bluuebunny/crossref_metadata_2025 huggingface dataset:
Stabilized Reversed Polymeric Micelles as Nanovector for Hydrophilic Compounds
Authors: Gagliardi Mariacristina , Vincenzi Agnese , Baroncelli Laura , Cecchini Marco
Published: February 2023

Small hydrophilic drugs are widely used for systemic administration, but they suffer from poor absorption and fast clearance. Their nanoencapsulation can improve biodistribution, targeted delivery, and pharmaceutical efficacy. Hydrophilics are effectively encapsulated in compartmented particles, such as liposomes or extracellular vesicles, which are biocompatible but poorly customizable. Polymeric vectors can form compartmental structures, also being functionalizable. Here, we report a system composed of polymeric stabilized reversed micelles for hydrophilic drugs encapsulation. We optimized the preparation procedure, and calculated the critical micellar concentration. Then, we developed a strategy for stabilization that improves micelle stability upon dilution. We tested the drug loading and delivery capabilities with creatine as a drug molecule. Prepared stabilized reversed micelles had a size of around 130 nm and a negative z-potential around −16 mV, making them functional as a drug carrier. The creatine cargo increased micelle size and depended on the loading conditions. The higher amount of loaded creatine was around 60 μg/mg of particles. Delivery tests indicated full release within three days in micelles with the lower cargo, while higher loadings can provide a sustained release for longer times. Obtained results are interesting and encouraging to test the same system with different drug cargoes.
Nanocomposite Foams with Balanced Mechanical Properties and Energy Return from EVA and CNT for the Midsole of Sports Footwear Application
Authors: Chang Boon Peng , Kashcheev Aleksandr , Veksha Andrei , Lisak Grzegorz , Goei Ronn , Leong Kah Fai , Tok Alfred ling Yoong , Lipik Vitali
Published: February 2023

Polymer foam that provides good support with high energy return (low energy loss) is desirable for sport footwear to improve running performance. Ethylene-vinyl acetate copolymer (EVA) foam is commonly used in the midsole of running shoes. However, EVA foam exhibits low mechanical properties. Conventional mineral fillers are usually employed to improve EVA’s mechanical performance, but the energy return is sacrificed. Here, we produced nanocomposite foams from EVA and multi-walled carbon nanotubes (CNT) using a chemical foaming process. Two kinds of CNT derived from the upcycling of commodity plastics were prepared through a catalytic chemical vapor deposition process and used as reinforcing and nucleating agents. Our results show that EVA foam incorporated with oxygenated CNT (O-CNT) demonstrated a more pronounced improvement of physical, mechanical, and dynamic impact response properties than acid-purified CNT (A-CNT). When CNT with weight percentage as low as 0.5 wt% was added to the nanocomposites, the physical properties, abrasion resistance, compressive strength, dynamic stiffness, and rebound performance of the EVA foams were improved significantly. Unlike the conventional EVA formulation filled with talc mineral fillers, the incorporation of CNT does not compromise the energy return of the EVA foam. From the long-cycle dynamic fatigue test, the CNT/EVA foam displays greater properties retention as compared to the talc/EVA foam. This work demonstrates a good balanced of mechanical-energy return properties of EVA nanocomposite foam with very low CNT content, which presents promising opportunities for lightweight–high rebound midsoles for running shoes.
Heat Transfer Efficiency and pMDI Curing Behavior during Hot-Pressing Process of Tea Oil Camellia (Camellia Oleifera Abel.) Shell Particleboard
Authors: Choupani Chaydarreh Kamran , Li Yongtao , Lin Xiuyi , Zhang Weiwei , Hu Chuanshuang
Published: February 2023

The use of agricultural biomass composites as new construction and building materials has grown rapidly in recent decades. Considering that energy consumption is one of the most important factors in production, the aim of this work is to examine how heat transfer is affected at various ratios and combinations of three-layer tea oil camellia shell (TOCS) based particleboard with the purpose of creating a mat-forming structure, which has the best physical and mechanical properties for furniture and construction use in a dry environment and consumes the least amount of energy. Additionally, it investigated how raw materials type affects the curing process of polymeric methylene diisocyanate (pMDI) using differential scanning calorimetry (DSC). According to the obtained data, the centerline temperature could reach a maximum of 125 °C after 3 min regardless of the materials or combinations, while the pMDI curing time was 100–110 °C. The results demonstrated that efficient heat transfer could help resin polymerization and improve panel properties. The effect of raw materials on the curing behavior of resin indicated that TOCS particles somehow caused more heat reactions at the curing point. It appeared that particleboard with a ratio of 40% commercial wood particles in the surface layers and 50% TOCS particles (mesh size: −3 + 14) in the core layer with a modulus of rupture (MOR) of 11.29 N/mm2 and internal bonding (IB) of 0.78 N/mm2 has the best properties and met EN 312: 2010 standard requirements for particleboard P2.
Numerical Analysis of Cracking Processes in RC Beams without Transverse Reinforcement
Authors: Smarzewski Piotr , Słowik Marta
Published: February 2023

