bluuebunny/crossref_metadata_2025 huggingface dataset:
The Relationship between Lifestyle Behaviors and Mental Illness in Women in College
Authors: Armstrong Noelle , Fu Ziyang , Woolf Kathleen
Published: July 2024

Women, particularly those in college, have the highest prevalence of any mental illness (MI), which negatively impacts social connection, academic performance, and health. Research into alternative treatment methods suggests that lifestyle behaviors are safer and more effective than medication at reducing MI symptoms. This study explores the relationship between lifestyle behaviors and MI in college women through an online survey. The survey included a food frequency questionnaire (Diet History Questionnaire II) and questions about lifestyle behaviors, symptoms of MI, and sociodemographic information. Diet quality was calculated using the Healthy Eating Index (HEI), and MI was assessed using the Depression, Anxiety, and Stress Scale-21. Independent sample t-tests, ANOVA, and chi-square analyses were conducted. A total of 222 women completed the survey. Overall, diet quality was poor, with a mean HEI of 62.6 ± 10.4. No significant differences or associations were found between MI groups for total HEI score, sleep, or tobacco use. However, alcohol use was significantly associated with MI (p = 0.049). Individuals with fewer concurrent unhealthy lifestyle behaviors had less severe symptoms of depression (p = 0.009) and anxiety (p < 0.001) compared to those with more unhealthy lifestyle behaviors. In this study, alcohol use was the only independent lifestyle behavior associated with symptoms of MI. We also found an association between the number of concurrent unhealthy lifestyle behaviors and depression and anxiety symptoms. Future research should explore the benefits of a healthy lifestyle on MI in a more diverse sample of women.
Effect of Subsoiling on the Nutritional Quality of Grains of Maize Hybrids of Different Eras
Authors: Wang Liqing , Yu Xiaofang , Gao Julin , Ma Daling , He Tong , Hu Shuping
Published: July 2024

To achieve high maize (Zea mays L.) yields and quality grain, it is necessary to develop stress-resistant cultivars and related cultivation practices, aiming to maximize efficiency. Thus, our objectives were (i) to investigate the impact of tillage practices and maize hybrids (which have improved over time) on yield and its components, and (ii) to characterize the response pattern of maize hybrid grain nutrient quality components to subsoiling. To achieve this, we conducted field trials with five maize hybrids from different eras under two tillage practices: rotary tillage and subsoiling. We compared grain yield, nutritional quality, and other indicators across different tillage conditions from the 1970s to the 2010s. The main results of this study are as follows: under rotary tillage conditions, the 2010s hybrid (DH618) significantly increased yields (9.37–55.89%) compared to hybrids from the 1970s–2000s. After subsoiling, the physiologically mature grains of all hybrids exhibited minimal changes in crude protein and fat content, while there was a significant reduction in the total soluble sugar content of the grains. After subsoiling, there was a substantial 8.14 to 12.79 percent increase in total starch accumulation in the grain for all hybrids during the period of 47–75 days post-anthesis. Furthermore, during the period of 47–75 days after anthesis, the consumption of grain crude protein significantly contributed to the accumulation of total starch in the grains. Ultimately, subsoiling significantly increased the yield of each hybrid and enhanced the total grain starch content at physiological maturity of all hybrids, with the 2010s hybrid (DH618) performing exceptionally well.
Transitioning to Microplastic-Free Seed Coatings: Challenges and Solutions
Authors: Langlet Rozenn , Valentin Romain , Morard Marie , Raynaud Christine Delgado
Published: July 2024

This review addresses the issue of replacing manufactured microplastics in seed coatings used in agriculture. Firstly, it focuses on the policy and regulatory actions taken on microplastics at a global level. There is no consensus within the scientific community on the definition of a microplastic and, more generally, on the classification of plastic debris. Nevertheless, several decision schemes have been proposed in an attempt to define the notion of microplastics. The different criteria relevant to this definition, such as the size, physical state, chemical structure, origin, and persistence of microplastics, are discussed, with a comparison being made between the REACH regulation and the scientific literature. Seed production and processing are also discussed, with the functions of seed coatings being explained in order to gain a better understanding of the properties to be considered in a substitution strategy for currently used microplastics. The main challenges are multiple; substitutes must provide the same performance as microplastics: (i) improving the adherence of the treatment to the seed, (ii) distributing the treatment more evenly over the seed, (iii) reducing the amount of dust-off when handling treated seed, and (iv) improving the seed flowability, which is particularly important during the sowing stage, all while preserving the physiological properties of the seed. Substitute polymers are proposed according to the desired performance and functional properties: two main chemical families of biopolymers were identified in the literature: polysaccharides and proteins. Among them, 13 and 6 polymers, respectively, complied with REACH regulation, demonstrating adhesion, dust reduction performances, and preservation of seed physiological quality in particular. This work aims to guide future studies on microplastic substitution in seed coatings, and to highlight research needs in this area. It is based on an analysis and discussion of the literature, identifying and listing potential substitutes.
Aramid Honeycomb Cores under Constant Pressure: Unveiling the Out-of-Plane Compression Deformation
Authors: Huang Xinzheng , Hu Xin , Guo Jinzhan , Zhang Dechao , Yao Shunming , Zhan Lihua , Ma Bolin , Huang Minghui , Zhang Lihua
Published: July 2024

