bluuebunny/crossref_metadata_2025 huggingface dataset:
Capacitive Effect and Electromagnetic Coupling on Manganin Gauge Limiting the Bandwidth for Pressure Measurements under Shock Conditions
Authors: Coustou Antony , Lefrançois Alexandre , Pons Patrick , Barbarin Yohan
Published: July 2023

In this study, we investigated the capacitive effect and the electromagnetic coupling on the measurement chain induced by impact experiments with a gas gun or powder gun. Reduced bandwidth and noise were noticed on experimental signals. Rogowski coil measurements were added on the cables to characterize the electromagnetic coupling. The perturbation currents on the cables were quantified depending on the configuration. The gauge, the transmission line and the conditioning system were modeled. The calculations reproduced the electrical wave arrival time, the transmission line transfer impedance and the conditioning system transfer impedance; and the bandwidth limitation has been displayed. A capacitive effect with the piezoresistive manganin gauge embedded into the sample was identified, depending on the experimental setup.
Smart Detecting and Versatile Wearable Electrical Sensing Mediums for Healthcare
Authors: Ali Ahsan , Ashfaq Muaz , Qureshi Aleen , Muzammil Umar , Shaukat Hamna , Ali Shaukat , Altabey Wael A. , Noori Mohammad , Kouritem Sallam A.
Published: July 2023

A rapidly expanding global population and a sizeable portion of it that is aging are the main causes of the significant increase in healthcare costs. Healthcare in terms of monitoring systems is undergoing radical changes, making it possible to gauge or monitor the health conditions of people constantly, while also removing some minor possibilities of going to the hospital. The development of automated devices that are either attached to organs or the skin, continually monitoring human activity, has been made feasible by advancements in sensor technologies, embedded systems, wireless communication technologies, nanotechnologies, and miniaturization being ultra-thin, lightweight, highly flexible, and stretchable. Wearable sensors track physiological signs together with other symptoms such as respiration, pulse, and gait pattern, etc., to spot unusual or unexpected events. Help may therefore be provided when it is required. In this study, wearable sensor-based activity-monitoring systems for people are reviewed, along with the problems that need to be overcome. In this review, we have shown smart detecting and versatile wearable electrical sensing mediums in healthcare. We have compiled piezoelectric-, electrostatic-, and thermoelectric-based wearable sensors and their working mechanisms, along with their principles, while keeping in view the different medical and healthcare conditions and a discussion on the application of these biosensors in human health. A comparison is also made between the three types of wearable energy-harvesting sensors: piezoelectric-, electrostatic-, and thermoelectric-based on their output performance. Finally, we provide a future outlook on the current challenges and opportunities.
Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges
Authors: Mohamed Abdul Cader Akmal Jahan , Banks Jasmine , Chandran Vinod
Published: July 2023

The fingerprint is a widely adopted biometric trait in forensic and civil applications. Fingerprint biometric systems have been investigated using contact prints and latent and contactless images which range from low to high resolution. While the imaging techniques are advancing with sensor variations, the input fingerprint images also vary. A general fingerprint recognition pipeline consists of a sensor module to acquire images, followed by feature representation, matching and decision modules. In the sensor module, the image quality of the biometric traits significantly affects the biometric system’s accuracy and performance. Imaging modality, such as contact and contactless, plays a key role in poor image quality, and therefore, paying attention to imaging modality is important to obtain better performance. Further, underlying physical principles and the working of the sensor can lead to their own forms of distortions during acquisition. There are certain challenges in each module of the fingerprint recognition pipeline, particularly sensors, image acquisition and feature representation. Present reviews in fingerprint systems only analyze the imaging techniques in fingerprint sensing that have existed for a decade. However, the latest emerging trends and recent advances in fingerprint sensing, image acquisition and their challenges have been left behind. Since the present reviews are either obsolete or restricted to a particular subset of the fingerprint systems, this work comprehensively analyzes the state of the art in the field of contact-based, contactless 2D and 3D fingerprint systems and their challenges in the aspects of sensors, image acquisition and interoperability. It outlines the open issues and challenges encountered in fingerprint systems, such as fingerprint performance, environmental factors, acceptability and interoperability, and alternate directions are proposed for a better fingerprint system.
Energy Harvesting System Whose Potential Is Mapped with the Modified Fibonacci Function
Authors: Margielewicz Jerzy , Gąska Damian , Litak Grzegorz , Caban Jacek , Dudziak Agnieszka , Ma Xiaoqing , Zhou Shengxi
Published: July 2023