The procedure of FEM calculations was presented in the paper. The numerical calculations concerned a simulation of crack distribution and propagation in concrete beams reinforced longitudinally without shear reinforcement. The analysis of the obtained FEM results showed different modes of failure in the beams when shear span-to-depth ratio was a/d = 2.5 and a/d = 1.8. In the analyzed beams, the ratio of longitudinal reinforcement and the mechanical properties of the steel bars were also changing parameters. The FEM results have showed that the shear failure of reinforced concrete beams without transverse reinforcement significantly depends on the ratio and yield strength of longitudinal steel bars. Furthermore, the results of numerical calculation for the beams of a/d = 2.5 were also juxtaposed with experiments performed by the author on two longitudinally reinforced concrete beams.
Evaluation of Babassu Cake Generated in the Extraction of the Oil as Feedstock for Biofuel Production
Authors: Silva Chastryane , Sousa Bruna , Nunes João , Malveira Jackson , Marques Rosali , Damasceno Luana , Braga Emanuelle , Lessa Tassio , Bertini Luciana , Maciel Maria , Rios Maria
Published: February 2023

The growing demand for energy and the concern about environmental impacts reinforce the necessity for renewable energy sources such as biofuels. In this study, cake generated in the babassu oil extraction was evaluated as a potential feedstock for solid biofuel production, and it contains a blend of cashew nutshell, sugarcane bagasse, carnauba straw, and carnauba stalk. All samples were characterized by proximate analysis and Higher Heating Value. Carbonization was used to improve energy performance and compaction to understand the mechanism and the characteristics of the biomasses compacted. In the extraction of babassu oil, fresh and aged (90 days) kernel samples were used. The fresh samples reached a yield of 59.8%, and the aged samples reached a yield of 70.66%. The carbonization of babassu cake was carried out in a Muffle furnace at temperatures of 250, 300, 350, and 400 °C. The fresh babassu cake showed an HHV of 23.06 MJ kg−1 and after carbonization of 28.07 (250 °C), 30.69 (300 °C), 28.24 (350 °C), and 18.27 MJ kg−1 (400 °C). At 400 °C, a decrease in HHV of 20.8% occurred, and an increase in Ash (%) of 195% occurred. Proximate analysis showed that biomasses are compatible, with some having a higher compatibility than other biological materials already used as fuels in the industry.
Lymphoscintigraphic Indications in the Diagnosis, Management and Prevention of Secondary Lymphedema
Authors: Mango Lucio
Published: February 2023

Secondary lymphedema is caused by damage to the lymphatic system, often following an oncological tumor removal intervention, or even by an accident. The diagnosis of lymphedema is not easy, because the disease can also be confused with other clinical manifestations (for example, venous insufficiency edema), though an experienced Lymphologist is usually able to diagnose it with good accuracy. To confirm the diagnosis, it is often necessary to resort to specialist imaging tests for an anatomo-functional definition of the pathology. Among these, lymphoscintigraphy is confirmed as the “gold standard” procedure for the diagnosis of lymphedema. Lymphoscintigraphy has been included in the Italian Guidelines by the Ministry of Health.
Fostering Practices of Salvation: On Communities of Care and Ecclesial Practices
Authors: Schaeffer Hans , Tamminga Koos
Published: February 2023

This article explores how Christian faith communities respond to challenges in health care. These challenges are described, and a broader context is sketched, through an exploration of an ethics of care. Subsequently, two examples of Christian communities who respond intentionally to the need for care are presented and studied by using four sub-elements of care (attentiveness, responsibility, competence, and responsiveness) as a heuristic lens. Next, the relationship between care and salvation is discussed. Concludingly, the article argues that Christian communities of care are well equipped for sustainable caregiving because of their spiritual resources, and because they provide a life-context well-suited for caregiving.
Primary Mandibular Condyle Xanthoma: Case Report and Literature Review
Authors: Negrello Sara , Pellacani Arrigo , Di Bartolomeo Mattia , Pollastri Giuseppe , Anesi Alexandre
Published: February 2023

Bone xanthoma is a rare benign primary bone lesion histologically characterized by sheets of foamy cells which are macrophages with a cytoplasm filled with droplets of fat. It is usually associated with endocrine or metabolic diseases, in the absence of which the lesion is called primary xanthoma. Because of the lack of pathognomonic radiologic and clinical features, they require a differential diagnosis with a broad spectrum of lesions with a varying degree of malignant potential. We describe a case of primary mandibular xanthoma of a 16-year-old girl without typical cutaneous manifestations and alterations in lipid values. The temporomandibular joint involvement at the mandibular condyle is peculiar in the case described here. We present even a qualitative systematic review of the literature on primary xanthoma of the jaws in others to draw up treatment guidelines.
Solitary Uncommon Metastasis in Non-Small Cell Lung Cancer
Authors: Cha Hyung Keun , Lim Jun Hyeok , Ryu Woo Kyung , Kim Lucia , Ryu Jeong-Seon
Published: February 2023