The primary challenge during the secondary bonding process of full-height honeycomb sandwich structures is the aramid honeycomb core’s height shrinkage. This paper systematically investigated the height evolution behavior of the honeycomb core by using a creep testing machine. The results showed that the out-of-plane compression deformation curve of aramid honeycomb cores is mainly divided into three stages: the dehumidification stage, the pressurization stage and the creep stage. Under conditions of high temperature and pressure, height shrinkage was attributed to the dehydration caused by moisture infiltration, and the compression creep resulted from the slippage of polymer molecular chains. Dehydration shrinkage is stable, whereas compression creep reflects typical viscoelastic polymer characteristics. By employing the viscoelastic Burgers mechanical model and applying the nonlinear surface fitting method, the total height shrinkage deformation behavior of the aramid honeycomb core during the curing process can be accurately predicted by summing the above three stages. This research contributes valuable insights for the manufacturing process of honeycomb sandwich structures.
Crystallization of Poly(ethylene terephthalate): A Review
Authors: Di Lorenzo Maria Laura
Published: July 2024

Poly(ethylene terephthalate) (PET) is a thermoplastic polyester with excellent thermal and mechanical properties, widely used in a variety of industrial fields. It is a semicrystalline polymer, and most of the industrial success of PET derives from its easily tunable crystallization kinetics, which allow users to produce the polymer with a high crystal fraction for applications that demand high thermomechanical resistance and barrier properties, or a fully amorphous polymer when high transparency of the product is needed. The main properties of the polymer are presented and discussed in this contribution, together with the literature data on the crystal structure and morphology of PET. This is followed by an in-depth analysis of its crystallization kinetics, including both primary crystal nucleation and crystal growth, as well as secondary crystallization. The effect of molar mass, catalyst residues, chain composition, and thermo-mechanical treatments on the crystallization kinetics, structure, and morphology of PET are also reviewed in this contribution.
Towards Enlightenment: Taixu’s Interpretation of Buddhist Psychology
Authors: Fan Wenli
Published: July 2024

Chinese intellectuals started to engage in Buddhist psychology in the early 20th century, a time when Western culture was greatly influencing the country. Taixu criticized Western psychology and proposed his Buddhist psychology. He proposed a tripartite psychology based on Buddhist doctrine: psychology on affection (qing 情); psychology on reflection (xiang 想); and psychology on wisdom (zhi 智). Perceiving Western psychology as lacking in both theoretical depth and breadth, he specifically criticized behaviorism. He integrated the interpretation of “sense faculties” (indriya) from the Śūraṅgama Sūtra, thereby reconstructing an Ideal Behavioral Science, a philosophical system that centers on behavior and encompasses all aspects of life. This paper argues that Taixu’s critique of Western psychology and his construction of Buddhist psychology responded to the ideological trends of his era. In Taixu’s conceptual system, Buddhist psychology was part of his theory on “Buddhism for human life” (rensheng fojiao 人生佛教), serving not only to explain the psychological state of human but also to guide cultivation and lead people to enlightenment, bearing practical significance. Taixu’s study of worldly knowledge, including psychology, attempts to comprehensively construct a modern Buddhist system that integrates Buddhist Dharma and secular learning.
Analysis of Attack Intensity on Autonomous Mobile Robots
Authors: Basan Elena , Basan Alexander , Mushenko Alexey , Nekrasov Alexey , Fidge Colin , Lesnikov Alexander
Published: July 2024

Autonomous mobile robots (AMRs) combine a remarkable combination of mobility, adaptability, and an innate capacity for obstacle avoidance. They are exceptionally well-suited for a wide range of applications but usually operate in uncontrolled, non-deterministic environments, so the analysis and classification of security events are very important for their safe operation. In this regard, we considered the influence of different types of attacks on AMR navigation systems to subdivide them into classes and unified the effect of attacks on the system through their level of consequences and impact. Then, we built a model of an attack on a system, taking into account five methods of attack implementation and identified the unified response thresholds valid for any type of parameter, which allows for creating universal correlation rules and simplifies this process, as the trigger threshold is related to the degree of impact that the attack has on the finite subsystem. Also, we developed a methodology for classifying incidents and identifying key components of the system based on ontological models, which makes it possible to predict risks and select the optimal system configuration. The obtained results are important in the context of separating different types of destructive effects based on attack classes. Our study showed that it is sometimes difficult to divide spoofing attacks into classes by assessing only one parameter since the attacker can use a complex attack scenario, mixing the stages of the scenarios. We then showed how adding an attack intensity factor can make classification more flexible. The connections between subsystems and parameters, as well as the attack impact patterns, were determined. Finally, a set of unique rules was developed to classify destructive effects with uniform response thresholds for each parameter. In this case, we can increase the number of parameters as well as the type of parameter value.
Validation and Application of Satellite-Derived Sea Surface Temperature Gradients in the Bering Strait and Bering Sea
Authors: Vazquez-Cuervo Jorge , Steele Michael , Wethey David S. , Gómez-Valdés José , García-Reyes Marisol , Spratt Rachel , Wang Yang
Published: July 2024

