bluuebunny/crossref_metadata_2025 huggingface dataset:
Mach Number Prediction for 0.6 m and 2.4 m Continuous Transonic Wind Tunnels
Authors: Zhao Luping , Jia Wei , Shao Yawen
Published: June 2023

With the development of the design technology, more and more advanced and diverse wind tunnels have been constructed to match complex requirements. However, it is hard to design a precise physical model of a wind tunnel that can be controlled. In addition, if a new wind tunnel is designed, the experimental data may be insufficient to build a controlling model. This article reports research on the following two models: (1) for a 0.6 m continuous transonic wind tunnel supported by a large amount of historical data, the false nearest neighbor (FNN) algorithm was adopted to calculate the order of the input variables, and the nonlinear auto-regressive model with the exogenous inputs–backpropagation network (NARX-BP) was proposed to build its Mach number prediction model; (2) for a new 2.4 m continuous transonic wind tunnel with only a small amount of experimental data, the method of model migration, the input and output slope/bias correction–particle swarm optimization (IOSBC-PSO) algorithm, was developed to convert the old model of the 0.6 m wind tunnel into the new model of the 2.4 m wind tunnel, so that the new Mach number prediction could be conducted. Through simulation experiments, it was found that by introducing the NARX-BP algorithm to build the Mach number prediction model, the root-mean-square error (RMSE) of the model decreased by 44.93–77.90%, and the maximum deviation (MD) decreased by 64.05–85.32% compared to the BP model. The performance of the IOSBC-PSO migration model was also better than that of the non-migration model, as evidenced by the 82.06% decrease of the RMSE value and the 78.25% decrease of the MD value. The experiments showed the effectiveness of the proposed strategy.
Extraction and Characterization of Silica from Empty Palm Fruit Bunch (EPFB) Ash
Authors: Nelson Ebitei Sintei , Iyuke Sunny , Daramola Michael Olawale , Okewale Akindele
Published: June 2023

Recently, there has been so much interest in using biomass waste for bio-based products. Nigeria is one of the countries with an extensive availability of palm biomass. During palm oil production, an empty palm fruit bunch (biomass) is formed, and a lot of ash is generated. This study aimed to extract and characterize silica from empty palm fruit bunch (EPFB) ash using the thermochemical method. The results show that EPFB ash contains a large amount of biogenic silica in its amorphous form. It could be extracted for further use via calcination at different temperatures and compared effectively to other biomass materials, such as rice husk ash, sugarcane bagasse, and cassava periderm. The extracted silica was characterized using XRF, XRD, TGA, SEM, and FTIR, revealing the highest silica concentration of 49.94% obtained at a temperature of 800 °C. The XRF analysis showed 99.44 wt.% pure silica, while the XRD spectrum showed that the silica in EPFB is inherently amorphous. As is evident from the study, silica obtained from EPFB ash is a potential source of silica and it is comparable to the commercial silica. Thus, it is potentially usable as a support for catalysts, in the development of zeolite-based catalysts and as an adsorbent.
How Children Co-Construct a Religious Abstract Concept with Their Caregivers: Theological Models in Dialogue with Linguistic Semantics
Authors: Viertel Franziska E. , Reis Oliver
Published: June 2023

In acquiring a meaningful and rich religious language, children need to build up semantic knowledge about religious words. Most religious concepts do not refer directly to visible entities. Instead, their meanings are often abstract and emerge from the social observation of the world. In our pilot study, we investigate the acquisition of the religious word merciful in 7–8-year-olds during dialogic reading of a biblical story. Merciful is a prototypical religious concept and therefore a fruitful subject for research on the acquisition of religious concepts. First, following the perspective of religious education, we present theological models that identify relevant semantic aspects that constitute mercy. Two of these models relate to interpersonal behavior, which is most common in contemporary understanding. In a second step, we analyze which theological models of mercy are evoked in dialogic reading between caregivers and their children and how they are expressed linguistically. In a third step, we designed a picture story test that allowed us to investigate how children apply their knowledge to novel (secular) contexts and which theological models are evident in children’s problem solving. Our results show that two different theological models of mercy prevail during dialogic reading: the model of forgiveness and the model of compassion. Although the model of forgiveness is central in our settings, the language data show that the model of compassion is also present in the caregiver’s and children’s language. During dialogic reading, the frequency of the semantic aspects of the model of forgiveness expressed between child and caregiver is significantly related. In the picture story test, children are more likely to select semantic aspects of the model of forgiveness in religious contexts than in secular contexts. Interestingly, in secular contexts, children chose semantic neighbors more often, indicating a more diffuse understanding of merciful.
The Impact of Marriage Norms and Gender on Anglican Clergy Actions in Response to Domestic Violence
Authors: Pepper Miriam , Powell Ruth , McEwan Tracy
Published: June 2023

