bluuebunny/crossref_metadata_2025 huggingface dataset:
Stacked Polarizing Elements for Controlling Parameters of Surface Relief Gratings Written in Photosensitive Materials
Authors: Porfirev Alexey P. , Khonina Svetlana N. , Ivliev Nikolay A. , Porfirev Denis P. , Kazanskiy Nikolay L.
Published: February 2024

Photosensitive materials are widely used for the direct fabrication of surface relief gratings (SRGs) without the selective etching of the material. It is known that the interferometric approach makes it possible to fabricate SRGs with submicron and even subwavelength periods. However, to change the period of the written SRGs, it is necessary to change the convergence angle, shift a sample, and readjust the interferometric setup. Recently, it was shown that structured laser beams with predetermined, periodically modulated polarization distributions can also be used to fabricate SRGs. A structured laser beam with the desired polarization distribution can be formed with just one polarizing optical element—for example, the so-called depolarizer, a patterned micro-retarder array. The use of such stacked elements makes it possible to directly control the modulation period of the polarization of the generated laser beam. We show that this approach allows one to fabricate SRGs with submicron periods. Moreover, the addition of q-plates, elements effectively used to generate cylindrical vector beams with polarization singularities, allows the efficient formation of fork polarization gratings (FPGs) and the fabrication of higher-order fork-shaped SRGs. Full control of the parameters of the generated FPGs is possible. We demonstrate the formation of FPGs of higher orders (up to 12) by only adding first- and second-order q-plates and half-wave plates to the depolarizers. In this work, we numerically and experimentally study the parameters of various types of SRGs formed using these stacked polarizing elements and show the significant potential of this method for the laser processing of photosensitive materials, which often also serve as polarization sensors.
INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection
Authors: Lee Sangin , Kim Taejoo , Shin Jeongmin , Kim Namil , Choi Yukyung
Published: February 2024

Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing complementary information to RGB images. Previous studies have shown that multi-modal feature fusion using convolution operation can be effective, but such methods rely solely on local feature correlations, which can degrade the performance capabilities. To address this issue, we propose an attention-based novel fusion network, referred to as INSANet (INtra-INter Spectral Attention Network), that captures global intra- and inter-information. It consists of intra- and inter-spectral attention blocks that allow the model to learn mutual spectral relationships. Additionally, we identified an imbalance in the multispectral dataset caused by several factors and designed an augmentation strategy that mitigates concentrated distributions and enables the model to learn the diverse locations of pedestrians. Extensive experiments demonstrate the effectiveness of the proposed methods, which achieve state-of-the-art performance on the KAIST dataset and LLVIP dataset. Finally, we conduct a regional performance evaluation to demonstrate the effectiveness of our proposed network in various regions.
A Hybrid System for Defect Detection on Rail Lines through the Fusion of Object and Context Information
Authors: Zhukov Alexey , Rivero Alain , Benois-Pineau Jenny , Zemmari Akka , Mosbah Mohamed
Published: February 2024

Defect detection on rail lines is essential for ensuring safe and efficient transportation. Current image analysis methods with deep neural networks (DNNs) for defect detection often focus on the defects themselves while ignoring the related context. In this work, we propose a fusion model that combines both a targeted defect search and a context analysis, which is seen as a multimodal fusion task. Our model performs rule-based decision-level fusion, merging the confidence scores of multiple individual models to classify rail-line defects. We call the model “hybrid” in the sense that it is composed of supervised learning components and rule-based fusion. We first propose an improvement to existing vision-based defect detection methods by incorporating a convolutional block attention module (CBAM) in the you only look once (YOLO) versions 5 (YOLOv5) and 8 (YOLOv8) architectures for the detection of defects and contextual image elements. This attention module is applied at different detection scales. The domain-knowledge rules are applied to fuse the detection results. Our method demonstrates improvements over baseline models in vision-based defect detection. The model is open for the integration of modalities other than an image, e.g., sound and accelerometer data.
A Transferable Lidar-Based Method to Conduct Contactless Assessments of Gait Parameters in Diverse Home-like Environments
Authors: Single Michael , Bruhin Lena C. , Colombo Aaron , Möri Kevin , Gerber Stephan M. , Lahr Jacob , Krack Paul , Klöppel Stefan , Müri René M. , Mosimann Urs P. , Nef Tobias
Published: February 2024

