bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Malaria on Blood Levels of Vitamin E: A Systematic Review and Meta-Analysis
Authors: Kotepui Manas , Masangkay Frederick Ramirez , Mahittikorn Aongart , Kotepui Kwuntida Uthaisar
Published: August 2023

Vitamin E has an antioxidant property and is associated with protection against malaria. The current study used systematic review and meta-analysis approaches examining the variance in blood levels of vitamin E in malaria patients as compared with uninfected individuals. The protocol for the systematic review was registered with PROSPERO (CRD4202341481). Searches for pertinent studies were carried out on Embase, MEDLINE, Ovid, PubMed, Scopus, ProQuest, and Google Scholar. The combined effect estimate (Cohen’s d) of the difference in vitamin E levels in malaria patients as compared with uninfected individuals was estimated using the random effects model. The searches yielded 2009 records, and 23 studies were included in the systematic review. The majority of the studies (80%) found that vitamin E levels were significantly lower in malaria patients than those who were not infected. Overall, the results revealed a significant reduction in blood levels of vitamin E in malaria patients when compared with uninfected individuals (p < 0.01, Cohen’s d: −2.74, 95% CI: −3.72–(−1.76), I2: 98.69%, 21 studies). There was a significant reduction in blood levels of vitamin E in patients suffering from severe malaria, in comparison with those experiencing less severe forms of the disease (p < 0.01, Cohen’s d: −0.56, 95% CI: −0.85–(−0.26), I2: 0%, 2 studies), but no variation in blood levels of vitamin E among patients suffering from either P. falciparum or P. vivax malaria (p = 0.13, Cohen’s d: −1.15, 95% CI: −2.62–0.33, I2: 93.22%, 3 studies). In summary, the present study strongly suggests that vitamin E levels are significantly reduced in malaria patients, with a more pronounced decrease observed in cases of severe malaria. However, the type of malaria parasite, specifically P. falciparum or P. vivax, did not appear to influence the levels of vitamin E. This study highlights the potential role of vitamin E in the pathogenesis of malaria and suggests that improved vitamin E status might be beneficial for improving disease outcomes.
Therapeutic Implications of PTEN in Non-Small Cell Lung Cancer
Authors: Sirhan Zaid , Alojair Rawan , Thyagarajan Anita , Sahu Ravi P.
Published: August 2023

Lung cancer remains one of the major human malignancies affecting both men and women worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent type. Multiple mechanisms have been identified that favor tumor growth as well as impede the efficacy of therapeutic regimens in lung cancer patients. Among tumor suppressor genes that play critical roles in regulating cancer growth, the phosphatase and tensin homolog (PTEN) constitutes one of the important family members implicated in controlling various functional activities of tumor cells, including cell proliferation, apoptosis, angiogenesis, and metastasis. Notably, clinical studies have also documented that lung tumors having an impaired, mutated, or loss of PTEN are associated with low survival or high tumor recurrence rates. To that end, PTEN has been explored as a promising target for anti-cancer agents. Importantly, the ability of PTEN to crosstalk with several signaling pathways provides new approaches to devise effective treatment options for lung cancer treatment. The current review highlights the significance of PTEN and its implications in therapeutic approaches against NSCLC.
Effects of Pulsed Electric Field on the Physicochemical and Structural Properties of Micellar Casein
Authors: Taha Ahmed , Casanova Federico , Talaikis Martynas , Stankevič Voitech , Žurauskienė Nerija , Šimonis Povilas , Pakštas Vidas , Jurkūnas Marijus , Gomaa Mohamed A. E. , Stirkė Arūnas
Published: August 2023

Pulsed electric field (PEF) as a green processing technology is drawing greater attention due to its eco-friendliness and potential to promote sustainable development goals. In this study, the effects of different electric field strengths (EFS, 0–30 kV/cm) on the structure and physicochemical features of casein micelles (CSMs) were investigated. It was found that the particle sizes of CSMs increased at low EFS (10 kV/cm) but decreased at high EFS (30 kV/cm). The absolute ζ-potential at 30 kV/cm increased from −26.6 (native CSMs) to −29.5 mV. Moreover, it was noticed that PEF treatment leads to changes in the surface hydrophobicity; it slightly increased at low EFS (10 kV/cm) but decreased at EFS > 10 kV/cm. PEF enhanced the protein solubility from 84.9 (native CSMs) to 87.1% (at 10 kV/cm). PEF at low EFS (10 kV/cm) intensified the emission fluorescence spectrum of CSMs, while higher EFS reduced the fluorescence intensity compared to native CSMs. Moreover, the analysis of the Amide Ι region showed that PEF-treated CSMs reduced the α-helix and increased the β-sheet content. Raman spectra confirmed that PEF treatment > 10 kV/cm buried tyrosine (Tyr) residues in a hydrophobic environment. It was also found that PEF treatment mainly induced changes in the disulfide linkages. In conclusion, PEF technology can be employed as an eco-friendly technology to change the structure and physiochemical properties of CSMs; this could improve their techno-functional properties.
Enhancing Char Formation and Flame Retardancy of Ethylene-Vinyl Acetate Copolymer (EVA)/Aluminum Hydroxide (ATH) Composites by Grafting Ladder Phenyl/Vinyl Polysilsesquioxane (PhVPOSS)
Authors: Hu Fa , Cheng Bo , Cong Kun , Li Dinghua , Zhang Wenchao , Qin Zhaolu , Yang Rongjie
Published: August 2023

