bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in Plant-Based Diets and the Associated Health Characteristics among Canadians
Authors: Longworth Zoe Lillian , Mohammadkhani Razieh , Szafron Michael , Lane Ginny , Vatanparast Hassan
Published: August 2024

In Canada, unhealthy dietary patterns comprise diets with poor nutrient density and are associated with chronic conditions. Plant-based diets have gained popularity due to their ability to provide a nutritionally adequate healthy diet. This study aims to compare sociodemographic, socioeconomic, and health characteristics, and diet quality between Canadian adults following plant-based and omnivore diets as well as assess the extent to which key nutrient intakes are of public health concern among Canadians following plant-based diets. The study used nationally representative nutritional data from the 2015 Canadian Community Health Survey and descriptive statistics were computed. The analysis determined that Canadians following strict plant-based diets (1% of total population) were significantly more likely to be an immigrant to Canada, less likely to meet national physical activity guidelines, and less likely to be overweight, compared to Canadians following omnivore diets. Compared to omnivore diets, plant-based diets were nutritionally superior according to the Nutrient-Rich Food index. Continued knowledge translation on what comprises healthy plant-based diets, public guidance on the intersection between diet and health, and the completion of prospective cohort studies are needed. To conclude, the research suggests well-planned plant-based diets, in comparison to omnivore diets, offer a nutrient-dense diet.
Chronic Illness Perceptions and Cardiovascular Disease Risk Behaviors in Black and Latinx Sexual Minority Men with HIV: A Cross-Sectional Analysis
Authors: Ramos S. Raquel , Kang Baram , Jeon Sangchoon , Fraser Marilyn , Kershaw Trace , Boutjdir Mohamed
Published: August 2024

Ethnic and racial sexual minority men with HIV have a disproportionately higher risk of HIV-related cardiovascular disease (CVD). There is a lack of tailored and culturally salient behavioral interventions to address HIV-related chronic illness in ethnic and racial sexual minority men, and literature on their understanding and awareness of modifiable behavioral risks is limited. The purpose of this study was to assess illness perceptions about HIV and HTN, and describe physical activity, tobacco, and e-cigarette use in Black and Latinx sexual minority men living with HIV. We used the validated Illness Perception Questionnaire-Revised (IPQ-R) to assess perceptions about two interrelated chronic diseases, HIV and CVD. To assess CVD behavioral risk, we assessed physical activity using the International Physical Activity Questionnaire. Tobacco and e-cigarette use were assessed using items from the Behavioral Risk Factor Surveillance System. Sleep difficulties were the most prevalent symptom attributed to HIV, and were statistically associated with fatigue, upset stomach, and loss of strength. Anxiety was reported to be caused by HIV (57%) and HTN (39%). Half of the participants engaged in vigorous activity for 128 min (SD = 135) daily, and 63% engaged in moderate activity for 94 min (SD = 88) daily. Over a third reported current tobacco use and 20% reported current e-cigarette use. This study provides formative data to better understand how Black and Latinx sexual minority men with HIV perceive intersecting chronic illnesses and their engagement in modifiable CVD risk behaviors. Sleep, mental health disparities, and financial hardships were commonly reported. More research is needed to address intersecting chronic illnesses and mental health conditions that are influenced by social positioning over the life course, and impact CVD risk factors. This study was not registered.
The Etiology of Bloodstream Infections at an Italian Pediatric Tertiary Care Hospital: A 17-Year-Long Series
Authors: Russo Chiara , Mariani Marcello , Bavastro Martina , Mesini Alessio , Saffioti Carolina , Ricci Erica , Ugolotti Elisabetta , Bandettini Roberto , Castagnola Elio
Published: August 2024