In this paper, we compare three energy harvesting systems in which we introduce additional bumpers whose mathematical model is mapped with a non-linear characteristic based on the hyperbolic sine Fibonacci function. For the analysis, we construct non-linear two-well, three-well and four-well systems with a cantilever beam and permanent magnets. In order to compare the effectiveness of the systems, we assume comparable distances between local minima of external wells and the maximum heights of potential barriers. Based on the derived dimensionless models of the systems, we perform simulations of non-linear dynamics in a wide spectrum of frequencies to search for chaotic and periodic motion zones of the systems. We present the issue of the occurrence of transient chaos in the analyzed systems. In the second part of this work, we determine and compare the effectiveness of the tested structures depending on the characteristics of the bumpers and an external excitation whose dynamics are described by the harmonic function, and find the best solutions from the point view of energy harvesting. The most effective impact of the use of bumpers can be observed when dealing with systems described by potential with deep external wells. In addition, the use of the Fibonacci hyperbolic sine is a simple and effective numerical tool for mapping non-linear properties of such motion limiters in energy harvesting systems.
Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access
Authors: Xie Wenjiao , Tian Runhe , Zhang Huisheng
Published: July 2023

In this paper, we consider a slot-controlled coded compressed sensing protocol for unsourced massive random access (URA) that concatenates a shared patterned Reed–Muller (PRM) inner codebook to an outer error-correction code. Due to the limitations of the geometry-based decoding algorithm in single-sequence settings and due to the message interference that may result in decreased decoding performance under multi-sequence circumstances, a list PRM projection algorithm and an iterative list PRM projection algorithm are proposed to supplant the signal detector associated with the inner PRM sequences in this paper. In detail, we first propose an enhanced path-saving algorithm, called list PRM projection detection, for use in single-user scenarios that maintains multiple candidates during the first few layers so as to remedy the risk of spreading errors. On this basis, we further propose an iterative list PRM projection algorithm for use in multi-user scenarios. The vectors for PRM codes and channel coefficients are jointly detected in an iterative manner, which offers significant improvements regarding the convergence rate for signal recovery. Furthermore, the performances of the proposed algorithms are analyzed mathematically, and we verify that the theoretical simulations are consistent with the numerical simulations. Finally, we concatenate the inner PRM codes that employ iterative list detection in two practical error-correction outer codes. According to the simulation results, we conclude that the packetized URA with the proposed iterative list projection detection works better than benchmarks in terms of the number of active users it can support in each slot and the amount of energy needed per bit to meet an expected error probability.
Food Choices after Cognitive Load: An Affective Computing Approach
Authors: Kappattanavar Arpita Mallikarjuna , Hecker Pascal , Moontaha Sidratul , Steckhan Nico , Arnrich Bert
Published: July 2023

Psychology and nutritional science research has highlighted the impact of negative emotions and cognitive load on calorie consumption behaviour using subjective questionnaires. Isolated studies in other domains objectively assess cognitive load without considering its effects on eating behaviour. This study aims to explore the potential for developing an integrated eating behaviour assistant system that incorporates cognitive load factors. Two experimental sessions were conducted using custom-developed experimentation software to induce different stimuli. During these sessions, we collected 30 h of physiological, food consumption, and affective states questionnaires data to automatically detect cognitive load and analyse its effect on food choice. Utilising grid search optimisation and leave-one-subject-out cross-validation, a support vector machine model achieved a mean classification accuracy of 85.12% for the two cognitive load tasks using eight relevant features. Statistical analysis was performed on calorie consumption and questionnaire data. Furthermore, 75% of the subjects with higher negative affect significantly increased consumption of specific foods after high-cognitive-load tasks. These findings offer insights into the intricate relationship between cognitive load, affective states, and food choice, paving the way for an eating behaviour assistant system to manage food choices during cognitive load. Future research should enhance system capabilities and explore real-world applications.
Finding Well-Coupled Optical Fiber Locations for Railway Monitoring Using Distributed Acoustic Sensing
Authors: Muñoz Felipe , Urricelqui Javier , Soto Marcelo A. , Jimenez-Rodriguez Marco
Published: July 2023

Distributed acoustic sensors (DAS) utilize optical fibers to monitor vibrations across thousands of independent locations. However, the measured acoustic waveforms experience significant variations along the sensing fiber. These differences primarily arise from changes in coupling between the fiber and its surrounding medium as well as acoustic interferences. Here, a correlation-based method is proposed to automatically find the spatial locations of DAS where temporal waveforms are repeatable. Signal repeatability is directly associated with spatial monitoring locations with both good coupling and low acoustic interference. The DAS interrogator employed is connected to an over 30-year-old optical fiber installed alongside a railway track. Thus, the optical fiber exhibits large coupling changes and different installation types along its path. The results indicate that spatial monitoring locations with good temporal waveform repeatability can be automatically discriminated using the proposed method. The correlation between the temporal waveforms acquired at locations selected by the algorithm proved to be very high considering measurements taken for three days, the first two on consecutive days and the third one a month after the first measurement.
Attitude Control of Ornithopter Wing by Using a MIMO Active Disturbance Rejection Strategy
Authors: Gouvêa Josiel Alves , Raptopoulos Luciano Santos Constantin , Pinto Milena Faria , Díaz Elkin Yesid Veslin , Dutra Max Suell , Sousa Lucas Costa de , Batista Victor Manuel Oliveira , Zachi Alessandro Rosa Lopes
Published: July 2023