The ladder phenyl/vinyl polysilsesquioxane (PhVPOSS) was used to improve the flame-retardancy performances of ethylene-vinyl acetate copolymer (EVA)/aluminum hydroxide (ATH) composites due to the reactivity of its vinyl groups. FTIR, XPS, 1H NMR, and SEM-EDS data demonstrated the PhVPOSS grafting onto EVA molecular chains. The PhVPOSS improved the thermal stability of EVA/ATH composites, as shown by the thermogravimetric analysis (TGA). Furthermore, with the cone calorimeter (CONE) experiments, EVA/ATH/PhVPOSS showed better fire safety than the EVA/ATH composites, with the PHRR, PSPR, and PCOP reduced by 7.89%, 57.4%, and 90.9%, respectively. The mechanism investigations of flame retardancy revealed that the charring behaviors of the EVA/ATH/PhVPOSS composites were improved by the formation of Si-C bonds and Si-O bonds, and a more compact and denser char layer can contribute more to the barrier effect.
Hydrodistillation and Steam Distillation of Fennel Seeds Essential Oil: Parameter Optimization and Application of Cryomilling Pretreatment
Authors: Marčac Nina , Balbino Sandra , Tonković Petra , Medved Ana Marija , Cegledi Ena , Dragović Sanja , Dragović-Uzelac Verica , Repajić Maja
Published: August 2023

The aim of this study was to examine the effectiveness of cryomilling (CM) pretreatment on the isolation of fennel seeds essential oil (EO). Therefore, the study included (i) the process optimization and comparison of the efficiencies of hydrodistillation (HD) and steam distillation (SD); (ii) the evaluation of the effect of the CM application prior to the distillation method (selected based on the results obtained in the first part) on the EO yield; (iii) the evaluation of possible quality differences of the EOs obtained with the performed isolation methods. The obtained results showed that HD (at a solid to liquid ratio 1:10 and a distillation time of 120 min) was more efficient in terms of the EO yield compared to SD (at a pressure of 0.83 bar and distillation time of 117 min as optimal conditions). Moreover, an increased EO yield or even reduced distillation time was observed when HD was combined with a 3 min or 5 min CM pretreatment. GC-MS analysis showed no qualitative differences in chemical composition upon any of the applied isolation procedures, although higher amounts of volatiles were found in the cryomilled samples. The results of this study could be of interest to academia and the EO industry, as CM showed a positive aspect in EO isolation that could provide economic benefits in terms of higher yields or energy savings.
Model-Based Optimization of Multi-Stage Nanofiltration Using the Solution-Diffusion–Electromigration Model
Authors: Hubach Tobias , Schlüter Stefan , Held Christoph
Published: August 2023

Nanofiltration is well suited to separate monovalent ions from multivalent ions, such as the separation of Li+ and Mg2+ from seawater, a potential lithium source for the production of lithium-ion batteries. To the best of our knowledge, there is no existing work on the optimization of a multi-stage membrane plant that differentiates between different ions and that is based on a validated transport model. This study presents a method for modeling predefined membrane interconnections using discretization along the membrane length and across the membrane thickness. The solution-diffusion–electromigration model was used as the transport model in a fundamental membrane flowsheet, and the model was employed to optimize a given flowsheet with a flexible objective function. The methodology was evaluated for three distinct separation tasks, and optimized operating points were found. These show that permeances and feed concentrations might cause negative rejections and positive rejections (especially for bivalent ions) depending on the ions’ properties and fluxes, thereby allowing for a favorable separation between the ions of different valence at optimized conditions. In an application-based case study for the separation of Li+ and Mg2+ from seawater, the method showed that under optimal conditions, the mol-based ratio of Mg2+/Li+ can be reduced from 2383 to 2.8 in three membrane stages.
The Numerical Investigations of Heat Transfer and Bubble Behaviors of R22 in Subcooled Flow Boiling in Casing Tubes
Authors: Hu Xiaodie , Wang Jinfeng , Xie Jing , Wang Bingjun , Wang Fei
Published: August 2023

Amidst the background of “double carbon”, energy saving and emission reduction is a popular direction in the current refrigeration industry. Therefore, the research on the boiling heat transfer of gas–liquid two-phase flow is helpful to strengthen the heat transfer and design a more efficient heat exchanger. In this paper, a research method combining numerical simulation and experimental verification is adopted. Firstly, an experimental platform used for the subcooled flow boiling of refrigerant in casing tubes is introduced and experiments are carried out to obtain experimental data, which provides a theoretical basis for the development of numerical simulation and verifies the feasibility of numerical simulation. A numerical model of subcooled flow boiling in R22 was established and the grid independence test was carried out. Based on the simulation results, three factors affecting the boiling heat transfer of R22 are analyzed: First, the boiling heat transfer coefficient of R22 increases with the increase of the mass flow rate of R22, but the increase decreases when the mass flow rate increases from 0.018 kg/s to 0.020 kg/s. Second, the boiling heat transfer coefficient of R22 increases significantly with the increase of hot water flow rate. Third, the influence of R22 subcooling on boiling heat transfer is more complex. When the subcooling is 5 °C and 1 °C, heat transfer can be enhanced; high subcooling at 5 °C can enhance convective heat transfer and low subcooling at 1 °C can accelerate the arrival of saturated boiling. In this paper, three kinds of bubble behaviors affecting heat transfer in supercooled flow boiling, including sliding, polymerization, and bounce are also studied, which provides a basis for further research on heat transfer mechanism of supercooled flow boiling.
Hydrogen/Deuterium Exchange in Ambrox Could Improve the Long-Term Scent and Shelf Life of Perfumes
Authors: Rosales Martínez Antonio , Rodríguez-García Ignacio
Published: August 2023

