bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Composite Hydrogel Material for Sodium Removal and Potassium Provision
Authors: Huang Jin , Gotoh Takehiko , Nakai Satoshi , Ueda Akihiro
Published: August 2023

Sodium ions are commonly found in natural water sources, and their high concentrations can potentially lead to adverse effects on both the water sources and soil quality. In this study, we successfully synthesized potassium polyacrylate (KMAA) hydrogel through free radical polymerization and evaluated its capability to remove sodium ions from and supply potassium ions to aqueous solutions. To assess its performance, inductively coupled plasma emission spectroscopy (ICP) was employed to analyze the sodium ion removal capacity and potassium ion exchange capability of the KMAA hydrogel at various initial sodium ion concentrations and pH values. The results demonstrated that the KMAA hydrogel exhibited remarkable efficiency in removing sodium ions and providing potassium ions. At pH 7, the maximum adsorption capacity for sodium ions was measured at 70.7 mg·g−1. The Langmuir model, with a correlation coefficient of 0.98, was found to be more suitable for describing the adsorption process of sodium ions. Moreover, at pH 4, the maximum exchange capacity for potassium ions reached 243.7 mg·g−1. The Freundlich model, with a correlation coefficient of 0.99, was deemed more appropriate for characterizing the ion exchange behavior of potassium ions. In conclusion, the successfully synthesized KMAA hydrogel demonstrates superior performance in removing sodium ions and supplying potassium ions, providing valuable insights for addressing high sodium ion concentrations in water sources and facilitating potassium fertilizer supply.
All-Factor Average Method of Reserve Parameters with Crude Oil Volume and Mass Constraints
Authors: Zhang Doujuan , Guo Haimin , Wu Yuyan , Chen Cunyuan , Li Ao , Zhang Jinyan , Wang Yonggang
Published: August 2023

In order to make the average value of each reserve parameter of a set of oil reserves more representative, this paper puts forward the all-factor average method of reserve parameters with crude oil volume and mass constraints. In the first step, the two constraint methods of crude oil volume and mass are adopted to calculate the average value of various parameters of the total items. The weight coefficient when the parameter is averaged is, respectively, the partial derivative of the volume or mass reserve calculation formula with respect to the parameter. Compared with the original calculation results, the average of their parameters all show a shift towards values with a significant share of reserves, especially effective porosity, oil saturation, and crude oil volume factor. The all-factor average method considers a more comprehensive set of factors than the original method. Therefore, each new average parameter should also be much more representative. Since the current reserve specification stipulates that each parameter needs to retain a certain number of decimal places, there inevitably is some carry error between the reserve results calculated by the parameters of the total items and the accumulated reserves of each unit. The second step is to select the optimal average value of each reserve parameter by using the full permutation combination selection method to reduce the carry error. A set of parameters that minimizes the sum of squared relative errors of crude oil volume and mass reserves is selected using the full permutation combination selection method, which is the optimal selection of the average value of the total set of items. Compared with the original method, the full permutation combination selection method can effectively reduce the carry error.
Atomization of Borosilicate Glass Melts for the Fabrication of Hollow Glass Microspheres
Authors: Helling Tobias , Reischl Florian , Rosin Andreas , Gerdes Thorsten , Krenkel Walter
Published: August 2023

Direct atomization of a free-flowing glass melt was carried out using a high-speed flame with the aim of producing tiny, self-expanding glass melt droplets to form hollow glass microspheres. Atomization experiments were carried out using a specially adapted free-fall atomizer in combination with a high-power gas burner to achieve sufficient temperatures to atomize the melt droplets and to directly expand them into hollow glass spheres. In addition, numerical simulations were carried out to investigate non-measurable parameters such as hot gas velocities and temperatures in the flame region by the finite volume-based software Star CCM+® (v. 2022.1.1), using the Reynolds-Averaged Navier–Stokes (RANS) turbulence and the segregated flow model. To calculate the combustion process, the laminar flamelet method was used. The experiments and simulations indicated that a maximum gas velocity of about 170 m/s was achieved at the point of atomization in the flame. The particle size distribution of the atomized glass droplets, either solid or hollow, ranged from 2 µm to 4 mm. Mean particle sizes in the range of 370 µm to 650 µm were highly dependent on process parameters such as gas velocity. They were in good agreement with theoretically calculated median diameters. The formation of hollow glass microspheres with the proposed concept could be demonstrated. However, only a small fraction of hollow glass spheres was found to be formed. These hollow spheres had diameters up to 50 µm and, as expected, a thin wall thickness.
Application of Edible Insect Flour as a Novel Ingredient in Fortified Snack Pellets: Processing Aspects and Physical Characteristics
Authors: Wójtowicz Agnieszka , Combrzyński Maciej , Biernacka Beata , Oniszczuk Tomasz , Mitrus Marcin , Różyło Renata , Gancarz Marek , Oniszczuk Anna
Published: August 2023