This work proposes a mathematical solution for the attitude control problem of an ornithopter wing. An ornithopter is an artificial bird or insect-like aerial vehicle whose flight and lift movements are produced and maintained by flapping wings. The aerodynamical drag forces responsible for the flying movements are generated by the wing attitude and torques applied to its joints. This mechanical system represents a challenging problem because its dynamics consist of MIMO nonlinear equations with couplings in the input variables. For dealing with such a mathematical model, an Active Disturbance Rejection Control-based (ADRC) method is considered. The cited control technique has been studied for almost two decades and its main characteristics are the use of an extended state observer to estimate the nonmeasurable signals of the plant and a state-feedback control law in standard form fed by that observer. However, even today, the application of the basic methodology requires the exact knowledge of the plant’s control gain which is difficult to measure in the case of systems with uncertain parameters. In addition, most of the related works apply the ADRC strategy to Single Input Single Output (SISO) plants. For MIMO systems, the control gain is represented by a square matrix of general entries but most of the reported works consider the simplified case of uncoupled inputs, in which a diagonal matrix is assumed. In this paper, an extension of the ADRC SISO strategy for MIMO systems is proposed. By adopting such a control methodology, the resulting closed-loop scheme exhibits some key advantages: (i) it is robust to parametric uncertainties; (ii) it can compensate for external disturbances and unmodeled dynamics; (iii) even for nonlinear plants, mathematical analysis using Laplace’s approach can be always used; and (iv) it can deal with system’s coupled input variables. A complete mathematical model for the dynamics of the ornithopter wing system is presented. The efficiency of the proposed control is analyzed mathematically, discussed, and illustrated via simulation results of its application in the attitude control of ornithopter wings.
An Intelligent Cost-Reference Particle Filter with Resampling of Multi-Population Cooperation
Authors: Zhang Xinyu , Ren Mengjiao , Duan Jiemin , Yi Yingmin , Lei Biyu , Wu Shuyue
Published: July 2023

Although the cost-reference particle filter (CRPF) has a good advantage in solving the state estimation problem with unknown noise statistical characteristics, its estimation accuracy is still affected by the lack of particle diversity and sensitivity to the particles’ initial value. In order to solve these problems of the CRPF, this paper proposed an intelligent cost-reference particle filter algorithm based on multi-population cooperation. A multi-population cooperative resampling strategy based on ring structure was designed. The particles were divided into multiple independent populations upon initialization, and each population generated particles with a different initial distribution. The particles in each population were divided into three different particle sets with high, medium and low weights by the golden section ratio according to the weight. The particle sets with high and medium weights were retained. Then, a cooperative strategy based on Gaussian mutation was designed to resample the low-weight particle set of each population. The high-weight particles of the previous population in the ring structure were randomly selected for Gaussian mutation to replace the low-weight particles in the current population. The low-weight particles of all populations were resampled in turn. The simulation results show that the intelligent CRPF based on multi-population cooperation proposed in this paper can reduce the sensitivity of the CRPF to the particles’ initial value and improve the particle diversity in resampling. Compared with the general CRPF and intelligent CRPF with adaptive MH resampling (MH-CRPF), the RMSE and MAE of the proposed method are lower.
A Sage–Husa Prediction Algorithm-Based Approach for Correcting the Hall Sensor Position in DC Brushless Motors
Authors: Wang Lu , Cheng Yong , Yin Wei
Published: July 2023

Accurate knowledge of the rotor position is essential for the control of brushless DC motors (BLDCM). Any deviation in this identification can cause fluctuations in motor current and torque, increase noise, and lead to reduced motor efficiency. This paper focused on a BLDCM equipped with a three-phase binary Hall sensor. Based on the principle of minimum deviation, this paper estimated the relative installation offset between the Hall sensors. It also provided a clear method for ideal phase commutation position recognition and eliminated the Hall sensor installation position deviation. The proposed pre-calibration method identified and eliminated the offset of the permanent magnet poles, the delay time caused by the Hall signal conditioning circuit, and the offset of the sensor signal identification due to armature response under different loads. Based on the pre-calibration results, a correction strategy for correcting the rotor position information of BLDCMs was proposed. This paper presented a self-adaptive position information prediction algorithm based on the Sage–Husa method. This filters out rotor position information deviations that are not eliminated in pre-calibration. Experimental results on a hydrogen circulation pump motor showed that, after the pre-calibration method was adopted, the Mean Square Error (MSE) of motor speed fluctuations decreased by 92.0%, motor vibration was significantly reduced, average phase current decreased by 62.8%, and the efficiency of the hydrogen circulation pump system was significantly improved. Compared to the traditional KF prediction algorithm, the Sage–Husa adaptive position information prediction algorithm reduced the speed fluctuation during the uniform speed operation stage and speed adjustment stage, the speed curve overshoot, and the commutation time deviation throughout the process by 44.8%, 56.0%, 54.9%, and 14.7%, respectively. This indicates a higher disturbance rejection ability and a more accurate and stable prediction of the commutation moment.
Sensitivity of Shipborne GNSS Estimates to Processing Modeling Based on Simulated Dataset
Authors: Panetier Aurélie , Bosser Pierre , Khenchaf Ali
Published: July 2023