Gait abnormalities in older adults are linked to increased risks of falls, institutionalization, and mortality, necessitating accurate and frequent gait assessments beyond traditional clinical settings. Current methods, such as pressure-sensitive walkways, often lack the continuous natural environment monitoring needed to understand an individual’s gait fully during their daily activities. To address this gap, we present a Lidar-based method capable of unobtrusively and continuously tracking human leg movements in diverse home-like environments, aiming to match the accuracy of a clinical reference measurement system. We developed a calibration-free step extraction algorithm based on mathematical morphology to realize Lidar-based gait analysis. Clinical gait parameters of 45 healthy individuals were measured using Lidar and reference systems (a pressure-sensitive walkway and a video recording system). Each participant participated in three predefined ambulation experiments by walking over the walkway. We observed linear relationships with strong positive correlations (R2>0.9) between the values of the gait parameters (step and stride length, step and stride time, cadence, and velocity) measured with the Lidar sensors and the pressure-sensitive walkway reference system. Moreover, the lower and upper 95% confidence intervals of all gait parameters were tight. The proposed algorithm can accurately derive gait parameters from Lidar data captured in home-like environments, with a performance not significantly less accurate than clinical reference systems.
Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review
Authors: Kapetanidis Panagiotis , Kalioras Fotios , Tsakonas Constantinos , Tzamalis Pantelis , Kontogiannis George , Karamanidou Theodora , Stavropoulos Thanos G. , Nikoletseas Sotiris
Published: February 2024

Respiratory diseases represent a significant global burden, necessitating efficient diagnostic methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound from the upper and lower respiratory system, as well as the voice, have emerged as valuable indicators of respiratory functionality. Recent advancements in machine learning (ML) algorithms offer promising avenues for the identification and diagnosis of respiratory diseases through the analysis and processing of such audio-based biomarkers. An ever-increasing number of studies employ ML techniques to extract meaningful information from audio biomarkers. Beyond disease identification, these studies explore diverse aspects such as the recognition of cough sounds amidst environmental noise, the analysis of respiratory sounds to detect respiratory symptoms like wheezes and crackles, as well as the analysis of the voice/speech for the evaluation of human voice abnormalities. To provide a more in-depth analysis, this review examines 75 relevant audio analysis studies across three distinct areas of concern based on respiratory diseases’ symptoms: (a) cough detection, (b) lower respiratory symptoms identification, and (c) diagnostics from the voice and speech. Furthermore, publicly available datasets commonly utilized in this domain are presented. It is observed that research trends are influenced by the pandemic, with a surge in studies on COVID-19 diagnosis, mobile data acquisition, and remote diagnosis systems.
Time-Aware Dual LSTM Neural Network with Similarity Graph Learning for Remote Sensing Service Recommendation
Authors: Zhang Jinkai , Ma Wenming , Zhang En , Xia Xuchen
Published: February 2024

Technological progress has led to significant advancements in Earth observation and satellite systems. However, some services associated with remote sensing face issues related to timeliness and relevance, which affect the application of remote sensing resources in various fields and disciplines. The challenge now is to help end-users make precise decisions and recommendations for relevant resources that meet the demands of their specific domains from the vast array of remote sensing resources available. In this study, we propose a remote sensing resource service recommendation model that incorporates a time-aware dual LSTM neural network with similarity graph learning. We further use the stream push technology to enhance the model. We first construct interaction history behavior sequences based on users’ resource search history. Then, we establish a category similarity relationship graph structure based on the cosine similarity matrix between remote sensing resource categories. Next, we use LSTM to represent historical sequences and Graph Convolutional Networks (GCN) to represent graph structures. We construct similarity relationship sequences by combining historical sequences to explore exact similarity relationships using LSTM. We embed user IDs to model users’ unique characteristics. By implementing three modeling approaches, we can achieve precise recommendations for remote sensing services. Finally, we conduct experiments to evaluate our methods using three datasets, and the experimental results show that our method outperforms the state-of-the-art algorithms.
CESA-MCFormer: An Efficient Transformer Network for Hyperspectral Image Classification by Eliminating Redundant Information
Authors: Liu Shukai , Yin Changqing , Zhang Huijuan
Published: February 2024

Hyperspectral image (HSI) classification is a highly challenging task, particularly in fields like crop yield prediction and agricultural infrastructure detection. These applications often involve complex image types, such as soil, vegetation, water bodies, and urban structures, encompassing a variety of surface features. In HSI, the strong correlation between adjacent bands leads to redundancy in spectral information, while using image patches as the basic unit of classification causes redundancy in spatial information. To more effectively extract key information from this massive redundancy for classification, we innovatively proposed the CESA-MCFormer model, building upon the transformer architecture with the introduction of the Center Enhanced Spatial Attention (CESA) module and Morphological Convolution (MC). The CESA module combines hard coding and soft coding to provide the model with prior spatial information before the mixing of spatial features, introducing comprehensive spatial information. MC employs a series of learnable pooling operations, not only extracting key details in both spatial and spectral dimensions but also effectively merging this information. By integrating the CESA module and MC, the CESA-MCFormer model employs a “Selection–Extraction” feature processing strategy, enabling it to achieve precise classification with minimal samples, without relying on dimension reduction techniques such as PCA. To thoroughly evaluate our method, we conducted extensive experiments on the IP, UP, and Chikusei datasets, comparing our method with the latest advanced approaches. The experimental results demonstrate that the CESA-MCFormer achieved outstanding performance on all three test datasets, with Kappa coefficients of 96.38%, 98.24%, and 99.53%, respectively.
Influence of the Injection Bias on the Capacitive Sensing of the Test Mass Motion of Satellite Gravity Gradiometers
Authors: Xu Hengtong , Lei Jungang , Li Detian , Li Yunpeng , Tao Wenze , Zhang Wenyan , Chen Meng
Published: February 2024