The aim of the study was to develop a suitable recipe for wheat-corn snack pellets fortified with insect flour addition and to evaluate the relevant processing aspects and physical characteristics of the developed products. Varying levels of edible insect flour (10, 20, and 30%) were incorporated into a new type of fortified snack pellet as a half product for further expansion. The effects of the edible insect flour level, as well as processing variables (moisture levels 32, 34, 36% and screw speeds 60, 80, 100 rpm), were analyzed on the extrusion stability and on selected snack pellets’ physical properties processed via single-screw extrusion cooking. This research indicated that an increasing amount of edible insect flour significantly affected the processing output and energy consumption. The incorporation of insect flour in blends significantly increased the specific mechanical energy and efficiency of pellet extrusion, especially at a high moisture level and high screw speed during processing. Moreover, the addition of insect flour in the snack pellets significantly reduced the bulk density and pellet durability. Principal component analysis confirmed that approximately 76.5% of the data variance was explained by the first two principal components, and significant correlations were noted between the properties of the tested snack pellets. It can be concluded that up to 20% of insect flour in newly developed extruded snack pellet formulations has no negative effect on processing and physical properties.
Review on Waste-to-Energy Approaches toward a Circular Economy in Developed and Developing Countries
Authors: Rezania Shahabaldin , Oryani Bahareh , Nasrollahi Vahid Reza , Darajeh Negisa , Lotfi Ghahroud Majid , Mehranzamir Kamyar
Published: August 2023

International interest in using waste-to-energy (WtE) technology toward a circular economy (CE) is developing, spurred by environmental challenges such as inefficient solid waste dumping, pollution, and resource depletion. Incineration, pyrolysis, gasification, landfill, and anaerobic digestion are standard WtE technologies. Although these methods have been used for many decades, all countries try to implement the best plans based on their technologies and capacities. Therefore, an up-to-date comprehensive study is needed to evaluate the existing barriers to draw a logical roadmap for WtE to CE. Therefore, this review addresses the recent policies adopted by developed and developing countries for WtE technologies. Based on the findings, most countries seek the most cost-effective and environmentally sustainable pathways in WtE to CE; meanwhile, international collaboration and governmental support are needed to overcome the existing barriers and find a sustainable and economically viable plan for both developed and developing countries in the future.
Effect of High-Voltage Electric Field on Thawing Kinetics and Quality Characteristics of Frozen Beef
Authors: Tian Yu , Ding Changjiang
Published: August 2023

This study investigated the impact of high-voltage electric field (HVEF) thawing technology on the thawing rate, water retention characteristics, microstructure, and nutritional composition of thawed beef. Compared with the control group, in which thawing occurred under natural conditions, the experimental group, in which beef was thawed under HVEF (12 kV, 16 kV, 20 kV, 24 kV, 28 kV), showed a significantly shorter thawing time, and the higher the voltage was, the faster the thawing rate. The total loss rate of thawed beef reached its minimum value of (54.2 ± 0.62) % at 28 kV, and the water retention of the experimental group was significantly better than that of the control group (p < 0.05). Therefore, it can be concluded that HVEF thawing enhances the water retention ability of beef. In a color comparison, it was evident that the color of the beef thawed by HVEF was significantly better than that of the control group. The results of scanning electron microscopy (SEM) indicated that thawing beef by HVEF can reduce the damage to the myofibril structure. Low-field nuclear magnetic resonance (LF-NMR) showed that beef thawed by HVEF had a significantly increased bound water content. According to the determination of malondialdehyde content, beef thawed by HVEF had a reduced degree of lipid oxidation; the content at 16 kV was 2.4 mg/kg, and the degree of lipid oxidation was the lowest. Fourier transform infrared (FTIR) spectroscopy analysis revealed that the absorption peak positions of the beef samples did not show significant changes under different conditions. However, the absorption peak intensity in the experimental group was generally higher than that in the control group. Examination of the protein secondary structure via infrared spectroscopy revealed that, compared with the control group, HVEF thawing transformed the proteins from an ordered structure to a disordered structure. The increase in disordered structure reduced the fiber gap of the sample and improved the water retention of the beef. The above experimental results indicate that HVEF thawing can improve the water-holding capacity of the sample and reduce the thawing damage to the quality of the sample.
Adomian Decomposition, Firing Change Process Analysis and Synchronous Control of Fractional-Order Hindmarsh–Rose Neurons in Electromagnetic Field
Authors: Lei Tengfei , Fu Haiyan , Zang Hongyan , Huang Lili , Sun Wenqiang
Published: August 2023

