bluuebunny/crossref_metadata_2025 huggingface dataset:
Editorial for Special Issue: “Liposomal and Lipid-Based Drug Delivery Systems and Vaccines”
Authors: Vodovozova Elena L.
Published: February 2024

Liposomes and lipid-based supramolecular systems have been used in clinical practice for more than 30 years as drug carriers and vaccines for the treatment of oncological diseases and infections [...]
Increased Accumulation of Ginsenosides in Panax ginseng Sprouts Cultivated with Kelp Fermentates
Authors: Park Kyung-Wuk , Kim Jeong-Ho , Jeong Beom-Gyun , Park Jun-Ki , Jang Ho-Yeol , Oh Yun-Seo , Kang Kyung-Yun
Published: February 2024

Currently, new agri-tech has been developed and adapted for the cultivation of crops using smart farming technologies, e.g., plant factories and hydroponics. Kelp (Laminaria japonica), which has a high industrial value, was considered as an alternative to chemicals for its eco-friendly and sustainably wide use in crop cultivation. In this study, a fermented kelp (FK) was developed for use in hydroponics. The FK contained various free and protein-bound amino acid compositions produced by fermenting the kelp with Saccharomyces cerevisiae. Supplementing FK as an aeroponic medium when cultivating ginseng sprouts (GSs) elevated the total phenolic and flavonoid contents. Additionally, seven ginsenosides (Rg1, Re, Rb1, Rc, Rg2, Rb2, and Rd) in GSs cultivated with FK in a smart-farm system were identified and quantified by a high-performance liquid chromatography-evaporative light scattering detector/mass spectrometry analysis. Administering FK significantly increased the ginsenosides in the GSs compared to the control group, which was cultivated with tap water. These results indicate the FK administration contributed to the increased accumulation of ginsenosides in the GSs. Overall, this study suggests that FK, which contains abundant nutrients for plant growth, can be used as a novel nutrient solution to enhance the ginsenoside content in GSs during hydroponic cultivation.
Adesmia pinifolia, a Native High-Andean Species, as a Potential Candidate for Phytoremediation of Cd and Hg
Authors: Parera Victoria , Pérez-Chaca M. Verónica , Gallardo Laura V. , Gatica-Aguilar Camila V. , Parera Carlos A. , Feresin Gabriela E.
Published: February 2024

This study highlights Adesmia pinifolia, a native high-Andean species, as a potential candidate for the phytoremediation of soils contaminated with Cd and Hg. In this work, a semi-hydronic assay with different doses of Cd (3, 4.5, and 6 mg L−1) and Hg (0.8, 1.2, and 1.6 mg L−1) was analysed to evaluate the establishment of plants, antioxidant defence systems, oxidative stress, and the ability to accumulate heavy metals. The results indicate high survival rates (>80%); however, Cd significantly reduced shoot and root biomass, while Hg increased root biomass with the 1.6 mg L−1 treatment. Cd and Hg tend to accumulate more in roots (2534.24 µg/g and 596.4 µg g−1, respectively) compared to shoots (398.53 µg g−1 and 140.8 µg g−1, respectively). A significant decrease in the bioconcentration factor of Cd and Hg in roots was observed as metal levels increased, reaching the maximum value at 3 mg L−1 (805.59 ± 54.38) and 0.8 mg L−1 (804.54 ± 38.09). The translocation factor, <1 for both metals, suggests that translocation from roots to shoots is limited. An overproduction of reactive oxygen species (ROS) was observed, causing lipid peroxidation and oxidative damage to plant membranes. Tolerance strategies against subsequent toxicity indicate that enhanced glutathione reductase (GR) activity and glutathione (GSH) accumulation modulate Cd and Hg accumulation, toxicity, and tolerance.
Hybrid-Aligned Fibers of Electrospun Gelatin with Antibiotic and Polycaprolactone Composite Membranes as an In Vitro Drug Delivery System to Assess the Potential Repair Capacity of Damaged Cornea
Authors: Shao Yi-Hsin , Huang Ssu-Meng , Liu Shih-Ming , Chen Jian-Chih , Chen Wen-Cheng
Published: February 2024

The cornea lacks the ability to repair itself and must rely on transplantation to repair damaged tissue. Therefore, creating alternative therapies using dressing membranes based on tissue engineering concepts to repair corneal damage before failure has become a major research goal. Themost outstanding features that are important in reconstructing a damaged cornea are the mechanical strength and transparency of the membrane, which are the most important standard considerations. In addition, preventing infection is an important issue, especially in corneal endothelial healing processes. The purpose of this study was to produce aligned fibers via electrospinning technology using gelatin (Gel) composite polycaprolactone (PCL) as an optimal transport and antibiotic release membrane. The aim of the composite membrane is to achieve good tenacity, transparency, antibacterial properties, and in vitro biocompatibility. Results showed that the Gel and PCL composite membranes with the same electrospinning flow rate had the best transparency. The Gel impregnated with gentamicin antibiotic in composite membranes subsequently exhibited transparency and enhanced mechanical properties provided by PCL and could sustainably release the antibiotic for 48 h, achieving good antibacterial effects without causing cytotoxicity. This newly developed membrane has the advantage of preventing epidermal tissue infection during clinical operations and is expected to be used in the reconstruction of damaged cornea in the future.
The Modification of Useful Injection-Molded Parts’ Properties Induced Using High-Energy Radiation
Authors: Bednarik Martin , Pata Vladimir , Ovsik Martin , Mizera Ales , Husar Jakub , Manas Miroslav , Hanzlik Jan , Karhankova Michaela
Published: February 2024