Ambrox is a marine natural compound with a delicious ambergris-type scent widely used in fine perfumery. The increase in the long-term scent and shelf life of perfumes has become a paramount endeavor in the fragrance industry. To the best of our knowledge, the exchange of hydrogen by deuterium to decrease the volatility of the constituents of a perfume has not yet been investigated. In this article, we propose this new use of deuteration to synthesize deuterated ambrox in order to decrease its volatility and improve the long-term scent and extend the shelf-life of perfumes.
ROV Sliding Mode Controller Design and Simulation
Authors: Ren Fushen , Hu Qing
Published: August 2023

Underwater robots play a vital role in the exploration and development of marine resources and the inspection and maintenance of offshore platforms. In this paper, the motion control technology of ROV is studied, the kinematics and dynamics of ROV are analyzed, the kinematics and dynamics models of ROV are established, and the degrees of freedom of the models are decouple according to the control requirements. The fluid damping coefficient of ROV was obtained using Fluent software, and an ROV control system based on sliding mode variable structure was designed. The saturation function was introduced into the sliding mode controller to reduce the adverse effects of buffeting. The classical PID controller, fuzzy PID controller, and sliding mode controller designed in this paper were simulated and analyzed by Simulink. A semi-physical simulation platform based on Unity3D was established. It can be seen from the simulation results and the pool experiment results that the performance of the sliding mode controller designed in this paper is better than the classical PID controller and the fuzzy PID controller. The sliding mode control method is used to control the ROV motion, which has better control effect and precision.
Green Techniques for Detecting Microplastics in Marine with Emphasis on FTIR and NIR Spectroscopy—Short Review
Authors: Mikulec Vlatka , Adamović Petra , Cvetković Želimira , Ivešić Martina , Gajdoš Kljusurić Jasenka
Published: August 2023

The amount of microplastics (MPs) present in marine ecosystems are a growing concern, with potential impacts on human health because they are associated with an increase in the ecotoxicity of certain foods, such as fish. As a result, there has been a growing interest in developing effective methods for the analysis of MPs in marine waters. Traditional methods for MP analysis involve visual inspection and manual sorting, which can be time-consuming and subject to human error. However, novel methods have been developed that offer more efficient and accurate analyses. One such method is based on spectroscopy, such as Fourier transform infrared spectroscopy (FTIR). Another method involves the use of fluorescent dyes, which can selectively bind to microplastics and allow for their detection under UV light. Additionally, machine learning approaches have been developed to analyze large volumes of water samples for MP detection and classification. These methods involve the use of specialized algorithms that can identify and classify MPs based on their size, shape, and texture. Overall, these novel methods offer more efficient and accurate analyses of MPs in marine waters, which is essential for understanding the extent and impacts of MP pollution and for developing effective mitigation strategies. However, there is still a need for continued research and development to optimize these methods and improve their sensitivity and accuracy.
Oxidation Kinetics Analysis of Crude Oils with Different Viscosities
Authors: Luo Bincheng , Yu Chunsheng , Chen Yuehao , Yue Kunhai , Yue Lifan , Chen Tao
Published: August 2023

In order to compare the oxidation kinetics parameters of crude oils with different properties in the process of crude oil oxidation, six different crude oil samples were selected to analyze the oxidation characteristics of crude oils with different properties. In order to study the oxidation of crude oil, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) synchronous analyzer were used for crude oil in the oxygen environment between 25 °C and 900 °C at a heating rate of 20 °C/min. The experimental results were based on crude oil oxidation using TGA and DTG experimental data to evaluate the oxidation mechanism of different crude oils, so as to better understand the situation in the oxidation reaction process. At the same time, the oxidation stage of crude oil was divided according to DSC data. Arrhenius method was used to analyze the oxidation kinetic parameters of crude oils with different properties, and the activation energies and pre-exponential factors of different crude oils were calculated. The experimental results show that the oxidation stage of crude oil can be divided into three stages: low-temperature oxidation, fuel deposition, and high-temperature oxidation. The low-temperature oxidation reaction begins at 280 °C, and the high-temperature oxidation reaction occurs at 400 °C. The low-temperature oxidation activation energy of an oil sample is 39.73–77.74 kJ/mol. The activation energy of the high-temperature oxidation is in the range of 106.27–264.47 kJ/mol. The activation energy of crude oil in the low-temperature oxidation stage increases with the increase of crude oil viscosity and decreases with the increase of crude oil viscosity in the high-temperature oxidation stage. Therefore, during the high-temperature oxidation stage, high-viscosity crude oil is more prone to reactions.
Modelling the Effect of Water Removal by Reverse Osmosis on the Distillation of Mixtures of Short-Chain Organic Acids from Anaerobic Fermentation
Authors: Simonetti Serena , Dionisi Davide
Published: August 2023

