bluuebunny/crossref_metadata_2025 huggingface dataset:
Auxin-Mediated Lateral Root Development in Root Galls of Cucumber under Meloidogyne incognita Stress
Authors: Ren Baoling , Guo Xin , Liu Jingjing , Feng Guifang , Hao Xiaodong , Zhang Xu , Chen Zhiqun
Published: September 2024

Root-knot nematodes induce the formation of feeding sites within the host roots and the relocation of auxin into galls results in abnormal lateral root growth. Here, we analyzed the changes in cucumber root architecture under Meloidogyne incognita stress and the distribution of auxin in these morphological and molecular root changes. The number of root tips significantly decreased, and regression analysis showed a positive relationship between the size of root galls and the numbers of nematodes in galls compared with the lateral roots on galls, emphasizing the effect of nematode parasitism on root development. Data generated via a promoter-reporter system using the transgenic hairy root system first characterized the auxin distribution during nematode parasitism in cucumber. Using DR5:GUS staining of root galls, we further detected the expression of CsPIN1 and CsAUX1, which regulate polar auxin transport. The results showed that both CsPIN1 and CsAUX1 were induced in galls, and the relative expression of the two genes significantly increased at 21 DAI. The TIBA treatment, which can disrupt polar auxin transport inhibited the numbers of cucumber root tips and total length following increasing concentration gradients. Moreover, the numbers of galls were significantly affected by TIBA treatment, which showed the vital role of auxin during nematode parasitism. Our findings suggest that the transportation of auxin plays an important role during gall formation and induces cucumber lateral root development within nematode feeding sites.
Integrative Modeling and Experimental Insights into 3D and 4D Printing Technologies
Authors: Pereira Angel Cabrera , Nayak Vasudev Vivekanand , Coelho Paulo G. , Witek Lukasz
Published: September 2024

This review focuses on advancements in polymer science as it relates to three-dimensional (3D) and four-dimensional (4D) printing technologies, with a specific emphasis on applications in the biomedical field. While acknowledging the breadth of 3D and 4D printing applications, this paper concentrates on the use of polymers in creating biomedical devices and the challenges associated with their implementation. It explores integrative modeling and experimental insights driving innovations in these fields, focusing on sustainable manufacturing with biodegradable polymers, a comparative analysis of 3D and 4D printing techniques, and applications in biomedical devices. Additionally, the review examines the materials used in both 3D and 4D printing, offering a detailed comparison of their properties and applications. By highlighting the transformative potential of these technologies in various industrial and medical applications, the paper underscores the importance of continued research and development. The scope of this review also includes an overview of future research directions to address current challenges, enhance material capabilities, and explore practical applications.
Modification of Lateritic Soil Using Waste Plastics for Sustainable Road Construction
Authors: Obianyo Ifeyinwa Ijeoma , Taiwo Ibitayo Akintayo , Dayyabu Abubakar , Mahamat Assia Aboubakar , Amuda Akeem , Muoka Anthony , Mambo Abdulhameed Danjuma , Onwualu Azikiwe Peter
Published: September 2024

Lateritic soil, a prevalent geological material in tropical regions, often exhibits poor engineering properties, leading to road pavement failures. Meanwhile, the alarming rise in plastic waste poses environmental concerns. This innovative study explores the potential of utilizing waste plastics as a lateritic soil addictive for sustainable road construction. Varying percentages by weight of shredded waste plastic (2%, 4%, 6%, 8%, and 10%) were incorporated into lateritic soil samples, evaluating its effects on soil geotechnical properties. The results revealed that lateritized plastic (shredded plastic waste and lateritic soil) containing 2% shredded plastic waste gave the optimum maximum dry density of 1.985 g/cm3, and the lateritized plastic containing 10% shredded plastic waste gave the highest optimum moisture content of 18%. However, the lower California bearing ratio obtained on the addition of plastic waste showed that the lateritized plastic is relatively weak and can only be used for roads with low traffic. The incorporation of shredded plastic waste into lateritic soil for stabilization is a promising polymer science-based method. By reducing the need for conventional materials and diverting plastic waste from landfills, this approach contributes to a more environmentally friendly infrastructure supporting the achievement of United Nation Sustainable Development Goals.
Influence of Chitosan on the Viability of Encapsulated and Dehydrated Formulations of Vegetative Cells of Actinomycetes
Authors: Mancera-López María Elena , Barrera-Cortés Josefina
Published: September 2024