The major sites of metastasis in non-small cell lung cancer (NSCLC) are bones, the brain, adrenal glands, the liver, the contralateral lung, and distant lymph nodes. Solitary metastasis in an uncommon site is very rare; therefore, it has not often been reported. Identifying whether a solitary lesion is a metastatic lesion is important because it decisively influences the stage and treatment decisions. We report a series of cases of NSCLC diagnosis with uncommon solitary metastasis. (1) A 71-year-old man was diagnosed with poorly differentiated NSCLC after a bronchoscopic biopsy of a tumor in the bronchus of the right middle lobe. A hypermetabolic lesion was observed in the tail of the pancreas using positron emission tomography/computed tomography (PET/CT), and metastasis of NSCLC was confirmed using endoscopic ultrasound fine-needle aspiration (EUS-FNA). (2) A 77-year-old man was diagnosed with squamous cell carcinoma after a bronchoscopic biopsy of a tumor in the bronchus of the left upper lobe. A hypermetabolic lesion was observed in the bilateral lobes of the thyroid gland using PET/CT, and metastasis of the squamous cell carcinoma was confirmed by FNA and cytology. (3) A 79-year-old woman was diagnosed with adenocarcinoma by brushing cytology performed on the apicoposterior segmental bronchus of the left upper lobe. Hypermetabolic lesions were observed using PET/CT in the subcutaneous layer of the right back and the left breast, and metastases of adenocarcinoma were confirmed by biopsies in each lesion. These three patients were treated with platinum-based chemotherapy for stage IV lung cancer. With this case series, we recommend that, when a solitary lesion is observed in NSCLC patients, a tissue biopsy should be performed, even if the lesion is located in an organ where lung cancer metastasis is uncommon.
Financial Literacy Confidence and Retirement Planning: Evidence from China
Authors: Chen Bingzheng , Chen Ze
Published: February 2023

Though ample empirical evidence demonstrates the relationship between objective financial literacy and retirement planning, we have a limited understanding of the role of individuals’ subjective financial literacy in their retirement planning. In this study, we examine how individuals’ financial literacy confidence bias affects their retirement planning behaviors using survey data in China. Based on the difference between respondents’ subjective and objective financial literacy from survey data, we construct measures of individuals’ financial literacy overconfidence and underconfidence for empirical analysis. Our results document the critical role of individuals’ assessment of financial literacy in their retirement planning. We find that individuals’ financial literacy overconfidence (underconfidence) significantly promotes (demotes) their retirement planning behaviors.
Spatial–Temporal Evolution Monitoring and Ecological Risk Assessment of Coastal Wetlands on Hainan Island, China
Authors: Chen Haiyan , Li Dalong , Chen Yaning , Zhao Zhizhong
Published: February 2023

Coastal wetlands are located at the intersection of land and sea and provide extremely important ecological services. The coastal wetlands of estuarine harbors are representative parts of the coastal wetlands. Changes that occur in estuarine harbor wetlands are microcosms of the changes occurring in the coastal wetlands more generally. The coastal wetlands of Hainan Island, China, are coastal wetlands typical of tropical islands and are extremely sensitive to climate change. In the context of global sea level rise, studying the characteristics of spatial and temporal distribution of coastal wetlands on Hainan Island, as well as changes in their vulnerability, could provide scientific and technological support to address the adverse effects of climate change. Using nine typical estuarine harbor wetlands as target areas, this study systematically studies the spatial–temporal evolution of coastal wetlands on Hainan Island from 1990 to 2020. The results suggest the following: (1) The total area of coastal wetlands has remained relatively stable, but the area of artificial wetlands, especially aquaculture ponds, has increased significantly. There is a clear spatial variability in the changes in mangrove wetlands, with a clear increase in the area of areas with a high degree of protection, such as Dongzhai Harbor (DZG). The area of the areas with a high intensity of human activity has been significantly reduced, such as Bamen Bay (BMG). (2) The overall ecological risk of coastal wetlands is low, with the average wetland risk index (WRI) of all harbors being below 0.15. The higher the degree of protection, the lower the ecological risk of the area, such as DZG. Human activities are the main factor causing increased ecological risk in wetlands. (3) Climate-change-induced sea level rise and the intensification of human activities are the main determinants of future trends in the spatial distribution of coastal wetlands and wetland ecosystem stability. The results of this study provide guidance on the conservation and restoration of coastal wetlands.
Real Representation of the Polarimetric Scattering Matrix for Monostatic Radar
Authors: Ciuca Madalina , Vasile Gabriel , Anghel Andrei , Gay Michel , Ciochina Silviu
Published: February 2023

Synthetic aperture radar with polarimetric diversity is a powerful tool in remote sensing. Each pixel is described by the scattering matrix corresponding to the emission/reception polarization states (usually horizontal and vertical). The algebraic real representation, a block symmetric matrix form, is introduced to adopt a more comprehensive framework (non-restricted by reciprocity assumptions) in mapping the scattering matrix by the consimilarity equivalence relation. The proposed representation can reveal potentially new information. For example, its eigenvalue decomposition, which is itself a necessary step in obtaining the consimilarity transformation products, may be useful in characterizing the degree of reciprocity/nonreciprocity. As a consequence, it can be employed in testing the reciprocity compliance assumed with monostatic PolSAR data. Full-wave simulated polarimetric data confirm that oriented scatterers can present complex eigenvalues, even with the monostatic geometry.
Automatic Extraction of Urban Impervious Surface Based on SAH-Unet
Authors: Chang Ruichun , Hou Dong , Chen Zhe , Chen Ling
Published: February 2023