Anaerobic fermentation (AF) to produce sustainable short-chain organic acids (SCOAs) has found no commercial application so far. This is due to several limitations, including the high energy consumption of the SCOAs’ separation from water by distillation. This study used AspenPlus simulations to investigate the benefits of reverse osmosis (RO) to remove water and concentrate the SCOAs from AF before their separation by distillation. The effect of RO on distillation reflux ratio, heat energy requirements, column diameter and equipment costs was simulated for the processing of model SCOA-containing streams, representing AF effluents. A total of 90 simulations were carried out, investigating three different SCOA compositions, corresponding to different ratios of lactic, acetic and propionic acids, three different concentrations of the total SCOAs (10, 50, 100 g/kg in the stream entering RO) and different extents of water removal by RO. RO brought a reduction in the distillation reboilers’ duty of up to more than 90%, with a reduction of column diameter of up to more than 70%. The total energy consumption, equipment cost and NPV (net present value) of the RO plus distillation process were in all cases more favourable than for the process without membranes.
Improved Faster R-CNN Network for Liquid Bag Foreign Body Detection
Authors: Huang Bo , Liu Jianhong , Zhang Qian , Liu Kang , Liu Xiang , Wang Jian
Published: August 2023

The production quality of medical fluid bags is closely related to patient health. In this paper, we used medical fluid bags to detect whether they contained foreign bodies. A visual acquisition system for the fluid bag was built. Vignetting correction was performed on the acquired images, and a foreign body recognition detection method based on an improved Faster R-CNN model was proposed. The feature extraction network of Faster R-CNN was discussed and studied regarding the characteristics of small foreign objects in liquid bags, and the ResNet152 network replaced the VGG16 network; furthermore, the feature fusion and attention mechanism were added to the feature extraction, and CIoU replaced the IoU loss function; the anchor box parameters were optimized and improved using the K-means clustering algorithm, and ROI Align replaced the ROI Pooling module. The improved network in this paper was compared with the Faster R-CNN model, which is a modification of feature extraction networks, such as ResNet50, ResNet101, and ResNet152, and the original VGG16 feature extraction network. The results show that the ResNet152 network had the best feature extraction effect among the feature extraction networks, and other optimizations were performed in this paper based on the use of ResNet152. In the precision−recall curve, the network in this paper showed the best effect. The improved algorithm presented in this paper was significantly improved compared with the original algorithm, with a detection accuracy of 97% and an average accuracy improvement of 7.8% in foreign object recognition.
On the Diversification Effect in Solvency II for Extremely Dependent Risks
Authors: Chen Yongzhao , Cheung Ka Chun , Yam Sheung Chi Phillip , Yuen Fei Lung , Zeng Jia
Published: August 2023

In this article, we investigate the validity of diversification effect under extreme-value copulas, when the marginal risks of the portfolio are identically distributed, which can be any one having a finite endpoint or belonging to one of the three maximum domains of attraction. We show that Value-at-Risk (V@R) under extreme-value copulas is asymptotically subadditive for marginal risks with finite mean, while it is asymptotically superadditive for risks with infinite mean. Our major findings enrich and supplement the context of the second fundamental theorem of quantitative risk management in existing literature, which states that V@R of a portfolio is typically non-subadditive for non-elliptically distributed risk vectors. In particular, we now pin down when the V@R is super or subadditive depending on the heaviness of the marginal tail risk. According to our results, one can take advantages from the diversification effect for marginal risks with finite mean. This justifies the standard formula for calculating the capital requirement under Solvency II in which imperfect correlations are used for various risk exposures.
The Relationship between Innovation and Risk Taking: The Role of Firm Performance
Authors: Widianingsih Yuni Pristiwati Noer , Setiawan Doddy , Aryani Y. Anni , Gantyowati Evi
Published: August 2023

One perspective suggests that firms heavily involved in innovation may face increased risks. It is essential to know the suitable proxies in measuring innovation related to risk taking. Many studies use research-and-development intensity (RDI) and research-and-development spending (RDS) as proxies for innovation related to risk taking. However, little evidence shows that positive association with risk taking. This study addresses this gap by using RDI and RDS as metrics for measuring innovation and assessing innovation-related risks. This study incorporated performance as a potential factor affecting the interaction between these variables. It is essential to consider the risks associated with innovation and allocate the RDI and RDS effectively to maximize revenue. We used a dataset of 3955 firm-year observations obtained from 548 listed firms in the Indonesian stock exchange for 2012–2021. We found that RDI and RDS positively affect risk taking. The test results show that the interaction between innovation and firm performance negatively affects risk taking. Thus, firm performance may mitigate the risks associated with innovation. Therefore, firms must balance their innovation projects with improved performance to minimize risks and achieve long-term success.
Application of Path Planning for a Mobile Robot Assistance System Based on OpenStreetMap Data
Authors: Stahr Pascal , Maaß Jochen , Gärtner Henner
Published: August 2023

