bluuebunny/crossref_metadata_2025 huggingface dataset:
How to Develop Drug Delivery System Based on Carbohydrate Nanoparticles Targeted to Brain Tumors
Authors: Silant’ev Vladimir E. , Shmelev Mikhail E. , Belousov Andrei S. , Patlay Aleksandra A. , Shatilov Roman A. , Farniev Vladislav M. , Kumeiko Vadim V.
Published: May 2023

Brain tumors are the most difficult to treat, not only because of the variety of their forms and the small number of effective chemotherapeutic agents capable of suppressing tumor cells, but also limited by poor drug transport across the blood-brain barrier (BBB). Nanoparticles are promising drug delivery solutions promoted by the expansion of nanotechnology, emerging in the creation and practical use of materials in the range from 1 to 500 nm. Carbohydrate-based nanoparticles is a unique platform for active molecular transport and targeted drug delivery, providing biocompatibility, biodegradability, and a reduction in toxic side effects. However, the design and fabrication of biopolymer colloidal nanomaterials have been and remain highly challenging to date. Our review is devoted to the description of carbohydrate nanoparticle synthesis and modification, with a brief overview of the biological and promising clinical outcomes. We also expect this manuscript to highlight the great potential of carbohydrate nanocarriers for drug delivery and targeted treatment of gliomas of various grades and glioblastomas, as the most aggressive of brain tumors.
A Comprehensive Review on Processing, Development and Applications of Organofunctional Silanes and Silane-Based Hyperbranched Polymers
Authors: Indumathy Balaraman , Sathiyanathan Ponnan , Prasad Gajula , Reza Mohammad Shamim , Prabu Arun Anand , Kim Hongdoo
Published: May 2023

Since the last decade, hyperbranched polymers (HBPs) have gained wider theoretical interest and practical applications in sensor technology due to their ease of synthesis, highly branched structure but dimensions within nanoscale, a larger number of modified terminal groups and lowering of viscosity in polymer blends even at higher HBP concentrations. Many researchers have reported the synthesis of HBPs using different organic-based core-shell moieties. Interestingly, silanes, as organic-inorganic hybrid modifiers of HBP, are of great interest as they resulted in a tremendous improvement in HBP properties like increasing thermal, mechanical and electrical properties compared to that of organic-only moieties. This review focuses on the research progress in organofunctional silanes, silane-based HBPs and their applications since the last decade. The effect of silane type, its bi-functional nature, its influence on the final HBP structure and the resultant properties are covered in detail. Methods to enhance the HBP properties and challenges that need to be overcome in the near future are also discussed.
Advancements and Limitations in 3D Printing Materials and Technologies: A Critical Review
Authors: Iftekar Syed Fouzan , Aabid Abdul , Amir Adibah , Baig Muneer
Published: May 2023

3D printing has revolutionized various industries by enabling the production of complex designs and shapes. Recently, the potential of new materials in 3D printing has led to an exponential increase in the technology’s applications. However, despite these advancements, the technology still faces significant challenges, including high costs, low printing speeds, limited part sizes, and strength. This paper critically reviews the recent trends in 3D printing technology, with a particular focus on the materials and their applications in the manufacturing industry. The paper highlights the need for further development of 3D printing technology to overcome its limitations. It also summarizes the research conducted by experts in this field, including their focuses, techniques, and limitations. By providing a comprehensive overview of the recent trends in 3D printing, this review aims to provide valuable insights into the technology’s prospects.
Synchronized 3D Printing and Corona Charging for One-Step Prototyping of Polarized Polylactic Acid Electrets
Authors: Wang Zhiwei , Song Qinghua , Wu Huarui , Feng Baolong , Li Yeyuan , Bu Ling
Published: May 2023

Three-dimensional (3D) printing technology is advantageous in the fast prototyping of complex structures, but its utilization in functional material fabrication is still limited due to a lack of activation capability. To fabricate and activate the functional material of electrets, a synchronized 3D printing and corona charging method is presented to prototype and polarize polylactic acid electrets in one step. By upgrading the 3D printer nozzle and incorporating a needle electrode to apply high voltage, parameters such as needle tip distance and applied voltage level were compared and optimized. Under different experimental conditions, the average surface distribution in the center of the samples was −1498.87 V, −1115.73 V, and −814.51 V. Scanning electron microscopy results showed that the electric field contributes to keeping the printed fiber structure straight. The polylactic acid electrets exhibited relatively uniform surface potential distribution on a sufficiently large sample surface. In addition, the average surface potential retention rate was improved by 12.021-fold compared to ordinary corona-charged samples. The above advantages are unique to the 3D-printed and polarized polylactic acid electrets, proving that the proposed method is suitable for quickly prototyping and effectively polarizing the polylactic acid electrets simultaneously.
The Effects of Self-Polymerized Polydopamine Coating on Mechanical Properties of Polylactic Acid (PLA)–Kenaf Fiber (KF) in Fused Deposition Modeling (FDM)
Authors: Hamat Sanusi , Ishak Mohamad Ridzwan , Salit Mohd Sapuan , Yidris Noorfaizal , Showkat Ali Syamir Alihan , Hussin Mohd Sabri , Abdul Manan Muhamad Saifuldin , Ahamad Suffin Muhamad Qauyum Zawawi , Ibrahim Maliki , Mohd Khalil Ahmad Nabil
Published: May 2023