The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.
Research on a Matching Method for Vehicle-Borne Laser Point Cloud and Panoramic Images Based on Occlusion Removal
Authors: Ji Jiashu , Wang Weiwei , Ning Yipeng , Bo Hanwen , Ren Yufei
Published: July 2024

Vehicle-borne mobile mapping systems (MMSs) have been proven as an efficient means of photogrammetry and remote sensing, as they simultaneously acquire panoramic images, point clouds, and positional information along the collection route from a ground-based perspective. Obtaining accurate matching results between point clouds and images is a key issue in data application from vehicle-borne MMSs. Traditional matching methods, such as point cloud projection, depth map generation, and point cloud coloring, are significantly affected by the processing methods of point clouds and matching logic. In this study, we propose a method for generating matching relationships based on panoramic images, utilizing the raw point cloud map, a series of trajectory points, and the corresponding panoramic images acquired using a vehicle-borne MMS as input data. Through a point-cloud-processing workflow, irrelevant points in the point cloud map are removed, and the point cloud scenes corresponding to the trajectory points are extracted. A collinear model based on spherical projection is employed during the matching process to project the point cloud scenes to the panoramic images. An algorithm for vectorial angle selection is also designed to address filtering out the occluded point cloud projections during the matching process, generating a series of matching results between point clouds and panoramic images corresponding to the trajectory points. Experimental verification indicates that the method generates matching results with an average pixel error of approximately 2.82 pixels, and an average positional error of approximately 4 cm, thus demonstrating efficient processing. This method is suitable for the data fusion of panoramic images and point clouds acquired using vehicle-borne MMSs in road scenes, provides support for various algorithms based on visual features, and has promising applications in fields such as navigation, positioning, surveying, and mapping.
Characterisation of Two Vineyards in Mexico Based on Sentinel-2 and Meteorological Data
Authors: del Rio Maria S. , Cicuéndez Victor , Yagüe Carlos
Published: July 2024

In Mexico, viticulture represents the second source of employment in the agricultural area after the fruit and vegetable sector. In developed countries, remote sensing is widely used for vineyard monitoring; however, this tool is barely used in the developing countries of Iberoamerica. In this research, our overall objective is to characterise two vineyards in the state of Queretaro (Mexico) using Sentinel-2 and meteorological data, specifically spectral and thermal indices. Results show that spectral indices obtained from Sentinel-2 bands have adequately characterised the phenological dynamics of the different varieties of the vineyards. The Modified Soil-Adjusted Vegetation Index (MSAVI) was adequately used to discriminate between the first stages of vineyards, while the Normalized Difference Vegetation Index (NDVI) was useful for monitoring vineyards during the rest stages of vineyards. Thermal indices have shown that the best grape varieties are those that can adapt to both cooler and warmer temperatures, have a reasonable ripening period, and can produce wines with balanced acidity and flavours. In conclusion, the combination of meteorological (including thermal indices) and remote sensing data (NDVI and MSAVI) provide information for choosing a suitable grape variety for this region.
Weakly Supervised Transformer for Radar Jamming Recognition
Authors: Zhang Menglu , Chen Yushi , Zhang Ye
Published: July 2024

Radar jamming recognition is a key step in electronic countermeasures, and accurate and sufficient labeled samples are essential for supervised learning-based recognition methods. However, in real practice, collected radar jamming samples often have weak labels (i.e., noisy-labeled or unlabeled ones), which degrade recognition performance. Additionally, recognition performance is hindered by limitations in capturing the global features of radar jamming. The Transformer (TR) has advantages in modeling long-range relationships. Therefore, a weakly supervised Transformer is proposed to address the issues of performance degradation under weak supervision. Specifically, complementary label (CL) TR, called RadarCL-TR, is proposed to improve radar jamming recognition accuracy with noisy samples. CL learning and a cleansing module are successively utilized to detect and remove potentially noisy samples. Thus, the adverse influence of noisy samples is mitigated. Additionally, semi-supervised learning (SSL) TR, called RadarSSL-PL-TR, is proposed to boost recognition performance under unlabeled samples via pseudo labels (PLs). Network generalization is improved by training with pseudo-labeling unlabeled samples. Moreover, the RadarSSL-PL-S-TR is proposed to further promote recognition performance, where a selection module identifies reliable pseudo-labeling samples. The experimental results show that the proposed RadarCL-TR and RadarSSL-PL-S-TR outperform comparison methods in recognition accuracy by at least 7.07% and 6.17% with noisy and unlabeled samples, respectively.
Genetic Algorithm-Based Cooperative Coding and Caching Data Dissemination Scheme in Multi-UAV-Enabled Internet of Vehicles
Authors: Xiao Ke , Hu Jie , Li Chunlin , Ji Wenjie , Xu Jinkun , Du Huang
Published: July 2024