Knowledge of epidemiology is essential for guiding correct antibiotic prescription, reducing bacteremia-associated mortality, and implementing targeted infection control programs. However, only a few studies have reported on the epidemiology of bloodstream infections (BSIs) in pediatrics. We performed a retrospective analysis of all BSIs (excluding those caused by common skin contaminants) diagnosed from 2006 to 2022 in patients younger than 18 years who were treated at an Italian pediatric tertiary care hospital. Overall, 2395 BSIs were recorded, including 2207 (92.15%) due to bacteria and 188 (7.85%) due to fungi. The incidence rate (BSIs/10,000 hospital discharges, IR) of bacterial BSIs significantly increased during the study period. In particular, BSIs caused by S. aureus (including MRSA), Enterobacterales (including ESBL and AmpC producers), Enterococcus spp., and P. aeruginosa became more common. The frequency of carbapenem-resistant strains was <1% and stable over time. Conversely, there was a significant reduction in the incidence of BSIs due to S. pneumoniae. The BSIs were stratified by patient age, and S. aureus was the most frequent cause of BSIs in all age groups, while E. coli was the most frequent in the Enterobacterales family. S. agalactiae was the third most frequent cause of neonatal early-onset BSIs. The prevalence of Enterococcus spp. increased in the subgroups from 8 days to 5 years of age, while P. aeruginosa became more prevalent in children over 5 years of age. S. aureus was also the most frequent isolate in both community- and hospital-onset BSIs, followed by E. coli. The prevalence of multidrug-resistant (MDR) pathogens was very low. It was <5% for both Gram-positive (i.e., MRSA and VRE) and Gram-negative (ESBL, AmpC, and carbapenem-resistant) pathogens, and MDR pathogens were almost exclusively detected in hospital-onset BSIs. Fungi accounted for just under 8% of BSIs. C. albicans was the most frequently isolated strain, followed by C. parapsilosis. Notably, the IR of fungemia did not change significantly during the study period, in spite of an increase in the absolute number of events. The continuous monitoring of local epidemiology is essential to identify changes in the IRs of pathogens and antibiotic susceptibility and to guide antibiotic treatments, especially in the phase when antibiograms are not yet available.
High-Precision Temperature Control of Laser Crystals
Authors: Zhang Xiang , Xu Hang , Feng Liwen , Liu Zhongqi , Wang Tianyi , Xu Jinqiang , Quan Shengwen , Huang Senlin
Published: August 2024

Temperature control is important in second harmonic generation (SHG) based on non-critical phase matching, which is widely used in the accelerator field to generate drive lasers. To further improve the stability of the drive laser for the DC-SRF photocathode electron gun at Peking University, a high-precision temperature control oven for lithium borate (LBO) crystals was developed. The oven’s structure was designed to minimize heat exchange with the external environment. The temperature control circuit uses a thermoelectric cooler to ensure the temperature stability of the sampling circuit. The program utilizes a cascaded proportional-integral-derivative and an anti-saturation integral algorithm to achieve high-precision temperature control. Experiments showed that fluctuation at the working temperature of the LBO crystal in this oven was within ±0.009 °C, corresponding to a root mean square (RMS) jitter of 0.003 °C, and the long-term power fluctuation of the 13.7 W green laser generated with SHG was less than 1%.
Bio-Based Polyurethane–Urea with Self-Healing and Closed-Loop Recyclability Synthesized from Renewable Carbon Dioxide and Vanillin
Authors: Han Tianyi , Tian Tongshuai , Jiang Shan , Lu Bo
Published: August 2024

Developing recyclable and self-healing non-isocyanate polyurethane (NIPU) from renewable resources to replace traditional petroleum-based polyurethane (PU) is crucial for advancing green chemistry and sustainable development. Herein, a series of innovative cross-linked Poly(hydroxyurethane-urea)s (PHUUs) were prepared using renewable carbon dioxide (CO2) and vanillin, which displayed excellent thermal stability properties and solvent resistance. These PHUUs were constructed through the introduction of reversible hydrogen and imine bonds into cross-linked polymer networks, resulting in the cross-linked PHUUs exhibiting thermoplastic-like reprocessability, self healing, and closed-loop recyclability. Notably, the results indicated that the VL-TTD*-50 with remarkable hot-pressed remolding efficiency (nearly 98.0%) and self-healing efficiency (exceeding 95.0%) of tensile strength at 60 °C. Furthermore, they can be degraded in the 1M HCl and THF (v:v = 2:8) solution at room temperature, followed by regeneration without altering their original chemical structure and mechanical properties. This study presents a novel strategy for preparing cross-linked PHUUs with self-healing and closed-loop recyclability from renewable resources as sustainable alternatives for traditional petroleum-based PUs.
Compound-Gaussian Clutter Model with Weibull-Distributed Textures and Parameter Estimation
Authors: Zou Pengjia , Chang Siyuan , Shui Penglang
Published: August 2024

Compound-Gaussian models (CGMs) are widely used to characterize sea clutter. Various types of texture distributions have been developed so that the CGMs can cover sea clutter in different conditions. In this paper, the Weibull distributions are used to model textures of sea clutter, and the CGM with Weibull-distributed textures is used to derive the CGWB distributions, a new type of biparametric distribution. Like the classic K-distributions and Compound-Gaussian with lognormal texture (CGLN) distributions, the biparametric CGWB distributions without analytical expressions can be represented by the closed-form improper integral. Further, the properties of the CGWB distributions are investigated, and four moment-based estimators using sample moments, fractional-order sample moments, and generalized sample moments are given to estimate the parameters of the CGWB distributions. Their performance is compared by simulated clutter data. Moreover, measured sea clutter data are used to examine the suitability of the CGWB distributions. The results show that the CGWB distributions can provide the best goodness-of-the-fit for low-resolution sea clutter data as alternatives to the classic K-distributions.
MLGTM: Multi-Scale Local Geometric Transformer-Mamba Application in Terracotta Warriors Point Cloud Classification
Authors: Zhou Pengbo , An Li , Wang Yong , Geng Guohua
Published: August 2024