The performance of the capacitive gap-sensing system plays a critical role in a satellite-based gravity gradiometer that is developed using an electrostatic accelerometer. The capacitive sensing gain mainly depends on the stabilized injection bias amplitude, the gain of the transformer bridge, and the trans-impedance amplifier. Previous studies have indicated that amplitude noise is the main factor influencing the noise of capacitive displacement detection. Analyzing the capacitive gap-sensing system indicates that the amplitude, frequency, phase, and broadband noises of the stabilized injection bias have varying levels of influence on the performance of the detection system. This paper establishes a model to clarify the mentioned effects. The validation of the sub-tests demonstrates that the analysis and evaluation results of various noise coefficients are highly consistent with the model’s predicted outcomes.
Exploring Wavefront Detection in Imaging Systems with Rectangular Apertures Using Phase Diversity
Authors: Li Yibo , Guo Jiang , Liu Rengcong
Published: February 2024

The attainment of a substantial aperture in the rotating synthetic aperture imaging system involves the rotation of a slender rectangular primary mirror. This constitutes a pivotal avenue of exploration in space telescope research. Due to the considerable aspect ratio of the primary mirror, environmental disturbances can significantly impact its surface shape. Active optical technology can rectify surface shape irregularities through the detection of wavefront information. The Phase Diversity (PD) method utilizes images captured by the imaging system to compute wavefront information. In this study, the PD method is applied to rotating synthetic and other rectangular aperture imaging systems, employing Legendre polynomials to model the wavefront. The study delved into the ramifications stemming from the aperture aspect ratio and aberration size.
Three-Dimensional Path Planning Based on Six-Direction Search Scheme
Authors: Li Kene , Li Liuying , Tang Chunyi , Lu Wanning , Fan Xiangsuo
Published: February 2024

In order to solve the problem of how to perform path planning for AUVs with multiple obstacles in a 3D underwater environment, this paper proposes a six-direction search scheme based on neural networks. In known environments with stationary obstacles, the obstacle energy is constructed based on a neural network and the path energy is introduced to avoid a too-long path being generated. Based on the weighted total energy of obstacle energy and path energy, a six-direction search scheme is designed here for path planning. To improve the efficiency of the six-direction search algorithm, two optimization methods are employed to reduce the number of iterations and total path search time. The first method involves adjusting the search step length dynamically, which helps to decrease the number of iterations needed for path planning. The second method involves reducing the number of path nodes, which can not only decrease the search time but also avoid premature convergence. By implementing these optimization methods, the performance of the six-direction search algorithm is enhanced in favor of path planning with multiple underwater obstacles reasonably. The simulation results validate the effectiveness and efficiency of the six-direction search scheme.
Identification of Panoramic Photographic Image Composition Using Fuzzy Rules
Authors: Chia Tsorng-Lin , Shin Yin-De , Huang Ping-Sheng
Published: February 2024

Making panoramic images has gradually become an essential function inside personal intelligent devices because panoramic images can provide broader and richer content than typical images. However, the techniques to classify the types of panoramic images are still deficient. This paper presents novel approaches for classifying the photographic composition of panoramic images into five types using fuzzy rules. A test database with 168 panoramic images was collected from the Internet. After analyzing the panoramic image database, the proposed feature model defined a set of photographic compositions. Then, the panoramic image was identified by using the proposed feature vector. An algorithm based on fuzzy rules is also proposed to match the identification results with that of human experts. The experimental results show that the proposed methods have demonstrated performance with high accuracy and this can be used for related applications in the future.
PSMOT: Online Occlusion-Aware Multi-Object Tracking Exploiting Position Sensitivity
Authors: Zhao Ranyang , Zhang Xinyan , Zhang Jianwei
Published: February 2024