This study focuses on developing an encapsulated and dehydrated formulation of vegetative actinobacteria cells for an efficient application in sustainable agriculture, both as a fungicidal agent in crop protection and as a growth-stimulating agent in plants. Three strains of actinobacteria were used: one from a collection (Streptomyces sp.) and two natives to agricultural soil, which were identified as S3 and S6. Vegetative cells propagated in a specific liquid medium for mycelium production were encapsulated in various alginate–chitosan composites produced by extrusion. Optimal conditions for cell encapsulation were determined, and cell damage from air-drying at room temperature was evaluated. The fresh and dehydrated composites were characterized by porosity, functional groups, size and shape, and their ability to protect the immobilized vegetative cells’ viability. Actinomycetes were immobilized in capsules of 2.1–2.7 mm diameter with a sphericity index ranging from 0.058 to 0.112. Encapsulation efficiency ranged from 50% to 88%, and cell viability after drying varied between 44% and 96%, depending on the composite type, strain, and airflow. Among the three immobilized and dried strains, S3 and S6 showed greater resistance to encapsulation and drying with a 4 L·min−1 airflow when immobilized in coated and core-shell composites. Encapsulation in alginate–chitosan matrices effectively protects vegetative actinobacteria cells during dehydration, maintaining their viability and functionality for agricultural applications.
Strengthening the Resilience of Pupils through Catholic Religious Education in Poland: From Theory to Practice
Authors: Zellma Anna , Mąkosa Paweł Michał
Published: September 2024

Many young people find themselves unable to cope with the challenges of today’s world and, as a result, lose their self-confidence and joy in life, suffer from depression, and even attempt suicide. The first community that should offer help in a crisis is, without doubt, the family, but it often needs support. Such support can and should be provided by the school since it has the necessary tools and children and adolescents spend a lot of time there. Undoubtedly, religious education at school should also involve preventive and even therapeutic measures in the face of the above challenges. The research problem of this article is as follows: Does Catholic religious education in Poland seek to strengthen pupils’ resilience, and if so, in what way? This study analysed the curricular assumptions and practical activities implemented within the framework of or inspired by religious education. Its findings show that resilience has already become an important issue for religious education even though, in the face of increasing challenges, it requires improving already-established activities and including new areas of improvement.
Introduction: Gurus, Priestesses, Saints, Mediums and Yoginis: Holy Women as Influencers in Hindu Culture
Authors: McDaniel June
Published: September 2024

This Special Issue is dedicated to Hindu holy women past and present and the ways that they have influenced society [...]
Incorporating Effects of Slope Units and Sliding Areas into Seismically Induced Landslide Risk Modeling in Tectonically Active Mountainous Areas
Authors: Wu Hao , Ye Chenzuo , Pei Xiangjun , Oguchi Takashi , He Zhihao , Yang Hailong , Huang Runqiu
Published: September 2024

Traditional Newmark models estimate earthquake-induced landslide hazards by calculating permanent displacements exceeding the critical acceleration, which is determined from static factors of safety and hillslope geometries. However, these studies typically predict the potential landslide mass only for the source area, rather than the entire landslide zone, which includes both the source and sliding/depositional areas. In this study, we present a modified Newmark Runout model that incorporates sliding and depositional areas to improve the estimation of landslide chain risks. This model defines the landslide runout as the direction from the source area to the nearest river channel within the same slope unit, simulating natural landslide behavior under gravitational effects, which enables the prediction of the entire landslide zone. We applied the model to a subset of the Minjiang Catchment affected by the 1933 MW 7.3 Diexi Earthquake in China to assess long-term landslide chain risks. The results indicate that the predicted total landslide zone closely matches that of the Xinmo Landslide that occurred on 24 June 2017, despite some uncertainties in the sliding direction caused by the old landslide along the sliding path. Distance-weighted kernel density analysis was used to reduce the prediction uncertainties. The hazard levels of the buildings and roads were determined by the distance to the nearest entire landslide zone, thereby assessing the landslide risk. The landslide dam risks were estimated using the kernel density module for channels blocked by the predicted landslides, modeling intersections of the total landslide zone and the channels. High-risk landslide dam zones spatially correspond to the locations of the knickpoints primarily induced by landslide dams, validating the model’s accuracy. These analyses demonstrate the effectiveness of the presented model for Newmark-based landslide risk estimations, with implications for geohazard chain risk assessments, risk mitigation, and land use planning and management.
A Novel Method for Simplifying the Distribution Envelope of Green Tide for Fast Drift Prediction in the Yellow Sea, China
Authors: Ding Yi , Gao Song , Huang Guoman , Wu Lingjuan , Wang Zhiyong , Yuan Chao , Yu Zhigang
Published: September 2024

Since 2008, annual outbreaks of green tides in the Yellow Sea have had severe impacts on tourism, fisheries, water sports, and marine ecology, necessitating effective interception and removal measures. Satellite remote sensing has emerged as a promising tool for monitoring large-scale green tides due to its wide coverage and instantaneous imaging capabilities. Additionally, drift prediction techniques can forecast the location of future green tides based on remote sensing monitoring information. This monitoring and prediction information is crucial for developing an effective plan to intercept and remove green tides. One key aspect of this monitoring information is the green tide distribution envelope, which can be generated automatically and quickly using buffer analysis methods. However, this method produces a large number of envelope vertices, resulting in significant computational burden during prediction calculations. To address this issue, this paper proposes a simplification method based on azimuth difference and side length (SM-ADSL). Compared to the isometric and Douglas–Peucker methods with the same simplification rate, SM-ADSL exhibits better performance in preserving shape and area. The simplified distribution envelope can shorten prediction times and enhance the efficiency of emergency decision-making for green tide disasters.
Dynamic Monitoring and Analysis of Ecological Environment Quality in Arid and Semi-Arid Areas Based on a Modified Remote Sensing Ecological Index (MRSEI): A Case Study of the Qilian Mountain National Nature Reserve
Authors: Zhang Xiuxia , Wang Xiaoxian , Li Wangping , Wu Xiaodong , Cheng Xiaoqiang , Zhou Zhaoye , Ling Qing , Liu Yadong , Liu Xiaojie , Hao Junming , Wang Tingting , Deng Lingzhi , Han Lisha
Published: September 2024