Domestic violence (DV) is a gendered issue, with women more likely to be victim/survivors and men more likely to perpetrate abuse. With a strong emphasis on protecting the safety of women and children, the ways in which faith-based communities and leaders engage DV has come under scrutiny. Clergy are potential responders to DV and shape cultural contexts in which DV occurs. Yet, how religious norms relate to actions taken when clergy respond to DV remains under-researched. Using a survey of Australian Anglican clergy, this paper explores how views about “headship” and the sanctity of marriage relate to the uptake of actions by clergy and churches. Increased support for headship predicted a lower take-up of victim/survivor safety-focused actions by clergy and a lower frequency of actions by churches focused on DV organizations. Male clergy were more likely than their female counterparts to engage with perpetrators and to counsel couples. No independent associations were observed between actions and heightened support for the sanctity of marriage. While the strength of relationships between DV actions and both norms and gender was generally weak, these findings indicate that more work is needed to heighten awareness of the importance of actions focused on victim/survivor safety, connections with DV support services, the problematic practice of couples counselling, and challenges around directly pastoring perpetrators.
The Relationship between Capital Structure and Firm Performance: The Moderating Role of Agency Cost
Authors: Ahmed Amanj Mohamed , Nugraha Deni Pandu , Hágen István
Published: June 2023

Since it first appeared, agency theory has argued that debt can decrease agency issues between agent and principal and enhance the value of firms. This paper explores the moderating effect of agency cost on the association between capital structure and firm performance. A panel econometric method, namely a fixed-effect regression model, was used to evaluate the above description. This investigation uses secondary data collected from published annual reports of manufacturing firms listed on Tehran Stock Exchange (TSE) during 2011–2019. Empirical results show that capital structure is negatively related to firm performance. Agency cost also has a negative impact on corporate performance; however, in the case of ROA and EPS, the relationship is positive. Interestingly, the findings illustrate that increasing the level of debt can reduce agency costs and enhance firm performance. Moreover, robust correlations are revealing that agency cost significantly affects the relationship between capital structure and corporate performance. These findings provide proof to support the assumptions of agency theory, which explains the association between capital structure and performance of firms. This study provides new perspectives on the relationship between capital structure and firm performance by using data from listed manufacturing firms in Iran; hence, these new insights from a developing market improve the understanding of capital structure in Asian and Middle Eastern markets.
Analysis of East Asia Wind Vectors Using Space–Time Cross-Covariance Models
Authors: Jeong Jaehong , Chang Won
Published: June 2023

As the risk posed by climate change becomes increasingly evident, countries across the world are constantly seeking alternative energy sources. Wind energy has substantial potential for future energy portfolios without having negative impacts on the environment. In developing nationwide and worldwide energy plans, understanding the spatio-temporal pattern of wind is crucial. We analyze wind vectors in the region of East Asia from the fifth-generation ECMWF atmospheric reanalysis. To model the wind vectors, we consider Tukey g-and-h transformation-based non-Gaussian processes, along with multivariate covariance functions. The proposed model can address non-Gaussian features and nonstationary dependence structures of wind vectors. In addition, a two-step inference scheme coupled with the composite likelihood method is applied to handle the computational issues posed by a large dataset. In the first step, we fit the temporal dependence structures of data with a location-specific non-Gaussian time series model. This allows us to remove substantial amounts of nonstationary variations in both space and time, and thus, relatively simple covariance models can handle large and complicated data in the second step. We show that the proposed method with a covariance structure reflecting the nonstationarity due to the latitude difference and the land–ocean difference leads to better predictions for wind speed as well as wind potential, which is crucial for planning wind power generation.
Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models
Authors: Zhao Xiaohu , Jia Kebin
Published: June 2023

The majority of the optical observations collected via spaceborne optical satellites are corrupted by clouds or haze, restraining further applications of Earth observation; thus, exploring an ideal method for cloud removal is of great concern. In this paper, we propose a novel probabilistic generative model named sequential-based diffusion models (SeqDMs) for the cloud-removal task in a remote sensing domain. The proposed method consists of multi-modal diffusion models (MmDMs) and a sequential-based training and inference strategy (SeqTIS). In particular, MmDMs is a novel diffusion model that reconstructs the reverse process of denosing diffusion probabilistic models (DDPMs) to integrate additional information from auxiliary modalities (e.g., synthetic aperture radar robust to the corruption of clouds) to help the distribution learning of main modality (i.e., optical satellite imagery). In order to consider the information across time, SeqTIS is designed to integrate temporal information across an arbitrary length of both the main modality and auxiliary modality input sequences without retraining the model again. With the help of MmDMs and SeqTIS, SeqDMs have the flexibility to handle an arbitrary length of input sequences, producing significant improvements only with one or two additional input samples and greatly reducing the time cost of model retraining. We evaluate our method on a public real-world dataset SEN12MS-CR-TS for a multi-modal and multi-temporal cloud-removal task. Our extensive experiments and ablation studies demonstrate the superiority of the proposed method on the quality of the reconstructed samples and the flexibility to handle arbitrary length sequences over multiple state-of-the-art cloud removal approaches.
Landslide Susceptibility Zoning in Yunnan Province Based on SBAS-InSAR Technology and a Random Forest Model
Authors: Liu Meiyu , Xu Bing , Li Zhiwei , Mao Wenxiang , Zhu Yan , Hou Jingxin , Liu Weizheng
Published: June 2023