In this paper, based on integer-order Hindmarsh–Rose (HR) neurons under an electric field, the fractional-order model is constructed, and the nonlinear term is decomposed by the Adomian decomposition method, and the numerical solution of the system is obtained. The firing behavior of the neuron model is analyzed by using a phase diagram, interspike interval (ISI) bifurcation diagram, sample entropy (SE) complexity, and largest Lyapunov exponent (LLE). Based on the sliding mode control theory, a chaos synchronization controller of the system is designed. Matlab simulation results show that the controller is realizable and effective, and also has the characteristic of fast response, which provides a reference for the control and application of a memristor neural network system.
Customized Wrist Immobilization Splints Produced via Additive Manufacturing—A Comprehensive Evaluation of the Viable Configurations
Authors: Sala Francesca , D’Urso Gianluca , Giardini Claudio
Published: August 2023

Orthopedic splints are external medical devices designed to support and protect the functions of the human musculoskeletal system from pathological conditions or traumatic events. Tailoring these medical solutions to the morphology of the patient’s limb is essential to ensure a correct and rapid rehabilitation pathway. Although traditional splinting techniques might achieve a unique fit, the procedures are highly dependent on the skill and experience of the medical operator, affecting the quality of the care treatment. In response to the drawbacks associated with traditional splinting techniques, the present article proposed an innovative and structured methodology to manufacture customized wrist immobilization splints, prioritizing simplicity and user-friendliness in fabrication activities. The customized splint manufacturing was based on the integration of reverse engineering (RE) and additive manufacturing (AM) techniques. The research designed a baseline model of a wrist splint, varying over different thickness values and manufacturing materials (ABS, nylon, PLA, PC, PA6-GF25, PA6-CF20). For every splint model, the production times and material costs were assessed. Technical tests were performed via finite element analysis (FEA). The conducted analysis and the resulting charts empower medical operators to select the most appropriate solution, ensuring a well-informed and effective decision-making approach.
Assessing Greenhouse Gas Emissions and Energy Efficiency of Four Treatment Methods for Sustainable Food Waste Management
Authors: Liu Xiaoming , Li Si , Chen Wenhao , Yuan Huizhou , Ma Yiguan , Siddiqui Muhammad Ahmar , Iqbal Asad
Published: August 2023

Food waste (FW) increases with urbanization and population growth, which puts pressure on the treatment system, causing a variety of harmful impacts on the environment. Proper FW treatment is imperative for ecological integrity and public health. Even though FW treatment is an extensively studied topic, the sustainable FW treatment considering holistic-lifecycle-based environmental impacts has rarely been evaluated. This study addresses this gap through a comprehensive analysis of various FW treatment methods, including co-treatment with sewage, anaerobic digestion, incineration, and aerobic composting. The impacts of greenhouse gas (GHG) emission and energy use efficiency are assessed by analyzing diverse FW treatment methods in Shenzhen, China. The study indicates that FW addition to sewage does not adversely affect the current sewage treatment plant, but benefits GHG avoidance and energy recovery. Compared with the other FW treatment methods, FW anaerobic digestion avoids the most GHG emissions with −71.3 kg CO2 eq/FU and recovers the most energy with −223 kWh/FU, followed by FW co-treated with sewage. The energy conversion efficiency of the combined heat and power (CHP) unit greatly affects FW incineration, while energy consumption in incineration and anaerobic digestion (AD) process is relatively minor. Perturbation analysis pinpoints key parameters influencing outcomes, including CHP efficiency, GHG emission factor of local electricity, and chemical oxygen demand (COD) in FW with ratios of −13~−0.942, −0.518~0.22, and −13~1.01, respectively, that should be given special attention. This study sheds light on sustainable FW management strategies, not only in China but also transferrable to regions confronting similar challenges. Advocating ecologically balanced and resource-efficient approaches, the study aligns with broader aims of fostering sustainable development.
Chan Gong’an and the “Flexible Method”: A Study on Xuedou Chongxian’s Classic Eulogies and Its Influence on Poetics
Authors: Fu Rongrong
Published: August 2023

This paper argues that as poetics in the Song Dynasty developed, the thinking mode and methods of written expression in Chan Buddhism provided a theoretical reference and creative practical experience for the formation of poetic theories. This point is particularly evident in the formation of the “flexible method”, which was a key theory in poetics of the Song Dynasty. The theory comprises three layers of meaning: it advocates respecting forms, changing the meaning of those forms, and retaining the inherent grace of the forms through a natural and fluent syntax and rhetoric of “defamiliarization”. This theory was highly mature in the writing of Lv Benzhong of the Southern Song Dynasty. Xuedou Chongxian (980–1052), a sixth-generation Chan Buddhist at Xuedou Temple, made a vital contribution to its development, which is highlighted by studying the “Hundred Classic Eulogies”. Xuedou Chongxian initially constructed the connotation and system of the theory of the “flexible method” in both theoretical and practical aspects. His theory of poetics is rooted in the ways of thinking and cultivating of the Yunmen sect. He incorporated his dual identity as a senior monk of the Yunmen School and a poet. He inherited Guanxiu’s view of poetry and the Chan concept of Shitou Xiqian and Zhimen Guangzuo, which greatly impacted the literati of the Northern Song Dynasty and provided a conceptual basis for maturing and improving the “flexible method” theory. Therefore, Xuedou Chongxian’s value in the theoretical construction of the “flexible method” should not be ignored.
Flesh, Body, World: Michel Henry on Incarnation
Authors: Scruggs Jonathan
Published: August 2023