The modification of polymer materials’ useful properties can be applicable in many industrial areas due to the ability to make commodity and technical plastics (plastics that offer many benefits, such as processability, by injection molding) useful in more demanding applications. In the case of injection-molded parts, one of the most suitable methods for modification appears to be high-energy irradiation, which is currently used primarily for the modification of mechanical and thermal properties. However, well-chosen doses can effectively modify the properties of the surface layer as well. The purpose of this study is to provide a complex description of high-energy radiation’s (β radiation) influence on the useful properties of injection-molded parts made from common polymers. The results indicate that β radiation initiates the cross-linking process in material and leads to improved mechanical properties. Besides the cross-linking process, the material also experiences oxidation, which influences the properties of the surface layer. Based on the measured results, the main outputs of this study are appropriately designed regression models that determine the optimal dose of radiation.
Use of Thermodynamically Consistent Phase Equilibrium Data to Obtain a Generalized Padé-Type Model for the Henry’s Constants of Gases in Ionic Liquids
Authors: Faúndez Claudio A. , Forero Luis A. , Valderrama José O.
Published: February 2024

A generalized Padé-type expression is proposed for Henry’s constant of gases in ionic liquids. The constants are determined using an equation of state, and generalized expressions for the Henry’s constants of the gases in the ionic liquids are proposed. The solute gases included in the study were oxygen, hydrogen, and carbon monoxide in three solvent ionic liquids ([MDEA][Cl], [Bmim][PF6], and [Hmim][TF2N]). The Valderrama–Patel–Teja equation of state with the mixing rules of Kwak and Mansoori are employed to correlate the solubility data, to examine the thermodynamic consistency of the experimental data, and to determine the fugacity (fi) for each concentration (xi) of the solute gas in the liquid phase. From these data, the fugacity coefficients (fiL/xi) are determined to obtain Henry´s constant as Hi = lim(fiL/xi) when xi→0. The calculated Henry’s constants are correlated in terms of the temperature and acentric factor of the gases to finally obtain a generalized expression for Henry´s constant, Hi.
New Method for Capacity Evaluation of Offshore Low-Permeability Reservoirs with Natural Fractures
Authors: Wang Kun , Xie Mingying , Liu Weixin , Li Li , Liu Siyu , Huang Ruijie , Feng Shasha , Liu Guotao , Li Min
Published: February 2024

In recent years, the development of two offshore low-permeability oil fields has revealed unexpected challenges. The actual productivity of these fields significantly deviates from the designed capacity. Some wells even outperform the expectations for low-permeability limestone fields. This discrepancy primarily stems from a lack of accurate understanding of natural fractures before and after drilling, resulting in substantial errors in capacity assessment. This paper addresses these challenges by proposing a new production capacity model and evaluation method for both vertical and horizontal wells in low-permeability limestone reservoirs. The method leverages logging curve data, incorporating vertical gradation and fractal analysis to effectively represent the fracture’s complexity and connectivity. It uniquely considers factors such as fracture fractal dimensions, threshold pressure, and stress sensitivity, significantly enhancing prediction accuracy. Furthermore, by analyzing the longitudinal gradient in logging curves, the method effectively identifies strong heterogeneity, leading to more accurate capacity evaluations in actual fields. The results demonstrate that our model reduces the average prediction error to less than 15%, markedly outperforming traditional methods. Calculation results of the newly developed capacity formula align closely with actual production data and tracer test results, showcasing its practical applicability and potential for widespread use. This study notably advances the evaluation of reasonable production capacity in similar offshore reservoirs.
An Optimal Switching Sequence Model Predictive Control Scheme for the 3L-NPC Converter with Output LC Filter
Authors: Herrera Felipe , Mora Andrés , Cárdenas Roberto , Díaz Matías , Rodríguez José , Rivera Marco
Published: February 2024

In some applications of microgrids and distributed generation, it is necessary to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is usuallyconnected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltages and currents in these systems. However, these strategies have some drawbacks, particularly when multiple-input–multiple-output plants (MIMO) are controlled using single-input–single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross–coupling between different control loops and state variables. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves an optimisation problem to achieve control of the LC filter variables, i.e., currents and output voltages. Hardware-in-the-loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS–RT HIL platform and a dSPACE Microlab Box controller. In addition to the good dynamic performance of the proposed OSS–MPC, it is demonstrated using HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different operating conditions.
Observations from the Proteomics Bench
Authors: König Simone , Schork Karin , Eisenacher Martin
Published: February 2024