Yunnan Province, China, has complex topography and geomorphology, many ravines and valleys, and frequent landslide geological disasters and is of great significance in the assessment of regional landslide geological disasters in Yunnan Province for disaster prevention and mitigation. In this study, Yunnan Province was selected as the research area, and the average annual deformation rate of radar line-of-sight in Yunnan Province over four years from 2018 to 2021 was obtained with SBAS-InSAR technology, which was used as one of the index factors for the susceptibility evaluation of Yunnan Province. The deformation rate reflects the slow movement of the land surface. In addition, elevation, slope, aspect, lithological classification, geological structure, rainfall, distance from roads, distance from rivers, topographic undulation, and NDVI were selected as evaluation index factors and combined with the annual mean deformation rate. A random forest model was used to evaluate and accurately analyze landslide geological disasters in Yunnan Province. The results showed that as an important index factor, the annual mean deformation rate of Yunnan Province can be added to the random forest model to improve the prediction accuracy. The area with high susceptibility accounted for 10% of the entire province, and the number of landslides in the region accounted for 68% of the province. Additionally, the results for prone zoning were highly correlated with the landslide distribution. The accuracy of the random forest model prediction was 0.80, and the AUC value was 0.87, indicating that the random forest model was a highly accurate and reliable evaluation method for studying landslide geological disasters. It is very suitable for the evaluation of landslide susceptibility in Yunnan Province.
Mitigation of Calibration Ringing in the Context of the MTG-S IRS Instrument
Authors: Dussarrat Pierre , Deschamps Guillaume , Theodore Bertrand , Coppens Dorothee , Standfuss Carsten , Tournier Bernard
Published: June 2023

EUMETSAT is currently developing the on-ground processing chain of the infrared sounders (IRS) on-board the Meteosat third-generation sounding satellites (MTG-S). In this context, the authors investigated the impact of a particular type of radiometric error, called hereafter calibration ringing. It arises in Fourier transform spectrometers when the instrument’s radiometric transfer function (RTF) varies within the domain of the instrument’s spectral response function (SRF). The expected radiometric errors were simulated in the context of the MTG-S IRS instrument in the long-wave infrared (LWIR) band. Making use of a principal components (PCs) decomposition, a software correction, called RTF uniformisation, was designed and its performance was assessed in the context of MTG-S IRS.
Comparison of Cloud Structures of Storms Producing Lightning at Different Distance Based on Five Years Measurements of a Doppler Polarimetric Vertical Cloud Profiler
Authors: Sokol Zbyněk , Popová Jana , Skripniková Kateřina , Torcasio Rosa Claudia , Federico Stefano , Fišer Ondřej
Published: June 2023

We processed five years of measurements (2018–2022) of a vertically pointing radar MIRA 35c at the Milešovka meteorological observatory with the aim of analyzing the cloud structure of thunderstorms and comparing differences in measured data for cases when lightning discharges were observed very close to the radar position, and for cases when lightning discharges were observed at a greater distance from the radar position. The MIRA 35c radar is a Doppler polarimetric radar working at 35 GHz (Ka-band) with a vertical resolution of 28.9 m and a time resolution of approximately 2 s. For the analysis, we considered radar data whose radar reflectivity was at least 10 dBZ at 5 km or higher above the radar to ensure that there was a cloud above the radar. We divided the radar data into “near” data (a lightning discharge was registered up to 1 km from the radar position) and “far” data (a lightning discharge was registered from 7.5 to 10 km from the radar position). We compared the following quantities: (i) Power in co-channel (pow), (ii) power in cross-channel (pow-cx), (iii) phase in co-channel (pha), (iv) phase in cross-channel (pha-cx), (v) equivalent radar reflectivity (Ze), (vi) Linear Depolarization Ratio (LDR), (vii) co-polar correlation coefficient (RHO), (viii) Doppler radial velocity (V), (ix) Doppler spectrum width (RMS), and (x) Differential phase (Phi). Pow, pow-cx, pha, pha-cx, and V are basic data measured by the radar, while Ze, LDR, RHO, RMS, and Phi are derived quantities. Our results showed that the characteristics of the compared radar quantities are clearly distinct for “near” dataset from “far” dataset. Furthermore, we found out that there is a clear evolution close to the time of discharges of the observed radar quantities in the “near” dataset, which is not that obvious in the “far” dataset.
Summer Extreme Dust Activity in the Taklimakan Desert Regulated by the South Asian High
Authors: Wang Chengyun , Wang Tianhe , Han Ying , Dong Yuanzhu , He Shanjuan , Tang Jingyi
Published: June 2023