Henry tirelessly insists that all flesh is an invisible, radically immanent, impressional material in which life arrives in itself. But this raises a theological problem: is the material, visible body of Christ to be excluded from what we understand by incarnation? To answer this and related questions, the problematic of the duplicity of appearing—the appearing of life and the appearing of the world—must be clarified. It is precisely through an analysis of flesh that Henry seeks to establish a rapport between the two modes of appearing, so a study of the flesh should allow us to articulate in one stroke an account of our access to the world and the thingly body. Against a simplistic reading that claims that, for Henry, an unbridgeable gorge separates life and the world, the flesh and the body, I argue that the objective, visible body is real, but that its reality is founded on the more immediate reality of the flesh. I use the results of this inquiry to argue further for two distinct but related senses of the concept “world”, one which names a phenomenological reality and another that picks out an ideological aberration endemic to modernity. While the flesh opens up the reality of the former, the latter is an imaginary and impossible world.
“Maybe I Need Christ or Maybe I Just Need Me”: Functions of Religion among Young Black Members of the LGBTQIA Community in the United States
Authors: Barnes Sandra Lynn
Published: August 2023

This qualitative study examines the functions of religion for a group of 76 young Black members of the LGBTQIA community ages 18–30 years old based on the question: What are some of the functions of religion that make continued congregational involvement viable for members of this community? Emerging adulthood theory suggests that late adolescence is a period of self-discovery and societal critique. To my knowledge, this theory has not been used to study the religious experiences of young Black sexual minorities. Content analysis shows the functions of religion as a controlling mechanism during childhood, a conflict mechanism during teen years, and religion/spirituality as a cathartic mechanism during late adolescence.
A Comprehensive Approach to Assess the Impact of Agricultural Production Factors on Selected Ecosystem Services in Poland
Authors: Bojar Waldemar , Żarski Wojciech , Kuśmierek-Tomaszewska Renata , Żarski Jacek , Baranowski Piotr , Krzyszczak Jaromir , Lamorski Krzysztof , Sławiński Cezary , Mattas Konstadinos , Staboulis Christos , Natos Dimitrios , Koç Ahmet Ali , Bayaner Ahmet , Ojeda Roldán Álvaro , Parra Rivero Obdulia
Published: August 2023

The conservation of environmental resources is aimed at ensuring the continuity of ecosystem services for future generations and maintaining ecosystem integrity. Given the extensive reliance of agriculture on the environment, it is crucial to identify factors that impact the quality of ecosystem services (ESs), which can be regulated at large and heterogeneous national or European scales. This research, conducted within the Polish use case of the AGRICORE project, aims to demonstrate the feasibility of establishing indicators depicted in three ES categories, which can be shaped under the actions of the Common Agricultural Policy (CAP). The study was conducted based on national sources, mostly the database of the Central Statistical Office. The analyses of regression showed a significant impact of selected agricultural productivity factors on the key performance indicators (KPIs) assessing the level of selected ESs. The yield of cereal grains, which quantitatively expresses the potential of current crop production, depended to the greatest extent (r = 0.81) on a comprehensive indicator of the agricultural production space suitability, as well as on the rise of the level of nitrogen fertilization (r = 0.68), and also on the reduced share of permanent grassland in the agricultural area (r = −0.53). It was proved that in territorial units, in which the level of nitrogen fertilization per 1 ha was greater, the share of soils with favorable pH > 5.5 was also greater. The gross nitrogen balance had a positive and significant correlation with the level of investment subsidies (r = 0.86), the share of agricultural land in the total area (r = 0.67), and the level of nitrogen fertilization (r = 0.66). Notably, there were positive correlations between the level of environmental subsidies and the increase in forestation (r = 0.68) and also between air quality and the share of cereals in the sowing structure (r = 0.86). Additionally, the impact of agricultural productivity factors on cultural eco-services was found, e.g., the share of ecological land had a positive impact on the number of natural monuments, the area of nature reserves, the number of agritourists, and agritourism nights, while the share of cereals in the sowing structure negatively correlated with the most of analyzed cultural indicators. These results are useful for the development of a module for the ABM model that employs the desired environmental parameters to provide different assessments of the impact of selected agricultural productivity factors and ecosystem services on the economic farm status.
Improving the Potential of Coniferous Forest Aboveground Biomass Estimation by Integrating C- and L-Band SAR Data with Feature Selection and Non-Parametric Model
Authors: Hu Yifan , Nie Yonghui , Liu Zhihui , Wu Guoming , Fan Wenyi
Published: August 2023