Many challenges in proteomics result from the high-throughput nature of the experiments. This paper first presents pre-analytical problems, which still occur, although the call for standardization in omics has been ongoing for many years. This article also discusses aspects that affect bioinformatic analysis based on three sets of reference data measured with different orbitrap instruments. Despite continuous advances in mass spectrometer technology as well as analysis software, data-set-wise quality control is still necessary, and decoy-based estimation, although challenged by modern instruments, should be utilized. We draw attention to the fact that numerous young researchers perceive proteomics as a mature, readily applicable technology. However, it is important to emphasize that the maximum potential of the technology can only be realized by an educated handling of its limitations.
Remote Sensing Identification and Spatiotemporal Change Analysis of Cladophora with Different Morphologies
Authors: Xu Wenting , Shen Qian , Zhang Bo , Yao Yue , Zhou Yuting , Shi Jiarui , Zhang Zhijun , Li Liwei , Li Junsheng
Published: February 2024

Cladophora qinghaiensis, an endemic species of Cladophora in saltwater lakes, was scientifically named in 2021 (hereafter referred to as Cladophora). Cladophora exists in different morphologies, including attached submerged Cladophora (AC), grown floating Cladophora (GFC), and death floating Cladophora (DFC). Previous satellite remote sensing has mainly focused on identifying floating algae. In this study, Qinghai Lake served as a case study, and a classification decision tree model (CDTM) was proposed. The model employed the chlorophyll spectral index (CSI) and the normalized difference vegetation index (NDVI) to differentiate AC, Floating Cladophora (FC), and water. Additionally, the floating Cladophora index (FCI) was introduced to further distinguish GFC and DFC within FC. The method was applicable to Sentinel-2 images from 2016–2023. Visual interpretation methods were used for Landsat series images from the summer months (July to September) to obtain the AC and FC. The results demonstrate that over the past 30 years, the areas inhabited by AC and FC have increased gradually. The three morphologies of Cladophora also exhibited seasonal variations, with growth observed annually in May–June, reaching peaks in August–September, and gradually declining in October. In addition, by combining factors such as water surface area and climatic factors, we analyzed the driving forces influencing the changes in Cladophora. In this research, AC and FC showed significant correlations with the water surface area, with correlation coefficients (r) of approximately 0.9 and 0.7, respectively. These new findings provide valuable insights regarding the spatiotemporal changes and underlying causes for different morphologies of Cladophora in global saline lakes.
A Multicomponent Linear Frequency Modulation Signal-Separation Network for Multi-Moving-Target Imaging in the SAR-Ground-Moving-Target Indication System
Authors: Ding Chang , Mu Huilin , Zhang Yun
Published: February 2024

Multi-moving-target imaging in a synthetic aperture radar (SAR) system poses a significant challenge owing to target defocusing and being contaminated by strong background clutter. Aiming at this problem, a new deep-convolutional-neural-network (CNN)-assisted method is proposed for multi-moving-target imaging in a SAR-GMTI system. The multi-moving-target signal can be modeled by a multicomponent LFM signal with additive perturbation. A fully convolutional network named MLFMSS-Net was designed based on an encoder–decoder architecture to extract the most-energetic LFM signal component from the multicomponent LFM signal in the time domain. Without prior knowledge of the target number, an iterative signal-separation framework based on the well-trained MLFMSS-Net is proposed to separate the multi-moving-target signal into multiple LFM signal components while eliminating the residual clutter. It works well, exhibiting high imaging robustness and low dependence on the system parameters, making it a suitable solution for practical imaging applications. Consequently, a well-focused multi-moving-target image can be obtained by parameter estimation and secondary azimuth compression for each separated LFM signal component. The simulations and experiments on both airborne and spaceborne SAR data showed that the proposed method is superior to traditional imaging methods in both imaging quality and efficiency.
An Innovative Sensor Integrated with GNSS and Accelerometer for Bridge Health Monitoring
Authors: Xie Yilin , Zhang Song , Meng Xiaolin , Nguyen Dinh Tung , Ye George , Li Haiyang
Published: February 2024

This paper presents an innovative integrated sensor that combines GNSS and a low-cost accelerometer for bridge health monitoring. GNSS and accelerometers are both significant and effective sensors for structural monitoring, but they each have limitations. The sampling rate of GNSS data is relatively low, making it challenging to capture high-frequency vibrations, while accelerometers struggle with low-frequency signals and are susceptible to environmental changes. Additionally, GNSS receivers and accelerometers are often installed separately, leading to challenges in data fusion processing due to differing temporal and geospatial references. The proposed integrated sensor addresses these issues by synchronizing GNSS and an accelerometer’s time and geospatial coordinate reference. This allows for a more accurate and reliable deformation and vibration measurement for bridge monitoring. The performance of the new sensor was assessed using a high-quality/cost Leica GM30 GNSS receiver and a Sherborne A545 accelerometer. Experiments conducted on the Wilford suspension bridge demonstrate the effectiveness of this innovative integrated sensor in measuring deformation and vibration for bridge health monitoring. The limitation of the low-cost MEMS (Micro Electromechanical System) accelerometer for the weak motion frequency detection is also pointed out.
Individual-Tree Segmentation from UAV–LiDAR Data Using a Region-Growing Segmentation and Supervoxel-Weighted Fuzzy Clustering Approach
Authors: Fu Yuwen , Niu Yifang , Wang Li , Li Wang
Published: February 2024

