwhile, tungsten oxide is grown on the surface of carbon paper using the hydrothermal method to test the electrochemical performance of the composite electrode. The prepared carbon paper and oxygen‐deficient tungsten oxide (WOx) composite electrode (CP@WOx) exhibit an area‐specific capacitance of 915.8 mF/cm² at a current density of 5 mA/cm². In addition, the electrode exhibits good cycling stability. After 20,000 cycles, the capacitance remains 104.1% of the original capacity at 50 mA/cm² current density. Solid‐state symmetric supercapacitors assembled using CP@WOx electrode exhibit excellent performance in terms of surface energy density of 6.25 µWh/cm2(at a power density of 0.6 mW/cm2) and maintain 100.4% of their original capacity after 7000 charge/discharge cycles. Relying on the higher productivity advantage of centrifugal spinning technology over electrostatic spinning technology and other preparation processes, this study develops a new way of thinking for the large‐scale production of composite electrode materials, which has more considerable potential for large‐scale development.

Recent innovations in land capability classification for sustainable development: a brief overview.

Land is a finite resource that must be managed wisely to ensure its sustainability. Consequently, land evaluation has become essential. Identifying and utilizing productive capacity of land efficiently and profitably is crucial; otherwise, resource degradation can severely impact natural ecosystems and food production. Over the years, various methodologies have been employed to assess land resources, and one such method is the Land Capability Classification (LCC). LCC is a widely used and fundamental approach to land-use planning, traditionally assessing land based on its intrinsic qualities and climate. This study aims to highlight new approaches and developments in land evaluation techniques. It provides a brief overview of recent technological and scientific advancements integrated into land evaluation. The findings suggest that LCC alone is inadequate for precise land assessment, emphasizing the need to integrate new technologies. Remote Sensing (RS) and Geographic Information System (GIS) technologies are becoming increasingly significant. Integrating various software, decision-making systems, and mathematical models can also enhance the accuracy of land assessment results. The continuous advancement of GIS and remote sensing technologies is paving the way for new tools to facilitate natural resource mapping, appraisal, surveillance, and management. Utilizing these technologies for future projections will be highly beneficial in accurately assessing the long-term impacts of current land management practices.

Electroencephalography-Based Brain-Computer Interfaces in Rehabilitation: A Bibliometric Analysis (2013–2023)

EEG-based Brain-Computer Interfaces (BCIs) have gained significant attention in rehabilitation due to their non-invasive, accessible ability to capture brain activity and restore neurological functions in patients with conditions such as stroke and spinal cord injuries. This study offers a comprehensive bibliometric analysis of global EEG-based BCI research in rehabilitation from 2013 to 2023. It focuses on primary research and review articles addressing technological innovations, effectiveness, and system advancements in clinical rehabilitation. Data were sourced from databases like Web of Science, and bibliometric tools (bibliometrix R) were used to analyze publication trends, geographic distribution, keyword co-occurrences, and collaboration networks. The results reveal a rapid increase in EEG-BCI research, peaking in 2022, with a primary focus on motor and sensory rehabilitation. EEG remains the most commonly used method, with significant contributions from Asia, Europe, and North America. Additionally, there is growing interest in applying BCIs to mental health, as well as integrating artificial intelligence (AI), particularly machine learning, to enhance system accuracy and adaptability. However, challenges remain, such as system inefficiencies and slow learning curves. These could be addressed by incorporating multi-modal approaches and advanced neuroimaging technologies. Further research is needed to validate the applicability of EEG-BCI advancements in both cognitive and motor rehabilitation, especially considering the high global prevalence of cerebrovascular diseases. To advance the field, expanding global participation, particularly in underrepresented regions like Latin America, is essential. Improving system efficiency through multi-modal approaches and AI integration is also critical. Ethical considerations, including data privacy, transparency, and equitable access to BCI technologies, must be prioritized to ensure the inclusive development and use of these technologies across diverse socioeconomic groups.

Spatiotemporal variation in grain production performance and efficiency of the cultivated landscapes in Upper Blue Nile Basin of Ethiopia: the impact of residual moisture-based farming on water and food security

Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.

Upper Palaeolithic fishing techniques: Insights from the engraved plaquettes of the Magdalenian site of Gönnersdorf, Germany.

The ~15,800 year-old Magdalenian site of Gönnersdorf, in Germany, has produced 406 engraved schist plaquettes which have been extensively studied in the past. The introduction of advanced imaging technologies, notably Reflectance Transformation Imaging (RTI), has now precipitated a re-evaluation of these artifacts, uncovering nuanced depictions of fishing practices previously unrecorded for the Upper Palaeolithic. Our investigation harnesses RTI to elucidate fine engraving details on the plaquettes, revealing depictions of fish and accompanying grid motifs. The analytical process enabled by RTI has exposed an intricate link between the grid patterns and fish figures, showing that they were a deliberate combination portraying the use of fishing nets. This discovery posits a significant departure from earlier interpretations of the site's iconography, which predominantly emphasized more naturalistic representations of fauna. Furthermore, these findings illuminate aspects of Magdalenian cultural praxis, suggesting that representations of aquatic life and fishing technologies were not merely utilitarian in nature but were embedded within a broader symbolic framework. This study enhances our comprehension of Magdalenian peoples' interaction with the aqueous milieu, revealing a sophisticated symbiosis between ecological adaptation and artistic expression.