As an important representative of ancient Chinese cultural heritage, the classification of Terracotta Warriors point cloud data aids in cultural heritage preservation and digital reconstruction. However, these data face challenges such as complex morphological and structural variations, sparsity, and irregularity. This paper proposes a method named Multi-scale Local Geometric Transformer-Mamba (MLGTM) to improve the accuracy and robustness of Terracotta Warriors point cloud classification tasks. To effectively capture the geometric information of point clouds, we introduce local geometric encoding, including local coordinates and feature information, effectively capturing the complex local morphology and structural variations of the Terracotta Warriors and extracting representative local features. Additionally, we propose a multi-scale Transformer-Mamba information aggregation module, which employs a dual-branch Transformer with a Mamba structure and finally aggregates them on multiple scales to effectively handle the sparsity and irregularity of the Terracotta Warriors point cloud data. We conducted experiments on several datasets, including the ModelNet40, ScanObjectNN, ShapeNetPart, ETH, and 3D Terracotta Warriors fragment datasets. The results show that our method significantly improves the classification task of Terracotta Warriors point clouds, demonstrating strong accuracy.
Analysis of Changes in Forest Vegetation Peak Growth Metrics and Driving Factors in a Typical Climatic Transition Zone: A Case Study of the Funiu Mountain, China
Authors: Tang Jiao , Wang Huimin , Cong Nan , Zu Jiaxing , Yang Yuanzheng
Published: August 2024

Phenology and photosynthetic capacity both regulate carbon uptake by vegetation. Previous research investigating the impact of phenology on vegetation productivity has focused predominantly on the start and end of growing seasons (SOS and EOS), leaving the influence of peak phenology metrics—particularly in typical climatic transition zones—relatively unexplored. Using a 24-year (2000–2023) enhanced vegetation index (EVI) dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS), we extracted and examined the spatiotemporal variation for peak of season (POS) and peak growth (defined as EVImax) of forest vegetation in the Funiu Mountain region, China. In addition to quantifying the factors influencing the peak phenology metrics, the relationship between vegetation productivity and peak phenological metrics (POS and EVImax) was investigated. Our findings reveal that POS and EVImax showed advancement and increase, respectively, negatively and positively correlated with vegetation productivity. This suggested that variations in EVImax and peak phenology both increase vegetation productivity. Our analysis also showed that EVImax was heavily impacted by precipitation, whereas SOS had the greatest effect on POS variation. Our findings highlighted the significance of considering climate variables as well as biological rhythms when examining the global carbon cycle and phenological shifts in response to climate change.
Comparison of the Impacts of Sea Surface Temperature in the Western Pacific and Indian Ocean on the Asian Summer Monsoon Anticyclone and Water Vapor in the Upper Troposphere
Authors: Chao Luyao , Tian Hongying , Tu Xiaoxu , Jiang Jiaying , Shen Kailong
Published: August 2024

The variation in the Asian summer monsoon anticyclone (ASMA) has long been of interest due to its effects on the weather and climate, as well as the vertical transport of pollutants in South Asia and East Asia. This study employs composite analysis to investigate the differences in the influences of sea surface temperature (SST) anomalies in the Western Pacific (WP) and the Indian Ocean (IO) on the ASMA and water vapor in the upper troposphere during summer. The underlying physical mechanisms were further explored. The results indicate that the warm SSTs in the WP have a greater impact on the intensity of the ASMA than those in the IO in summer. On the contrary, the cold SSTs in the IO have a greater impact on intensity of the ASMA than those in the WP in summer. The difference in the impact of SSTs in the WP and IO on the boundaries of the ASMA is relatively small. During positive SST anomalies in the WP, the increase in tropospheric temperature in South Asia and the strengthening of Walker circulation in the WP both contribute to the enhancement of the ASMA. The variations in tropospheric temperature and Walker circulation caused by positive SST anomalies in the IO are similar to those in the WP, except that the rising branch of the Walker circulation is located in the central and western IO. The decrease in SST in the WP region causes insignificant changes in the ASMA. During the cold SST period in the IO, the significant decrease in tropospheric temperature and the weakening of the Walker circulation in the IO region lead to a significant decrease in the intensity of the ASMA at the southern ASMA. When the SST in the WP and IO regions is warmer, the high value centers of water vapor in the troposphere generally coincide with the high value centers of temperature, accompanied by enhanced convection, significantly increasing the water vapor south of the ASMA. The anomalous sinking movement in the Western Pacific leads to relatively small changes in water vapor from the near-surface to 150 hPa over the southeast of the ASMA.
Daily-Life Walking Speed, Quality and Quantity Derived from a Wrist Motion Sensor: Large-Scale Normative Data for Middle-Aged and Older Adults
Authors: Chan Lloyd L. Y. , Lord Stephen R. , Brodie Matthew A.
Published: August 2024