Models based on joint detection and re-identification (ReID), which significantly increase the efficiency of online multi-object tracking (MOT) systems, are an evolution from separate detection and ReID models in the tracking-by-detection (TBD) paradigm. It is observed that these joint models are typically one-stage, while the two-stage models become obsolete because of their slow speed and low efficiency. However, the two-stage models have naive advantages over the one-stage anchor-based and anchor-free models in handling feature misalignment and occlusion, which suggests that the two-stage models, via meticulous design, could be on par with the state-of-the-art one-stage models. Following this intuition, we propose a robust and efficient two-stage joint model based on R–FCN, whose backbone and neck are fully convolutional, and the RoI-wise process only involves simple calculations. In the first stage, an adaptive sparse anchoring scheme is utilized to produce adequate, high-quality proposals to improve efficiency. To boost both detection and ReID, two key elements—feature aggregation and feature disentanglement—are taken into account. To improve robustness against occlusion, the position-sensitivity is exploited, first to estimate occlusion and then to direct the post-process for anti-occlusion. Finally, we link the model to a hierarchical association algorithm to form a complete MOT system called PSMOT. Compared to other cutting-edge systems, PSMOT achieves competitive performance while maintaining time efficiency.
Modulating Driver Alertness via Ambient Olfactory Stimulation: A Wearable Electroencephalography Study
Authors: Jiang Mengting , Chaichanasittikarn Oranatt , Seet Manuel , Ng Desmond , Vyas Rahul , Saini Gaurav , Dragomir Andrei
Published: February 2024

Poor alertness levels and related changes in cognitive efficiency are common when performing monotonous tasks such as extended driving. Recent studies have investigated driver alertness decrement and possible strategies for modulating alertness with the goal of improving reaction times to safety critical events. However, most studies rely on subjective measures in assessing alertness changes, while the use of olfactory stimuli, which are known to be strong modulators of cognitive states, has not been commensurately explored in driving alertness settings. To address this gap, in the present study we investigated the effectiveness of olfactory stimuli in modulating the alertness state of drivers and explored the utility of electroencephalography (EEG) in developing objective brain-based tools for assessing the resulting changes in cortical activity. Olfactory stimulation induced a significant differential effect on braking reaction time. The corresponding effect to the cortical activity was characterized using EEG-derived metrics and the devised machine learning framework yielded a high discriminating accuracy (92.1%). Furthermore, neural activity in the alpha frequency band was found to be significantly associated with the observed drivers’ behavioral changes. Overall, our results demonstrate the potential of olfactory stimuli to modulate the alertness state and the efficiency of EEG in objectively assessing the resulting cognitive changes.
Bibliometric Study on the Conceptualisation of Smart City and Education
Authors: Scala Debora , Aguilar Cuesta Ángel Ignacio , Rodríguez-Domenech Maria Ángeles , Cañizares Ruiz María del Carmen
Published: February 2024

In recent years, research in the smart city sector has experienced exponential growth, establishing itself as a fundamental and multifaceted field of study. Education is one of the sectors of interest in smart cities. Concurrently, the extensive academic literature on smart cities makes identifying the main areas of interest related to education, leading institutions and authors, potential interconnections between different disciplines, and existing gaps more complicated. This article maps the knowledge domain of education in smart cities through a bibliometric analysis to identify current trends, research networks, and topics of greatest interest. A total of 88 articles, published between 2000 and 2023, were examined using an interdisciplinary approach. The leading countries are mainly located in Europe and North America and include China. Bibliometrics provides an intellectual configuration of knowledge on education in smart cities; a co-word analysis identifies conceptual sub-domains in specific themes. In general, education within smart cities represents a universal challenge that requires a structured and interdisciplinary approach at all levels. Finally, this paper offers some suggestions for future research, adopting a more comprehensive view of the areas of investigation through a holistic analysis of stakeholders.
Experimental Study on Runoff and Sediment Production of the Fully Weathered Granite Backfill Slope under Heavy Rain in Longling, Yunnan Province
Authors: Gao Kai , Kong Zhigang , Li Yanqing , Zhao Fei , Cai Baoxin , Shi Dehua , Wang Ren
Published: February 2024