Unmanned Aerial Vehicles (UAVs) have emerged as efficient tools in disaster-stricken areas, facilitating efficient data dissemination for post-disaster rescue operations. However, the limited onboard energy of UAVs imposes significant constraints on their operational lifespan, thereby presenting substantial challenges for efficient data dissemination. Therefore, this work investigates a data dissemination scheme to enhance the UAVs’ bandwidth efficiency in multi-UAV-enabled Internet of Vehicles, thereby reducing UAVs’ energy consumption and improving overall system performance when UAVs hover along designated flight trajectories for data dissemination. Specifically, first, we present a software-defined network-based framework for data dissemination in multi-UAV-enabled IoV. According to this framework, we formulate a problem called C2BS (Coding-based Cooperative Broadcast Scheduling) that focuses on optimizing the UAVs’ bandwidth efficiency by leveraging the combined benefits of coding and caching. Furthermore, we demonstrate the NP-hardness of the C2BS problem by employing a polynomial time reduction technique on the simultaneous matrix completion problem. Then, inspired by the benefits offered by genetic algorithms, we propose a novel approach called the Genetic algorithm-based Cooperative Scheduling (GCS) algorithm to address the C2BS problem. This approach encompasses a coding scheme for representing individuals, a fitness function for assessing individuals, operators (i.e., crossover and mutation) for generating offspring, a local search technique to enhance search performance, and a repair operator employed to rectify infeasible solutions. Additionally, we present an analysis of the time complexity for the GCS algorithm. Finally, we present a simulation model to evaluate the performance. Experimental findings provide evidence of the excellence of the proposed scheme.
Robust BEV 3D Object Detection for Vehicles with Tire Blow-Out
Authors: Yang Dongsheng , Fan Xiaojie , Dong Wei , Huang Chaosheng , Li Jun
Published: July 2024

The bird’s-eye view (BEV) method, which is a vision-centric representation-based perception task, is essential and promising for future Autonomous Vehicle perception. It has advantages of fusion-friendly, intuitive, end-to-end optimization and is cheaper than LiDAR. The performance of existing BEV methods, however, would be deteriorated under the situation of a tire blow-out. This is because they quite rely on accurate camera calibration which may be disabled by noisy camera parameters during blow-out. Therefore, it is extremely unsafe to use existing BEV methods in the tire blow-out situation. In this paper, we propose a geometry-guided auto-resizable kernel transformer (GARKT) method, which is designed especially for vehicles with tire blow-out. Specifically, we establish a camera deviation model for vehicles with tire blow-out. Then we use the geometric priors to attain the prior position in perspective view with auto-resizable kernels. The resizable perception areas are encoded and flattened to generate BEV representation. GARKT predicts the nuScenes detection score (NDS) with a value of 0.439 on a newly created blow-out dataset based on nuScenes. NDS can still obtain 0.431 when the tire is completely flat, which is much more robust compared to other transformer-based BEV methods. Moreover, the GARKT method has almost real-time computing speed, with about 20.5 fps on one GPU.
Band-Stop Frequency-Selective Surface (FSS) with Elliptic Response Designed by the Extracted Pole Technique
Authors: Montejo-Garai José R. , Page Juan E. , Perez-Palomino Gerardo , Guirado Robert
Published: July 2024

This paper describes and validates an advanced synthesis design process of Frequency-Selective Surfaces (FSSs) with elliptic band-stop responses. A systematic procedure based on the Generalized Chebyshev Function and the extracted pole technique enables control of the position of the transmission zeros and the attenuation level to obtain an equiripple rejection response. A systematic process is followed to obtain the lumped LC values of the resonator circuits extracted as poles and the impedance inverters. Then, equivalent dipoles and transmission lines are obtained to carry out the electromagnetic design at normal incidence for a linearly polarized field. The impact of the higher-order modes of the periodic structure on the electrical response of the FSS, which can be relevant due to the stringent selected specifications, has been also analyzed. A fourth-order band-stop filter with a 3 GHz bandwidth centered at 30 GHz and its attenuation at 50 dB has been designed considering three different implementations: two filters using a vacuum as a transmission line with different connection lengths and a third one using a dielectric substrate to enable its manufacturing. In order to verify the design procedure using experimental results, the third filter with printed dipoles in the dielectric substrate has been manufactured and measured, thus validating the developed process.
A Technology Aid to Help People with Blindness and Moderate Intellectual Disability Retrieve Common Objects from Storage Units: A Proof-of-Concept Study
Authors: Filippini Chiara , Lancioni Giulio E. , Alberti Gloria , Pezzuoli Francesco , Ceccarani Patrizia
Published: July 2024