Walking is crucial for independence and quality of life. This study leverages wrist-worn sensor data from UK Biobank participants to establish normative daily-life walking data, stratified by age and sex, to provide benchmarks for research and clinical practice. The Watch Walk digital biomarkers were developed, validated, and applied to 92,022 participants aged 45–79 who wore a wrist sensor for at least three days. Normative data were collected for daily-life walking speed, step-time variability, step count, and 17 other gait and sleep biomarkers. Test–retest reliability was calculated, and associations with sex, age, self-reported walking pace, and mobility problems were examined. Population mean maximal and usual walking speeds were 1.49 and 1.15 m/s, respectively. The daily step count was 7749 steps, and step regularity was 65%. Women walked more regularly but slower than men. Walking speed, step count, longest walk duration, and step regularity decreased with age. Walking speed is associated with sex, age, self-reported pace, and mobility problems. Test–retest reliability was good to excellent (ICC ≥ 0.80). This study provides large-scale normative data and benchmarks for wrist-sensor-derived digital gait and sleep biomarkers from real-world data for future research and clinical applications.
SPIN-Based Linear Temporal Logic Path Planning for Ground Vehicle Missions with Motion Constraints on Digital Elevation Models
Authors: Toscano-Moreno Manuel , Mandow Anthony , Martínez María Alcázar , García-Cerezo Alfonso José
Published: August 2024

Linear temporal logic (LTL) formalism can ensure the correctness of mobile robot planning through concise, readable, and verifiable mission specifications. For uneven terrain, planning must consider motion constraints related to asymmetric slope traversability and maneuverability. However, even though model checker tools like the open-source Simple Promela Interpreter (SPIN) include search optimization techniques to address the state explosion problem, defining a global LTL property that encompasses both mission specifications and motion constraints on digital elevation models (DEMs) can lead to complex models and high computation times. In this article, we propose a system model that incorporates a set of uncrewed ground vehicle (UGV) motion constraints, allowing these constraints to be omitted from LTL model checking. This model is used in the LTL synthesizer for path planning, where an LTL property describes only the mission specification. Furthermore, we present a specific parameterization for path planning synthesis using a SPIN. We also offer two SPIN-efficient general LTL formulas for representative UGV missions to reach a DEM partition set, with a specified or unspecified order, respectively. Validation experiments performed on synthetic and real-world DEMs demonstrate the feasibility of the framework for complex mission specifications on DEMs, achieving a significant reduction in computation cost compared to a baseline approach that includes a global LTL property, even when applying appropriate search optimization techniques on both path planners.
Non-Intrusive Continuous Monitoring of Leaks for an In-Service Penstock
Authors: Nati Marius , Despina-Stoian Cristina , Nastasiu Dragos , Stanescu Denis , Digulescu Angela , Ioana Cornel , Nanchen Vincent
Published: August 2024

In modern industries, pipelines play a crucial role, both as an essential element in energy transportation (water, gas and electricity) and also in the distribution of these resources. The large size of piping infrastructures, their age and unpredictable external factors are the main difficulties in monitoring the piping system. In this context, the detection and the localization of leaks are challenging but essential, as leaks lead to substantial economic losses. Current methods have many limitations, involving invasive procedures, working only with short pipes or requiring a system shutdown. This paper presents a non-intrusive method based on acoustic signal processing. Leak detection is performed using matched filters, while localization is performed based on the phase diagram representation method and diagram-based entropy computation. Our continuous monitoring system was used for two months and a full comparison with the video inspection-based technique was conducted. The results indicate that this method has a high accuracy, regardless of the length of the pipe.
Impact Localization in Complex Cylindrical Shell Structures Based on the Time-Reversal Virtual Focusing Triangulation Method
Authors: Huang Xiufeng , Xu Rongwu , Yu Wenjing , Wu Shiji
Published: August 2024