Summer dust aerosol in the Taklimakan Desert (TD) affects not only the albedo of the snow and ice sheets on the Tibetan Plateau (TP) but also air quality and precipitation in the downstream areas. In this study, the summer extreme dust activity in the TD was jointly investigated by using satellite observations and MERRA-2 reanalysis datasets and divided into two states: dust active period and dust inactive period. The horizontal and vertical distribution of summer dust during both the dust active and inactive periods, as derived from the MERRA-2 dataset, is consistent with satellite observations. By comparing the upper-level circulation and surface meteorological elements at two periods, we identify the South Asian High (SAH) as the dominant factor driving the extreme dust activity in the TD during summer. When the SAH is centered on the Iranian Plateau (IP), the dust aerosol in the TD exhibits increased activity and is lifted to higher altitudes due to significantly enhanced westerly winds, near-surface wind speed, and an ascending motion. Conversely, when the SAH is centered on the TP, the summer dust activity shows the opposite behavior. These new findings on the regulatory mechanism of the SAH on the summer dust activity in the TD are highly significant for understanding the occurrence and transport of summer Asian dust and its potential impact on heavy precipitation in the downstream areas.
Weakly Supervised Perennial Weed Detection in a Barley Field
Authors: Thomas Leon-Friedrich , Änäkkälä Mikael , Lajunen Antti
Published: June 2023

In the field of precision agriculture, weed detection models combined with selective spraying by ground or aerial robotics are seen as promising approaches for increasing yield harvests while simultaneously minimizing herbicide use. The available labeled training data are a major bottleneck for developing and applying supervised deep learning models, and more automated methods for labeled data generation are therefore needed. Our research aims to address this need by introducing a rule-based method for label data generation for perennial weeds. For this research, a dataset of a barley field was collected using an unmanned aerial vehicle (UAV) with a flight altitude of 10 m. A multispectral and a thermal camera were used for the data collection. The preprocessed dataset consists of multispectral and thermal orthomosaic images along with a canopy height model. The methodological part of this article introduces a proposed rule-based method for labeled data generation for perennial weeds based on the Normalized Difference Vegetation Index (NDVI), and this approach is further used to generate labels for the measured data. The preprocessed data combined with the generated labels was used to train U-net models. Three data combinations are used for the training and testing: multispectral, multispectral–thermal and multispectral–thermal–canopy–height–model. This approach was used to evaluate whether additional data improve model performance. To evaluate the models on ground truth labels, they are tested on a manually annotated test dataset, which consists of 10% of the whole dataset. The tested models achieved an F1 score of 0.82–0.83 on the test dataset. This finding demonstrates that the rule-based labeling method generates valid labels for the perennial weed detection task. Furthermore, our study shows that data fusion improved the model slightly. The data combination of multispectral–thermal–canopy–height–model as input resulted in the best-performing model, with an F1 score of 0.835.
LiDAR Inertial Odometry Based on Indexed Point and Delayed Removal Strategy in Highly Dynamic Environments
Authors: Wu Weizhuang , Wang Wanliang
Published: May 2023

Simultaneous localization and mapping (SLAM) is considered a challenge in environments with many moving objects. This paper proposes a novel LiDAR inertial odometry framework, LiDAR inertial odometry-based on indexed point and delayed removal strategy (ID-LIO) for dynamic scenes, which builds on LiDAR inertial odometry via smoothing and mapping (LIO-SAM). To detect the point clouds on the moving objects, a dynamic point detection method is integrated, which is based on pseudo occupancy along a spatial dimension. Then, we present a dynamic point propagation and removal algorithm based on indexed points to remove more dynamic points on the local map along the temporal dimension and update the status of the point features in keyframes. In the LiDAR odometry module, a delay removal strategy is proposed for historical keyframes, and the sliding window-based optimization includes the LiDAR measurement with dynamic weights to reduce error from dynamic points in keyframes. We perform the experiments both on the public low-dynamic and high-dynamic datasets. The results show that the proposed method greatly increases localization accuracy in high-dynamic environments. Additionally, the absolute trajectory error (ATE) and average RMSE root mean square error (RMSE) of our ID-LIO can be improved by 67% and 85% in the UrbanLoco-CAMarketStreet dataset and UrbanNav-HK-Medium-Urban-1 dataset, respectively, when compared with LIO-SAM.
Hybrid Domain Consistency Constraints-Based Deep Neural Network for Facial Expression Recognition
Authors: Zhu Xiaoliang , Sun Junyi , Liu Gendong , Shen Chen , Dai Zhicheng , Zhao Liang
Published: May 2023