For visually impaired people, orientation and mobility are challenging and require a great deal of concentration. Especially unfamiliar routes are difficult to follow. This paper presents a navigation algorithm based on a geographic information system that can be optimally adapted to the needs of this user group. A three-stage process is being developed for this purpose. The first step is to check the map against ISO 19157, followed by map augmentation and the generation of a navigable graph. Finally, a new cost function for an A* algorithm is developed to make the best use of the modified map data and adapt it to the user’s needs. It is shown that map data from the geographic information system OpenStreetMap is well suited to the task, although the map data needs to be verified and augmented with additional information before being used. Finally, we compare the presented solution with a standard A* algorithm.
SAR and Optical Image Registration Based on Deep Learning with Co-Attention Matching Module
Authors: Chen Jiaxing , Xie Hongtu , Zhang Lin , Hu Jun , Jiang Hejun , Wang Guoqian
Published: August 2023

Image registration is the basis for the joint interpretation of synthetic aperture radar (SAR) and optical images. However, the significant nonlinear radiation difference (NRD) and the geometric imaging model difference render the registration quite challenging. To solve this problem, both traditional and deep learning methods are used to extract structural information with dense descriptions of the images, but they ignore that structural information of the image pair is coupled and often process images separately. In this paper, a deep learning-based registration method with a co-attention matching module (CAMM) for SAR and optical images is proposed, which integrates structural feature maps of the image pair to extract keypoints of a single image. First, joint feature detection and description are carried out densely in both images, for which the features are robust to radiation and geometric variation. Then, a CAMM is used to integrate both images’ structural features and generate the final keypoint feature maps so that the extracted keypoints are more distinctive and repeatable, which is beneficial to global registration. Finally, considering the difference in the imaging mechanism between SAR and optical images, this paper proposes a new sampling strategy that selects positive samples from the ground-truth position’s neighborhood and augments negative samples by randomly sampling distractors in the corresponding image, which makes positive samples more accurate and negative samples more abundant. The experimental results show that the proposed method can significantly improve the accuracy of SAR–optical image registration. Compared to the existing conventional and deep learning methods, the proposed method yields a detector with better repeatability and a descriptor with stronger modality-invariant feature representation.
Research on Detection and Safety Analysis of Unfavorable Geological Bodies Based on OCTEM-PHA
Authors: Zhu Tao , Hu Jianhua , Wen Guanping , Zhou Tan
Published: August 2023

The caving method and mining disturbance may cause geological issues. The advance prediction of unfavorable geological bodies should be conducted to ensure product safety in the underground mine. In this study, we proposed the OCTEM-PHA analysis process and analyzed the Tongkeng Mine in Guangxi. Further, we conducted opposing-coil transient electromagnetic method (OCTEM) detection on four detection lines in T5-1 stope at mine level 386 by using portable geological remote sensing equipment and created inversion maps. Plot profiles and coupling were analyzed with inversion maps to explore the five types of risk factors presented in the mine. The preliminary hazard analysis (PHA) method was used for five types of risk factors to predict the accident consequence and develop safety countermeasures. The results indicate the following: (1) the OCTEM-PHA safety analysis process for unfavorable geological bodies is realistic and feasible. (2) OCTEM shows an excellent response to both high- and low-resistance anomalies in practical engineering applications. The coupling analysis of profiles and inversion maps helps visually analyze the area of apparent resistivity anomalies. (3) The studied mine did not show overhanging formed by the overlying rock layer and large loose void areas. However, the crumbling mining area should be further optimized for balanced mining, the treatment of groundwater and surface water should be improved, and the comparative analysis with the follow-up detection results should be increased.
Evaluation and Application of SMRT Model for L-Band Brightness Temperature Simulation in Arctic Sea Ice
Authors: Fan Yanfei , Li Lele , Chen Haihua , Guan Lei
Published: August 2023

Using L-band microwave radiative transfer theory to retrieve ice and snow parameters is one of the focuses of Arctic research. At present, due to limitations of frequency and substrates, few operational microwave radiative transfer models can be used to simulate L-band brightness temperature (TB) in Arctic sea ice. The snow microwave radiative transfer (SMRT) model, developed with the support of the European Space Agency in 2018, has been used to simulate high-frequency TB in polar regions and has obtained good results, but no studies have shown whether it can be used appropriately in the L-band. Therefore, in this study, we systematically evaluate the ability of the SMRT model to simulate L-band TB in the Arctic sea ice and snow environment, and we show that the results are significantly optimized by improving the simulation method. In this paper, we first consider the thermal insulation effect of snow by adding the thermodynamic equation, then use a reasonable salinity profile formula for multi-layer model simulation to solve the problem of excessive L-band penetration in the SMRT single-layer model, and finally add ice lead correction to resolve the large influence it has on the results. The improved SMRT model is evaluated using Operation IceBridge (OIB) data from 2012 to 2015 and compared with the snow-corrected classical L-band radiative transfer model for Arctic sea ice proposed in 2010 (KA2010). The results show that the SMRT model has better simulation results, and the correlation coefficient (R) between SMRT-simulated TB and Soil Moisture and Ocean Salinity (SMOS) satellite TB is 0.65, and the RMSE is 3.11 K. Finally, the SMRT model with the improved simulation method is applied to the whole Arctic from November 2014 to April 2015, and the simulated R is 0.63, and the RMSE is 5.22 K. The results show that the SMRT multi-layer model is feasible for simulating L-band TB in the Arctic sea ice and snow environment, which provides a basis for the retrieval of Arctic parameters.
Hyperspectral Unmixing Network Accounting for Spectral Variability Based on a Modified Scaled and a Perturbed Linear Mixing Model
Authors: Cheng Ying , Zhao Liaoying , Chen Shuhan , Li Xiaorun
Published: August 2023

Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by variations in environmental conditions. These and other factors interfere with the accurate discrimination of source type. Several spectral mixing models have been proposed for hyperspectral unmixing to address the spectral variability problem. The interpretation for the spectral variability of these models is usually insufficient, and the unmixing algorithms corresponding to these models are usually classic unmixing techniques. Hyperspectral unmixing algorithms based on deep learning have outperformed classic algorithms. In this paper, based on the typical extended linear mixing model and the perturbed linear mixing model, the scaled and perturbed linear mixing model is constructed, and a spectral unmixing network based on this model is constructed using fully connected neural networks and variational autoencoders to update the abundances, scales, and perturbations involved in the variable endmembers. Adding spatial smoothness constraints to the scale and adding regularization constraints to the perturbation improve the robustness of the model, and adding sparseness constraints to the abundance determination prevents overfitting. The proposed approach is evaluated on both synthetic and real data sets. Experimental results show the superior performance of the proposed method against other competitors.
A Hierarchical Motion Planning Method for Mobile Manipulator
Authors: Chen Hanlin , Zang Xizhe , Liu Yubin , Zhang Xuehe , Zhao Jie
Published: August 2023

This paper focuses on motion planning for mobile manipulators, which includes planning for both the mobile base and the manipulator. A hierarchical motion planner is proposed that allows the manipulator to change its configuration autonomously in real time as needed. The planner has two levels: global planning for the mobile base in two dimensions and local planning for both the mobile base and the manipulator in three dimensions. The planner first generates a path for the mobile base using an optimized A* algorithm. As the mobile base moves along the path with the manipulator configuration unchanged, potential collisions between the manipulator and the environment are checked using the environment data obtained from the on-board sensors. If the current manipulator configuration is in a potential collision, a new manipulator configuration is searched. A sampling-based heuristic algorithm is used to effectively find a collision-free configuration for the manipulator. The experimental results in simulation environments proved that our heuristic sampling-based algorithm outperforms the conservative random sampling-based method in terms of computation time, percentage of successful attempts, and the quality of the generated configuration. Compared with traditional methods, our motion planning method could deal with 3D obstacles, avoid large memory requirements, and does not require a long time to generate a global plan.
Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation
Authors: Li Liaoyuan , Han Jianhai , Li Xiangpan , Guo Bingjing , Wang Xinjie
Published: August 2023

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians’ experience and the patient’s characteristics. And the training should have high accuracy on the premise of safety. Therefore, trajectory customization, optimization, and tracking control algorithms are conducted based on a new upper limb rehabilitation robot. First, joint friction and initial load were identified and compensated. The admittance algorithm was used to realize the trajectory customization. Second, the improved butterfly optimization algorithm (BOA) was used to optimize the nonuniform rational B-spline fitting curve (NURBS). Then, a variable gain control strategy is designed, which enables the robot to track the trajectory well with small human–robot interaction (HRI) forces and to comply with a large HRI force to ensure safety. Regarding the return motion, an error subdivision method is designed to slow the return movement. The results showed that the customization force is less than 6 N. The trajectory tracking error is within 12 mm without a large HRI force. The control gain starts to decrease in 0.5 s periods while there is a large HRI force, thereby improving safety. With the decrease in HRI force, the real position can return to the desired trajectory slowly, which makes the patient feel comfortable.
Synthesis of Graphene Oxide-Coupled CoNi Bimetallic MOF Nanocomposites for the Simultaneous Analysis of Catechol and Hydroquinone
Authors: Zheng Shengbiao , Zhang Nini , Li Liang , Liu Tianna , Zhang Yuyang , Tang Jing , Guo Jiahao , Su Shao
Published: August 2023