In addressing the challenging issue of impact source localization for large-scale anisotropic stiffened compartmental cylindrical shell structures, this paper presents a novel impact localization method. The method is based on a time-reversal virtual focusing triangulation approach and does not rely on prior knowledge of the structure or specific measurements of wave velocity. By employing energy power filtering to select key sensors, wavelet packet decomposition is utilized to extract narrowband Lamb wave signals, which are then synthesized. Further enhancement of signal recognition is achieved through time-reversal amplification techniques. Experimental results demonstrate that under non-motorized operating conditions, this method achieves an average error of 0.89 m. Under motorized operating conditions, the average error is 1.12 m. Although the presence of background noise leads to an increase in error, the overall localization performance is superior to traditional triangulation methods. Additionally, selecting the top three sensors in terms of energy power ranking can more accurately record impact response.
An Object-Centric Hierarchical Pose Estimation Method Using Semantic High-Definition Maps for General Autonomous Driving
Authors: Pyo Jeong-Won , Choi Jun-Hyeon , Kuc Tae-Yong
Published: August 2024

To achieve Level 4 and above autonomous driving, a robust and stable autonomous driving system is essential to adapt to various environmental changes. This paper aims to perform vehicle pose estimation, a crucial element in forming autonomous driving systems, more universally and robustly. The prevalent method for vehicle pose estimation in autonomous driving systems relies on Real-Time Kinematic (RTK) sensor data, ensuring accurate location acquisition. However, due to the characteristics of RTK sensors, precise positioning is challenging or impossible in indoor spaces or areas with signal interference, leading to inaccurate pose estimation and hindering autonomous driving in such scenarios. This paper proposes a method to overcome these challenges by leveraging objects registered in a high-precision map. The proposed approach involves creating a semantic high-definition (HD) map with added objects, forming object-centric features, recognizing locations using these features, and accurately estimating the vehicle’s pose from the recognized location. This proposed method enhances the precision of vehicle pose estimation in environments where acquiring RTK sensor data is challenging, enabling more robust and stable autonomous driving. The paper demonstrates the proposed method’s effectiveness through simulation and real-world experiments, showcasing its capability for more precise pose estimation.
Adaptive Control for a Two-Axis Semi-Strapdown Stabilized Platform Based on Disturbance Transformation and LWOA-PID
Authors: Huang Qixuan , Zhou Jiaxing , Chen Xiang , Li Qing , Chen Runjing
Published: August 2024

A two-axis semi-strapdown stabilized platform is a device designed to eliminate aircraft disturbances and ensure the stability of the sensor’s orientation. A traditional two-axis semi-strapdown stabilization platform for aircraft can effectively control disturbance in pitch and yaw channel, but it cannot achieve ideal disturbance control in the roll channel. In order to solve this problem, an adaptive control method based on disturbance transformation and LWOA-PID is proposed. Disturbance transformation is the process of integrating the angular position disturbance of the roll from the previous moment into the combined disturbance of the pitch and yaw at the current moment. This is followed by decoupling the combined disturbance of the pitch and yaw at the current moment, thereby eliminating the disturbance caused by the roll from the previous moment. This process is repeated to achieve the goal of eliminating roll channel disturbances. To ensure the line of sight (LOS) pointing accuracy stability in the two-axis semi-strapdown stabilized platform system for aircraft, a whale optimization adaptive proportional–integral–derivative (LWOA-PID) controller based on Latin hypercube sampling is designed. It is then compared with the classical PID controller in Matlab/Simulink. The simulation results indicate that the disturbance conversion module proposed in this paper can eliminate the impact of roll axis disturbances on the LOS pointing accuracy of the two-axis semi-strapdown stabilized platform for aircraft. Compared to the classical PID controller, the LWOA-PID controller reduces tracking errors for step and sinusoidal signals by 50% and 75%, respectively. It also shortens optimization time by 37.5% compared to the WOA-PID while maintaining the same level of accuracy. Furthermore, when combined with the conversion module, the tracking error is reduced by an additional order of magnitude.
A Multilayer Architecture towards the Development and Distribution of Multimodal Interface Applications on the Edge
Authors: Malamas Nikolaos , Panayiotou Konstantinos , Karabatea Apostolia , Tsardoulias Emmanouil , Symeonidis Andreas L.
Published: August 2024

Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly.
Crack Detection Method for Wind Turbine Tower Bolts Using Ultrasonic Spiral Phased Array
Authors: Sun Hongyu , Dong Jingqi , Diao Xi , Huang Xincheng , Huang Ziyi , Cai Zhichao
Published: August 2024

High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry.
Semi-Supervised Building Extraction with Optical Flow Correction Based on Satellite Video Data in a Tsunami-Induced Disaster Scene
Authors: Qiao Huijiao , Qian Weiqi , Hu Haifeng , Huang Xingbo , Li Jiequn
Published: August 2024