Increases in the area of impervious surfaces have occurred with urbanization. Such surfaces are an important indicator of urban expansion and the natural environment. The automatic extraction of impervious surface data can provide useful information for urban and regional management and planning and can contribute to the realization of the United Nations Sustainable Development Goal 11—Sustainable Cities and Communities. This paper uses Google Earth Engine (GEE) high-resolution remote sensing images and OpenStreetMap (OSM) data for Chengdu, a typical city in China, to establish an impervious surface dataset for deep learning. To improve the extraction accuracy, the Small Attention Hybrid Unet (SAH-Unet) model is proposed. It is based on the Unet architecture but with attention modules and a multi-scale feature fusion mechanism. Finally, depthwise-separable convolutions are used to reduce the number of model parameters. The results show that, compared with other classical semantic segmentation networks, the SAH-Unet network has superior precision and accuracy. The final scores on the test set were as follows: Accuracy = 0.9159, MIOU = 0.8467, F-score = 0.9117, Recall = 0.9199, Precision = 0.9042. This study provides support for urban sustainable development by improving the extraction of impervious surface information from remote sensing images.
A Three-Dimensional Block Adjustment Method for Spaceborne InSAR Based on the Range-Doppler-Phase Model
Authors: Wang Rui , Lv Xiaolei , Chai Huiming , Zhang Li
Published: February 2023

The block adjustment method can correct systematic errors in the bistatic Synthetic Aperture Radar Interferometry (InSAR) satellite system and effectively improve the accuracy of the InSAR-generated Digital Elevation Model (DEM). Presently, non-parametric methods, which use the polynomial to model the systematic errors of InSAR-generated DEMs, are most frequently used in spaceborne InSAR-DEM adjustment. However, non-parametric methods are not directly related to the physical parameters in the InSAR imaging process. Given the issue, this paper conducts adjustments in the parameter domain and proposes a three-dimensional block adjustment method for spaceborne bistatic InSAR systems based on the Range-Doppler-Phase (RDP) model. First, we theoretically analyze the sensitivities of spatial baseline, azimuth time, and slant range to the RDP geolocation model and confirm the analysis method with a simulated geolocation result. Second, we use total differential and differential geometry theories to derive adjustment equations of available control data based on sensitivity analysis. Third, we put forward an iterative solution strategy to solve the corrections of parallel baseline, azimuth time, and slant range to improve the plane and elevation accuracies of InSAR-generated DEMs. We used 29 scenes of TanDEM-X Co-registered Single look Slant range Complex (CoSSC) data to conduct simulated and real data experiments. The simulated results show that the proposed method can improve the accuracies of baseline, range, and timing to 0.05 mm, 0.1 m, and 0.006 ms, respectively. In the real data experiment, the proposed method improves the plane and elevation accuracies to 4.14 m and 1.34 m, respectively, and effectively suppresses the fracture phenomenon in the DEM mosaic area.
Introduction to a Thematic Set of Papers on Remote Sensing for Natural Hazards Assessment and Control
Authors: Mazzanti Paolo , Romeo Saverio
Published: February 2023

Remote sensing is currently showing high potential to provide valuable information at various spatial and temporal scales concerning natural hazards and their associated risks. Recent advances in technology and processing methods have strongly contributed to the development of disaster risk reduction research. In this Special Issue titled “Remote Sensing for Natural Hazards Assessment and Control”, we propose state-of-the-art research that specifically addresses multiple aspects of the use of remote sensing for natural hazards. The aim was to collect innovative methodologies, expertise, and capabilities to detect, assess monitor, and model natural hazards. In this regard, 18 open-access papers showcase scientific studies based on the exploitation of a broad range of remote sensing data and techniques, as well as focusing on a well-assorted sample of natural hazard types.
Carrier Characteristic Bias Estimation between GNSS Signals and Its Calibration in High-Precision Joint Positioning
Authors: Guo Yao , Rao Yongnan , Wang Xue , Zou Decai , Shi Huihui , Ji Ning
Published: February 2023