The ecosystems within the Qilian Mountain National Nature Reserve (QMNNR) and its surrounding areas have been significantly affected by changes in climate and land use, which have, in turn, constrained the region’s socio-economic development. This study investigates the regional characteristics and application requirements of the ecological environment in the arid and semi-arid zones of the reserve. In view of the saturated characteristics of NDVI in the reserve and the high-altitude saline-alkali environmental conditions, this study proposed a Modified Remote Sensing Ecology Index (MRSEI) by introducing the kernel NDVI and comprehensive salinity index (CSI). This approach enhances the applicability of the remote sensing ecological index. The temporal and spatial dynamics of ecological and environmental quality within the QMNNR from 2000 to 2022 were quantitatively assessed using the MRSEI. The effect of land use on ecological quality was quantified by analyzing the MRSEI contribution rate. The findings in this paper indicate that (1) in arid and semi-arid regions, the MRSEI provides a more precise representation of surface ecological environmental quality compared to the remote sensing ecological index (RSEI). The high correlation (R2 = 0.908) and significant difference between MRSEI and RSEI demonstrate that MRSEI enhances the accuracy of evaluating ecological environmental quality. The impact of land use on ecological quality was quantitatively assessed by analyzing the contribution rate of the MRSEI. (2) The ecological quality of the QMNNR exhibited an upward trend from 2000 to 2022, with an increase rate of 1.3 × 10−3 y−1. The area characterized by improved ecological and environmental quality constitutes approximately 53.68% of the total area. Conversely, the ecological quality of the degraded areas accounts for roughly 28.77%. (3) Among the various land use types, the improvement in ecological environmental quality within the reserve is primarily attributed to the expansion of forest and grassland areas, along with a reduction in unused land. Forest and grassland types account for over 90% of the total area classified with “good” and “excellent” ecological grades, whereas unused land types represent more than 44% of the total area classified with “poor” ecological grades. Overall, this study provides a valuable framework for analyzing ecological and environmental changes in arid and semi-arid regions.
Intersensor Calibration of Spaceborne Passive Microwave Radiometers and Algorithm Tuning for Long-Term Sea Ice Trend Analysis Based on AMSR-E Observations
Authors: Seki Mieko , Hori Masahiro , Naoki Kazuhiro , Kachi Misako , Imaoka Keiji
Published: September 2024

Sea ice monitoring is key to analyzing the Earth’s climate system. Long-term sea ice extent (SIE) has been continuously monitored using various spaceborne passive microwave radiometers (PMRs) since November 1978. As the lifetime of a satellite is usually approximately 5 years, bias caused by differences in PMRs should be eliminated to obtain objective SIE trends. Most sea ice products have been analyzed for long-term trends with a bias adjustment based on the coarse resolution special sensor microwave imager (SSM/I) in operation for the longest period. However, since 2002, Japanese microwave radiometers of the Advanced Microwave Scanning Radiometer (AMSR) series, which have the highest spatial resolution in PMR, have been available. In this study, we developed standardization techniques for processing SIE including calibration of the brightness temperature (TB), tuning the sea ice concentration (SIC) algorithm, and adjusting the SIC threshold to retrieve a consistent SIE trend based on the AMSR for the Earth Observing System (AMSR-E, one of the AMSR that operated from May 2002 to October 2011). Analysis results showed that the root-mean-square error between AMSR-E SICs and those of moderate resolution imaging spectroradiometer (MODIS) was 15%. In this study, SIE was defined as the sum of the areas where the AMSR-E SIC was >15%. When retrieving SIE, we adjusted the SIC threshold for each PMR to be consistent with the SIE calculated based on the 15% SIC threshold for AMSR-E. We then calculated a time-series of the SIE trends over approximately 45 years using the adjusted SIE data. Therefore, we revealed the dramatic decrease in global sea ice extent since 1978. This technique enables retrieval of more accurate long-term sea ice trends for more than half a century in the future.
Disentangling the Effects of Atmospheric and Soil Dryness on Autumn Phenology across the Northern Hemisphere
Authors: Dong Kangbo , Wang Xiaoyue
Published: September 2024