Heavy or intermittent rainfall can cause slopes to become unstable and erode, resulting in significant damage, loss of life, and destruction of property. Targeted management solutions are based on an analysis of slopes’ flow generation and sediment production patterns during periods of rainfall. This study used a fully granite backfill slope as its research subject and examined the features of slope erosion during intermittent rainfall. We examined the processes of slope flow generation and soil erosion during intermittent rain through indoor artificially simulated rainfall experiments. Three intermittent rainfall events with a 220 mm/h intensity were designed during the experiment. Each rainfall event lasted for 60 min, with an interval of 60 min between the events. By analyzing multiple rainfall events, this study reveals the patterns of runoff and sediment yield on different slopes in response to variations in rainfall intensity and slope gradient. The runoff volume on other slope surfaces exhibits a similar pattern in reaction to changes in rainfall events. As the frequency of rainfall events increases, the surface runoff tends to be higher. Additionally, with variations in slope steepness, the runoff volume generally follows an increasing trend. Notably, the slope with a 20° incline shows the smallest runoff volume. The sediment yield on different slope surfaces gradually increases as the slope increases. In particular, on a 20° slope, the sediment yield experiences a substantial increase, indicating that the impact of the slope on the sediment yield becomes more pronounced. In different rainfall events, the morphology of the slope changes due to the influence of gravity and hydraulics, resulting in oscillations in both the average runoff rate and sediment yield. Furthermore, as the slope steepens, the amplitude of these oscillations increases. The process of slope erosion involves three stages: raindrop splash erosion, runoff erosion, and collapse damage. The sequence of slope damage locations is as follows: footslope, mid-slope, and hilltop. For the backfilled slope of completely weathered granite, the artificial slope can be controlled to around 20°. Erosion on the slope mainly occurs after the formation of gullies, and slope management should focus on preventing gully formation before it happens.
Sustainable Energy: Concept and Definition in the Context of the Energy Transition—A Critical Review
Authors: Halawa Edward
Published: February 2024

The term sustainable energy is very familiar to all of us, yet its exact definition or meaning has so far been vague. To date, the widely adopted definition of sustainable energy has been inspired by the definition of sustainable development formulated more than 30 years ago in Our Common Future—the UN’s Report of the World Commission on Environment and Development. The current definition conceals the true spirit of the report, and this has some ramifications. It raises the question as to whether we have put too much emphasis on attaining the future dimension of sustainability in the middle of a situation where energy survivability is in fact the real issue in many parts of the world. In this paper, the role of energy in sustaining the livelihoods of low-income communities is discussed. The existing definition of sustainable energy that the whole world seems to have embraced is looked at critically and its downsides exposed. The identified pillars of sustainable energy and the associated issues are discussed, and the need for an additional pillar, i.e., affordability, is discussed and called for. This paper will argue that the global definition of sustainable energy seems inappropriate and should be jettisoned, and a more realistic definition should be formulated, adopted, and embraced at the local (i.e., national or regional) level taking into account local attributes and factors. The current push for a transition from the reliance on conventional energy sources to “cleaner” energy sources (generally associated with renewable energy) has further exacerbated the issue of energy affordability that has made the conditions even more dire for so many groups of the world’s population. In the midst of this situation, those who push for a rushed energy transition seem to be those who also produce an unsustainably high carbon footprint but who can easily offset their carbon footprint through the ‘net-zero’ concept.
Epidemiology of Dengue in Argentina during the 2010/11 to 2019/20 Seasons: A Contribution to the Burden of Disease
Authors: Rapaport Solana , Mauriño Mariana , Morales María Alejandra , Fabbri Cintia , Luppo Victoria , Buyayisqui María Pía , Varela Teresa , Giovacchini Carlos , Urueña Analía
Published: February 2024

Background: Dengue is an important public health problem in Argentina, as in many other countries. We reviewed and updated information on the dengue disease burden in Argentina over a 10-year period. Methods: We conducted a retrospective descriptive study from 2010 to 2020 based on data from the National Health Surveillance System. The main outcomes included dengue cases, incidence rates, deaths, and serotype distribution by season, age group, and region. Results: A total of 109,998 confirmed cases of dengue were reported. Seasonality stands out, prevailing during summer and autumn. Two main outbreaks (seasons 2015/16 and 2019/20), with increasing magnitude, were observed. The 2019/20 season showed the highest number of cases (58,731) and incidence rate (135/100,000). The Northeast region had the highest number of cases and incidence rate. In 2020, for the first time, autochthonous cases were registered in the Cuyo region. The only region with no autochthonous cases was the South. Adolescents and young adults showed the highest incidence rate. The case fatality rate for the period was 0.05%. Four serotypes circulated, but the predominant one was DEN-1 (78%). Conclusions: Dengue has been expanding temporally and spatially. Although the DEN-1 serotype widely predominated, the increasing circulation of other serotypes raises concerns regarding re-exposure and the severity of future cases. Understanding epidemiological trends is key to defining public prevention and control policies.
Genomic and Phylogenetic Characterisation of SARS-CoV-2 Genomes Isolated in Patients from Lambayeque Region, Peru
Authors: Aguilar-Martinez Sergio Luis , Sandoval-Peña Gustavo Adolfo , Molina-Mora José Arturo , Tsukayama-Cisneros Pablo , Díaz-Vélez Cristian , Aguilar-Gamboa Franklin Rómulo , Bonilla-Aldana D. Katterine , Rodriguez-Morales Alfonso J.
Published: February 2024