Accurate individual-tree segmentation is essential for precision forestry. In previous studies, the canopy height model-based method was convenient to process, but its performance was limited owing to the loss of 3D information, and point-based methods usually had high computational costs. Although some hybrid methods have been proposed to solve the above problems, most canopy height model-based methods are used to detect subdominant trees in one coarse crown and disregard the over-segmentation and accurate segmentation of the crown boundaries. This study introduces a combined approach, tested for the first time, for treetop detection and tree crown segmentation using UAV–LiDAR data. First, a multiscale adaptive local maximum filter was proposed to detect treetops accurately, and a Dalponte region-growing method was introduced to achieve crown delineation. Then, based on the coarse-crown result, the mean-shift voxelization and supervoxel-weighted fuzzy c-means clustering method were used to identify the constrained region of each tree. Finally, accurate individual-tree point clouds were obtained. The experiment was conducted using a synthetic uncrewed aerial vehicle (UAV)–LiDAR dataset with 21 approximately 30 × 30 m plots and an actual UAV–LiDAR dataset. To evaluate the performance of the proposed method, the accuracy of the remotely sensed biophysical observations and retrieval frameworks was determined using the tree location, tree height, and crown area. The results show that the proposed method was efficient and outperformed other existing methods.
Segmentation of Individual Tree Points by Combining Marker-Controlled Watershed Segmentation and Spectral Clustering Optimization
Authors: Liu Yuchan , Chen Dong , Fu Shihan , Mathiopoulos Panagiotis Takis , Sui Mingming , Na Jiaming , Peethambaran Jiju
Published: February 2024

Accurate identification and segmentation of individual tree points are crucial for assessing forest spatial distribution, understanding tree growth and structure, and managing forest resources. Traditional methods based on Canopy Height Models (CHM) are simple yet prone to over- and/or under-segmentation. To deal with this problem, this paper introduces a novel approach that combines marker-controlled watershed segmentation with a spectral clustering algorithm. Initially, we determined the local maxima within a series of variable windows according to the lower bound of the prediction interval of the regression equation between tree crown radius and tree height to preliminarily segment individual trees. Subsequently, using this geometric shape analysis method, the under-segmented trees were identified. For these trees, vertical tree crown profile analysis was performed in multiple directions to detect potential treetops which were then considered as inputs for spectral clustering optimization. Our experiments across six plots showed that our method markedly surpasses traditional approaches, achieving an average Recall of 0.854, a Precision of 0.937, and an F1-score of 0.892.
An Adaptive INS/CNS/SMN Integrated Navigation Algorithm in Sea Area
Authors: Tian Zhaoxu , Cheng Yongmei , Yao Shun , Li Zhenwei
Published: February 2024

In this paper, we present an innovative inertial navigation system (INS)/celestial navigation system (CNS)/scene-matching navigation (SMN) adaptive integrated navigation algorithm designed to achieve prolonged and highly precise navigation in sea areas. The algorithm establishes the structure of the INS/CNS/SMN integrated navigation system. To ensure the availability of CNS in the Nanhai Sea (South China Sea) area, a cloud and fog model is meticulously constructed. Three distinct types of sea area landmarks are defined, and an automated classification model for sea area landmarks, employing support vector machines (SVM), is developed. Corresponding matching methods and strategies for these landmarks are also delineated. Concurrently, the observable probability of each landmark is computed to generate a probability cloud, representing the usability of sea area landmarks. The proposed INS/CNS/SMN adaptive integrated navigation algorithm is simulated and validated across varied altitudes and trajectories in the sea area. The results show that CNS and SMN can dynamically assist INS in achieving prolonged and highly precise navigation.
YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion
Authors: Zhao Shan , Yuan Yang , Wu Xuan , Wang Yunlei , Zhang Fukai
Published: February 2024

In recent years, significant progress has been witnessed in the field of deep learning-based object detection. As a subtask in the field of object detection, traffic sign detection has great potential for development. However, the existing object detection methods for traffic sign detection in real-world scenes are plagued by issues such as the omission of small objects and low detection accuracies. To address these issues, a traffic sign detection model named YOLOv7-Traffic Sign (YOLOv7-TS) is proposed based on sub-pixel convolution and feature fusion. Firstly, the up-sampling capability of the sub-pixel convolution integrating channel dimension is harnessed and a Feature Map Extraction Module (FMEM) is devised to mitigate the channel information loss. Furthermore, a Multi-feature Interactive Fusion Network (MIFNet) is constructed to facilitate enhanced information interaction among all feature layers, improving the feature fusion effectiveness and strengthening the perception ability of small objects. Moreover, a Deep Feature Enhancement Module (DFEM) is established to accelerate the pooling process while enriching the highest-layer feature. YOLOv7-TS is evaluated on two traffic sign datasets, namely CCTSDB2021 and TT100K. Compared with YOLOv7, YOLOv7-TS, with a smaller number of parameters, achieves a significant enhancement of 3.63% and 2.68% in the mean Average Precision (mAP) for each respective dataset, proving the effectiveness of the proposed model.
A Novel Framed Slotted Aloha Medium Access Control Protocol Based on Capture Effect in Vehicular Ad Hoc Networks
Authors: Lai Lianyou , Song Zhongzhe , Xu Weijian
Published: February 2024