In recent decades, drought has intensified along with continuous global warming, significantly impacting terrestrial vegetation. High atmospheric water demand, indicated by vapor pressure deficit (VPD), and insufficient soil moisture (SM) are considered the primary factors causing drought stress in vegetation. However, the influences of VPD and SM on the autumn phenology are still unknown. Using satellite observations and meteorological data, we examined the impacts of VPD and SM on the end of the growing season (EOS) across the Northern Hemisphere (>30°N) from 1982 to 2022. We found that VPD and SM were as important as temperature, precipitation, and radiation in controlling the variations in the EOS. Moreover, the EOS was predominantly influenced by VPD or SM in more than one-third (33.8%) of the study area. In particular, a ridge regression analysis indicated that the EOS was more sensitive to VPD than to SM and the other climatic factors, with 25% of the pixels showing the highest sensitivity to VPD. In addition, the effects of VPD and SM on the EOS varied among biome types and climate zones. VPD significantly advanced the EOS in 25.8% of temperate grasslands, while SM had the greatest impact on advancing the EOS in 17.7% of temperate coniferous forests. Additionally, 27.7% of the midlatitude steppe (BSk) exhibited a significant negative correlation between VPD and the EOS, while 19.4% of the marine west coast climate (Cfb) showed a positive correlation between SM and the EOS. We also demonstrated that the correlation between VPD and the EOS was linearly affected by VPD and the leaf area index, while the correlation between SM and the EOS was affected by SM, precipitation, and the leaf area index. Our study highlights the importance of VPD and SM in regulating autumn phenology and enhances our understanding of terrestrial ecosystem responses to climate change.
A Robust Translational Motion Compensation Method for Moving Target ISAR Imaging Based on Phase Difference-Lv’s Distribution and Auto-Cross-Correlation Algorithm
Authors: Liu Can , Luo Yunhua , Yu Zhongjun
Published: September 2024

Translational motion compensation constitutes a pivotal and essential procedure in inverse synthetic aperture radar (ISAR) imaging. Many researchers have previously proposed their methods to address this requirement. However, conventional methods may struggle to produce satisfactory results when dealing with non-stationary moving targets or operating under conditions of low signal-to-noise ratios (SNR). Aiming at this challenge, this article proposes a parametric non-search method that contains two main stages. The radar echoes can be modeled as polynomial phase signals (PPS). In the initial stage, the energy of the received two-dimensional signal is coherently integrated into a peak point by leveraging phase difference (PD) and Lv’s distribution (LVD), from which the high-order polynomial coefficients can be obtained accurately. The estimation of the first-order coefficients is conducted during the second stage. The auto-cross-correlation function for range profiles is introduced to enhance the accuracy and robustness of estimation. Subsequently, a novel mathematical model for velocity estimation is proposed, and its least squares solution is derived. Through this model, a sub-resolution solution can be obtained without requiring interpolation. By employing all the estimated polynomial coefficients, the non-stationary motion of the target can be fully compensated, yielding the acquisition of a finely focused image. Finally, the experimental findings validate the superiority and robustness of the proposed method in comparison to state-of-the-art approaches.
Generic FPGA Pre-Processing Image Library for Industrial Vision Systems
Authors: Ferreira Diogo , Moutinho Filipe , Matos-Carvalho João P. , Guedes Magno , Deusdado Pedro
Published: September 2024

Currently, there is a demand for an increase in the diversity and quality of new products reaching the consumer market. This fact imposes new challenges for different industrial sectors, including processes that integrate machine vision. Hardware acceleration and improvements in processing efficiency are becoming crucial for vision-based algorithms to follow the complexity growth of future industrial systems. This article presents a generic library of pre-processing filters for execution in field-programmable gate arrays (FPGAs) to reduce the overall image processing time in vision systems. An experimental setup based on the Zybo Z7 Pcam 5C Demo project was developed and used to validate the filters described in VHDL (VHSIC hardware description language). Finally, a comparison of the execution times using GPU and CPU platforms was performed as well as an evaluation of the integration of the current work in an industrial application. The results showed a decrease in the pre-processing time from milliseconds to nanoseconds when using FPGAs.
Autonomous Planetary Liquid Sampler (APLS) for In Situ Sample Acquisition and Handling from Liquid Environments
Authors: Nazarious Miracle Israel , Becker Leonie , Zorzano Maria-Paz , Martin-Torres Javier
Published: September 2024

Many natural and artificial liquid environments, such as rivers, oceans, lakes, water storage tanks, aquariums, and urban water distribution systems, are difficult to access. As a result, technology is needed to enable autonomous liquid sampling to monitor water quality and ecosystems. Existing in situ sample acquisition and handling systems for liquid environments are currently limited to a single use and are semi-autonomous, relying on an operator. Liquid sampling systems should be robust and light and withstand long-term operation in remote locations. The system components involved in liquid sampling should be sterilisable to ensure reusability. Here, we introduce a prototype of a liquid sampler that can be used in various liquid environments and may be valuable for the scientific characterisation of different natural, remote, and planetary settings. The Autonomous Planetary Liquid Sampler (APLS) is equipped with pre-programmed, fully autonomous extraction, cleaning, and sterilisation functionalities. It can operate in temperatures between −10 °C and 60 °C and pressure of up to 0.24 MPa (~24 m depth below mean sea level on Earth). As part of the control experiment, we demonstrate its safe and robust autonomous operation in a laboratory environment using a liquid media with Bacillus subtilis. A typical sampling procedure required 28 s to extract 250 mL of liquid, 5 s to fill the MilliQ water, 25 s for circulation within the system for cleaning and disposal, and 200 s to raise the system temperature from ~30 °C ambient laboratory temperature to 150 °C. The temperature is then maintained for another 3.2 h to sterilise the critical parts, allowing a setup reset for a new experiment. In the future, the liquid sampler will be combined with various existing analytical instruments to characterise the liquid solution and enable the autonomous, systematic monitoring of liquid environments on Earth.
Hardware Development and Evaluation of Multihop Cluster-Based Agricultural IoT Based on Bluetooth Low-Energy and LoRa Communication Technologies
Authors: Effah Emmanuel , Ghartey George , Aidoo Joshua Kweku , Thiare Ousmane
Published: September 2024