Objective: this study aims to identify and characterise genomic and phylogenetically isolated SARS-CoV-2 viral isolates in patients from Lambayeque, Peru. Methods: Nasopharyngeal swabs were taken from patients from the Almanzor Aguinaga Asenjo Hospital, Chiclayo, Lambayeque, Peru, which had been considered mild, moderate, and severe cases of COVID-19. Patients had to have tested positive for COVID-19, using a positive RT-PCR for SARS-CoV-2. Subsequently, the SARS-CoV-2 complete viral genome sequencing was carried out using Illumina MiSeq®. The sequences obtained from the sequence were analysed in Nextclade V1.10.0 to assign the corresponding clades, identify mutations in the SARS-CoV-2 genes and perform quality control of the sequences obtained. All sequences were aligned using MAFFT v7.471. The SARS-CoV-2 isolate Wuhan NC 045512.2 was used as a reference sequence to analyse mutations at the amino acid level. The construction of the phylogenetic tree model was achieved with IQ-TREE v1.6.12. Results: It was determined that during the period from December 2020 to January 2021, the lineages s C.14, C.33, B.1.1.485, B.1.1, B.1.1.1, and B.1.111 circulated, with lineage C.14 being the most predominant at 76.7% (n = 23/30). These lineages were classified in clade 20D mainly and also within clades 20B and 20A. On the contrary, the variants found in the second batch of samples of the period from September to October 2021 were Delta (72.7%), Gamma (13.6%), Mu (4.6%), and Lambda (9.1%), distributed between clades 20J, 21G, 21H, 21J, and 21I. Conclusions: This study reveals updated information on the viral genomics of SARS-CoV-2 in the Lambayeque region, Peru, which is crucial to understanding the origins and dispersion of the virus and provides information on viral pathogenicity, transmission and epidemiology.
Research Progress and Prospects of Public Transportation Charging Station Layout Methods
Authors: Lei Hao , Hu Xinghua , Zhao Jiahao , Deng Dongde , Wang Ran
Published: February 2024

Electric buses have been vigorously promoted and implemented in major countries worldwide and have generated a huge demand for charging stations. Optimizing the daily charging experience of electric buses, adapting the daily operation scheduling, improving the utilization rate of charging stations, reducing the load on the power grid, and improving the operation efficiency of electric bus line networks require the reasonable layout of the charging stations. In this study, public transportation charging station layout and siting is the research object. We summarize the progress of analysis methods from the charging station and vehicle sides; introduce related research on the planning and layout of charging stations based on optimization models, including cost analysis and siting and layout for electric bus systems; summarize the data-driven station planning and siting research; and provide an overview of the current charging demand estimation, accuracy, and charging efficiency. Finally, we address the problems of the charging demand estimation accuracy, the mismatch between the charging station layouts for electric buses, and the charging demand on a long time scale. We suggest that research be conducted on data fusion for the temporal and spatial refinement of charging demand prediction in the context of the electrification of public transportation systems and the big data of telematics.
Determination of the Performance Characteristics of a Traction Battery in an Electric Vehicle
Authors: Malozyomov Boris V. , Martyushev Nikita V. , Kukartsev Vladislav V. , Konyukhov Vladimir Yu. , Oparina Tatiana A. , Sevryugina Nadezhda S. , Gozbenko Valeriy E. , Kondratiev Viktor V.
Published: February 2024

Electric vehicles are the most innovative and promising area of the automotive industry. The efficiency of a traction battery is an important factor in the performance of an electric vehicle. This paper presents a mathematical model of an electric truck, including modules for the traction battery to determine the depth of battery discharge during the operation of the electric truck, a traction electric system for the electric truck and a system for calculating traction forces on the shaft in electric motors. As a result of the modelling, the charging and discharging currents of an accumulator battery in a real cycle of movement in peak and nominal modes of operation in electric motors and at different voltages of the accumulator battery are determined. A functional scheme of a generalized model of the electric vehicle traction electrical equipment system is developed. An experimental battery charge degree, torques of asynchronous electric motors, temperature of electric motors and inverters, battery voltage and the speed of electric motors have been measured and analysed. The developed complex mathematical model of an electric vehicle including a traction battery, two inverters and two asynchronous electric motors integrated into an electric portal bridge allowed us to obtain and study the load parameters of the battery in real driving cycles. Data were verified by comparing simulation results with the data obtained during driving.
Composição e análise de uma ópera cômica: investigando a construção do sentido musical
Authors: Biato Eduardo Bertolossi
Published: February 2024