Forests play a significant role in terrestrial ecosystems by sequestering carbon, and forest biomass is a crucial indicator of carbon storage potential. However, the single-frequency SAR estimation of forest biomass often leads to saturation issues. This research aims to improve the potential for estimating forest aboveground biomass (AGB) by feature selection based on a scattering mechanism and sensitivity analysis and utilizing a non-parametric model that combines the advantage of dual-frequency SAR data. By employing GF-3 and ALOS-2 data, this study explores the scattering mechanism within a coniferous forest by using results of target decomposition and the pixel statistics method. By selecting an appropriate feature (backscatter coefficients and polarization parameters) and using stepwise regression models and a non-parametric model (the random forest adaptive genetic algorithm (RF-AGA)), the results revealed that the RF-AGA model with feature selection exhibited excellent AGB estimation performance without obvious saturation (RMSE = 10.42 t/ha, R2 = 0.93, leave-one-out cross validation). The σHV, σVH, Pauli three-component decomposition, Yamaguchi three-component decomposition, and VanZyl3 component decomposition of thee C-band and σHV, σVH,σHH, Yamaguchi three-component decomposition, and VanZyl3 component decomposition of the L-band are suited for estimating the AGB of coniferous forests. Volume scattering was the dominant mechanism, followed by surface scattering, while double-bounce scattering had the smallest proportion. This study highlights the potential of investigating scattering mechanisms, sensitivity factors, and parameter selection in the C- and L-band SAR data for improved forest AGB estimation.
A Modified Range Doppler Algorithm for High-Squint SAR Data Imaging
Authors: Guo Yanan , Wang Pengbo , Men Zhirong , Chen Jie , Zhou Xinkai , He Tao , Cui Lei
Published: August 2023

The high-squint airborne Synthetic Aperture Radar (SAR) has the ability to detect the target area flexibly, and the detection swath is significantly increased compared with the side-looking SAR system. Therefore, it is of great significance to carry out research on high-precision imaging methods for high-squint airborne SAR. However, the high-squint SAR echoes have large Range Cell Migration (RCM), resulting in severe range–azimuth coupling and strong spatial variation. In this paper, a Modified Range Doppler Algorithm (MRDA) is proposed to cope with these effects introduced by the significant RCM in high-squint airborne SAR imaging. The bulk compensation preprocessing is first adopted to remove the considerable RCM and severe cross-coupling in a two-dimensional frequency domain. Then, Non-Linear Chirp Scaling (NLCS) in the range direction is utilized to equalize the range-variant chirp rate caused by the residual RCM and coupling and, therefore, the consistent range phase compensation can be fulfilled in range frequency domain. The modified correlation processing is executed to compensate the residual Doppler phase modulation, the residual RCM and the range-variant cubic phase modulation, which guarantees the characteristics of high efficiency and high precision. The simulations have demonstrated that the MRDA can focus the SAR echoes with large squint angles more effectively than the algorithms based on the Linear Range Walk Correction (LRWC) method.
Analysis of Regional Ambient Seismic Noise in the Chukchi Sea Area in the Arctic Based on OBS Data from the Ninth Chinese National Arctic Scientific Survey
Authors: Li Qianqian , Liu Yaxin , Xing Lei , Han Xiao , Lin Yuzhao , Zhang Jin , Zhang Hongmao
Published: August 2023

Ambient noise plays a crucial role in influencing the observation quality at seismic stations. By studying the distribution patterns of ambient noise, we can gain initial insights into the noise conditions within a specific research area. This paper investigates the properties of ambient noise in different frequency bands under environmental settings in the Chukchi Sea region, utilizing data collected from ocean bottom seismometers (OBSs) deployed during the Ninth Chinese National Arctic Scientific Survey. The probability density function (PDF) method is used to reveal the distinctive features of ambient noise. In addition, by comparing the crowed number values of ambient noise in the Chukchi Sea area with the global new low-noise model (NLNM) and new high-noise model (NHNM), a more comprehensive understanding of the patterns, distribution characteristics, and sources of ambient noise in the Arctic Chukchi Sea area is gained. The study suggests that the overlying sea ice in the Arctic Chukchi Sea area can suppress the microseismic band ambient noise, and the overall level of ambient noise in the Chukchi Sea area lies between the land seismic ambient noise level and the ambient noise level in the middle- and low-latitude sea areas. Meanwhile, an abnormal power spectrum caused by different levels of natural earthquakes is observed. This study fills the gap by using seafloor seismic instruments to investigate ambient noise in the Chukchi Sea area.
A Novel Adaptively Optimized PCNN Model for Hyperspectral Image Sharpening
Authors: Xu Xinyu , Li Xiaojun , Li Yikun , Kang Lu , Ge Junfei
Published: August 2023