In this paper, we present the development and evaluation of a contextually relevant, cost-effective, multihop cluster-based agricultural Internet of Things (MCA-IoT) network. This network utilizes commercial off-the-shelf (COTS) Bluetooth Low-Energy (BLE) and LoRa communication technologies, along with the Raspberry Pi 3 Model B+ (RPi 3 B+), to address the challenges of climate change-induced global food insecurity in smart farming applications. Employing the lean engineering design approach, we initially implemented a centralized cluster-based agricultural IoT (CA-IoT) hardware testbed incorporating BLE, RPi 3 B+, STEMMA soil moisture sensors, UM25 m, and LoPy low-power Wi-Fi modules. This system was subsequently adapted and refined to assess the performance of the MCA-IoT network. This study offers a comprehensive reference on the novel, location-independent MCA-IoT technology, including detailed design and deployment insights for the agricultural IoT (Agri-IoT) community. The proposed solution demonstrated favorable performance in indoor and outdoor environments, particularly in water-stressed regions of Northern Ghana. Performance evaluations revealed that the MCA-IoT technology is easy to deploy and manage by users with limited expertise, is location-independent, robust, energy-efficient for battery operation, and scalable in terms of task and size, thereby providing a versatile range of measurements for future applications. Our results further demonstrated that the most effective approach to utilizing existing IoT-based communication technologies within a typical farming context in sub-Saharan Africa is to integrate them.
Player Experience Evaluation in Game-Based Systems for Older Adults
Authors: Salazar-Cardona Johnny Alexander , Ceballos-Cardona Bryjeth , Paderewski-Rodriguez Patricia , Gutiérrez-Vela Francisco , Arango-López Jeferson
Published: September 2024

Significant efforts are currently being made to improve the quality of life of the older adult population. These efforts focus on aspects such as health, social interaction, and mental health. One of the approaches that has shown positive results in several studies is the application of game-based systems. These systems are not only used for entertainment, but also as tools for learning and promoting positive feelings. They are a means to overcome loneliness and isolation, as well as to improve health and provide support in daily life. However, it is important to note that, while these experiences are gradually being introduced to the older adult population, they are often designed with a younger audience in mind who are assumed to be more technologically proficient. This supposition can make older adults initially feel intimidated when interacting with this type of technology, which limits their ability to fully utilize and enjoy these technological solutions. Therefore, the purpose of this article is to apply a game experience and fun evaluation process oriented toward the older adult population based on the playability theory of human–computer interaction in virtual reality game experiences. This is expected to offer highly rewarding and pleasurable experiences, which will improve engagement with the older population and promote active and healthy aging.
Augmented Physics-Based Models for High-Order Markov Filtering
Authors: Tang Shuo , Imbiriba Tales , Duník Jindřich , Straka Ondřej , Closas Pau
Published: September 2024

Hybrid physics-based data-driven models, namely, augmented physics-based models (APBMs), are capable of learning complex state dynamics while maintaining some level of model interpretability that can be controlled through appropriate regularizations of the data-driven component. In this article, we extend the APBM formulation for high-order Markov models, where the state space is further augmented with past states (AG-APBM). Typically, state augmentation is a powerful method for state estimation for a high-order Markov model, but it requires the exact knowledge of the system dynamics. The proposed approach, however, does not require full knowledge of dynamics, especially the Markovity order. To mitigate the extra computational burden of such augmentation we propose an approximated-state APBM (AP-APBM) implementation leveraging summaries from past time steps. We demonstrate the performance of AG- and AP-APBMs in an autoregressive model and a target-tracking scenario based on the trajectory of a controlled aircraft with delay-feedback control. The experiments showed that both proposed strategies outperformed the standard APBM approach in terms of estimation error and that the AP-APBM only degraded slightly when compared to AG-APBM. For example, the autoregressive (AR) model simulation in our settings showed that AG-APBM and AP-APBM reduced the estimate error by 31.1% and 26.7%. The time cost and memory usage were reduced by 37.5% and 20% by AP-APBM compared to AG-APBM.
A Comprehensive Review on the Viscoelastic Parameters Used for Engineering Materials, Including Soft Materials, and the Relationships between Different Damping Parameters
Authors: Koruk Hasan , Rajagopal Srinath
Published: September 2024