The capture effect is a frequently observed phenomenon in vehicular ad hoc networks (VANETs) communication. When conflicts arise during time slot access, failure to access does not necessarily occur; instead, successful access may still be achieved. The capture effect can enhance the likelihood of multiple access and improve communication efficiency. The security of VANETs communication is undoubtedly the primary concern. One crucial approach to enhance security involves the design of an efficient and reliable medium access control (MAC) protocol. Taking into account both aspects, we propose a novel framed slotted Aloha (FSA) MAC protocol model. Firstly, we derive the closed-form expression for the capture probability in the Rician fading channel in this paper. Subsequently, we analyze how the number of vehicles and time slots influence the success probability of vehicle access channels as well as examine the impact of the capture effect on this success probability. Then, under constraints regarding vehicle access channel success probability, we derive optimal values for slot numbers, access times, and transmission power while proposing a comprehensive implementation method to ensure high access channel success probabilities. We verify both theoretical derivations and proposed methods through simulation experiments.
Void-Engineered Metamaterial Delay Line with Built-In Impedance Matching for Ultrasonic Applications
Authors: Palanisamy Rajendra P. , Chavez Luis A. , Castro Raymond , Findikoglu Alp T.
Published: February 2024

Metamaterials exhibit unique ultrasonic properties that are not always achievable with traditional materials. However, the structures and geometries needed to achieve such properties are often complex and difficult to obtain using common fabrication techniques. In the present research work, we report a novel metamaterial acoustic delay line with built-in impedance matching that is fabricated using a common 3D printer. Delay lines are commonly used in ultrasonic inspection when signals need to be separated in time for improved sensitivity. However, if the impedance of the delay line is not perfectly matched with those of both the sensor and the target medium, a strong standing wave develops in the delay line, leading to a lower energy transmission. The presented metamaterial delay line was designed to match the acoustic impedance at both the sensor and target medium interfaces. This was achieved by introducing graded engineered voids with different densities at both ends of the delay line. The measured impedances of the designed metamaterial samples show a good match with the theoretical predictions. The experimental test results with concrete samples show that the acoustic energy transmission is increased by 120% and the standing wave in the delay line is reduced by over a factor of 2 compared to a commercial delay line.
Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications
Authors: Manokhin Mikhail , Chollet Paul , Desgreys Patricia
Published: February 2024

Analog-to-feature (A2F) conversion based on non-uniform wavelet sampling (NUWS) has demonstrated the ability to reduce energy consumption in wireless sensors while employed for electrocardiogram (ECG) anomaly detection. The technique involves extracting only relevant features for a given task directly from analog signals and conducting classification in the digital domain. Building on this approach, we extended the application of the proposed generic A2F converter to address a human activity recognition (HAR) task. The performed simulations include the training and evaluation of neural network (NN) classifiers built for each application. The corresponding results enabled the definition of valuable features and the hardware specifications for the ongoing complete circuit design. One of the principal elements constituting the developed converter, the integrator brought from the state-of-the-art design, was modified and simulated at the circuit level to meet our requirements. The revised value of its power consumption served to estimate the energy spent by the communication chain with the A2F converter. It consumes at least 20 and 5 times less than the chain employing the Nyquist approach in arrhythmia detection and HAR tasks, respectively. This fact highlights the potential of A2F conversion with NUWS in achieving flexible and energy-efficient sensor systems for diverse applications.
An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach
Authors: Abdallah Ismail Ben , Bouteraa Yassine
Published: February 2024

The utilization of robotic systems in upper limb rehabilitation has shown promising results in aiding individuals with motor impairments. This research introduces an innovative approach to enhance the efficiency and adaptability of upper limb exoskeleton robot-assisted rehabilitation through the development of an optimized stimulation control system (OSCS). The proposed OSCS integrates a fuzzy logic-based pain detection approach designed to accurately assess and respond to the patient’s pain threshold during rehabilitation sessions. By employing fuzzy logic algorithms, the system dynamically adjusts the stimulation levels and control parameters of the exoskeleton, ensuring personalized and optimized rehabilitation protocols. This research conducts comprehensive evaluations, including simulation studies and clinical trials, to validate the OSCS’s efficacy in improving rehabilitation outcomes while prioritizing patient comfort and safety. The findings demonstrate the potential of the OSCS to revolutionize upper limb exoskeleton-assisted rehabilitation by offering a customizable and adaptive framework tailored to individual patient needs, thereby advancing the field of robotic-assisted rehabilitation.
Analysis of VOCs in Liquids through Vaporization in a Tubular Oven Monitored by Chemical Ionization Mass Spectrometry
Authors: Abar Taous , Mestdagh Hélène , Heninger Michel , Lemaire Joel
Published: February 2024