Herein, a three-dimensional flower-like cobalt-nickel bimetallic metal-organic framework (CoNi-MOF) coupled with two-dimensional graphene oxide (GO) nanocomposites was successfully synthesized for the selective and simultaneous electrochemical determination of catechol (CC) and hydroquinone (HQ). The three-dimensional flower-like structure of the CoNi-MOF/GO nanocomposite has a multilayer structure and a large surface area, which greatly improves its electrocatalytic activity towards CC and HQ. Differential pulse voltammetry (DPV) results showed that the peak-to-peak separation of CC (0.223 V) and HQ (0.120 V) was 103 mV at a CoNi-MOF/GO modified glassy carbon electrode (CoNi-MOF/GO/GCE), suggesting that the proposed modified electrode can selectively and simultaneously determine them. Under optimal conditions, the CoNi-MOF/GO/GCE showed an excellent analytical performance for the simultaneous determination of CC and HQ, including a wide linear range (0.1–100 μM), low detection limit (0.04 μM for HQ and 0.03 μM for CC) and high anti-interference ability. As expected, the developed modified electrode has been used to analyze CC and HQ in river water, with acceptable results.
Intelligent Measuring of the Volume Fraction Considering Temperature Changes and Independent Pressure Variations for a Two-Phase Homogeneous Fluid Using an 8-Electrode Sensor and an ANN
Authors: Qaisi Ramy Mohammed Aiesh , Fouladinia Farhad , Mayet Abdulilah Mohammad , Guerrero John William Grimaldo , Loukil Hassen , Raja M. Ramkumar , Muqeet Mohammed Abdul , Eftekhari-Zadeh Ehsan
Published: August 2023

Two-phase fluids are widely utilized in some industries, such as petrochemical, oil, water, and so on. Each phase, liquid and gas, needs to be measured. The measuring of the void fraction is vital in many industries because there are many two-phase fluids with a wide variety of liquids. A number of methods exist for measuring the void fraction, and the most popular is capacitance-based sensors. Aside from being easy to use, the capacitance-based sensor does not need any separation or interruption to measure the void fraction. In addition, in the contemporary era, thanks to Artificial Neural Networks (ANN), measurement methods have become much more accurate. The same can be said for capacitance-based sensors. In this paper, a new metering system utilizing an 8-electrode sensor and a Multilayer Perceptron network (MLP) is presented to predict an air and water volume fractions in a homogeneous fluid. Some characteristics, such as temperature, pressure, etc., can have an impact on the results obtained from the aforementioned sensor. Thus, considering temperature changes, the proposed network predicts the void fraction independent of pressure variations. All simulations were performed using the COMSOL Multiphysics software for temperature changes from 275 to 370 degrees Kelvin. In addition, a range of 1 to 500 Bars, was considered for the pressure. The proposed network has inputs obtained from the mentioned software, along with the temperature. The only output belongs to the predicted void fraction, which has a low MAE equal to 0.38. Thus, based on the obtained result, it can be said that the proposed network precisely measures the amount of the void fraction.
Breathing Chest Wall Kinematics Assessment through a Single Digital Camera: A Feasibility Study
Authors: Molinaro Nunzia , Schena Emiliano , Silvestri Sergio , Massaroni Carlo
Published: August 2023

The identification of respiratory patterns based on the movement of the chest wall can assist in monitoring an individual’s health status, particularly those with neuromuscular disorders, such as hemiplegia and Duchenne muscular dystrophy. Thoraco-abdominal asynchrony (TAA) refers to the lack of coordination between the rib cage and abdominal movements, characterized by a time delay in their expansion. Motion capture systems, like optoelectronic plethysmography (OEP), are commonly employed to assess these asynchronous movements. However, alternative technologies able to capture chest wall movements without physical contact, such as RGB digital cameras and time-of-flight digital cameras, can also be utilized due to their accessibility, affordability, and non-invasive nature. This study explores the possibility of using a single RGB digital camera to record the kinematics of the thoracic and abdominal regions by placing four non-reflective markers on the torso. In order to choose the positions of these markers, we previously investigated the movements of 89 chest wall landmarks using OEP. Laboratory tests and volunteer experiments were conducted to assess the viability of the proposed system in capturing the kinematics of the chest wall and estimating various time-related respiratory parameters (i.e., fR, Ti, Te, and Ttot) as well as TAA indexes. The results demonstrate a high level of agreement between the detected chest wall kinematics and the reference data. Furthermore, the system shows promising potential in estimating time-related respiratory parameters and identifying phase shifts indicative of TAA, thus suggesting its feasibility in detecting abnormal chest wall movements without physical contact with a single RGB camera.
Fabrication of Micro-Cantilever Sensor Based on Clay Minerals for Humidity Detection
Authors: Xu Yiting , Liu Song , Zhang Junfeng , Chai Songyang , Li Jianjun , Xue Changguo , Wu Shangquan
Published: August 2023

In this paper, novel humidity sensors based on montmorillonite, kaolinite, and composite films coated on micro-cantilevers were prepared to measure the relative humidity (RH) values by the deflection of a micro-cantilever (MC) at room temperature. The humidity-sensing properties, such as response and recovery, sensitivity, repeatability, humidity hysteresis, and long-term stability, were investigated in the range of working humidity (10–80% RH). The humidity response in the close humidity range of 10% RH to 80% RH revealed a linear increase in water absorption of montmorillonite, kaolinite, and montmorillonite/kaolinite mixed dispersant (1:1) as a function of RH with linear correlation factors between the humidity change and deflection estimated to be 0.994, 0.991, and 0.946, respectively. Montmorillonite’s sensitivity was better than kaolinite’s, with the mixed-clay mineral film’s response falling somewhere in between. This research provides a feasible and effective approach to constructing high-performance MC humidity sensors that can be operated at room temperature based on clay minerals.
A Multi-Sensor Fusion Approach Based on PIR and Ultrasonic Sensors Installed on a Robot to Localise People in Indoor Environments
Authors: Ciuffreda Ilaria , Casaccia Sara , Revel Gian Marco
Published: August 2023