The atmospheric water vapor is commonly monitored from ground Global Navigation Satellite System (GNSS) measurements, by retrieving the tropospheric delay under the Zenith Wet Delay (ZWD) component, linked to the water vapor content in the atmosphere. In recent years, the GNSS ZWD retrieval has been performed on shipborne antennas to gather more atmospheric data above the oceans for climatology and meteorology study purposes. However, when analyzing GNSS data acquired by a moving antenna, it is more complex to decorrelate the height of the antenna and the ZWD during the Precise Point Positioning (PPP) processing. Therefore, the observation modeling and processing parametrization must be tuned. This study addresses the impact of modeling on the estimation of height and ZWD from the simulation of shipborne GNSS measurements. The GNSS simulation is based on an authors-designed simulator presented in this article. We tested different processing models (elevation cut-off angle, elevation weighting function, and random walk of ZWD) and simulation configurations (the constellations used, the sampling of measurements, the location of the antenna, etc.). According to our results, we recommend processing shipborne GNSS measurements with 3° of cut-off angle, elevation weighting function square root of sine, and an average of 5 mm·h−1/2 of random walk on ZWD, the latter being specifically adapted to mid-latitudes but which could be extended to other areas. This processing modeling will be applied in further studies to monitor the distribution of water vapor above the oceans from systematic analysis of shipborne GNSS measurements.
Susceptibility Analysis of Glacier Debris Flow Based on Remote Sensing Imagery and Deep Learning: A Case Study along the G318 Linzhi Section
Authors: Chen Jiaqing , Gao Hong , Han Le , Yu Ruilin , Mei Gang
Published: July 2023

Glacial debris flow is a common natural disaster, and its frequency has been increasing in recent years due to the continuous retreat of glaciers caused by global warming. To reduce the damage caused by glacial debris flows to human and physical properties, glacier susceptibility assessment analysis is needed. Most research efforts consider the effect of existing glacier area and ignore the effect of glacier ablation volume change. In this paper, we consider the impact of glacier ablation volume change to investigate the susceptibility of glacial debris flow. The susceptibility to mudslide was evaluated by taking the glacial mudslide-prone ditch of G318 Linzhi section of Sichuan-Tibet Highway as the research object. First, by using a simple band ratio method with manual correction, we produced a glacial mudslide remote sensing image dataset, and second, we proposed a deep-learning-based approach using a weight-optimized glacial mudslide semantic segmentation model for accurately and automatically mapping the boundaries of complex glacial mudslide-covered remote sensing images. Then, we calculated the ablation volume by the change in glacier elevation and ablation area from 2015 to 2020. Finally, glacial debris flow susceptibility was evaluated based on the entropy weight method and Topsis method with glacial melt volume in different watersheds as the main factor. The research results of this paper show that most of the evaluation indices of the model are above 90%, indicating that the model is reasonable for glacier boundary extraction, and remote sensing images and deep learning techniques can effectively assess the glacial debris flow susceptibility and provide support for future glacial debris flow disaster prevention.
TDFusion: When Tensor Decomposition Meets Medical Image Fusion in the Nonsubsampled Shearlet Transform Domain
Authors: Zhang Rui , Wang Zhongyang , Sun Haoze , Deng Lizhen , Zhu Hu
Published: July 2023

In this paper, a unified optimization model for medical image fusion based on tensor decomposition and the non-subsampled shearlet transform (NSST) is proposed. The model is based on the NSST method and the tensor decomposition method to fuse the high-frequency (HF) and low-frequency (LF) parts of two source images to obtain a mixed-frequency fused image. In general, we integrate low-frequency and high-frequency information from the perspective of tensor decomposition (TD) fusion. Due to the structural differences between the high-frequency and low-frequency representations, potential information loss may occur in the fused images. To address this issue, we introduce a joint static and dynamic guidance (JSDG) technique to complement the HF/LF information. To improve the result of the fused images, we combine the alternating direction method of multipliers (ADMM) algorithm with the gradient descent method for parameter optimization. Finally, the fused images are reconstructed by applying the inverse NSST to the fused high-frequency and low-frequency bands. Extensive experiments confirm the superiority of our proposed TDFusion over other comparison methods.
High Sensitivity and Wide Range Refractive Index Sensor Based on Surface Plasmon Resonance Photonic Crystal Fiber
Authors: Wang Fengmin , Wei Yong , Han Yanhong
Published: July 2023