Data and reports indicate an increasing frequency and intensity of natural disasters worldwide. Buildings play a crucial role in disaster responses and damage assessments, aiding in planning rescue efforts and evaluating losses. Despite advances in applying deep learning to building extraction, challenges remain in handling complex natural disaster scenes and reducing reliance on labeled datasets. Recent advances in satellite video are opening a new avenue for efficient and accurate building extraction research. By thoroughly mining the characteristics of disaster video data, this work provides a new semantic segmentation model for accurate and efficient building extraction based on a limited number of training data, which consists of two parts: the prediction module and the automatic correction module. The prediction module, based on a base encoder–decoder structure, initially extracts buildings using a limited amount of training data that are obtained instantly. Then, the automatic correction module takes the output of the prediction module as input, constructs a criterion for identifying pixels with erroneous semantic information, and uses optical flow values to extract the accurate corresponding semantic information on the corrected frame. The experimental results demonstrate that the proposed method outperforms other methods in accuracy and computational complexity in complicated natural disaster scenes.
MOVING: A Multi-Modal Dataset of EEG Signals and Virtual Glove Hand Tracking
Authors: Mattei Enrico , Lozzi Daniele , Di Matteo Alessandro , Cipriani Alessia , Manes Costanzo , Placidi Giuseppe
Published: August 2024

Brain–computer interfaces (BCIs) are pivotal in translating neural activities into control commands for external assistive devices. Non-invasive techniques like electroencephalography (EEG) offer a balance of sensitivity and spatial-temporal resolution for capturing brain signals associated with motor activities. This work introduces MOVING, a Multi-Modal dataset of EEG signals and Virtual Glove Hand Tracking. This dataset comprises neural EEG signals and kinematic data associated with three hand movements—open/close, finger tapping, and wrist rotation—along with a rest period. The dataset, obtained from 11 subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers. The use of these two devices allows for fast assembly (∼1 min), although introducing more noise than the gold standard devices for data acquisition. The study investigates which frequency bands in EEG signals are the most informative for motor task classification and the impact of baseline reduction on gesture recognition. Deep learning techniques, particularly EEGnetV4, are applied to analyze and classify movements based on the EEG data. This dataset aims to facilitate advances in BCI research and in the development of assistive devices for people with impaired hand mobility. This study contributes to the repository of EEG datasets, which is continuously increasing with data from other subjects, which is hoped to serve as benchmarks for new BCI approaches and applications.
IoT Forensics: Current Perspectives and Future Directions
Authors: Ahmed Abdulghani Ali , Farhan Khalid , Jabbar Waheb A. , Al-Othmani Abdulaleem , Abdulrahman Abdullahi Gara
Published: August 2024

The Internet of Things forensics is a specialised field within digital forensics that focuses on the identification of security incidents, as well as the collection and analysis of evidence with the aim of preventing future attacks on IoT networks. IoT forensics differs from other digital forensic fields due to the unique characteristics of IoT devices, such as limited processing power and connectivity. Although numerous studies are available on IoT forensics, the field is rapidly evolving, and comprehensive surveys are needed to keep up with new developments, emerging threats, and evolving best practices. In this respect, this paper aims to review the state of the art in IoT forensics and discuss the challenges in current investigation techniques. A qualitative analysis of related reviews in the field of IoT forensics has been conducted, identifying key issues and assessing primary obstacles. Despite the variety of topics and approaches, common issues emerge. The majority of these issues are related to the collection and pre-processing of evidence because of the counter-analysis techniques and challenges associated with gathering data from devices and the cloud. Our analysis extends beyond technological problems; it further identifies the procedural problems with preparedness, reporting, and presentation as well as ethical issues. In particular, it provides insights into emerging threats and challenges in IoT forensics, increases awareness and understanding of the importance of IoT forensics in preventing cybercrimes, and ensures the security and privacy of IoT devices and networks. Our findings make a substantial contribution to the field of IoT forensics, as they not only involve a critical analysis of the challenges presented in existing works but also identify numerous problems. These insights will greatly assist researchers in identifying appropriate directions for their future research.
Collision Avoidance Path Planning and Tracking Control for Autonomous Vehicles Based on Model Predictive Control
Authors: Dong Ding , Ye Hongtao , Luo Wenguang , Wen Jiayan , Huang Dan
Published: August 2024

In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajectory tracking, adaptive cruise control (ACC), and active obstacle avoidance under high vehicle speed. Firstly, an MPC-based trajectory tracking controller is designed based on the vehicle dynamics model. Then, the MPC was combined with ACC to design the control strategies for vehicle braking to avoid collisions. Additionally, active steering for collision avoidance was developed based on the safety distance model. Finally, considering the distance between the vehicle and the obstacle and the relative speed, an obstacle avoidance function is constructed. A path planning controller based on nonlinear model predictive control (NMPC) is designed. In addition, the alternating direction multiplier method (ADMM) is used to accelerate the solution process and further ensure the safety of the obstacle avoidance process. The proposed algorithm is tested on the Simulink and CarSim co-simulation platform in both static and dynamic obstacle scenarios. Results show that the method effectively achieves collision avoidance through braking. It also demonstrates good stability and robustness in steering to avoid collisions at high speeds. The experiments confirm that the vehicle can return to the desired path after avoiding obstacles, verifying the effectiveness of the algorithm.
Performance Evaluation of Structural Health Monitoring System Applied to Full-Size Composite Wing Spar via Probability of Detection Techniques
Authors: Galasso Bernardino , Ciminello Monica , Apuleo Gianvito , Bardenstein David , Concilio Antonio
Published: August 2024