Facial expression recognition (FER) has received increasing attention. However, multiple factors (e.g., uneven illumination, facial deflection, occlusion, and subjectivity of annotations in image datasets) probably reduce the performance of traditional FER methods. Thus, we propose a novel Hybrid Domain Consistency Network (HDCNet) based on a feature constraint method that combines both spatial domain consistency and channel domain consistency. Specifically, first, the proposed HDCNet mines the potential attention consistency feature expression (different from manual features, e.g., HOG and SIFT) as effective supervision information by comparing the original sample image with the augmented facial expression image. Second, HDCNet extracts facial expression-related features in the spatial and channel domains, and then it constrains the consistent expression of features through the mixed domain consistency loss function. In addition, the loss function based on the attention-consistency constraints does not require additional labels. Third, the network weights are learned to optimize the classification network through the loss function of the mixed domain consistency constraints. Finally, experiments conducted on the public RAF-DB and AffectNet benchmark datasets verify that the proposed HDCNet improved classification accuracy by 0.3–3.84% compared to the existing methods.
Automatic Passenger Counting on the Edge via Unsupervised Clustering
Authors: Delzanno Giorgio , Caputo Luca , D’Agostino Daniele , Grosso Daniele , Mustajab Abdul Hannan , Bixio Luca , Rulli Matteo
Published: May 2023

We present a device- and network-based solution for automatic passnger counting that operates on the edge in real time. The proposed solution consists of a low-cost WiFi scanner device equipped with custom algorithms for dealing with MAC address randomization. Our low-cost scanner is able to capture and analyze 802.11 probe requests emitted by passengers’ devices such as laptops, smartphones, and tablets. The device is configured with a Python data-processing pipeline that combines data coming from different types of sensors and processes them on the fly. For the analysis task, we have devised a lightweight version of the DBSCAN algorithm. Our software artifact is designed in a modular way in order to accommodate possible extensions of the pipeline, e.g., either additional filters or data sources. Furthermore, we exploit multi-threading and multi-processing for speeding up the entire computation. The proposed solution has been tested with different types of mobile devices, obtaining promising experimental results. In this paper, we present the key ingredients of our edge computing solution.
The Methods of Fall Detection: A Literature Review
Authors: Newaz Nishat Tasnim , Hanada Eisuke
Published: May 2023

Fall Detection Systems (FDS) are automated systems designed to detect falls experienced by older adults or individuals. Early or real-time detection of falls may reduce the risk of major problems. This literature review explores the current state of research on FDS and its applications. The review shows various types and strategies of fall detection methods. Each type of fall detection is discussed with its pros and cons. Datasets of fall detection systems are also discussed. Security and privacy issues related to fall detection systems are also considered in the discussion. The review also examines the challenges of fall detection methods. Sensors, algorithms, and validation methods related to fall detection are also talked over. This work found that fall detection research has gradually increased and become popular in the last four decades. The effectiveness and popularity of all strategies are also discussed. The literature review underscores the promising potential of FDS and highlights areas for further research and development.
Microfluidic Biosensor Based on Molybdenum Disulfide (MoS2) Modified Thin-Core Microfiber for Immune Detection of Toxoplasma gondii
Authors: Chen Huiji , Luo Binbin , Wu Shengxi , Shi Shenghui , Dai Qin , Peng Zehua , Zhao Mingfu
Published: May 2023

Toxoplasma gondii (T. gondii) is a zoonotic parasite that is widely distributed and seriously endangers public health and human health. Therefore, accurate and effective detection of T. gondii is crucial. This study proposes a microfluidic biosensor using a thin-core microfiber (TCMF) coated with molybdenum disulfide (MoS2) for immune detection of T. gondii. The single-mode fiber was fused with the thin-core fiber, and the TCMF was obtained by arc discharging and flame heating. In order to avoid interference and protect the sensing structure, the TCMF was encapsulated in the microfluidic chip. MoS2 and T. gondii antigen were modified on the surface of TCMF for the immune detection of T. gondii. Experimental results showed that the detection range of the proposed biosensor for T. gondii monoclonal antibody solutions was 1 pg/mL to 10 ng/mL with sensitivity of 3.358 nm/log(mg/mL); the detection of limit was calculated to be 87 fg/mL through the Langmuir model; the dissociation constant and the affinity constant were calculated to be about 5.79 × 10−13 M and 1.727 × 1014 M−1, respectively. The specificity and clinical characteristics of the biosensor was explored. The rabies virus, pseudorabies virus, and T. gondii serum were used to confirm the excellent specificity and clinical characteristics of the biosensor, indicating that the proposed biosensor has great application potential in the biomedical field.
An Efficient Method for Laser Welding Depth Determination Using Optical Coherence Tomography
Authors: Xie Guanming , Wang Sanhong , Zhang Yueqiang , Hu Biao , Fu Yu , Yu Qifeng , Li You
Published: May 2023

Online monitoring of laser welding depth is increasingly important, with the growing demand for the precise welding depth in the field of power battery manufacturing for new energy vehicles. The indirect methods of welding depth measurement based on optical radiation, visual image and acoustic signals in the process zone have low accuracy in the continuous monitoring. Optical coherence tomography (OCT) provides a direct welding depth measurement during laser welding and shows high achievable accuracy in continuous monitoring. Statistical evaluation approach accurately extracts the welding depth from OCT data but suffers from complexity in noise removal. In this paper, an efficient method coupled DBSCAN (Density-Based Spatial Clustering of Application with Noise) and percentile filter for laser welding depth determination was proposed. The noise of the OCT data were viewed as outliers and detected by DBSCAN. After eliminating the noise, the percentile filter was used to extract the welding depth. By comparing the welding depth determined by this approach and the actual weld depth of longitudinal cross section, an average error of less than 5% was obtained. The precise laser welding depth can be efficiently achieved by the method.
Estimating Thoracic Movement with High-Sampling Rate THz Technology
Authors: Hoog Antink Christoph , Schulz Romina , Rohr Maurice , Wenzel Konstantin , Liebermeister Lars , Kohlhaas Robert , Preu Sascha
Published: June 2023