In order to detect the refractive index (RI) of high refractive index materials such as trichlorobenzene and aniline in the near-infrared and mid-infrared spectra and expand the detection range of the refractive index, a surface plasmon resonance (SPR) photonic crystal fiber (PCF) sensor based on an elliptical sensing channel is proposed for high refractive index detection. The fiber core and the analyte channel are surrounded by two types of air holes with different sizes. When the surface plasmon resonance effect appears at the interface between the fiber core and the elliptical sensing layer, obvious resonance peaks appear in the near-infrared and mid-infrared bands. The full vector finite element method (FEM) is used to study the sensing characteristics of the sensor and the influence of structural parameters on the resonance peak. The results demonstrate that the sensor achieves detection in the refractive index range of 1.41–1.58, in the wavelength range of 1600–3200 nm. The average wavelength sensitivity is 9217.22 nm/RIU, and the refractive index resolution is 10.85 × 10−6 RIU. The proposed sensor realizes high refractive index detection in the near-infrared and mid-infrared bands, and obtains an ultra-wide detection range and higher sensitivity. The sensor has broad application prospects in chemical detection, biomedical sensing and other fields, and provides a theoretical reference for the design of a photonic crystal fiber surface plasmon resonance sensor.
An L-Shaped Three-Level and Single Common Element Sparse Sensor Array for 2-D DOA Estimation
Authors: Du Bo , Cui Weijia , Ba Bin , Xu Haiyun , Gao Wubin
Published: July 2023

The degree of freedom (DOF) is an important performance metric for evaluating the design of a sparse array structure. Designing novel sparse arrays with higher degrees of freedom, while ensuring that the array structure can be mathematically represented, is a crucial research direction in the field of direction of arrival (DOA) estimation. In this paper, we propose a novel L-shaped sparse sensor array by adjusting the physical placement of the sensors in the sparse array. The proposed L-shaped sparse array consists of two sets of three-level and single-element sparse arrays (TSESAs), which estimate the azimuth and elevation angles, respectively, through one-dimensional (1-D) spatial spectrum search. Each TSESA is composed of a uniform linear subarray and two sparse subarrays, with one single common element in the two sparse subarrays. Compared to existing L-shaped sparse arrays, the proposed array achieves higher degrees of freedom, up to 4Q1Q2+8Q1−5, when estimating DOA using the received signal covariance. To facilitate the correct matching of azimuth and elevation angles, the cross-covariance between the two TSESA arrays is utilized for estimation. By comparing and analyzing performance parameters with commonly used L-shaped and other sparse arrays, it is found that the proposed L-shaped TSESA has higher degrees of freedom and array aperture, leading to improved two-dimensional (2-D) DOA estimation results. Finally, simulation experiments validate the excellent performance of the L-shaped TSESA in 2-D DOA estimation.
Novel Multi-Parametric Sensor System for Comprehensive Multi-Wavelength Photoplethysmography Characterization
Authors: Lambert Cause Joan , Solé Morillo Ángel , da Silva Bruno , García-Naranjo Juan C. , Stiens Johan
Published: July 2023

Photoplethysmography (PPG) is widely used to assess cardiovascular health. However, its usage and standardization are limited by the impact of variable contact force and temperature, which influence the accuracy and reliability of the measurements. Although some studies have evaluated the impact of these phenomena on signal amplitude, there is still a lack of knowledge about how these perturbations can distort the signal morphology, especially for multi-wavelength PPG (MW-PPG) measurements. This work presents a modular multi-parametric sensor system that integrates continuous and real-time acquisition of MW-PPG, contact force, and temperature signals. The implemented design solution allows for a comprehensive characterization of the effects of the variations in these phenomena on the contour of the MW-PPG signal. Furthermore, a dynamic DC cancellation circuitry was implemented to improve measurement resolution and obtain high-quality raw multi-parametric data. The accuracy of the MW-PPG signal acquisition was assessed using a synthesized reference PPG optical signal. The performance of the contact force and temperature sensors was evaluated as well. To determine the overall quality of the multi-parametric measurement, an in vivo measurement on the index finger of a volunteer was performed. The results indicate a high precision and accuracy in the measurements, wherein the capacity of the system to obtain high-resolution and low-distortion MW-PPG signals is highlighted. These findings will contribute to developing new signal-processing approaches, advancing the accuracy and robustness of PPG-based systems, and bridging existing gaps in the literature.
An Exploratory Attitude and Belief Analysis of Ecotourists’ Destination Image Assessments and Behavioral Intentions
Authors: Harrill Rich , Zuñiga-Collazos Alexander , Castillo-Palacio Marysol , Padilla-Delgado Lina Marcela
Published: July 2023