Although the physical properties of a structure, such as stiffness, can be determined using some statical tests, the identification of damping parameters requires a dynamic test. In general, both theoretical prediction and experimental identification of damping are quite difficult. There are many different techniques available for damping identification, and each method gives a different damping parameter. The dynamic indentation method, rheometry, atomic force microscopy, and resonant vibration tests are commonly used to identify the damping of materials, including soft materials. While the viscous damping ratio, loss factor, complex modulus, and viscosity are quite common to describe the damping of materials, there are also other parameters, such as the specific damping capacity, loss angle, half-power bandwidth, and logarithmic decrement, to describe the damping of various materials. Often, one of these parameters is measured, and the measured parameter needs to be converted into another damping parameter for comparison purposes. In this review, the theoretical derivations of different parameters for the description and quantification of damping and their relationships are presented. The expressions for both high damping and low damping are included and evaluated. This study is considered as the first comprehensive review article presenting the theoretical derivations of a large number of damping parameters and the relationships among many damping parameters, with a quantitative evaluation of accurate and approximate formulas. This paper could be a primary resource for damping research and teaching.
Statistics of the Sum of Double Random Variables and Their Applications in Performance Analysis and Optimization of Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface-Assisted Non-Orthogonal Multi-Access Systems
Authors: Minh Bui Vu , Tran Phuong T. , Pham Thu-Ha Thi , Le Anh-Tu , Le Si-Phu , Partila Pavol
Published: September 2024

For the future of sixth-generation (6G) wireless communication, simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) technology is emerging as a promising solution to achieve lower power transmission and flawless coverage. To facilitate the performance analysis of RIS-assisted networks, the statistics of the sum of double random variables, i.e., the sum of the products of two random variables of the same distribution type, become vitally necessary. This paper applies the statistics of the sum of double random variables in the performance analysis of an integrated power beacon (PB) energy-harvesting (EH)-based NOMA-assisted STAR-RIS network to improve its outage probability (OP), ergodic rate, and average symbol error rate. Furthermore, the impact of imperfect successive interference cancellation (ipSIC) on system performance is also analyzed. The analysis provides the closed-form expressions of the OP and ergodic rate derived for both imperfect and perfect SIC (pSIC) cases. All analyses are supported by extensive simulation results, which help recommend optimized system parameters, including the time-switching factor, the number of reflecting elements, and the power allocation coefficients, to minimize the OP. Finally, the results demonstrate the superiority of the proposed framework compared to conventional NOMA and OMA systems.
An Adaptive and Automatic Power Supply Distribution System with Active Landmarks for Autonomous Mobile Robots
Authors: Li Zhen , Gao Yuliang , Zhu Miaomiao , Tang Haonan , Zhang Lifeng
Published: September 2024

With the development of automation and intelligent technologies, the demand for autonomous mobile robots in the industry has surged to alleviate labor-intensive tasks and mitigate labor shortages. However, conventional industrial mobile robots’ route-tracking algorithms typically rely on passive markers, leading to issues such as inflexibility in changing routes and high deployment costs. To address these challenges, this study proposes a novel approach utilizing active landmarks—battery-powered luminous landmarks that enable robots to recognize and adapt to flexible navigation requirements. However, the reliance on batteries necessitates frequent recharging, prompting the development of an automatic power supply system. This system integrates omnidirectional contact electrodes on mobile robots, allowing to recharge active landmarks without precise positional alignment. Despite these advancements, challenges such as the large size of electrodes and non-adaptive battery charging across landmarks persist, affecting system efficiency. To mitigate these issues, this research focuses on miniaturizing active landmarks and optimizing power distribution among landmarks. The experimental results of this study demonstrated the effectiveness of our automatic power supply method and the high accuracy of landmark detection. Our power distribution calculation method can adaptively manage energy distribution, improving the system’s persistence by nearly three times. This study aims to enhance the practicality and efficiency of mobile robot remote control systems utilizing active landmarks by simplifying installation processes and extending operational durations with adaptive and automatic power supply distribution.
Location Privacy Protection for the Internet of Things with Edge Computing Based on Clustering K-Anonymity
Authors: Jiang Nanlan , Zhai Yinan , Wang Yujun , Yin Xuesong , Yang Sai , Xu Pingping
Published: September 2024

With the development of the Internet of Things (IoT) and edge computing, more and more devices, such as sensor nodes and intelligent automated guided vehicles (AGVs), can serve as edge devices to provide Location-Based Services (LBS) through the IoT. As the number of applications increases, there is an abundance of sensitive information in the communication process, pushing the focus of privacy protection towards the communication process and edge devices. The challenge lies in the fact that most traditional location privacy protection algorithms are not suited for the IoT with edge computing, as they primarily focus on the security of remote servers. To enhance the capability of location privacy protection, this paper proposes a novel K-anonymity algorithm based on clustering. This novel algorithm incorporates a scheme that flexibly combines real and virtual locations based on the requirements of applications. Simulation results demonstrate that the proposed algorithm significantly improves location privacy protection for the IoT with edge computing. When compared to traditional K-anonymity algorithms, the proposed algorithm further enhances the security of location privacy by expanding the potential region in which the real node may be located, thereby limiting the effectiveness of “narrow-region” attacks.
Characterization of Flow with a V-Shaped NMR Sensor
Authors: Schmid Eric , Pertzel Tim Oliver , Nirschl Hermann , Guthausen Gisela
Published: September 2024