Probability of detection (POD) is an acknowledged mean of evaluation for many investigations aiming at detecting some specific property of a subject of interest. For instance, it has had many applications for Non-Destructive Evaluation (NDE), aimed at identifying defects within structural architectures, and can easily be used for structural health monitoring (SHM) systems, meant as a compact and more integrated evolution of the former technology. In this paper, a probability of detection analysis is performed to estimate the reliability of an SHM system, applied to a wing box composite spar for bonding line quality assessment. Such a system is based on distributed fiber optics deployed on the reference component at specific locations for detecting strains; the attained data are then processed by a proprietary algorithm whose capability was already tested and reported in previous works, even at full-scale level. A finite element (FE) model, previously validated by experimental results, is used to simulate the presence of damage areas, whose effect is to modify strain transfer between adjacent parts. Numerical data are used to verify the capability of the SHM system in revealing the presence of the modeled physical discontinuities with respect to a specific set of loads, running along the beam up to cover its complete extension. The POD is then estimated through the analysis of the collected data sets, wide enough to assess the global SHM system performance. The results of this study eventually aim at improving the current strategies adopted for SHM for bonding analysis by identifying the intimate behavior of the system assessed at the date. The activities herein reported have been carried out within the RESUME project.
Advances in the Production of PBCA Microparticles Using a Micromixer with HH-Geometry in a Microfluidic System
Authors: Vieira Aline Rocha , Oliveira Aline Furtado , Pessoa Fabiana Vieira Lima Solino , Miranda Beatriz Nogueira Messias de , Baby André Rolim
Published: August 2024

Different reaction control methods for producing nano/microstructures of poly(butyl cyanoacrylate) (PBCA) have been studied, focusing on pH and monomer-to-initiator ratios. However, these methods often require multiple steps and reagents. In the synthesis of PBCA microparticles using three versions of micromixers designed with HH geometry and varying numbers of channels (4, 10, and 15), different synthesis formulations were investigated by varying monomer concentrations. PBCA microparticles synthesized with 19.2% (w/w) n-butyl cyanoacrylate (n-BCA) monomer, a residence time of 0.06 s, a flow rate of 78 mL·min−1, and a phase ratio of 45/55 (W/O), exhibited an average diameter of 642.2 nm as determined by dynamic light scattering (DLS) analysis. In contrast, PBCA microparticles synthesized with 5.0% (w/w) n-BCA monomer, the same residence time of 0.06 s, a flow rate of 39 mL·min−1, and a phase ratio of 20/80 (W/O), exhibited an average diameter of 74.73 µm according to laser diffraction particle size analysis. Polymer formation was confirmed by Fourier-transform infrared (FTIR) spectroscopy in both formulation and process conditions. These results indicate that the parameters for the production of microparticles with different monomer concentrations in the microfluidic system with HH geometry and 15 channels can be optimized for potential applications in cosmetics and pharmaceutical ingredients.
Thermal Comfort Challenges in Home-Based Enterprises: A Field Study from Surakarta’s Urban Low-Cost Housing in a Tropical Climate
Authors: Handayani Kusumaningdyah Nurul , Murtyas Solli , Wijayanta Agung Tri , Hagishima Aya
Published: August 2024

The growing global concern over heat-related health risks, exacerbated by climate change, disproportionately affects low-income populations, particularly in tropical regions like Indonesia. This study investigates indoor thermal conditions in home-based enterprises (HBEs) within the informal urban settlements of Surakarta City, Indonesia, focusing on the struggle for thermal comfort under constrained conditions. By addressing the thermal comfort challenges in low-income urban housing, this research contributes to sustainable development goals, aiming to enhance living conditions in tropical climates. Our methodology included detailed field measurements of thermal comfort using standard indices in these dwellings, complemented by surveys and interviews to understand building designs, occupant behaviors, and adaptation strategies. Findings indicate that temperatures inside the dwellings frequently exceeded 30 °C during 50–60% of working hours, prompting residents to adopt coping strategies such as opening windows, adjusting work schedules, and utilizing shading devices. Space limitations necessitated multifunctional use of dwellings, exacerbating heat and humidity from activities like cooking and ironing. Despite reliance on natural ventilation, ineffective architectural layouts impeded airflow. This study highlights the urgent need for sustainable architectural solutions that accommodate the dual residential and commercial functions of these spaces, aiming to improve living conditions in such challenging environments.
A Technological Perspective of Bringing Climate Change Adaptation, Disaster Risk Reduction, and Food Security Together in South Africa
Authors: Zembe Annegrace , Nemakonde Livhuwani David , Chipangura Paul , Coetzee Christo , Mangara Fortune
Published: August 2024