Colombia is noteworthy as a biodiversity hotspot, featuring an extraordinary number of endemic orchids, birds, and butterflies. This exploratory study examined how the perceptions of destination image, considering the cognitive and affective image, can be a predictor or positive influencer of behavioral intentions of ecotourists through symmetric data analysis. The success of a birdwatching destination can be attributed more to the development of a positive overall image, by having a direct and strong influence on behavioral intentions, indirect effects such as affective image can also be identified such as intention to visit and intention to recommend. Using partial least squares (PLS), the author(s) analyzed 64 survey responses collected of rural areas from an invitation made to associations of professional birdwatchers, including a new 15-statement scale specialized on birdwatching as a result of personal interviews with tourism management professionals and entrepreneurs who are experts in birdwatching. The findings supported the reliability of the model, and symmetric analysis presented the higher influence of emotions and affections in increasing intentions of recommendation, considering birdwatching as based on personal relationships. Additionally, the cognitive image for the birders despite representing destination attributes did not have the same impact on behavioral intentions. Therefore, managers should develop positioning strategies based on the generation of emotions.
The Factors Affecting the Quality of the Temperature Vegetation Dryness Index (TVDI) and the Spatial–Temporal Variations in Drought from 2011 to 2020 in Regions Affected by Climate Change
Authors: Guo Yuchen , Han Liusheng , Zhang Dafu , Sun Guangwei , Fan Junfu , Ren Xiaoyu
Published: July 2023

The temperature vegetation dryness index (TVDI) is widely used for the monitoring of global or regional drought because of its strong drought-monitoring capabilities and ease of implementation. However, the temporal errors in the land surface temperature (LST) and normalized difference vegetation index (NDVI) can affect warm and cold edges, thus determining the quality of the TVDI, especially in regions affected by climate change, such as Shandong Province. This paper explores this issue in the region in 2011, using daily MODIS MOD09GA and MOD11A1 data products. For each image acquisition time, the warm and cold edges of the NDVI–LST were extracted based on the NDVI, derived from red and near-infrared reflectance data, and the LST, derived from the MOD11A1 dataset. Then, the variations in the warm and cold edges with the LST and NDVI were analyzed. Subsequently, the influence of warm and cold edges, based on the daily values of the temperature, NDVI and precipitation during the observed period, was assessed using a linear regression. The soil moisture (SM) data obtained from the Global Land Data Assimilation System (GLDAS) datasets and the crop water stress index (CWSI) obtained from the MOD16A2 products were used for the assessment. The spatial and temporal variations in drought in Shandong Province from 2011 to 2020 were measured based on Theil–Sen median trend analysis and the Mann–Kendall test. The results show that apparently random variations were evident in the temporal evolution of the slope of the warm edge, indicating that daily data were appropriate to determine the boundary of the warm edge. Daily data were also appropriate to determine the boundary of the cold edge in a similar way. Additionally, the temperature, NDVI and precipitation in this region affected by climate change had a negative correlation with the slope and a positive correlation with the intercept. The validation results show that there was a significant negative correlation between the observed TVDI and GLDAS soil moisture values (R2 > 0.62) in 12 scatter plots. Therefore, we deduced that the monthly or yearly TVDI product produced by the daily MODIS data has a higher precision than that produced by 8-day or monthly data in regions affected by climate change. The spatial and temporal variations show that the trend of slight and moderate droughts first increased and then decreased, and, in particular, some areas presented severe drought from 2011 to 2015. The results obtained in this study are important for the scheduling of irrigation and drought warnings.
Life Cycle Assessment of Current Portuguese Railway and Future Decarbonization Scenarios
Authors: Ramos da Silva Tiago , Moura Bruna , Monteiro Helena
Published: July 2023

Given the current EU decarbonization targets, the railway transport is a key player to boost mobility toward more sustainable transportation, as it is currently the cleanest high-volume mode of locomotion available. However, a study analyzing the life cycle environmental impact of the existing conventional Portuguese railway has never been performed. Aiming to address this research gap, this paper presents an attributional life cycle assessment (LCA) to quantify the environmental impacts of the Portuguese railway infrastructure and rolling stock, using the Douro line case study. Through the LCA methodology, the current setting (using electric and diesel rolling stock) and three scenarios of full-line electrification (considering 2019, 2030, and 2050 electricity mixes) were analyzed for hotspot identification and an outlook on EU-aligned long-term sustainability prospects. In the current scenario, railway operation accounts for 74% of the total carbon footprint, mostly due to the fuel use of diesel trains and the expended electricity of electric train and infrastructure operation. The total electrification of the line and rolling stock can reduce carbon emissions by 38%, 56%, and 63%, if the 2019, 2030, and 2050 electricity mixes are considered, respectively. Further reductions could also be achieved with on-site renewable energy generation and through future low-carbon construction work strategies.
Effects of Irrigation and Nitrogen Fertilizer on Soil Carbon Leaching in Cotton Fields in Arid Areas
Authors: Zhang Baoyue , Gao Zhijian , Zhi Jinhu , Bai Xinlu , Yang Lili , Xia Wenhao
Published: July 2023