Hyperspectral satellite imagery has developed rapidly over the last decade because of its high spectral resolution and strong material recognition capability. Nonetheless, the spatial resolution of available hyperspectral imagery is inferior, severely affecting the accuracy of ground object identification. In the paper, we propose an adaptively optimized pulse-coupled neural network (PCNN) model to sharpen the spatial resolution of the hyperspectral imagery to the scale of the multispectral imagery. Firstly, a SAM-CC strategy is designed to assign hyperspectral bands to the multispectral bands. Subsequently, an improved PCNN (IPCNN) is proposed, which considers the differences of the neighboring neurons. Furthermore, the Chameleon Swarm Optimization (CSA) optimization is adopted to generate the optimum fusion parameters for IPCNN. Hence, the injected spatial details are acquired in the irregular regions generated by the IPCNN. Extensive experiments are carried out to validate the superiority of the proposed model, which confirms that our method can realize hyperspectral imagery with high spatial resolution, yielding the best spatial details and spectral information among the state-of-the-art approaches. Several ablation studies further corroborate the efficiency of our method.
A Collaborative Superpixelwise Autoencoder for Unsupervised Dimension Reduction in Hyperspectral Images
Authors: Yao Chao , Zheng Lingfeng , Feng Longchao , Yang Fan , Guo Zehua , Ma Miao
Published: August 2023

The dimension reduction (DR) technique plays an important role in hyperspectral image (HSI) processing. Among various DR methods, superpixel-based approaches offer flexibility in capturing spectral–spatial information and have shown great potential in HSI tasks. The superpixel-based methods divide the samples into groups and apply the DR technique to the small groups. Nevertheless, we find these methods would increase the intra-class disparity by neglecting the fact the samples from the same class may reside on different superpixels, resulting in performance decay. To address this problem, a novel unsupervised DR named the Collaborative superpixelwise Auto-Encoder (ColAE) is proposed in this paper. The ColAE begins by segmenting the HSI into different homogeneous regions using a superpixel-based method. Then, a set of Auto-Encoders (AEs) is applied to the samples within each superpixel. To reduce the intra-class disparity, a manifold loss is introduced to restrict the samples from the same class, even if located in different superpixels, to have similar representations in the code space. In this way, the compact and discriminative spectral–spatial feature is obtained. Experimental results on three HSI data sets demonstrate the promising performance of ColAE compared to existing state-of-the-art methods.
Estimating Maize Yield from 2001 to 2019 in the North China Plain Using a Satellite-Based Method
Authors: Hai Che , Wang Lunche , Chen Xinxin , Gui Xuan , Wu Xiaojun , Sun Jia
Published: August 2023

Maize is one of the main food crops and is widely planted in China; however, it is difficult to get timely and precise information on yields. Because of the benefits of remote sensing technology, satellite-based models (e.g., eddy covariance light use efficiency, EC-LUE) have a lot of potential for monitoring crop productivity. In this study, the gross primary productivity (GPP) of maize in the NCP was estimated using the EC-LUE model, and the GPP was subsequently transformed into yield using the harvest index. Specifically accounting for the spatiotemporal variation in the harvest index, the statistical yield and estimated GPP from the previous year were used to generate region-specific harvest indexes at the county scale. The model’s performance was assessed using statistical yield data. The results demonstrate that the increase in the total GPP in the summer maize-growing season in the NCP is directly related to the increase in the planting area, and the harvest index has significant heterogeneity in space, and the fluctuation in time is small, and the estimated yield can simulate 64% and 55%, respectively, of the variability in the yield at the county and city scales. The model also accurately captures the inter-annual changes in yield (the average absolute percentage errors are less than 20% for almost all years), but model performance varies by region. It performs better in continuous areas of maize-growing. The results from this study demonstrate that the EC-LUE model can be applied to estimate the yield from a variety of crops (other than winter wheat) and that it can be used in conjunction with a region-specific harvest index to track the production of large-scale crops.
A Novel Cross-Sensor Transfer Diagnosis Method with Local Attention Mechanism: Applied in a Reciprocating Pump
Authors: Wang Chen , Chen Ling , Zhang Yongfa , Zhang Liming , Tan Tian
Published: August 2023

Data-driven mechanical fault diagnosis has been successfully developed in recent years, and the task of training and testing data from the same distribution has been well-solved. However, for some large machines with complex mechanical structures, such as reciprocating pumps, it is often not possible to obtain data from specific sensor locations. When the sensor position is changed, the distribution of the features of the signal data also changes and the fault diagnosis problem becomes more complicated. In this paper, a cross-sensor transfer diagnosis method is proposed, which utilizes the sharing of information collected by sensors between different locations of the machine to complete a more accurate and comprehensive fault diagnosis. To enhance the model’s perception ability towards the critical part of the fault signal, the local attention mechanism is embedded into the proposed method. Finally, the proposed method is validated by applying it to experimentally acquired vibration signal data of reciprocating pumps. Excellent performance is demonstrated in terms of fault diagnosis accuracy and sensor generalization capability. The transferability of practical industrial faults among different sensors is confirmed.
Introducing a New Mobile Electroencephalography System and Evaluating Its Quality in Comparison to Clinical Electroencephalography
Authors: Samimisabet Paria , Krieger Laura , Nethar Themis , Pipa Gordon
Published: August 2023