As disasters and climate change risks, particularly droughts and floods, continue to affect food security globally, most governments, including South Africa, have resorted to the use of technology to incorporate climate change adaptation and disaster risk reduction to address FS issues. This is because most institutions and policies that address climate change adaptation, disaster risk reduction, and food security operate in parallel, which usually leads to the polarisation of interventions and conflicting objectives, thus leaving the issue of FS unresolved. The study aimed to investigate how food security projects are incorporating climate change adaptation and disaster risk reduction using technology. A qualitative research design was applied, whereby in-depth interviews were conducted with ten project participants from two projects, while 24 key informants were purposively selected from government and research institutions. The study’s main findings revealed that both projects incorporate climate change adaptation and disaster risk reduction measures in most of their food value chains. Although the projects are different, they still face similar challenges, such as a lack of expertise, resources, and funding, and an inadequate regulatory environment to improve their farming practices. The study brings in the practical side of addressing the coherence between food security, climate change adaptation, and disaster risk reduction through technology.
Characterization and Anti-Biofilm Activity of Lytic Enterococcus Phage vB_Efs8_KEN04 against Clinical Isolates of Multidrug-Resistant Enterococcus faecalis in Kenya
Authors: Soro Oumarou , Kigen Collins , Nyerere Andrew , Gachoya Moses , Georges Martin , Odoyo Erick , Musila Lillian
Published: August 2024

Enterococcus faecalis (E. faecalis) is a growing cause of nosocomial and antibiotic-resistant infections. Treating drug-resistant E. faecalis requires novel approaches. The use of bacteriophages (phages) against multidrug-resistant (MDR) bacteria has recently garnered global attention. Biofilms play a vital role in E. faecalis pathogenesis as they enhance antibiotic resistance. Phages eliminate biofilms by producing lytic enzymes, including depolymerases. In this study, Enterococcus phage vB_Efs8_KEN04, isolated from a sewage treatment plant in Nairobi, Kenya, was tested against clinical strains of MDR E. faecalis. This phage had a broad host range against 100% (26/26) of MDR E. faecalis clinical isolates and cross-species activity against Enterococcus faecium. It was able to withstand acidic and alkaline conditions, from pH 3 to 11, as well as temperatures between −80 °C and 37 °C. It could inhibit and disrupt the biofilms of MDR E. faecalis. Its linear double-stranded DNA genome of 142,402 bp contains 238 coding sequences with a G + C content and coding gene density of 36.01% and 91.46%, respectively. Genomic analyses showed that phage vB_Efs8_KEN04 belongs to the genus Kochikohdavirus in the family Herelleviridae. It lacked antimicrobial resistance, virulence, and lysogeny genes, and its stability, broad host range, and cross-species lysis indicate strong potential for the treatment of Enterococcus infections.
PHYSICO-CHEMICAL PROPERTIES OF POLYMER-BITUMEN BINDERS MODIFIED WITH SHUNGITE FROM VARIOUS DEPOSITS OF KARELIA
Authors: Yadykina V. , Lebedev M. , Vyrodova K.
Published: August 2024

The use of polymer-bitumen binders as part of an asphalt concrete mixture allows to improve the quality of road surfaces. The most commonly used polymer is styrene and butadiene copolymer, however, it does not provide sufficient durability of asphalt concrete and has a high cost. There is a positive experience in solving these problems through the use of polymer composites filled with fine powders. One of the promising polymer fillers is shungite. The purpose of this work was to study the effect of shungite from various deposits of Karelia on the structure and properties of polymer-bitumen binder. It was found that the introduction of shungite in the amount of 5 wt.% changes the physico-chemical characteristics of polymer-bitumen binders: the viscosity and softening temperature increase markedly, the temperature of brittleness, as well as extensibility and elasticity change to a lesser extent. Changes in these properties indicate the structuring of the binder by finely dispersed shungite. This phenomenon may be associated with the transfer of bitumen from a volumetric to a structured state due to its interaction with the surface of the shungite powder, as well as due to the diffusion of low-molecular components of the binder into the pores of the filler. Moreover, shungite samples from different deposits do not affect the studied characteristics in the same way. The explanation for this may lie in the different content of active adsorption centers on the surface of shungite, which is in a linear relationship with the main characteristics of the polymer-bitumen binder modified with shungite.