Background: People with blindness and intellectual disability can have problems locating, identifying, and retrieving objects needed for daily activities (e.g., clothes and food items) from familiar storage contexts, such as cupboards and cabinets. Objective: This preliminary study assessed a technological system designed to help three people with those problems improve their performance. Methods: The technological system, which involved the use of tags with radio frequency identification codes, a smartphone, and a tag reader, aimed to guide the participants in searching and retrieving objects from three different storage units. In practice, the system provided different feedbacks depending on whether the participants were searching (a) in a wrong storage unit, (b) in a wrong shelf/drawer of the right storage unit, or (c) in the right shelf/drawer of the right storage unit. Results: All participants were successful in retrieving objects correctly with the technological system. The results also showed that (a) the participants preferred using the system over a control strategy, (b) were able to switch on and off the system independently, and (b) staff rated the system positively. Conclusions: These preliminary findings suggest that the system might be a useful support tool for people with blindness and intellectual disability.
Microscale Lateral Perovskite Light Emitting Diode Realized by Self-Doping Phenomenon
Authors: Gao Wenzhe , Huang He , Wang Chenming , Zhang Yongzhe , Zheng Zilong , Li Jinpeng , Chen Xiaoqing
Published: July 2024

High-definition near-eye display technology has extremely close sight distance, placing a higher demand on the size, performance, and array of light-emitting pixel devices. Based on the excellent photoelectric performance of metal halide perovskite materials, perovskite light-emitting diodes (PeLEDs) have high photoelectric conversion efficiency, adjustable emission spectra, and excellent charge transfer characteristics, demonstrating great prospects as next-generation light sources. Despite their potential, the solubility of perovskite in photoresist presents a hurdle for conventional micro/nano processing techniques, resulting in device sizes typically exceeding 50 μm. This limitation impedes the further downsizing of perovskite-based components. Herein, we propose a plane-structured PeLED device that can achieve microscale light-emitting diodes with a single pixel device size < 2 μm and a luminescence lifetime of approximately 3 s. This is accomplished by fabricating a patterned substrate and regulating ion distribution in the perovskite through self-doping effects to form a PN junction. This breakthrough overcomes the technical challenge of perovskite–photoresist incompatibility, which has hindered the development of perovskite materials in micro/nano optoelectronic devices. The strides made in this study open up promising avenues for the advancement of PeLEDs within the realm of micro/nano optoelectronic devices.
Natural Frequency Transmissibility for Detection of Cracks in Horizontal Axis Wind Turbine Blades
Authors: Henderson Rachel , Azhari Fae , Sinclair Anthony
Published: July 2024

Defects on horizontal axis wind turbine blades are difficult to identify and monitor with conventional forms of non-destructive examination due to the blade’s large size and limited accessibility during continuous operation. This article examines both strain and acceleration transmissibility as methods of continuous damage detection on wind turbine blades. A scaled 117 cm offshore wind turbine blade was first designed, 3D printed, and modelled numerically in ANSYS. Transverse cracks were deliberately introduced to the blade at 10 cm intervals along its leading edge. Subsequent changes in the transmissibility, relative to an undamaged baseline model, were measured using different variable combinations at the blade’s first three natural frequencies. Experimental results indicated that strain transmissibility was able to locate a 1.0 cm defect at a range of 70–110 cm from the blade hub using the amplitudes of the first natural frequency of vibration. The numerical model was able to simulate the strain experimental results and was determined to be valid for future defect characterization. Acceleration transmissibility was unable to experimentally identify defects sized at 1.0 cm and below but was able to identify 1.0 cm sized defects numerically. It was concluded that transmissibility is viable for continuous damage detection on blades but that further research into other defect types and locations is required prior to conducting full-scale testing.
Two-Field Excitation for Contactless Inductive Flow Tomography
Authors: Sieger Max , Gudat Katharina , Mitra Rahul , Sonntag Stefanie , Stefani Frank , Eckert Sven , Wondrak Thomas
Published: July 2024