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain’s electrical activity. Its applications include perception, learning, memory, language, decision making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named “DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24 channels, 24-bit resolution, up to 6 h of battery life, portability, and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine’s design and compares it with the lab-based EEG system “asalabTM” in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.
Laboratory Performance Evaluation of a Low-Cost Electrochemical Formaldehyde Sensor
Authors: Pei Zheyuan , Balitskiy Maxim , Thalman Ryan , Kelly Kerry E.
Published: August 2023

Formaldehyde is a known human carcinogen and an important indoor and outdoor air pollutant. However, current strategies for formaldehyde measurement, such as chromatographic and optical techniques, are expensive and labor intensive. Low-cost gas sensors have been emerging to provide effective measurement of air pollutants. In this study, we evaluated eight low-cost electrochemical formaldehyde sensors (SFA30, Sensirion®, Staefa, Switzerland) in the laboratory with a broadband cavity-enhanced absorption spectroscopy as the reference instrument. As a group, the sensors exhibited good linearity of response (R2 > 0.95), low limit of detection (11.3 ± 2.07 ppb), good accuracy (3.96 ± 0.33 ppb and 6.2 ± 0.3% N), acceptable repeatability (3.46% averaged coefficient of variation), reasonably fast response (131–439 s) and moderate inter-sensor variability (0.551 intraclass correlation coefficient) over the formaldehyde concentration range of 0–76 ppb. We also systematically investigated the effects of temperature and relative humidity on sensor response, and the results showed that formaldehyde concentration was the most important contributor to sensor response, followed by temperature, and relative humidity. The results suggest the feasibility of using this low-cost electrochemical sensor to measure formaldehyde concentrations at relevant concentration ranges in indoor and outdoor environments.
Smartphone- and Paper-Based Delivery of Balance Intervention for Older Adults Are Equally Effective, Enjoyable, and of High Fidelity: A Randomized Controlled Trial
Authors: Lugade Vipul , Torbitt Molly , O’Brien Suzanne R. , Silsupadol Patima
Published: August 2023

Home-based rehabilitation programs for older adults have demonstrated effectiveness, desirability, and reduced burden. However, the feasibility and effectiveness of balance-intervention training delivered through traditional paper-versus novel smartphone-based methods is unknown. Therefore, the purpose of this study was to evaluate if a home-based balance-intervention program could equally improve balance performance when delivered via smartphone or paper among adults over the age of 65. A total of 31 older adults were randomized into either a paper or phone group and completed a 4-week asynchronous self-guided balance intervention across 12 sessions for approximately 30 min per session. Baseline, 4-week, and 8-week walking and standing balance evaluations were performed, with exercise duration and adherence recorded. Additional self-reported measures were collected regarding the enjoyment, usability, difficulty, and length of the exercise program. Twenty-nine participants completed the balance program and three assessments, with no group differences found for any outcome measure. Older adults demonstrated an approximately 0.06 m/s faster gait velocity and modified balance strategies during walking and standing conditions following the intervention protocol. Participants further self-reported similar enjoyment, difficulty, and exercise effectiveness. Results of this study demonstrated the potential to safely deliver home-based interventions as well as the feasibility and effectiveness of delivering balance intervention through a smartphone-based application.
Effects of Data Augmentation on the Nine-Axis IMU-Based Orientation Estimation Accuracy of a Recurrent Neural Network
Authors: Choi Ji Seok , Lee Jung Keun
Published: August 2023

The nine-axis inertial and measurement unit (IMU)-based three-dimensional (3D) orientation estimation is a fundamental part of inertial motion capture. Recently, owing to the successful utilization of deep learning in various applications, orientation estimation neural networks (NNs) trained on large datasets, including nine-axis IMU signals and reference orientation data, have been developed. During the training process, the limited amount of training data is a critical issue in the development of powerful networks. Data augmentation, which increases the amount of training data, is a key approach for addressing the data shortage problem and thus for improving the estimation performance. However, to the best of our knowledge, no studies have been conducted to analyze the effects of data augmentation techniques on estimation performance in orientation estimation networks using IMU sensors. This paper selects three data augmentation techniques for IMU-based orientation estimation NNs, i.e., augmentation by virtual rotation, bias addition, and noise addition (which are hereafter referred to as rotation, bias, and noise, respectively). Then, this paper analyzes the effects of these augmentation techniques on estimation accuracy in recurrent neural networks, for a total of seven combinations (i.e., rotation only, bias only, noise only, rotation and bias, rotation and noise, and rotation and bias and noise). The evaluation results show that, among a total of seven augmentation cases, four cases including ‘rotation’ (i.e., rotation only, rotation and bias, rotation and noise, and rotation and bias and noise) occupy the top four. Therefore, it may be concluded that the augmentation effect of rotation is overwhelming compared to those of bias and noise. By applying rotation augmentation, the performance of the NN can be significantly improved. The analysis of the effect of the data augmentation techniques presented in this paper may provide insights for developing robust IMU-based orientation estimation networks.
Validation of a Robotic Testbench for Evaluating Biomechanical Effects of Implant Rotation in Total Knee Arthroplasty on a Cadaveric Specimen
Authors: Wilhelm Nikolas , von Deimling Constantin , Haddadin Sami , Glowalla Claudio , Burgkart Rainer
Published: August 2023