I intend to demonstrate the contribution of specific cognitive devices in regulating processes that determine the perceptive choices and the ways of constructing musical meaning in the compositional process of a comic opera. To this end, from the libretto A Sonâmbula, by Machado de Assis, I develop the composition and a reflective analysis of the composition of an opera in two cycles: (i) In the first, according to the principles of formalist semantics, I generate the first version of opera; and (ii) in the second, from the application of devices of an incorporated semantics, I produce the final version of the opera. Comparing the artistic re-sults of the two cycles, I discuss the process of producing the musical meaning that regulates compositional acts, highlighting the role of cognitive devices described by enacting theories of contemporary cognitive sciences, still little addressed by the literature on musical compo-sition, particularly in the operatic genre.
Desenvolvimento da Escala de Avaliação dos Efeitos da Musicoterapia em Grupo na Dependência Química: análise teórica e semântica
Authors: Pedrosa Frederico , Garcia Frederico , Loureiro Cybelle Maria Veiga
Published: February 2024

This text discusses methodological and developmental research on the Assessment Scale of the Effects of Group Music Therapy on Chemical Dependence (MTDQ). To do so, we used the theoretical procedures for constructing Psychological Assessment Instruments outlined by Luiz Pasquali, namely Semantic Analysis and Judges Analysis. We found that the MTDQ was evaluated as relevant and appropriate to the population for which it is intended, that the items are theoretically connected to their respective domains, and that all domains are perti-nent for the evaluation of MT in CD. Finally, we indicate that further studies will be con-ducted to verify the structural validity as well as the reliability of the constructed test.
Performance musical na indeterminação: introdução a um modelo de construção performativa
Authors: Macedo Tatiana Dumas
Published: February 2024

An exciting focus for the analysis of musical interpretation of contemporary music text is to consider, as Clarke (2006) pointed out, the relationship between content and form of the no-tational representation of music and its musical realization by the performer—the latter's in-tention—in the sense of discussing how these musicians perform their active role through creative acts. As I intend to argue, such acts are strategies, decision-making, and actions that aim to overcome the gaps in meaning that emerge in the reading of the musical text. To in-clude this perspective in the argument of the present study, I begin by examining musical notation as a means for realizing the musical idea and, particularly, the notational represen-tation in the context of indeterminacy in music. The study is completed with a discussion around improvisation as a condition for interpreting contemporary music text.
Converse: discutindo um processo colaborativo e suas bases cognitivas
Authors: Bertissolo Guilherme , Sfoggia Lia Gunther , Cardassi Luciane
Published: February 2024

Converse is a collaborative work developed by the authors in 2018 based on the concept of State of Readiness, proposed by Sfoggia during her doctoral research. It is a notion inferred in the context of Capoeira Regional, and refers to the need for capoeira players to constantly remain alert and available, and how this state influences their way of moving. The fact that what may happen in the next moment cannot be foreseen, the possibility of being attacked at any moment, the lack of confidence. This leads to the necessity to stay in a continuous state of body readiness to act. In this article, we briefly describe the concept and its context, elabo-rate on the impact of performative research and collaboration in the creative process itself. After this initial discussion, we focus on the cognitive mechanisms involved in the many de-cision making processes in Converse, as seen through the prism of music and movement.
Discussões decorrentes da aplicação parcial do Protocolo de Microanálise da Prática Musical no formato remoto
Authors: Soares Leandro Taveira
Published: February 2024

In this article, I discuss the elaboration process of the Music Practice Microanalysis Protocol (PMPM) — resulting from the conciliation and adaptation of the instruments proposed by McPherson and colleagues (2015; 2017/2019), Miksza and colleagues (2018) and Osborne and colleagues (2020) — and the discussions arising from the partial application of the protocol in the remote format — due to the social distancing related to the COVID-19 pandemic. I em-phasize that the discussion about the possibility of using digital/online tools and platforms to carry out the microanalytical experiments was productive and promising and that the par-tial application of the protocol demonstrated the procedural viability of the remote applica-tion of all stages of the protocol, with different degrees of effectiveness depending on the pro-file and character of each methodological instrument — oral and/or practical — and the technological conditions — for capturing and transmitting data — related to the use of digi-tal/online platforms. By proposing the implementation of a microanalytical protocol aimed at evaluating the self-regulated learning of undergraduate music students, this study has the potential to contribute to the progressive discussion — still embryonic in the literature — about the inclusion of the perspective of self-regulated learning as an indicator and bench-mark for the process of re-elaboration and revision of curricula and programs of training courses for instrumentalist musicians at the undergraduate level.
A forma e o fenômeno psicológico musical em Mário de Andrade: uma experiência pré-conceitual do sujeito cognoscente
Authors: Vetromilla Márcia Hallak Martins da Costa
Published: February 2024