In order to formulate a reasonable water input model for cotton fields in southern Xinjiang for scientific and rational fertilization, to reduce soil carbon leaching, and to improve soil carbon sequestration capacity, an undisturbed soil column leaching test was used to simulate the current field management method in the study area. Two methods, drip irrigation and flood irrigation, were set up, and three irrigation and three nitrogen fertilizer levels were used to carry out the undisturbed soil column leaching test. The results showed that the amount and mode of water and nitrogen input affected the distribution and leaching loss of organic carbon and inorganic carbon in the soil. When the nitrogen application rate increased from 270 kg·hm−2 to 450 kg·hm−2, the leaching loss of soluble organic carbon and soluble inorganic carbon increased significantly. When the water input increased from 6000 m3·hm−2 to 9000 m3·hm−2, the leaching loss of DOC and DIC increased significantly. The carbon leaching loss under drip irrigation was higher than that under flood irrigation. The leaching rates of DOC and DIC were fastest under the conditions of high water (9000 m3·hm−2) and high fertilizer (450 kg·hm−2). This shows that water and nitrogen input and irrigation methods are important factors affecting soil carbon leaching. In the case of excessive water input, long-term high-frequency irrigation is the main factor affecting carbon leaching.
Effects of Soybean–Corn Rotation on Crop Yield, Economic Benefits, and Water Productivity in the Corn Belt of Northeast China
Authors: Zhang Huiqi
Published: July 2023

The Corn Belt of Northeast China (CBNC) is the most important commercial grain base in China. However, long-term intensive cultivation has caused the productivity of black soil to decline. The sustainable development of corn and soybean is seriously threatened. Field experiments of a corn–soybean rotation were conducted to evaluate the crop yields, economic returns, and water productivity in the CBNC from 2017 to 2020. The field treatments included continuous soybean (CS), continuous corn (CC), soybean–corn (SC), and soybean–corn–corn (SCC). The total yield for 2017–2020 is compared using the equivalent yield of corn, indicating that the crop yield of the CC treatment was the highest and that of the CS treatment was the lowest. The crop yield of the CS treatment was 0.58-fold lower than that of the CC treatment. The 4-year total income of the treatments showed that the total and net revenue of the CC treatment was the highest. The 4-year total net income of the CS treatment was 0.66- and 0.72-fold lower compared with those of the SC and SCC treatments, respectively. There was no significant difference between the treatments of rotation. The crop water productivity (WPC) and biomass water productivity (WPB) of the CS treatment were the lowest, at 0.30- and 0.54-fold lower than those of the CC treatment in 2017–2020, respectively. The WPC and WPB of the CC treatment were the largest. If soybean–corn rotation was implemented in the CBNC, the SC treatment would be a better choice than the SCC treatment for the CBNC, and farmers would need to be subsidized at least USD 1047.5 ha−1 to equal the income from growing corn. In considering production, financial gains, and water productivity, the CC treatment was, as a result, still the best planting pattern for the CBNC under the test site’s conditions.
A Study on Smallholder Farmers’ Willingness to Sustain Cooperation with New Farmers—Analysis Based on the Perspective of Smallholder Farmers’ Satisfaction
Authors: Wu Liancui , Du Runjie , Liu Qiang
Published: July 2023

In the context of rural revitalization, it is important to promote the establishment of lasting cooperation between small farmers and new farmers to drive farmers to increase their income and achieve common prosperity. Based on the research data of 342 small farmers in six provinces, the article empirically analyzes the willingness of small farmers to continue cooperation with new farmers in the future from the perspective of satisfaction using an ordered logistic model. The research results show that small farmers’ satisfaction with the benefit linkage model, with the benefit distribution, and with benefit dispute handling positively and significantly influence small farmers’ willingness to continue cooperation with new farmers in the future. For every 1% increase in satisfaction with the benefit linkage model, the probability of continuing to cooperate with new farmers in the future increases by 9.40%, and for every 1% increase in satisfaction with the benefit distribution and satisfaction with benefit dispute handling, the probability of continuing to cooperate with new farmers increases by 7.30% and 9.40%, respectively. Accordingly, this paper puts forward policy suggestions such as respecting the choice of interest linkage model of small farmers, improving the benefit distribution mechanism, and handling cooperation disputes reasonably, in order to improve the satisfaction of small farmers’ cooperation, promote the construction of lasting cooperation between small farmers and new farmers, and build a rural community of interest.
Synergistic Effect of Benincasa hispida Peel Extract and KI on the Corrosion Inhibition of Mild Steel in HCl
Authors: Wang Qihui , Zhao Chongkang , Zhang Qi , Zhou Xing , Yan Zhitao , Sun Yi , Sun Da , Li Xueming
Published: July 2023

This study employed Benincasa hispida peel as a raw material for the preparation of Benincasa hispida peel extract (BHPE) via hot water extraction and freeze-drying processes. The synergistic effect of BHPE and KI on the corrosion inhibition of mild steel in 1 M HCl was investigated. The compositional analysis shows that BHPE consists mainly of a mixture of sugars, characterized by a high density of hydroxyl groups and unsaturated functional groups, characteristic of highly effective corrosion inhibitors. Electrochemical experiments and surface analysis show that the composite of BHPE and KI can effectively provide protection to mild steel. Moreover, the synergistic coefficient of BHPE and KI under various concentration conditions was greater than 1, and the highest corrosion inhibition efficiency was 94.4%. In addition, the corrosion inhibition mechanism of BHPE was thoroughly investigated using quantum chemistry (QC) and molecular dynamics simulation (MDS).
An Employee Competency Development Maturity Model for Industry 4.0 Adoption
Authors: Treviño-Elizondo Bertha Leticia , García-Reyes Heriberto
Published: July 2023