In this study, we developed and validated a robotic testbench to investigate the biomechanical compatibility of three total knee arthroplasty (TKA) configurations under different loading conditions, including varus–valgus and internal–external loading across defined flexion angles. The testbench captured force–torque data, position, and quaternion information of the knee joint. A cadaver study was conducted, encompassing a native knee joint assessment and successive TKA testing, featuring femoral component rotations at −5°, 0°, and +5° relative to the transepicondylar axis of the femur. The native knee showed enhanced stability in varus–valgus loading, with the +5° external rotation TKA displaying the smallest deviation, indicating biomechanical compatibility. The robotic testbench consistently demonstrated high precision across all loading conditions. The findings demonstrated that the TKA configuration with a +5° external rotation displayed the minimal mean deviation under internal–external loading, indicating superior joint stability. These results contribute meaningful understanding regarding the influence of different TKA configurations on knee joint biomechanics, potentially influencing surgical planning and implant positioning. We are making the collected dataset available for further biomechanical model development and plan to explore the 6 Degrees of Freedom (DOF) robotic platform for additional biomechanical analysis. This study highlights the versatility and usefulness of the robotic testbench as an instrumental tool for expanding our understanding of knee joint biomechanics.
An Integrated Method for Tunnel Health Monitoring Data Analysis and Early Warning: Savitzky–Golay Smoothing and Wavelet Transform Denoising Processing
Authors: Zhao Ning , Wei Jincheng , Long Zhiyou , Yang Chao , Bi Jiefu , Wan Zhaolong , Dong Shi
Published: August 2023

A tunnel health monitoring (THM) system ensures safe operations and effective maintenance. However, how to effectively process and denoise several data collected by THM remains to be addressed, as well as safety early warning problems. Thus, an integrated method for Savitzky–Golay smoothing (SGS) and Wavelet Transform Denoising (WTD) was used to smooth data and filter noise, and the coefficient of the non-uniform variation method was proposed for early warning. The THM data, including four types of sensors, were attempted using the proposed method. Firstly, missing values, outliers, and detrend in the data were processed, and then the data were smoothed by SGS. Furthermore, data denoising was carried out by selecting wavelet basis functions, decomposition scales, and reconstruction. Finally, the coefficient of non-uniform variation was employed to calculate the yellow and red thresholds. In data smoothing, it was found that the Signal Noise Ratio (SNR) and Root Mean Square Error (RMSE) of SGS smoothing were superior to those of the moving average smoothing and five-point cubic smoothing by approximately 10% and 30%, respectively. An interesting phenomenon was discovered: the maximum and minimum values of the denoising effects with different wavelet basis functions after selection differed significantly, with the SNR differing by 14%, the RMSE by 8%, and the r by up to 80%. It was found that the wavelet basis functions vary, while the decomposition scales are consistently set at three layers. SGS and WTD can effectively reduce the complexity of the data while preserving its key characteristics, which has a good denoising effect. The yellow and red warning thresholds are categorized into conventional and critical controls, respectively. This early warning method dramatically improves the efficiency of tunnel safety control.
Lightning Current Measurement Form and Arrangement Scheme of Transmission Line Based on Point-Type Optical Current Transducer
Authors: Ge Jinming , Yin Yibo , Wang Wei
Published: August 2023

Lightning strikes are the main cause of transmission line faults, and the accurate lightning current number is an important basis to guide scientific lightning protection. The use of sensors with excellent sensing performance to carry out lightning current monitoring on transmission lines is beneficial to the accumulation of key parameters of original lightning strikes, so it is necessary to study the lightning current measurement structure of transmission lines. In this paper, an optical current-sensing unit is used to monitor the lightning current on transmission lines. A measuring structure that can monitor key parameters of the lightning current under different types of lightning strikes is proposed. First, establish the lightning current return channel model and the equivalent model of the tower, study the influence of the transmission tower on the current in the lightning channel, and analyze the direct measurement position of the lightning current on the tower; establish the multi-wave impedance model of the tower, and build a multi-base tower. The simulation model of the transmission system analyzes the transmission characteristics of the lightning current on the transmission line and the lightning protection line in the case of different types of faults; from the perspective of the measurement of key parameters of the lightning current, the lightning current measurement structure of the transmission system is constructed to analyze different lightning strikes. The measurement effect of each monitoring position in the case of a lightning strike and the waveform characteristics of the fault current in the case of insulator flashover are analyzed.