Contactless inductive flow tomography (CIFT) is a flow measurement technique allowing for visualization of the global flow in electrically conducting fluids. The method is based on the principle of induction by motion: very weak induced magnetic fields arise from the fluid motion under the influence of a primary excitation magnetic field and can be measured precisely outside of the fluid volume. The structure of the causative flow field can be reconstructed from the induced magnetic field values by solving the according linear inverse problem using appropriate regularization methods. The concurrent use of more than one excitation magnetic field is necessary to fully reconstruct three-dimensional liquid metal flows. In our laboratory demonstrator experiment, we impose two excitation magnetic fields perpendicular to each other to a mechanically driven flow of the liquid metal alloy GaInSn. In the first approach, the excitation fields are multiplexed. Here, the temporal resolution of the measurement needs to be kept as high as possible. Consecutive application by multiplexing enables determining the flow structure in the liquid with a temporal resolution down to 3 s with the existing equipment. In another approach, we concurrently apply two sinusoidal excitation fields with different frequencies. The signals are disentangled on the basis of the lock-in principle, enabling a successful reconstruction of the liquid metal flow.
Performance-Degradation Analysis of the Planetary Roller Screw Mechanism under Multi-Factor Coupling Effects
Authors: Chen Kui , Zhao Yongsheng , Zheng Jigui , Shi Wei , Zhang Zhaojing
Published: July 2024

The performance-degradation pattern of the planetary roller screw mechanism (PRSM) is difficult to predict and evaluate due to a variety of factors. Load-carrying capacity, transmission accuracy, and efficiency are the main indicators for evaluating the performance of the PRSM. In this paper, a testing device for the comprehensive performance of the PRSM is designed by taking into account the coupling relationships among temperature rise, vibration, speed, and load. First, the functional design and error calibration of the testing device were conducted. Secondly, the PRSM designed in the supported project was taken as the research object to conduct degradation tests on its load-bearing capacity and transmission accuracy and analyze the changes in transmission efficiency. Third, the thread profile and wear condition were scanned and inspected using a universal tool microscope and an optical microscope. Finally, based on the monitoring module of the testing device, the vibration status during the PRSM testing process was collected in real time, laying a foundation for the subsequent assessment of the changes in the performance state of the PRSM. The test results reveal the law of performance degradation of the PRSM under the coupled effects of temperature, vibration, speed, and load.
A New Method for Detecting Dehydration of the Human Body Using Non-Contact Millimeter Wave Radiometry
Authors: Owda Amani Yousef
Published: July 2024

Dehydration is a common problem in the aging population. Medical professionals can detect dehydration using either blood or urine tests. This requires experimental tests in the lab as well as urine and blood samples to be obtained from the patients. This paper proposed 100 GHz millimeter wave radiometry for early detection of dehydration. Reflectance measurements were performed on healthy and dehydrated patients of both genders (120 males and 80 females) in the aging population. Based on the cause of dehydration, the patient groups were divided into three categories: (1) patients dehydrated due to less thirst sensation, (2) patients dehydrated due to illnesses (vomiting and diarrhea), and (3) patients dehydrated due to diabetes. Reflectance measurements were performed on eight locations: (1) the palm, (2) the back of the hand, (3) the fingers, (4) the inner wrist, (5) the outer wrist, (6) the volar side of the arm, (7) the dorsal surface of the arm, and (8) the elbow. Skin dehydrated due to vomiting and diarrhea was found to have lower reflectance at all the measurement locations compared with healthy and other types of dehydrated skin. The elbow region showed the highest difference in reflectance between healthy and dehydrated skin. This indicates that radiometric sensitivity is sufficient to detect dehydration in a few seconds. This will reduce the patient’s waiting time and the healthcare professional’s intervention time as well as allow early treatment of dehydration, thus avoiding admission to hospitals.
Evaluation of the Diagnostic Sensitivity of Digital Vibration Sensors Based on Capacitive MEMS Accelerometers
Authors: Fidali Marek , Augustyn Damian , Ochmann Jakub , Uchman Wojciech
Published: July 2024

In recent years, there has been an increasing use of digital vibration sensors that are based on capacitive MEMS accelerometers for machine vibration monitoring and diagnostics. These sensors simplify the design of monitoring and diagnostic systems, thus reducing implementation costs. However, it is important to understand how effective these digital sensors are in detecting rolling bearing faults. This article describes a method for determining the diagnostic sensitivity of diagnostic parameters provided by commercially available vibration sensors based on MEMS accelerometers. Experimental tests were conducted in laboratory conditions, during which vibrations from 11 healthy and faulty rolling bearings were measured using two commercial vibration sensors based on MEMS accelerometers and a piezoelectric accelerometer as a reference sensor. The results showed that the diagnostic sensitivity of the parameters depends on the upper-frequency band limit of the sensors, and the parameters most sensitive to the typical fatigue faults of rolling bearings are the peak and peak-to-peak amplitudes of vibration acceleration. Despite having a lower upper-frequency range compared to the piezoelectric accelerometer, the commercial vibration sensors were found to be sensitive to rolling bearing faults and can be successfully used in continuous monitoring and diagnostics systems for machines.
Combining Laser-Induced Breakdown Spectroscopy and Visible Near-Infrared Spectroscopy for Predicting Soil Organic Carbon and Texture: A Danish National-Scale Study
Authors: Wangeci Alex , Adén Daniel , Nikolajsen Thomas , Greve Mogens H. , Knadel Maria
Published: July 2024