We use a high-sampling rate terahertz (THz) homodyne spectroscopy system to estimate thoracic movement from healthy subjects performing breathing at different frequencies. The THz system provides both the amplitude and phase of the THz wave. From the raw phase information, a motion signal is estimated. An electrocardiogram (ECG) signal is recorded with a polar chest strap to obtain ECG-derived respiration information. While the ECG showed sub-optimal performance for the purpose and only provided usable information for some subjects, the signal derived from the THz system showed good agreement with the measurement protocol. Over all the subjects, a root mean square estimation error of 1.40 BPM is obtained.
A Review of NDT Methods for Wheel Burn Detection on Rails
Authors: Zhang Yanbo , Liu Xiubo , Xiong Longhui , Chen Zhuo , Wei Jianmei
Published: June 2023

Wheel burn can affect the wheel–rail contact state and ride quality. With long-term operation, it can cause rail head spalling or transverse cracking, which will lead to rail breakage. By analyzing the relevant literature on wheel burn, this paper reviews the characteristics, mechanism of formation, crack extension, and NDT methods of wheel burn. The results are as follows: Thermal-induced, plastic-deformation-induced, and thermomechanical-induced mechanisms have been proposed by researchers; among them, the thermomechanical-induced wheel burn mechanism is more probable and convincing. Initially, the wheel burns appear as an elliptical or strip-shaped white etching layer with or without deformation on the running surface of the rails. In the latter stages of development, this may cause cracks, spalling, etc. Magnetic Flux Leakage Testing, Magnetic Barkhausen Noise Testing, Eddy Current Testing, Acoustic Emission Testing, and Infrared Thermography Testing can identify the white etching layer, and surface and near-surface cracks. Automatic Visual Testing can detect the white etching layer, surface cracks, spalling, and indentation, but cannot detect the depth of rail defects. Axle Box Acceleration Measurement can be used to detect severe wheel burn with deformation.
Continuous Structural Displacement Monitoring Using Accelerometer, Vision, and Infrared (IR) Cameras
Authors: Choi Jaemook , Ma Zhanxiong , Kim Kiyoung , Sohn Hoon
Published: June 2023

With the rapid development of computer vision, vision cameras have been used as noncontact sensors for structural displacement measurements. However, vision-based techniques are limited to short-term displacement measurements because of their degraded performance under varying illumination and inability to operate at night. To overcome these limitations, this study developed a continuous structural displacement estimation technique by combining measurements from an accelerometer with vision and infrared (IR) cameras collocated at the displacement estimation point of a target structure. The proposed technique enables continuous displacement estimation for both day and night, automatic optimization of the temperature range of an infrared camera to ensure a region of interest (ROI) with good matching features, and adaptive updating of the reference frame to achieve robust illumination–displacement estimation from vision/IR measurements. The performance of the proposed method was verified through lab-scale tests on a single-story building model. The displacements were estimated with a root-mean-square error of less than 2 mm compared with the laser-based ground truth. In addition, the applicability of the IR camera for displacement estimation under field conditions was validated using a pedestrian bridge test. The proposed technique eliminates the need for a stationary sensor installation location by the on-site installation of sensors and is therefore attractive for long-term continuous monitoring. However, it only estimates displacement at the sensor installation location, and cannot simultaneously estimate multi-point displacements which can be achieved by installing cameras off-site.
Machine Learning Techniques for Developing Remotely Monitored Central Nervous System Biomarkers Using Wearable Sensors: A Narrative Literature Review
Authors: ZhuParris Ahnjili , de Goede Annika A. , Yocarini Iris E. , Kraaij Wessel , Groeneveld Geert Jan , Doll Robert Jan
Published: June 2023

Background: Central nervous system (CNS) disorders benefit from ongoing monitoring to assess disease progression and treatment efficacy. Mobile health (mHealth) technologies offer a means for the remote and continuous symptom monitoring of patients. Machine Learning (ML) techniques can process and engineer mHealth data into a precise and multidimensional biomarker of disease activity. Objective: This narrative literature review aims to provide an overview of the current landscape of biomarker development using mHealth technologies and ML. Additionally, it proposes recommendations to ensure the accuracy, reliability, and interpretability of these biomarkers. Methods: This review extracted relevant publications from databases such as PubMed, IEEE, and CTTI. The ML methods employed across the selected publications were then extracted, aggregated, and reviewed. Results: This review synthesized and presented the diverse approaches of 66 publications that address creating mHealth-based biomarkers using ML. The reviewed publications provide a foundation for effective biomarker development and offer recommendations for creating representative, reproducible, and interpretable biomarkers for future clinical trials. Conclusion: mHealth-based and ML-derived biomarkers have great potential for the remote monitoring of CNS disorders. However, further research and standardization of study designs are needed to advance this field. With continued innovation, mHealth-based biomarkers hold promise for improving the monitoring of CNS disorders.
Lower Limb Exoskeleton for Rehabilitation with Flexible Joints and Movement Routines Commanded by Electromyography and Baropodometry Sensors
Authors: Rosales-Luengas Yukio , Espinosa-Espejel Karina I. , Lopéz-Gutiérrez Ricardo , Salazar Sergio , Lozano Rogelio
Published: June 2023