The analysis of chemical compounds present at trace levels in liquids is important not only for environmental measurements but also, for example, in the health sector. The reference technique for the analysis of Volatile Organic Compounds (VOCs) in liquids is GC, which is difficult to use with an aqueous matrix. In this work, we present an alternative technique to GC to analyze VOCs in water. A tubular oven is used to completely vaporize the liquid sample deposited on a gauze. The oven is heated in the presence of a dinitrogen flow, and the gas is analyzed at the exit of the oven by a chemical ionization mass spectrometer developed in our laboratory. It is a low magnetic field Fourier Transform Ion Cyclotron Resonance (FT-ICR) optimized for real-time analysis. The Proton Transfer Reaction (PTR) used during the Chemical Ionization event results in the selective ionization of the VOCs present in the gas phase. The optimization of the desorption conditions is described for the main operating parameters: temperature ramp, liquid quantity, and nitrogen flow. Their influence is studied using a 100 ppmv aqueous toluene solution. The analytical method is then tested on a mixture of seven VOCs.
In-Situ Classification of Highly Deformed Corrugated Board Using Convolution Neural Networks
Authors: Rogalka Maciej , Grabski Jakub Krzysztof , Garbowski Tomasz
Published: February 2024

The extensive use of corrugated board in the packaging industry is attributed to its excellent cushioning, mechanical properties, and environmental benefits like recyclability and biodegradability. The integrity of corrugated board depends on various factors, including its geometric design, paper quality, the number of layers, and environmental conditions such as humidity and temperature. This study introduces an innovative application of convolutional neural networks (CNNs) for analyzing and classifying images of corrugated boards, particularly those with deformations. For this purpose, a special device with advanced imaging capabilities, including a high-resolution camera and image sensor, was developed and used to acquire detailed cross-section images of the corrugated boards. The samples of seven types of corrugated board were studied. The proposed approach involves optimizing CNNs to enhance their classification performance. Despite challenges posed by deformed samples, the methodology demonstrates high accuracy in most cases, though a few samples posed recognition difficulties. The findings of this research are significant for the packaging industry, offering a sophisticated method for quality control and defect detection in corrugated board production. The best classification accuracy obtained achieved more than 99%. This could lead to improved product quality and reduced waste. Additionally, this study paves the way for future research on applying machine learning for material quality assessment, which could have broader implications beyond the packaging sector.
E-Textiles for Sports and Fitness Sensing: Current State, Challenges, and Future Opportunities
Authors: Yang Kai , McErlain-Naylor Stuart A. , Isaia Beckie , Callaway Andrew , Beeby Steve
Published: February 2024

E-textiles have emerged as a fast-growing area in wearable technology for sports and fitness due to the soft and comfortable nature of textile materials and the capability for smart functionality to be integrated into familiar sports clothing. This review paper presents the roles of wearable technologies in sport and fitness in monitoring movement and biosignals used to assess performance, reduce injury risk, and motivate training/exercise. The drivers of research in e-textiles are discussed after reviewing existing non-textile and textile-based commercial wearable products. Different sensing components/materials (e.g., inertial measurement units, electrodes for biosignals, piezoresistive sensors), manufacturing processes, and their applications in sports and fitness published in the literature were reviewed and discussed. Finally, the paper presents the current challenges of e-textiles to achieve practical applications at scale and future perspectives in e-textiles research and development.
Microwave and Antenna Systems in Medical Applications
Authors: Lui Hoi-Shun , Persson Mikael
Published: February 2024

The non-ionizing nature of microwave radiation and the low cost of microwave electronics offer innovative solutions for medical diagnosis, treatment, and health monitoring [...]
Myoelectric, Myo-Oxygenation, and Myotonometry Changes during Robot-Assisted Bilateral Arm Exercises with Varying Resistances
Authors: Chan Hsiao-Lung , Meng Ling-Fu , Kao Yung-An , Chang Ya-Ju , Chang Hao-Wei , Chen Szi-Wen , Wu Ching-Yi
Published: February 2024