A distinctive feature of modern Global Navigation Satellite System (GNSS) signals is that they transmit multiple signal components at the same carrier frequencies. The idea of joints across the signal channels from the same carrier frequency and even across different frequencies has been presented in many studies for tracking purposes. Carrier joint tracking is required on the premise that the frequency and phase relationship between signals are nominal values, and the bias of carrier characteristics between signals is drowned in noise as the signal reaches the ground, which requires high-gain receiving equipment to restore the original signal. The space signal-quality monitoring and evaluation system built by the National Timing Center of the Chinese Academy of Sciences is based on a 40 m dish antenna, which can automatically track a single satellite and achieve a high-fidelity reception of navigation signals to a certain extent, realizing fine signal quality monitoring (SQM) of GNSS satellites. Based on this platform, we discuss four types of time distributions of the combined signals among different signal components and provide a method to estimate the carrier characteristic bias between GNSS signals. We derived the correction method of carrier characteristic bias in the joint reception by the joint tracking mathematical model. Under the conditions of narrow correlation and unobstructed case, the carrier characteristic deviation does not vary significantly with the correlator interval and the satellite elevation angle. Based on the results of stability analysis, it is recommended that the receivers should update the carrier frequency bias correction number of the intra-frequency signal and carrier phase bias correction number of the intra-frequency signal monthly. The carrier phase deviation correction number of the inter-frequency signal is performed daily. The measured data from satellites show that the phase accumulation error of the joint tracking carrier loop can be eliminated to achieve long-term stable tracking after frequency bias correction. After the carrier phase bias correction, the joint positioning accuracy of the B2a and B2b signals was improved by 0.81%, and those of the B1C, L1C, E1C, and B2a signals were improved by 0.35%, 0.04%, 0.20%, and 0.11%, respectively. The positioning accuracy improvement effect of inter-frequency signals was greater than that of intra-frequency signals after carrier phase correction.
Passive Microwave Remote Sensing of Snow Depth: Techniques, Challenges and Future Directions
Authors: Tanniru Srinivasarao , Ramsankaran RAAJ
Published: February 2023

Monitoring snowpack depth is essential in many applications at regional and global scales. Space-borne passive microwave (PMW) remote sensing observations have been widely used to estimate snow depth (SD) information for over four decades due to their responsiveness to snowpack characteristics. Many approaches comprised of static and dynamic empirical models, non-linear, machine-learning-based models, and assimilation approaches have been developed using spaceborne PMW observations. These models cannot be applied uniformly over all regions due to inherent limitations in the modelling approaches. Further, the global PMW SD products have masked out in their coverage critical regions such as the Himalayas, as well as very high SD regions, due to constraints triggered by prevailing topographical and snow conditions. Therefore, the current review article discusses different models for SD estimation, along with their merits and limitations. Here in the review, various SD models are grouped into four types, i.e., static, dynamic, assimilation-based, and machine-learning-based models. To demonstrate the rationale behind these drawbacks, this review also details various causes of uncertainty, and the challenges present in the estimation of PMW SD. Finally, based on the status of the available PMW SD datasets, and SD estimation techniques, recommendations for future research are included in this article.
MCANet: A Multi-Branch Network for Cloud/Snow Segmentation in High-Resolution Remote Sensing Images
Authors: Hu Kai , Zhang Enwei , Xia Min , Weng Liguo , Lin Haifeng
Published: February 2023

Because clouds and snow block the underlying surface and interfere with the information extracted from an image, the accurate segmentation of cloud/snow regions is essential for imagery preprocessing for remote sensing. Nearly all remote sensing images have a high resolution and contain complex and diverse content, which makes the task of cloud/snow segmentation more difficult. A multi-branch convolutional attention network (MCANet) is suggested in this study. A double-branch structure is adopted, and the spatial information and semantic information in the image are extracted. In this way, the model’s feature extraction ability is improved. Then, a fusion module is suggested to correctly fuse the feature information gathered from several branches. Finally, to address the issue of information loss in the upsampling process, a new decoder module is constructed by combining convolution with a transformer to enhance the recovery ability of image information; meanwhile, the segmentation boundary is repaired to refine the edge information. This paper conducts experiments on the high-resolution remote sensing image cloud/snow detection dataset (CSWV), and conducts generalization experiments on two publicly available datasets (HRC_WHU and L8 SPARCS), and the self-built cloud and cloud shadow dataset. The MIOU scores on the four datasets are 92.736%, 91.649%, 80.253%, and 94.894%, respectively. The experimental findings demonstrate that whether it is for cloud/snow detection or more complex multi-category detection tasks, the network proposed in this paper can completely restore the target details, and it provides a stronger degree of robustness and superior segmentation capabilities.
Using Nighttime Lights Data to Assess the Resumption of Religious and Socioeconomic Activities Post-COVID-19
Authors: Alahmadi Mohammed , Mansour Shawky , Dasgupta Nataraj , Martin David J.
Published: February 2023

The COVID-19 pandemic greatly impacted socioeconomic life globally. Nighttime-lights (NTLs) data are mainly related to anthropogenic phenomena and thus have the ability to monitor changes in socioeconomic activity. However, the overglow effect is a source of uncertainty and affects the applicability of NTL data for accurately monitoring socioeconomic changes. This research integrates the NTL and fine bare-land-cover data to construct a novel index named the Bare Adjusted NTL Index (BANTLI) to lessen the overglow uncertainty. BANTLI was used to measure the post-pandemic resumption of religious rituals and socioeconomic activity in Makkah and Madinah at different spatial levels. The results demonstrate that BANTLI significantly eliminates the overglow effect. In addition, BANTLI brightness recovered during the post-pandemic periods, but it has remained below the level of the pre-pandemic period. Moreover, not all wards and rings are affected equally: wards and rings that are near the city center experienced the most explicit reduction of BANTLI brightness compared with the suburbs. The Hajj pilgrimage period witnessed a larger decrease in BANTLI brightness than the pandemic period in Makkah. The findings indicate that (i) BANTLI successfully mitigates the overglow effect in the NTL data, and (ii) the cultural context is important to understand the impact of COVID-19.
Flexible Film Bulk Acoustic Resonator Based on Low-Porosity β-Phase P(VDF-TrFE) Film for Human Vital Signs Monitoring
Authors: Yu Zhentao , Gao Feng , He Xiangyu , Jin Hao , Dong Shurong , Cao Zhen , Luo Jikui
Published: February 2023