Laser-induced breakdown spectroscopy (LIBS) and visible near-infrared spectroscopy (vis-NIRS) are spectroscopic techniques that offer promising alternatives to traditional laboratory methods for the rapid and cost-effective determination of soil properties on a large scale. Despite their individual limitations, combining LIBS and vis-NIRS has been shown to enhance the prediction accuracy for the determination of soil properties compared to single-sensor approaches. In this study, we used a comprehensive Danish national-scale soil dataset encompassing mostly sandy soils collected from various land uses and soil depths to evaluate the performance of LIBS and vis-NIRS, as well as their combined spectra, in predicting soil organic carbon (SOC) and texture. Firstly, partial least squares regression (PLSR) models were developed to correlate both LIBS and vis-NIRS spectra with the reference data. Subsequently, we merged LIBS and vis-NIRS data and developed PLSR models for the combined spectra. Finally, interval partial least squares regression (iPLSR) models were applied to assess the impact of variable selection on prediction accuracy for both LIBS and vis-NIRS. Despite being fundamentally different techniques, LIBS and vis-NIRS displayed comparable prediction performance for the investigated soil properties. LIBS achieved a root mean square error of prediction (RMSEP) of <7% for texture and 0.5% for SOC, while vis-NIRS achieved an RMSEP of <8% for texture and 0.5% for SOC. Combining LIBS and vis-NIRS spectra improved the prediction accuracy by 16% for clay, 6% for silt and sand, and 2% for SOC compared to single-sensor LIBS predictions. On the other hand, vis-NIRS single-sensor predictions were improved by 10% for clay, 17% for silt, 16% for sand, and 4% for SOC. Furthermore, applying iPLSR for variable selection improved prediction accuracy for both LIBS and vis-NIRS. Compared to LIBS PLSR predictions, iPLSR achieved reductions of 27% and 17% in RMSEP for clay and sand prediction, respectively, and an 8% reduction for silt and SOC prediction. Similarly, vis-NIRS iPLSR models demonstrated reductions of 6% and 4% in RMSEP for clay and SOC, respectively, and a 3% reduction for silt and sand. Interestingly, LIBS iPLSR models outperformed combined LIBS-vis-NIRS models in terms of prediction accuracy. Although combining LIBS and vis-NIRS improved the prediction accuracy of texture and SOC, LIBS coupled with variable selection had a greater benefit in terms of prediction accuracy. Future studies should investigate the influence of reference method uncertainty on prediction accuracy.
Efficient Integration of Ultra-low Power Techniques and Energy Harvesting in Self-Sufficient Devices: A Comprehensive Overview of Current Progress and Future Directions
Authors: Citroni Rocco , Mangini Fabio , Frezza Fabrizio
Published: July 2024

Compact, energy-efficient, and autonomous wireless sensor nodes offer incredible versatility for various applications across different environments. Although these devices transmit and receive real-time data, efficient energy storage (ES) is crucial for their operation, especially in remote or hard-to-reach locations. Rechargeable batteries are commonly used, although they often have limited storage capacity. To address this, ultra-low-power design techniques (ULPDT) can be implemented to reduce energy consumption and prolong battery life. The Energy Harvesting Technique (EHT) enables perpetual operation in an eco-friendly manner, but may not fully replace batteries due to its intermittent nature and limited power generation. To ensure uninterrupted power supply, devices such as ES and power management unit (PMU) are needed. This review focuses on the importance of minimizing power consumption and maximizing energy efficiency to improve the autonomy and longevity of these sensor nodes. It examines current advancements, challenges, and future direction in ULPDT, ES, PMU, wireless communication protocols, and EHT to develop and implement robust and eco-friendly technology solutions for practical and long-lasting use in real-world scenarios.
Estimating the Workability of Concrete with a Stereovision Camera during Mixing
Authors: Ojala Teemu , Punkki Jouni
Published: July 2024

The correct workability of concrete is an essential parameter for its placement and compaction. However, an absence of automatic and transparent measurement methods to estimate the workability of concrete hinders the adaptation from laborious traditional methods such as the slump test. In this paper, we developed a machine-learning framework for estimating the slump class of concrete in the mixer using a stereovision camera. Depth data from five different slump classes was transformed into Haralick texture features to train several machine-learning classifiers. The best-performing classifier achieved a multiclass classification accuracy of 0.8179 with the XGBoost algorithm. Furthermore, we found through statistical analysis that while the denoising of depth data has little effect on the accuracy, the feature extraction of mixer blades and the choice of region of interest significantly increase the accuracy and the efficiency of the classifiers. The proposed framework shows robust results, indicating that stereovision is a competitive solution to estimate the workability of concrete during concrete production.
Impact of China’s Digital Economy on Integrated Urban–Rural Development
Authors: Huo Zhaoxin , Liu Huifang
Published: July 2024