Robot-assisted bilateral arm training has demonstrated its effectiveness in improving motor function in individuals post-stroke, showing significant enhancements with increased repetitions. However, prolonged training sessions may lead to both mental and muscle fatigue. We conducted two types of robot-assisted bimanual wrist exercises on 16 healthy adults, separated by one week: long-duration, low-resistance workouts and short-duration, high-resistance exercises. Various measures, including surface electromyograms, near-infrared spectroscopy, heart rate, and the Borg Rating of Perceived Exertion scale, were employed to assess fatigue levels and the impacts of exercise intensity. High-resistance exercise resulted in a more pronounced decline in electromyogram median frequency and recruited a greater amount of hemoglobin, indicating increased muscle fatigue and a higher metabolic demand to cope with the intensified workload. Additionally, high-resistance exercise led to increased sympathetic activation and a greater sense of exertion. Conversely, engaging in low-resistance exercises proved beneficial for reducing post-exercise muscle stiffness and enhancing muscle elasticity. Choosing a low-resistance setting for robot-assisted wrist movements offers advantages by alleviating mental and physiological loads. The reduced training intensity can be further optimized by enabling extended exercise periods while maintaining an approximate dosage compared to high-resistance exercises.
Mapping the Therapeutic Options for Multiple Sclerosis in Brazil: A Comprehensive Analysis
Authors: Desidério Chamberttan Souza , Pessoa-Gonçalves Yago Marcos , Trevisan Rafael Obata , Dias-Sousa Marlos Aureliano , Bovi Weslley Guimarães , Rodrigues Wellington Francisco , da Silva Marcos Vinicius , Júnior Virmondes Rodrigues , Oliveira Carlo José Freire
Published: February 2024

Multiple sclerosis is an autoimmune disease that affects the central nervous system. In Brazil, there are currently several therapeutic options for the treatment of this condition, with some being distributed free of charge, while others are not included in the list of free medications. The objective of this article is to provide a pharmacoepidemiological analysis of the available medications in the country, covering their mechanisms of action, the historical context of approval and free distribution within the healthcare system, and their geographical distribution of application. Additionally, we discuss the impact of the inclusion of these medications on hospitalization and mortality rates in the country. We hope that this work serves as a resource for healthcare professionals to better understand pharmacoepidemiology and for health policymakers seeking data for the planning of public policies aimed at the treatment of multiple sclerosis.
Beyond the Shadow of Adults—Youth, Adultism, and Human Rights in the Contemporary Faroe Islands
Authors: Gaini Firouz
Published: February 2024

This article discusses young people’s human rights situation in the Faroe Islands today by addressing youth participation issues from a cultural adultism perspective. It argues that the local cultural values and intergenerational relations in the family influence the multilayered and shifting nature of ‘Faroese adultism’. My purpose is to explore the ways through which young people are challenging adultism in their everyday life practices: what do they intend to change and what do they wish to sustain in their cultural struggle? This article is mainly based on empirical data from focus group discussions with young participants. The findings reveal that young people from the Faroe Islands—located in the Nordic Atlantic—do not consider adultism to have a negative impact on their wellbeing. This article, relying on theoretical scholarship and ideas from youth studies and island studies, contributes to a more nuanced understanding of human rights in the context of a small (family-oriented) island community in cultural and social transformation.
From the Initial Celebration to the Current Disappointment, the Evolution of the Internet beyond Determinisms
Authors: Ramon-Pinat Ezequiel , Longhi Ludovico
Published: February 2024

In the first phase, the eruption of the Internet was embraced by academics who saw it as a way of involving young people in politics who had suffered from disaffection and rejection. They emphasized its emancipatory, horizontal, and participatory qualities. Decades later, a wave of disenchantment, apathy, and rejection of platforms has swept through the academy. The previous generation of technological determinists, who welcomed it with open arms, left the arena to their counterparts: the ones that claimed that we had no chance of participation and perpetuated industrial age exploitation. In this article, we will present the two opposite visions, but first, we will briefly review the Internet’s beginnings, its motivations, and its technical characteristics in order to better understand the two antagonistic positions.
Floating PV Systems as an Alternative Power Source: Case Study on Three Representative Islands of Indonesia
Authors: Esparza Ignacio , Olábarri Candela Ángela , Huang Luofeng , Yang Yifeng , Budiono Chayun , Riyadi Soegeng , Hetharia Wolter , Hantoro Ridho , Setyawan Dony , Utama I. K. A. P. , Wood Tim , Luo Zhenhua
Published: February 2024

Floating solar renewable energy is of enormous potential in Indonesia. This paper presents a comprehensive study of the design of Floating Photovoltaic (FPV) systems with Battery Energy Storage Systems (BESS) for three islands in Indonesia. These islands represent three typical scenarios in Indonesia (a) using a national grid powered by fossil fuel generators, (b) using a local grid powered by diesel generators, and (c) no grid at all. In-person surveys were conducted at these islands to collect data, and then FPV and BESS were designed to meet the demands of each island. Subsequently, the systems’ energy simulations were conducted using the System Advisor Model, demonstrating daily energy demand and supply in hour variation. Based on the results, a series of sustainability analyses were created from the aspects of economics, society, and the environment. The economic analysis demonstrated cost savings by using FPV to replace contemporary energy methods. The social analysis provides valuable insights into the local community, forming a demographic profile and obtaining perceptions and opinions regarding the new energy approach. The environmental analysis quantifies the potential CO2 emissions. Overall, the work provides valuable insights into the roadmap for implementing floating solar technologies in Indonesia which can also inform global ocean-based solar energy developments.
Supply Chain Concentration, Financing Constraints, and Carbon Performance
Authors: Wu Shuchang , Wang Han , Guo Yun , Fan Yingjie
Published: February 2024