Quality control in a production plant shows its maximum potential in the form of inline measurements. Defects and imperfections can be detected early and directly, and waste and costs can be reduced. Nuclear Magnetic Resonance offers a wide range of applications but requires dedicated adaptation to the respective process and material conditions. A V-shaped low-field NMR sensor was developed for non-invasive inline measurements on anode slurries in a battery production plant. In battery production, inline monitoring of the quality of anode slurries is demanded, offering the possibility of predictive control of the following process steps. Methods of low-field NMR to determine flow properties were adapted to the desired application. Further, magnetic resonance imaging measurements were made to determine the flow properties of model substances and anode slurries, thus providing verification. The sensor measurements show the ability to measure the flow behavior of, amongst other fluids, anode slurries in a form suitable for inline quality control in a battery production plant.
Analysis of Relationship between Microwave Magnetic Properties and Magnetic Structure of Permalloy Films
Authors: Buznikov Nikita A. , Lagarkov Andrey N. , Maklakov Sergey A. , Maklakov Sergey S. , Osipov Alexey V. , Rozanov Konstantin N. , Zezyulina Polina A.
Published: September 2024

Changes in the microwave permeability of permalloy films with an increase in the film thickness are studied. Measurement data on the evolution of microwave permeability with film thickness are analyzed in the framework of a model for the film with a regular stripe domain structure and out-of-plane magnetic anisotropy. A correlation between the microwave magnetic properties and magnetic structure of permalloy films is established. It is demonstrated that the observed decrease in the ferromagnetic resonance frequency and the static permeability with a growth in the film thickness can ascribed to the appearance of perpendicular anisotropy and the formation of a stripe domain structure. The calculated dependences of the ferromagnetic resonance frequency and static permeability on the film thickness are in reasonable agreement with the measurement results. Based on the analysis of these dependences, the domain width in the permalloy films is estimated. It is found that for thick permalloy films, the domain width is of the order of the film thickness. The results obtained may be useful for high-frequency applications of soft magnetic films.
Sensors in Bone: Technologies, Applications, and Future Directions
Authors: Anwar Afreen , Kaur Taruneet , Chaugule Sachin , Yang Yeon-Suk , Mago Aryan , Shim Jae-Hyuck , John Aijaz Ahmad
Published: September 2024

Osteoporosis, a prevalent ailment worldwide, compromises bone strength and resilience, particularly afflicting the elderly population. This condition significantly heightens susceptibility to fractures even from trivial incidents, such as minor falls or impacts. A major challenge in diagnosing osteoporosis is the absence of discernible symptoms, allowing osteoporosis to remain undetected until the occurrence of a fracture event. Early symptom detection and swift diagnosis are critical for preventing severe issues related to bone diseases. Assessing bone turnover markers aids in identifying, diagnosing, and monitoring these conditions, guiding treatment decisions. However, conventional techniques for measuring bone mineral density are costly, time-consuming, and require specialized expertise. The integration of sensor technologies into medical practices has transformed how we monitor, diagnose, and treat various health conditions, including bone health and orthopedics. This review aims to provide a comprehensive overview of the current state of sensor technologies used in bone, covering their integration with bone tissue, various applications, recent advancements, challenges, and future directions.
Fused Audio Instance and Representation for Respiratory Disease Detection
Authors: Truong Tuan , Lenga Matthias , Serrurier Antoine , Mohammadi Sadegh
Published: September 2024

Audio-based classification techniques for body sounds have long been studied to aid in the diagnosis of respiratory diseases. While most research is centered on the use of coughs as the main acoustic biomarker, other body sounds also have the potential to detect respiratory diseases. Recent studies on the coronavirus disease 2019 (COVID-19) have suggested that breath and speech sounds, in addition to cough, correlate with the disease. Our study proposes fused audio instance and representation (FAIR) as a method for respiratory disease detection. FAIR relies on constructing a joint feature vector from various body sounds represented in waveform and spectrogram form. We conduct experiments on the use case of COVID-19 detection by combining waveform and spectrogram representation of body sounds. Our findings show that the use of self-attention to combine extracted features from cough, breath, and speech sounds leads to the best performance with an area under the receiver operating characteristic curve (AUC) score of 0.8658, a sensitivity of 0.8057, and a specificity of 0.7958. Compared to models trained solely on spectrograms or waveforms, the use of both representations results in an improved AUC score, demonstrating that combining spectrogram and waveform representation helps to enrich the extracted features and outperforms the models that use only one representation. While this study focuses on COVID-19, FAIR’s flexibility allows it to combine various multi-modal and multi-instance features in many other diagnostic applications, potentially leading to more accurate diagnoses across a wider range of diseases.
Ultra-Wideband Common-Mode Rejection Structure with Autonomous Phase Balancing for Ultra-High-Speed Digital Transmission
Authors: Min Byung-Cheol , Choi Jeong-Sik , Choi Hyun-Chul , Kim Kang-Wook
Published: September 2024