P(VDF-TrFE) is a promising material for flexible acoustic devices owing to its good piezoelectric performance and excellent stretchability. However, the high density of internal pores and large surface roughness of the conventional P(VDF-TrFE) results in a high propagation attenuation for acoustic waves, which limits its use in flexible acoustic devices. In this paper, a novel method based on two-step annealing is proposed to effectively remove the pores inside the P(VDF-TrFE) film and reduce its surface roughness. The obtained P(VDF-TrFE) film possesses excellent characteristics, including a high breakdown strength of >300 kV/mm, a high-purity β-phase content of more than 80%, and high piezoelectric coefficients (d33) of 42 pm/V. Based on the low-porosity β-phase P(VDF-TrFE) film, we fabricated flexible film bulk acoustic resonators (FBARs) which exhibit high sharp resonance peaks. The pressure sensor was made by sandwiching the FBARs with two PDMS microneedle patches. Heartbeat and respiration rate monitoring were achieved using the pressure sensor. This work demonstrates the feasibility of high-performance flexible piezoelectric acoustic resonators based on low-porosity P(VDF-TrFE) films, which could see wider applications in the wearable sensors for both physical and chemical sensing.
Healthcare Monitoring Using Low-Cost Sensors to Supplement and Replace Human Sensation: Does It Have Potential to Increase Independent Living and Prevent Disease?
Authors: Liu Zhuofu , Cascioli Vincenzo , McCarthy Peter W.
Published: February 2023

Continuous monitoring of health status has the potential to enhance the quality of life and life expectancy of people suffering from chronic illness and of the elderly. However, such systems can only come into widespread use if the cost of manufacturing is low. Advancements in material science and engineering technology have led to a significant decrease in the expense of developing healthcare monitoring devices. This review aims to investigate the progress of the use of low-cost sensors in healthcare monitoring and discusses the challenges faced when accomplishing continuous and real-time monitoring tasks. The major findings include (1) only a small number of publications (N = 50) have addressed the issue of healthcare monitoring applications using low-cost sensors over the past two decades; (2) the top three algorithms used to process sensor data include SA (Statistical Analysis, 30%), SVM (Support Vector Machine, 18%), and KNN (K-Nearest Neighbour, 12%); and (3) wireless communication techniques (Zigbee, Bluetooth, Wi-Fi, and RF) serve as the major data transmission tools (77%) followed by cable connection (13%) and SD card data storage (10%). Due to the small fraction (N = 50) of low-cost sensor-based studies among thousands of published articles about healthcare monitoring, this review not only summarises the progress of related research but calls for researchers to devote more effort to the consideration of cost reduction as well as the size of these components.
Position and Attitude Determination in Urban Canyon with Tightly Coupled Sensor Fusion and a Prediction-Based GNSS Cycle Slip Detection Using Low-Cost Instruments
Authors: Vanek Bálint , Farkas Márton , Rózsa Szabolcs
Published: February 2023

We present a position and attitude estimation algorithm of moving platforms based on the tightly coupled sensor fusion of low-cost multi baseline GNSS, inertial, magnetic and barometric observations obtained by low-cost sensors and affordable dual-frequency GNSS receivers. The sensor fusion algorithm is realized by an Extended Kalman Filter and estimates the states including GNSS receiver inter-channel biases, integer ambiguities and non-GNSS receiver biases. Tightly coupled sensor fusion increases the reliability of the position and attitude solution in challenging environments such as urban canyons by utilizing the inertial observations in case of GNSS outage. Moreover, GNSS observations can be efficiently used to mitigate IMU sensor drifts. Standard GNSS cycle slips detection methods, such as the application of triple differences or linear combinations such as Melbourne–Wübbena combination and the phase ionospheric residual extended TurboEdit method. However, these techniques are not well suited for the localization in quickly changing environments such as urban canyons. We present a new method of tightly coupled sensor fusion supported by a prediction based cycle slip detection technique, applied to a GNSS setup using three antennas leading to multiple moving baselines on the platform. Thus, not only the GNSS signal properties but also the dynamics of the moving platform are considered in the cycle slip detection. The developed algorithm is tested in an open-sky validation measurement and two sets of measurement in an urban canyon area. The sensor fusion algorithm processes the data sets using the proposed prediction-based cycle slip method, the loss-of-lock indicator-based, and for comparison, the Melbourne–Wübbena and the TurboEdit cycle slip detection methods are also included. The obtained position and attitude estimation results are compared to the internal solution of raw data source GNSS receivers and to the observations of a high-accuracy GNSS/INS unit including a fiber optic gyro. The validation test confirms the proper cycle slip detection in an ideal environment. The more challenging urban canyon test results show the reliability and the accuracy of the proposed method. In the case of the second urban canyon test, the proposed method improved the integer ambiguity resolution success rate by 19% and these results show the lowest horizontal and vertical coordinate distortion in comparison of the linear combination and the loss-of-lock-based cycle slip methods.
Three-Dimensional Scanning Applied for Flexible and In Situ Calibration of Galvanometric Scanner Systems
Authors: Mikkelstrup Anders Faarbæk , Nikolov Georgi Nikolaev , Kristiansen Morten
Published: February 2023