By addressing the cognitive processes involved in understanding musical form, the article seeks to emphasize that in its beginnings, Brazilian musicology, through the writings of Mário de Andrade, addressed the issue directly and indirectly, still in the first half of the 20th century, without, however, have received due recognition. Suppose the musical form is no longer syntactically formulated by the contemporary composer, at least in classical-romantic terms; in that case, this demands the ability to form by interpreting from instrumental music performers. This contemporary performer is increasingly accustomed to consciously, discur-sively, and conceptually objectifying resources of pre-conceptual understanding of his music experience, which will provide the concretization of his interpretative projects. Hence, the challenge faced by Mário de Andrade when formulating his musical aesthetics seemed to in-clude the presence of the unspeakable, the inexplicable, the imaginative in musical semantics. Mário de Andrade reveals himself to be extremely sensitive to issues that concern the field of musical cognition. His writings emphasize the participation of physiological, bodily move-ment, and metaphorical aspects in understanding and critical production of music. He ap-pears more interested in the processes of synthesis than in those of analysis, concerned with getting rid of technical knowledge to indulge in the creative act.
A cognitive concept of musical meaning
Authors: Merlino Julio
Published: February 2024

Almost two centuries after the publication of Hanslick's On the Musically Beautiful: A Contribution to the Revision of Music Aesthetics and the consolidation of the formalist current, its principles are still at the core of understanding musical meaning as an emerging property of musical form. The consolidated creative paradigm of a composer "picking up" music from his imagination and then decoding it into a musical notation to produce a music sheet that will stand for the music itself to be read by a performer that will, in turn, restitute the musical work to its sonic nature still is roughly the norm in the Western world. This paradigm, however, poses several challenges to musical meaning in other musical practices, especially those that mainly employ improvisation. Starting from a different concept of writing, dislodging the musical work from its usual "place" on the music sheet, and going through the notion of experience as the primary human process of knowledge formation, this article proposes a concept of musical meaning as “embodied” in musical experience, determined and conditioned by devices explained by theoretical frameworks from the enactivist cognitive sciences.
The use of mental imagery in voice pedagogy and the teaching of the head voice register
Authors: Jaber Maíra dos Santos
Published: February 2024

This article aims to discuss the use of mental imagery in voice pedagogy and identify some mental images and metaphors used by singing teachers to teach head voice register. The exploratory research is predominantly qualitative and uses as data collection tools online survey, besides cognitive sciences and voice pedagogy literature analysis. Ten singing teachers answered the survey: five of them are specialized in contemporary commercial music styles (CCM), four are specialized in teaching classical singing, and one is specialized in teaching Musical Theatre and CCM styles. The teachers have more than seventeen years of experience, and they are in activity at the moment of the research. The results reveal that all the teachers use mental imagery in their pedagogue vocabulary, and 90% admit they use it to teach head voice. Four different mental strategies are identified in this study as pedagogic tools used by the teachers, linking sensory and physiological phenomena. Explanations in cognitive literature combined with the analysis of the terms and concepts related by the teachers suggest that mental imagery and metaphors, as cognitive instruments the human mind uses to structure thoughts and actions, can be a helpful tool to connect mind and body when the singing students need to structure a new concept like head voice register. Further investigation is required to test this hypothesis with the students.
Gradient Rotating Magnetic Fields Impairing F-Actin-Related Gene CCDC150 to Inhibit Triple-Negative Breast Cancer Metastasis by Inactivating TGF-β1/SMAD3 Signaling Pathway
Authors: Zhang Ge , Yu Tongyao , Chai Xiaoxia , Zhang Shilong , Liu Jie , Zhou Yan , Yin Dachuan , Zhang Chenyan
Published: February 2024

Triple-negative breast cancer (TNBC) is the most aggressive and lethal malignancy in women, with a lack of effective targeted drugs and treatment techniques. Gradient rotating magnetic field (RMF) is a new technology used in oncology physiotherapy, showing promising clinical applications due to its satisfactory biosafety and the abundant mechanical force stimuli it provides. However, its antitumor effects and underlying molecular mechanisms are not yet clear. We designed two sets of gradient RMF devices for cell culture and animal handling. Gradient RMF exposure had a notable impact on the F-actin arrangement of MDA-MB-231, BT-549, and MDA-MB-468 cells, inhibiting cell migration and invasion. A potential cytoskeleton F-actin-associated gene, CCDC150, was found to be enriched in clinical TNBC tumors and cells. CCDC150 negatively correlated with the overall survival rate of TNBC patients. CCDC150 promoted TNBC migration and invasion via activation of the transforming growth factor β1 (TGF-β1)/SMAD3 signaling pathway in vitro and in vivo. CCDC150 was also identified as a magnetic field response gene, and it was marked down-regulated after gradient RMF exposure. CCDC150 silencing and gradient RMF exposure both suppressed TNBC tumor growth and liver metastasis. Therefore, gradient RMF exposure may be an effective TNBC treatment, and CCDC150 may emerge as a potential target for TNBC therapy.