This paper presents the development of an instrumented exoskeleton with baropodometry, electromyography, and torque sensors. The six degrees of freedom (Dof) exoskeleton has a human intention detection system based on a classifier of electromyographic signals coming from four sensors placed in the muscles of the lower extremity together with baropodometric signals from four resistive load sensors placed at the front and rear parts of both feet. In addition, the exoskeleton is instrumented with four flexible actuators coupled with torque sensors. The main objective of the paper was the development of a lower limb therapy exoskeleton, articulated at hip and knees to allow the performance of three types of motion depending on the detected user’s intention: sitting to standing, standing to sitting, and standing to walking. In addition, the paper presents the development of a dynamical model and the implementation of a feedback control in the exoskeleton.
Application of ZnO/WO3 Composite Nanofiber Photocatalysts in Textile Wastewater Treatment
Authors: Xu Yongxin , Yan Hui , Chen Tiwei
Published: June 2023

Semiconductor photocatalysis technology is an environmentally friendly and efficient emerging technology. This method can use sunlight as a driving force to quickly decompose organic pollutants in water bodies. Zinc oxide (ZnO) and tungsten oxide (WO3) photocatalysts can absorb sunlight and participate in photocatalytic degradation reactions due to their relatively narrow band gap. Highly photosensitive WO3 nanofibers and ZnO/WO3 composite nanofibers were fabricated via the electrospinning method. When 100 mg/L of rhodamine B (Rh B) solution was used as the degradation substrate, the degradation efficiencies of WO3 and ZnO/WO3 for Rh B dye were 70% and 90%, respectively, after a photocatalytic reaction of 120 min. The surface morphology, crystal structure, and optical properties of ZnO/WO3 composite nanofibers and WO3 nanofibers were characterized by SEM, XRD, XPS, and UV-vis absorption spectra, and the experimental results were analyzed and explained using different mechanisms. The results show that ZnO/WO3 composite nanofibers have better UV-visible light absorption performance, and the sample has a higher UV-visible light utilization rate. This was mainly due to the fact that a P-N heterojunction was formed in the semiconductor composite, and the electron–hole pair could realize rapid separation under the drive of a built-in electric field force, which promoted the migration of carrier. Therefore, the photocatalytic activity of the ZnO/WO3 catalyst was significantly higher than that of the WO3 catalyst, which promoted rapid improvement of the photocatalytic degradation efficiency of the Rh B dye.
Integrating Environment with Health: An Islamic Perspective
Authors: Mohidem Nur Adibah , Hashim Zailina
Published: May 2023

With the increasing challenge of addressing environmental health issues, various approaches have been proposed to reduce environmental problems. For Muslims all over the world, the Qur’an, Hadith, and Sunnah are recognised as the authoritative messages for spiritual and behavioural guidance on how humans can react to protect the environment and health. This review aims to integrate the environment with health from the perspective of Islam. An exploration of Qur’anic, Hadith, and Sunnah Muslim scholar views and articles was carried out to identify environmental health issues. Integrating Islamic aspects into environmental health includes: (i) environmental dimensions of natural and social environments; (ii) dimensions of health including disease, wellness, intellectual health, transcendence, and Qalbe Salim; and (iii) principles that can be used to describe people’s attitudes towards the environment through unity, balance, and responsibility. Differences between Islamic and Western views on the environment include that taqwa-centric is the highest level of environmental responsibility, with religious duty serving as the key driver of environmental activity. About 89 verses were identified in 42 Qur’anic chapters, with a strong emphasis on the health aspect in relation to the water, biodiversity, corruption of the earth, waste minimisation, and climate change. The Hadith and Sunnah highlight cleanliness as another important value in Islamic ethics, focusing on environmental conservation. Current and future research trends may be able to identify research gaps concerning the Islamic aspect of handling environmental health issues, which can then be implemented into the educational system. These findings imply that Islam could be a powerful source and educational medium for environmental health interventions in large communities, as well as for improving and preserving a healthy environment.
City Color Planning Systems in East Asia in the 21st Century: A Comparative Investigation of Three Capital Cities
Authors: Wen Yajun , Himeno Yuka , Chung Jaehoon
Published: June 2023