Galvanometric laser scanner (GLS) systems are widely used for materials processing due to their high precision, processing velocity, and repeatability. However, GLS systems generally suffer from scan field distortions due to joint and task space relationship errors. The problem is further pronounced in robotic applications, where the GLS systems are manipulated in space, as unknown errors in the relative pose of the GLS can be introduced. This paper presents an in situ, data-driven methodology for calibrating GLS systems using 3D scanning, emphasising the flexibility, generalisation, and automated industrial integration. Three-dimensional scanning serves two primary purposes: (1) determining the relative pose between the GLS system and the calibration plate to minimise calibration errors and (2) supplying an image processing algorithm with dense and accurate data to measure the scan field distortion based on the positional deviations of marked fiducials. The measured deviations are used to train a low-complexity Radial Basis Function (RBF) network to predict and correct the distorted scan field. The proposed method shows promising results and significantly reduces the scan field distortion without the use of specialised calibration tools and with limited knowledge of the optical design of the GLS system.
Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms
Authors: Przybyszewski Andrzej W. , Śledzianowski Albert , Chudzik Artur , Szlufik Stanisław , Koziorowski Dariusz
Published: February 2023

Humans are a vision-dominated species; what we perceive depends on where we look. Therefore, eye movements (EMs) are essential to our interactions with the environment, and experimental findings show EMs are affected in neurodegenerative disorders (ND). This could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to establish whether changes in EM-evoked responses can tell us about the progression of ND, such as Alzheimer’s (AD) and Parkinson’s diseases (PD), in different stages. In the present review, we have analyzed the results of psychological, neurological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with machine learning (ML) methods. Thanks to ML algorithms, from the high-dimensional parameter space, we were able to find significant EM changes related to ND symptoms that gave us insights into ND mechanisms. The predictive algorithms described use various approaches, including granular computing, Naive Bayes, Decision Trees/Tables, logistic regression, C-/Linear SVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes, e.g., related to place or/and orientation problems. In conclusion, EM parameters with clinical symptoms are powerful precision instruments that, in addition to their potential for predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.
Origami and Kirigami Structure for Impact Energy Absorption: Its Application to Drone Guards
Authors: Park Chan-Young , Lee Yoon-Ah , Jang Jinwoo , Han Min-Woo
Published: February 2023

As the use of drones grows, so too does the demand for physical protection against drone damage resulting from collisions and falls. In addition, as the flight environment becomes more complicated, a shock absorption system is required, in which the protective structure can be deformed based on the circumstances. Here, we present an origami- and kirigami-based structure that provides protection from various directions. This research adds a deformation capacity to existing fixed-shape guards; by using shape memory alloys, the diameter and height of the protective structure are controlled. We present three protective modes (1: large diameter/low height; 2: small diameter/large height; and 3: lotus shaped) that mitigate drone falls and side collisions. From the result of the drop impact test, mode 2 showed a 78.2% reduction in the maximum impact force at side impact. We incorporated kirigami patterns into the origami structures in order to investigate the aerodynamic effects of the hollow patterns. Airflow experiments yielded a macro understanding of flow-through behaviors on each kirigami pattern. In the wind speed experiment, the change in airflow velocity induced by the penetration of the kirigami pattern was measured, and in the force measurement experiment, the air force applied to the structure was determined.
Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms of Healthy Volunteers and Patients with Valvular Heart Diseases
Authors: Sieciński Szymon , Tkacz Ewaryst Janusz , Kostka Paweł Stanisław
Published: February 2023

Heart rate variability (HRV) is the physiological variation in the intervals between consecutive heartbeats that reflects the activity of the autonomic nervous system. This parameter is traditionally evaluated based on electrocardiograms (ECG signals). Seismocardiography (SCG) and/or gyrocardiography (GCG) are used to monitor cardiac mechanical activity; therefore, they may be used in HRV analysis and the evaluation of valvular heart diseases (VHDs) simultaneously. The purpose of this study was to compare the time domain, frequency domain and nonlinear HRV indices obtained from electrocardiograms, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) in healthy volunteers and patients with valvular heart diseases. An analysis of the time domain, frequency domain and nonlinear heart rate variability was conducted on electrocardiograms and gyrocardiograms registered from 29 healthy male volunteers and 30 patients with valvular heart diseases admitted to the Columbia University Medical Center (New York City, NY, USA). The results of the HRV analysis show a strong linear correlation with the HRV indices calculated from the ECG, SCG and GCG signals and prove the feasibility and reliability of HRV analysis despite the influence of VHDs on the SCG and GCG waveforms.
Event-Guided Image Super-Resolution Reconstruction
Authors: Guo Guangsha , Feng Yang , Lv Hengyi , Zhao Yuchen , Liu Hailong , Bi Guoling
Published: February 2023