For ultra-high-speed digital transmission, required by 5G/6G communications, ultra-wideband common-mode rejection (CMR) structures with autonomous phase-balancing capability are proposed. Common-mode noise, caused by phase and amplitude unbalances, is one of the most undesired disturbances affecting modern digital circuits. According to the circuit design guides with a typically used differential line (DL) for high-speed digital transmission, common-mode rejection is achieved using CMR filters, and the unbalanced phase, caused by a length difference between the two signal lines of a DL, is compensated by inserting an additional delay line. However, due to nonlinear phase interactions between the two DLs and unbalanced electromagnetic (EM) interferences, the conventional compensation method is frequency-limited at around 10 GHz. To significantly enhance the common-mode rejection level and extend the phase recovery bandwidth, the proposed CMR structure utilizes a planar balanced line (BL), such as a coplanar stripline (CPS) or a parallel stripline (PSL), along with additional conductor strips arranged laterally near the BL. To demonstrate the performance of the proposed BL-based CMR structures, various types of CMR structures are fabricated, and the measurement results are compared with the 3D EM simulation results. As a result, it is proven that the proposed BL-based CMR structures have the capability to reject the common-mode noise with suppression levels of more than 10 dB and to simultaneously recover the phase balance from near DC to over 40 GHz.
Design, Calibration and Morphological Characterization of a Flexible Sensor with Adjustable Chemical Sensitivity and Possible Applications to Sports Medicine
Authors: Zompanti Alessandro , Basoli Francesco , Saggio Giovanni , Mattioli Francesco , Sabatini Anna , Grasso Simone , Marino Martina , Longo Umile Giuseppe , Trombetta Marcella , Santonico Marco
Published: September 2024

Active life monitoring via chemosensitive sensors could hold promise for enhancing athlete monitoring, training optimization, and performance in athletes. The present work investigates a resistive flex sensor (RFS) in the guise of a chemical sensor. Its carbon ‘texture’ has shown to be sensitive to CO2, O2, and RH changes; moreover, different bending conditions can modulate its sensitivity and selectivity for these gases and vapors. A three-step feasibility study is presented including: design and fabrication of the electronic read-out and control; calibration of the sensors to CO2, O2 and RH; and a morphological study of the material when interacting with the gas and vapor molecules. The 0.1 mm−1 curvature performs best among the tested configurations. It shows a linear response curve for each gas, the ranges of concentrations are adequate, and the sensitivity is good for all gases. The curvature can be modulated during data acquisition to tailor the sensitivity and selectivity for a specific gas. In particular, good results have been obtained with a curvature of 0.1 mm−1. For O2 in the range of 20–70%, the sensor has a sensitivity of 0.7 mV/%. For CO2 in the range of 4–80%, the sensitivity is 3.7 mV/%, and for RH the sensitivity is 33 mV/%. Additionally, a working principle, based on observation via scanning electron microscopy, has been proposed to explain the chemical sensing potential of this sensor. Bending seems to enlarge the cracks present in the RFS coverage; this change accounts for the altered selectivity depending on the sensor’s curvature. Further studies are needed to confirm result’s reliability and the correctness of the interpretation.
Competence in Unsustainability Resolution—A New Paradigm
Authors: Dikou Angela
Published: September 2024

Environmental unsustainability in coupled human–nature systems is accumulating. Yet, there is no accreditation requirement for unsustainability resolution competency in higher education. Thus, a new and complete representation of the pedagogy for unsustainability resolution competence has been induced, using what is already available and working. The nature of unsustainability problems points to collaboration and holism attitudes. Resolution requires social skills, namely participation, perspective taking, and the generation of social capital, and cognitive skills, namely project management, knowledge building, and modeling. Resolution is scaffolded in three successive steps during the collaborative process within a systems approach: (i) collapse complexity; (ii) select a path/trajectory; and (iii) operationalize a plan. The hierarchically cumulative abilities toward unsustainability resolution competence are to source data and information about the coupled human–nature system (SEARCH); simplify the dynamics of the human–nature system (SIMULATE); generate and test alternative paths and end points for the coupled human–nature system (STRATEGIZE); chose a favorable path among the available alternatives (SELECT); operationalize the favorable path into a plan (strategy–program–project) with measurable management and policy objectives (IMPLEMENT); and develop criteria/indicators to monitor and adjust when necessary the implementation of the plan toward system goals (STEER). For each one of these learning objectives, the Bloom’s taxonomy and a progression from behaviorist through cognitivist to constructivist tools apply. The development of mastery requires the comparison and contrast of many similar cases with the same unsustainability problem and project-based learning with specific cases for deep learning. In this way, it is the resolutions of unsustainability in human–nature systems that will be accumulating.