Since the advent of the 21st century, with the promulgation of landscape laws and related landscape management regulations, city color, as a vital component of the urban landscape, has garnered increasing attention. In East Asia, numerous cities have embraced city color planning as a means to enhance their urban landscape and shape the distinctive features of the city. Therefore, this study focuses on exploring the characteristics of city color planning systems in East Asia by adopting qualitative analysis methods, using Tokyo, Seoul, and Beijing as case study examples. We used publications, academic research, and official documents clustered into seven domains to identify the following: government agency, introduction time, relevant laws, upper plan, tools/management, planning method, and planning contents. The results revealed that compared with Europe, city color planning in East Asia is government-led top-down planning, and there are remarkable similarities in the formulation process, planning methods, and color selection, while there are obvious deficiencies in the professionalism of the planning authorities and public participation. The results of this study provide a valuable reference for city color planning in the future, thereby enhancing the urban landscape and shaping unique city identities in East Asia.
Implementing European Union Provisions and Enabling Frameworks for Renewable Energy Communities in Nine Countries: Progress, Delays, and Gaps
Authors: Krug Michael , Di Nucci Maria Rosaria , Schwarz Lucas , Alonso Irene , Azevedo Isabel , Bastiani Massimo , Dyląg Anna , Laes Erik , Hinsch Arthur , Klāvs Gaidis , Kudreņickis Ivars , Maleki Pouyan , Massa Gilda , Meynaerts Erika , Pappa Stavroula , Standal Karina
Published: June 2023

With the Clean Energy for all Europeans legislative package, the European Union (EU) aimed to put consumers “at the heart” of EU energy policy. The recast of the Renewable Energy Directive (RED II) acknowledged the importance of energy communities for the energy transition and introduced new provisions for renewable energy communities (RECs), empowering them to participate in the energy market. This article analyses the progress of transposing and implementing key provisions of the RED II that apply to RECs in nine European countries and focuses on timeliness and completeness of transposition. It comprises both a qualitative and quantitative assessment covering (1) the definition, rights, and market activities of RECs; (2) key elements of enabling frameworks; and (3) consideration of REC specificities in support schemes for renewable energy. The analysis shows considerable variation in transposition performance between the analysed countries. The authors investigate the reasons for this variation and relate them to findings of European implementation and compliance research. Key factors identified include actor-related and capacity-related factors, institutional fit, and characteristics of the RED II itself. Future research in this field needs multi-faceted avenues and should pay particular attention to the influence of national governments and incumbents, not only in the transposition process, but already in upstream policy formulation at the European level.
Exploring Livelihood Strategies of Farmers and Herders and Their Human Well-Being in Qilian Mountain National Park, China
Authors: Li Jiatong , Tang Haiping , Kuang Foyuan
Published: June 2023

National parks have implemented restrictive measures on human activities to protect the ecological environment, which has changed the livelihood dependence and strategies of farmers and herders. Exploring the impact of livelihood strategies on the human well-being of farmers and herdsmen within the national park construction area can help to better develop livelihood intervention measures to achieve sustainable livelihoods for farmers and herders. A total of 329 farmers and herders in Qilian Mountain National Park in China were investigated, and one-way ANOVA and ordinary least squares were employed to analyze the impact of farmers’ and herders’ livelihood strategies on human well-being in different periods of national park construction. Our results show that the livelihood strategies of farmers and herders play an important role in their well-being. Farmers and herders adopted diversified livelihood strategies after the National Park System Pilot officially launched (after 2015). The well-being advantage of adopting a diversified livelihood strategy became evident over time. Specifically, farmers and herders adopting the settlement diversification livelihood strategy were able to better adapt to the development concept of the national park after the national park pilot was officially established (after 2017). However, nomadic, settled agricultural, and pastoral households were always at a disadvantage in terms of well-being. In addition, distance, nationality, gender, and education level were important factors affecting the well-being of farmers and herders. The results of this study are helpful for improving our understanding of the influence of livelihood strategies on the well-being of farmers and herders and the related challenges they face in the construction of national parks.
Evaluation of Bus Lane Layouts Based on a Bi-Level Programming Model—Using Part of the Qingshan Lake District of Nanchang City, China, as an Example
Authors: Xue Yunqiang , Cheng Lin , Zhong Meng , Sun Xiaokang
Published: June 2023

Bus lanes have gradually become an indispensable infrastructure for the development of urban public transportation networks. A bi-level programming model is used herein to compare the total travel time of social vehicles and buses before and after the bus lane is set up to judge whether the bus lane layout plan is scientific and reasonable considering the road network. The model’s effectiveness is verified using areas of Qingshan Lake in Nanchang City, and the operational efficiency of one bus lane before and after establishing the dedicated bus lane is analyzed. The case results show that the bus lane layout evaluation needs to consider the traffic benefits of a specific road and also judge whether the total travel time of the network traffic volume is improved from the macroscopic road network level. The research results provide theoretical support for the rational layout of bus lanes and are of practical significance for prioritizing the development of public transportation and promoting the sustainable development of urban transportation.