The event camera efficiently detects scene radiance changes and produces an asynchronous event stream with low latency, high dynamic range (HDR), high temporal resolution, and low power consumption. However, the large output data caused by the asynchronous imaging mechanism makes the increase in spatial resolution of the event camera limited. In this paper, we propose a novel event camera super-resolution (SR) network (EFSR-Net) based on a deep learning approach to address the problems of low spatial resolution and poor visualization of event cameras. The network model is capable of reconstructing high-resolution (HR) intensity images using event streams and active sensor pixel (APS) frame information. We design the coupled response blocks (CRB) in the network that are able of fusing the feature information of both data to achieve the recovery of detailed textures in the shadows of real images. We demonstrate that our method is able to reconstruct high-resolution intensity images with more details and less blurring in synthetic and real datasets, respectively. The proposed EFSR-Net can improve the peak signal-to-noise ratio (PSNR) metric by 1–2 dB compared with state-of-the-art methods.
Electrochemical Analysis of Attoliter Water Droplets in Organic Solutions through Partitioning Equilibrium
Authors: Moon Hyeongkwon , Park Jun Hui
Published: February 2023

Herein, we report the electrochemical monitoring of attoliters of water droplets in an organic medium by the electrolysis of an extracted redox species from the continuous phase upon collisional events on an ultramicroelectrode. To obtain information about a redox-free water droplet in an organic solvent, redox species with certain concentrations need to be contained inside it. The redox species inside the droplet were delivered by a partitioning equilibrium between the organic phase and the water droplets. The mass transfer of the redox species from the surrounding organic phase to the droplet is very fast because of the radial diffusion, which resultantly establishes the equilibrium. Upon the collisional contact between the droplet and the electrode, the extracted redox species in the water droplets were selectively electrolyzed, even though the redox species in the organic continuous phase remained unreacted because of the different solvent environments. The electrolysis of the redox species in the droplets, where the concentration is determined by the equilibrium constant of the redox species in water/oil, can be used to estimate the size of single water droplets in an organic solution.
Analysis of the Accuracy Potential of a Stereo High-Speed Camera System in 3D Measurements in Highly Dynamic Experiments
Authors: Duran Vergara Laura Camila , Liebold Frank , Maas Hans-Gerd
Published: February 2023

In the context of setting up a stereo high-speed camera system for accurate 3D measurements in highly dynamic experiments, the potential of a “Fastcam SA-X2” stereo system is evaluated by testing different camera configurations and motion scenarios. A thorough accuracy analysis is performed using spatial rigid-body transformations and relative measurement analyses of photogrammetrically reconstructed surfaces of nondeformable objects. The effects of camera calibration, exposure time, object velocity, and object surface pattern quality on the quality of adjusted 3D coordinates are taken into consideration. While the exposure time does not significantly influence the quality of the static measurements, the results of dynamic experiments demonstrate that not only an insufficient frame rate but also an increased noise level resulting from short exposure times affects 3D coordinate accuracy. Using appropriate configurations to capture dynamic events, the errors in dynamic experiments do not differ significantly from the errors obtained in static measurements. A spatial mapping error of less than 1 μm is obtained through the experiments, with proper testing configurations for an object surface area of 5×20 mm. These findings are relevant for users of high-speed stereo imaging techniques to perform geometric 3D measurements, deformation, and crack analyses.
An Energy-Efficient T-Based Routing Topology for Target Tracking in Battery Operated Mobile Wireless Sensor Networks
Authors: Kalaivanan K. , Idayachandran G. , Vetrivelan P. , Henridass A. , Bhanumathi V. , Chang Elizabeth , Methuselah P. Sam
Published: February 2023

Real-time smart applications are now possible because to developments in communication and sensor technology. Wireless sensor networks (WSNs) are used to collect data from specific disaster sites, such as fire events, gas leaks, land mines, earthquake, landslides, etc., where it is necessary to know the exact location of the detected information to safely rescue the people. For instance, the detection and disposal of explosive materials is a difficult task because land mines consistently threaten human life. Here, the T-based Routing Topology (TRT) is suggested to gather data from sensors (metal detectors, Ground Penetrating Radars (GPR), Infra-Red sensors, etc.), Global Positioning System (GPS), and cameras in land mine-affected areas. Buried explosive materials can be found and located with high accuracy. Additionally, it will be simpler to eliminate bombs and reduce threats to humans. The efficiency of the suggested data collection method is evaluated using Network Simulator-2 (NS-2). Also, the proposed T-based routing topology requires a minimal number of nodes to cover the entire searching area and establish effective communication. In contrast, the number of nodes participating in the sensing area grows, as the depth of the tree increases in the existing tree topology-based data gathering. And for cluster topology, the number of nodes deployment depends on the transmission range of the sensor nodes.