This paper measures the comprehensive level of the digital economy and integrated urban–rural development across Chinese provinces from 2013 to 2022. Using a two-way fixed effects model, it explores the nonlinear relationship, regional heterogeneity, and underlying causes of how the digital economy empowers integrated urban–rural development. The study finds that: (1) The digital economy promotes integrated urban–rural development, with a quadratic polynomial regression model and threshold regressive model revealing an inverted U-shaped relationship. The turning point has not yet been reached, and the promoting relationship shows a diminishing marginal trend. (2) In terms of sub-dimensions, the strengths of the promoting effect are ranked as follows: digital infrastructure construction, industrial digitization, and digital industrialization. (3) Regionally, the digital economy’s promoting effect on integrated urban–rural development is strongest in Central China, followed by Eastern China, and weakest in Western China. The innovation and contribution of this paper lie in discovering the nonlinear impact of the digital economy on China’s integrated urban–rural development, analyzing its intrinsic driving forces and regional differences, and providing valuable references for implementing regionally differentiated development policies for the digital economy and integrated urban–rural development in various regions of China.
The Evolution of Forest Landscape Connectivity and Ecological Network Construction: A Case Study of Zhejiang’s Ecological Corridors
Authors: Bai Yuhan , Zhao Jiajia , Shen Hangrui , Li Xinyao , Wen Bo
Published: July 2024

As main components of terrestrial ecosystems, forests play irreplaceable roles in maintaining ecological balance and protecting the basic environment for human survival and development. In this study, the dynamic changes in the forest landscape connectivity in Zhejiang province in 2000, 2010, and 2020 were detected by identifying ecological sources and evaluating connectivity indexes based on morphological spatial analysis (MSPA) and a minimum cumulative resistance (MCR) model. The results are as follows: (1) The forest area of Zhejiang increased by 64.88% from 2000 to 2020, indicating that the overall habitat quality has improved and that ecological risks have decreased, which are attributed to Zhejiang’s adherence to comprehensive environmental management. (2) Regions with low connectivity are distributed mainly in the north, where human activities are intensive. The overall pattern of high connectivity in the middle of the region and low connectivity elsewhere demonstrates the uneven distribution of forest landscape connectivity across the province. (3) The extracted ecological corridors have a mesh-like structure that is dense in the middle and slack in the north. Important corridors have disappeared over time, indicating potential issues in maintaining connectivity for species migration. (4) These results can provide optimization strategies for ecological infrastructure planning in Zhejiang province and offer a theoretical reference for the optimization of the ecological network system.
A Framework for Assessing Innovations, Business Models and Sustainability for Software Companies Using Hybrid Multiple-Criteria Decision-Making
Authors: Torbacki Witold
Published: July 2024

The management staff of software companies are constantly looking for ways to build market advantage and win business strategies. Introducing changes in companies is a costly process and carries the risk of poor allocation of resources. This article provides decision-makers with a tool that increases the chance of making the right business decisions and can also be a guide in the transformation of business models. The scientific aim of this article was to simultaneously cover three areas, innovation, business models, and sustainable development, to develop a scheme enabling the construction of rankings of the elements of these areas in a version dedicated to software producing companies. Rankings, which are built using the hybrid Multiple-Criteria Decision-Making (MCDM) method, indicate to decision-makers the need for building strategic development plans, which aspects are the most important, and what the order of possible implementations should be. Based on a multi-criteria analysis, it was found that (i) in terms of innovation, companies should focus their attention first on implementing product, process, and technological innovations; (ii) within innovative business models, attempts should be made to produce IT systems using virtualization and dockerization, as well as efforts should be made to closely bind customers with the offered products and services and offer temporary rental of IT systems instead of classic licenses; and (iii) in the context of the classic three levels of sustainable development, companies should focus primarily on economic and financial issues.
Unveiling the Dynamics of Residential Energy Consumption: A Quantitative Study of Demographic and Personality Influences in Singapore Using Machine Learning Approaches
Authors: Chew Jovan , Sharma Anurag , Kumar Dhivya Sampath , Zhang Wenjie , Anant Nandini , Dong Jiaxin
Published: July 2024

In the pursuit of instigating a progressive transition towards a more sustainable future, policy officials all over the world are fervently advocating the use of energy conservation techniques targeted at residential customers. Keeping this in mind, a quantitative study was conducted in this work using the data from Singapore, which aims to investigate the relationships between a resident’s pattern of energy utilisation and numerous demographic parameters as well as personality attributes. Moreover, the study was conducted with existing machine learning and data analytics approaches, including k-prototype unsupervised learning and statistical hypothesis tests. The obtained results denote a persuasive correlation between the consumption behaviour of the consumer for different appliances and factors such as income, energy knowledge, usage frequency, personality, etc. For instance, there is a higher probability of a consumer acting frugally and sparingly if they believe their energy consumption is insignificant. These findings can help policymakers identify the appropriate target populations for raising energy awareness in Singapore.