This work illustrates an innovative localisation sensor network that uses multiple PIR and ultrasonic sensors installed on a mobile social robot to localise occupants in indoor environments. The system presented aims to measure movement direction and distance to reconstruct the movement of a person in an indoor environment by using sensor activation strategies and data processing techniques. The data collected are then analysed using both a supervised (Decision Tree) and an unsupervised (K-Means) machine learning algorithm to extract the direction and distance of occupant movement from the measurement system, respectively. Tests in a controlled environment have been conducted to assess the accuracy of the methodology when multiple PIR and ultrasonic sensor systems are used. In addition, a qualitative evaluation of the system’s ability to reconstruct the movement of the occupant has been performed. The system proposed can reconstruct the direction of an occupant with an accuracy of 70.7% and uncertainty in distance measurement of 6.7%.
Traffic Noise Assessment Using Intelligent Acoustic Sensors (Traffic Ear) and Vehicle Telematics Data
Authors: Ghaffarpasand Omid , Almojarkesh Anwar , Morris Sophie , Stephens Elizabeth , Chalabi Alaa , Almojarkesh Usamah , Almojarkesh Zenah , Pope Francis D.
Published: August 2023

Here, we introduce Traffic Ear, an acoustic sensor pack that determines the engine noise of each passing vehicle without interrupting traffic flow. The device consists of an array of microphones combined with a computer vision camera. The class and speed of passing vehicles were estimated using sound wave analysis, image processing, and machine learning algorithms. We compared the traffic composition estimated with the Traffic Ear sensor with that recorded using an automatic number plate recognition (ANPR) camera and found a high level of agreement between the two approaches for determining the vehicle type and fuel, with uncertainties of 1–4%. We also developed a new bottom-up assessment approach that used the noise analysis provided by the Traffic Ear sensor along with the extensively detailed urban mobility maps that were produced using the geospatial and temporal mapping of urban mobility (GeoSTMUM) approach. It was applied to vehicles travelling on roads in the West Midlands region of the UK. The results showed that the reduction in traffic engine noise over the whole of the study road was over 8% during rush hours, while the weekday–weekend effect had a deterioration effect of almost half. Traffic noise factors (dB/m) on a per-vehicle basis were almost always higher on motorways compared the other roads studied.
Audiovisual Tracking of Multiple Speakers in Smart Spaces
Authors: Sanabria-Macias Frank , Marron-Romera Marta , Macias-Guarasa Javier
Published: August 2023

This paper presents GAVT, a highly accurate audiovisual 3D tracking system based on particle filters and a probabilistic framework, employing a single camera and a microphone array. Our first contribution is a complex visual appearance model that accurately locates the speaker’s mouth. It transforms a Viola & Jones face detector classifier kernel into a likelihood estimator, leveraging knowledge from multiple classifiers trained for different face poses. Additionally, we propose a mechanism to handle occlusions based on the new likelihood’s dispersion. The audio localization proposal utilizes a probabilistic steered response power, representing cross-correlation functions as Gaussian mixture models. Moreover, to prevent tracker interference, we introduce a novel mechanism for associating Gaussians with speakers. The evaluation is carried out using the AV16.3 and CAV3D databases for Single- and Multiple-Object Tracking tasks (SOT and MOT, respectively). GAVT significantly improves the localization performance over audio-only and video-only modalities, with up to 50.3% average relative improvement in 3D when compared with the video-only modality. When compared to the state of the art, our audiovisual system achieves up to 69.7% average relative improvement for the SOT and MOT tasks in the AV16.3 dataset (2D comparison), and up to 18.1% average relative improvement in the MOT task for the CAV3D dataset (3D comparison).
A Generalized Hamilton Robust Control Scheme of Trajectory Tracking for Intelligent Vehicles
Authors: Zhang Yu , Pei Wenhui , Zhang Qi , Ma Baosen
Published: August 2023

To ensure the accuracy and stability of intelligent-vehicle-trajectory tracking, a robust trajectory-tracking control strategy based on generalized Hamilton theory is proposed. Firstly, a dynamic Hamilton dissipative controller (DHDC) and trajectory-tracking Hamilton dissipative controller (TTHDC) were designed based on the established vehicle-dynamics control system and trajectory-tracking control system using the orthogonal decomposition method and control-switching method. Next, the feedback-dissipative Hamilton realizations of the two systems were obtained separately to ensure the convergence of the system. Secondly, based on the dissipative Hamilton system designed by TTHDC, a generalized Hamilton robust controller (GHRC) was designed. Finally, the co-simulation of Carsim and MATLAB/Simulink was used to verify the effectiveness of the three control algorithms. The simulation results show that DHDC and TTHDC can achieve self-stabilizing control of vehicles and enable certain control effects for the trajectory tracking of vehicles. The GHRC solves the problems of low tracking accuracy and poor stability of DHDC and TTHDC. Compared with the sliding mode controller (SMC) and linear quadratic regulator (LQR) controller, the GHRC can reduce the lateral error by 84.44% and the root mean square error (RMSE) by 83.92%, which effectively improves the accuracy and robustness of vehicle-trajectory tracking.