Industry 4.0 (I4.0) is challenging for organizations, as workers lack digital competencies, and research on new roles is limited. Additionally, existing models for its adoption focus on technology incorporation, process improvement, and organizational transformation. Therefore, the opportunity exists for designing a new model that emphasizes developing employees’ competencies. A systematic literature review was conducted regarding existing models for I4.0 adoption and the desired worker competencies. After examining the gap in the current models and the categorization of their main elements, a new maturity model (MM) for I4.0 adoption, based on the development of employees’ competencies, is proposed. The MM helps practitioners and researchers assess an organization’s I4.0 adoption level in order to improve future actions. A validation process for the MM was implemented through the Delphi method. Additionally, a roadmap to guide workforce development is presented, which considers the digital challenges face by employees in advancing a strategic I4.0 adoption. The proposed roadmap allows for depicting new deployment strategies aligned with digital trends and employees’ commitments to sustaining the implementation efforts. This research recognizes talent, organizational culture, and communication plans as key elements for defining actions for developing the skills and competencies required for embracing the I4.0 enabling technologies.
Preference of Major Stored Product Insects in Fortified Rice with Basil
Authors: Lampiri Evagelia , Agrafioti Paraskevi , Rumbos Christos I. , Athanassiou Christos G.
Published: July 2023

As the world’s population grows, the needs for feeding it follow the same path. Considering these conditions, ensuring the quantity and quality of raw materials, such as cereals, seems imperative. Stored product insects are responsible for significant losses in the post-harvest stages of agricultural products and the available chemical methods for their control are decreasing, due to their negative impact on the environment and humans. To this end, the evaluation of the efficacy of non-chemical methods for the management of storage insects is crucial. In the present study, we conducted two trials of choice tests based on rice fortified with basil to determine its potential as a non-chemical repellent of stored product insects. In the first trial, we evaluated the repellent activity of rice enriched with basil on adults of Sitophilus oryzae, Rhyzopertha dominica, Tribolium castaneum and Oryzaephilus surinamensis, as well as on T. castaneum larvae. In the second trial, the same procedure was followed with deltamethrin-treated rice fortified with basil. The results of the first trial showed that for most of the insect species tested, the rice fortified with basil was moderately repellent, while for O. surinamensis, it was attractive. Surprisingly, in the second trial, the deltamethrin-treated rice fortified with basil showed a repellent effect on O. surinamensis adults and T. castaneum larvae, while no repellency was observed for the rest of insect species examined. Observation time was not significant for any of the insect species, combinations and trials, with the exception of the rice fortified with basil vs. Blanc combination in O. surinamensis. Our findings suggest that the use of deltamethrin-treated rice fortified with basil was effective as a repellent for O. surinamensis adults and T. castaneum larvae.
An HBIM Integrated Approach Using Non-Destructive Techniques (NDT) to Support Energy and Environmental Improvement of Built Heritage: The Case Study of Palazzo Maffei Borghese in Rome
Authors: Cornaro Cristina , Bovesecchi Gianluigi , Calcerano Filippo , Martinelli Letizia , Gigliarelli Elena
Published: July 2023

Built heritage energy and environmental improvement is increasingly being recognised as a key driver in the fight against climate change. This effort necessitates a thorough understanding of the building to guide the selection of technologies and design solutions. To have a picture of the buildings’ characteristics and behaviour that is as complete as possible, in situ studies are essential, although the complexities and heterogeneities of historical buildings make these analyses still challenging, especially in professional practice. To address these issues, the paper describes an integrated approach including the field application of Non-Destructive Techniques (namely, Heat Flow Meter measurements, Infrared thermographies and indoor environmental monitoring) within a Heritage Building Information Modelling process. This interdisciplinary/integrated approach fostered the use of each type of analysis’s results to guide the subsequent analyses and incrementally deepen the knowledge of the building. The methodology was applied to a case study in the historical city centre of Rome in Italy. The analyses will be of service in developing dynamic building performance simulations to support the design of the interventions.
Emerging Themes for Digital Accessibility in Education
Authors: Prado Bruna de Brito , Gobbo Junior José Alcides , Bezerra Barbara Stolte
Published: July 2023

The aim of this research is to verify gaps in the research into digital accessibility in education by conducting a systematic review of articles featuring the following terms: “digital accessibility”, “education”, “educational”, and “teaching”. It was found that the architectonics and attitudinal dimensions could not be encompassed in the typologies of articles resulting from the systematic review. It was necessary to search for index, indicator, and dimensions to evaluate digital education, including attitudinal dimensions—which refers to stigma and discrimination that people with disabilities face.