Companies have been implementing various strategies, such as supply chain reconfiguration and process optimization, striving to find an efficient and effective solution for enhancing carbon performance over the last decade. Although various factors that may influence supply chain carbon performance have been investigated, the impact of supply chain concentration remains unclear due to insufficient research and inconsistencies in conclusions from the existing research. It is essential for enterprises to understand whether and to what extent supply chain concentration is an effective measure for improving carbon performance. Equally important is understanding the situations in which supply chain concentration works more effectively. In this research, we will construct fixed effects models using data from Chinese A-share listed companies from 2012 to 2021 to investigate the effects and mechanisms of supply chain concentration on corporate carbon performance. Our results suggest that supply chain concentration has a significant positive effect on carbon performance, with financing constraints playing a partial mediating role in this relationship. In addition, we have found that managerial myopia has a negative moderating effect on the positive relationship between supply chain concentration and carbon performance, whereas unexpected public events positively moderate this relationship. Further research indicates that the effect of supply chain concentration on carbon performance is stronger for state-owned enterprises and low-growth enterprises in China.
Corrosion Behaviour of Recycled Aluminium AlSi9Cu3(Fe) Machining Chips by Hot Extrusion and Thixoforming
Authors: Gudić Senka , Vrsalović Ladislav , Krolo Jure , Nagode Aleš , Dumanić Labetić Ivana , Lela Branimir
Published: February 2024

The corrosion properties of an EN AC AlSi9Cu3(Fe) alloy (reference sample (RS)) and samples produced by recycling chips of RS by direct hot extrusion (DHES) and subsequent thixoforming (TFS) were tested in 0.5 M NaCl solution. The plastic deformation changes the microstructure of RS, and brittle, coarse Si particles and intermetallic compounds (IMCs) were effectively broken into ultrafine-grained particles and redistributed homogeneously into the α-Al matrix in DHES. TFS exhibits a globular structure, and polyhedral clusters rich in Si and IMCs were observed along the grain boundary. Electrochemical measurements combined with surface characterisation show that the microstructure significantly influences the tested samples’ corrosive properties. It was confirmed that corrosion resistance increased in the following order: RS < TFS < DHES. Similarly, the corrosion potential becomes nobler, the corrosion current decreases, the passive area increases, and the oxide layer becomes more stable (higher resistance and thickness). Also, the percentage of the surface affected by corrosion and the volume of pits reduce. The effect of microstructure is particularly pronounced in the level of the corrosion current and the volume of pits formed. The corrosion current of DHES and TFS decreases by 4–5 times, while the pit volume of DHES and TFS decreases by several orders of magnitude compared to RS. The corrosion stability of DHES and TFS in relation to RS is a consequence of the comminution of the Si particles and the IMC. The refined and homogeneous microstructure contributes positively to forming a stable oxide film on DHES and TFS and increases their corrosion resistance in an aggressive environment. The applied recycling method represents an innovative and sustainable process for the recycling of semisolid materials, with lower energy consumption and less greenhouse gas emissions compared to conventional recycling. The fact that the products obtained through recycling have a significantly higher corrosion resistance further increases the economic and environmental impact of the process.
The Bottle House: Upcycling Plastic Bottles to Improve the Thermal Performance of Low-Cost Homes
Authors: Onyenokporo Nwakaego C. , Beizaee Arash , Adekeye Olutola F. , Oyinlola Muyiwa A.
Published: February 2024

Due to the effects of climate change, diminishing natural resources, and continuous urbanization, there is an increasing need for buildings to be more sustainable. This study explores the potential of upcycling plastic waste for the sustainable construction of low-cost homes in developing countries and contributes to filling the gap in existing studies regarding qualitative results of the in situ performance of buildings made from upcycled materials. This study compares the Bottle house with conventional buildings made of mud and cement. This study seeks to encourage the adoption of the bottle house concept for affordable housing by conducting a thermal comfort survey of its occupants. To obtain the thermal sensation vote (TSV) of the occupants, thermal comfort questionnaires were developed based on the seven-point ASHRAE thermal sensation scale. Additionally, a Testo 480 multifunction meter, which comprised an anemometer, radiant globe thermometer, air thermometer, and relative humidity probe, was used to calculate the predicted mean vote (PMV) concurrently. From the results of the TSV, mean votes of the participants of −2.0, 2.0, and 2.4 were observed for the bottle house, mud houses, and cement houses, respectively. In comparison, adjusted PMV mean values of 1.9, 2.1 and 2.1 were recorded for the bottle house, mud houses, and cement houses, respectively. The TSV and PMV results both indicate that the occupants of the bottle house felt more thermally comfortable when compared to occupants in the other dwellings. This can be attributed to the measures incorporated during the construction of the bottle house. Furthermore, the use of a simulation study helped proffer solutions to further improve the indoor temperatures of the buildings used in this study. The results of this paper will provide evidence of the prospects of upcycling plastic waste for construction and its impact on occupant’s thermal comfort when compared to conventional building materials.