This research examines the impact of self-polymerized polydopamine (PDA) coating on the mechanical properties and microstructural behavior of polylactic acid (PLA)/kenaf fiber (KF) composites in fused deposition modeling (FDM). A biodegradable FDM model of natural fiber-reinforced composite (NFRC) filaments, coated with dopamine and reinforced with 5 to 20 wt.% bast kenaf fibers, was developed for 3D printing applications. Tensile, compression, and flexural test specimens were 3D printed, and the influence of kenaf fiber content on their mechanical properties was assessed. A comprehensive characterization of the blended pellets and printed composite materials was performed, encompassing chemical, physical, and microscopic analyses. The results demonstrate that the self-polymerized polydopamine coating acted as a coupling agent, enhancing the interfacial adhesion between kenaf fibers and the PLA matrix and leading to improved mechanical properties. An increase in density and porosity was observed in the FDM specimens of the PLA–PDA–KF composites, proportional to their kenaf fiber content. The enhanced bonding between kenaf fiber particles and the PLA matrix contributed to an increase of up to 13.4% for tensile and 15.3% for flexural in the Young’s modulus of PLA–PDA–KF composites and an increase of up to 30% in compressive stress. The incorporation of polydopamine as a coupling agent in the FDM filament composite led to an improvement in tensile, compressive, and flexural stresses and strain at break, surpassing that of pure PLA, while the reinforcement provided by kenaf fibers was enhanced more by delayed crack growth, resulting in a higher strain at break. The self-polymerized polydopamine coatings exhibit remarkable mechanical properties, suggesting their potential as a sustainable material for diverse applications in FDM.
Modification of the Physical Properties of a Nafion Film Due to Inclusion of n-Dodecyltriethylammonium Cation: Time Effect
Authors: Zamudio-García Javier , Martínez de Yuso María V. , Cuevas Ana L. , Marrero-López David , Benavente Juana
Published: May 2023

This study investigates the effects of modifying commercial Nafion-212 thin films with dodecyltriethylammonium cation (DTA+) on their electrical resistance, elastic modulus, light transmission/reflection and photoluminescence properties. The films were modified through a proton/cation exchange process for immersion periods ranging from 1 to 40 h. X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were employed to analyze the crystal structure and surface composition of the modified films. The electrical resistance and the different resistive contributions were determined via impedance spectroscopy. Changes in the elastic modulus were evaluated using stress–strain curves. Additionally, optical characterization tests, including light/reflection (250–2000 nm) and photoluminescence spectra, were also performed on both unmodified and DTA+-modified Nafion films. The results reveal significant changes in the electrical, mechanical and optical properties of the films, depending on the exchange process time. In particular, the inclusion of the DTA+ into the Nafion structure improved the elastic behavior of the films by significantly decreasing the Young modulus. Furthermore, the photoluminescence of the Nafion films was also enhanced. These findings can be used to optimize the exchange process time to achieve specific desired properties.
Fermentation-Derived Albumin-Based Hydrogels for Tissue Adhesion Applications
Authors: Della Sala Francesca , Malle Birgitte Mølholm , Ambrosio Luigi , Borzacchiello Assunta
Published: May 2023

Currently, most of the clinically available surgical glues and sealants lack elasticity, good adhesion and biocompatibility properties. Hydrogels as tissue adhesives have received extensive attention for their tissue-mimicking features. Here, a novel surgical glue hydrogel based on a fermentation-derived human albumin (rAlb) and biocompatible crosslinker for tissue-sealant applications has been developed. In order to reduce the risks of viral transmission diseases and an immune response, Animal-Free Recombinant Human Albumin from the saccharomyces yeast strain was used. A more biocompatible crosslinking agent, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC), was used and compared with glutaraldehyde (GA). The design of crosslinked albumin-based adhesive gels was optimized by varying the albumin concentration, the mass ratio between albumin and the crosslinking agent as well as the crosslinker type. Tissue sealants were characterized in terms of mechanical (tensile and shear), adhesive and in vitro biocompatibility properties. The results indicated that the mechanical and adhesive properties improved as the albumin concentration increased and the mass ratio between albumin and crosslinker decreased. Moreover, the EDC-crosslinked albumin gels have better biocompatibility properties than GA-crosslinked glues.
Multi Scale Analysis of the Retting and Process Effect on the Properties of Flax Bio-Based Composites
Authors: Ragoubi Mohamed , Lecoublet Morgan , Khennache Medhi , Poilane Christophe , Leblanc Nathalie
Published: May 2023

This research aimed to evaluate, at different scales (technical flax fiber, fiber band and flax composites, bio-based composites), the effect of retting and processing parameters on the biochemical, microstructural, and mechanical properties of flax-epoxy bio-based materials. On the technical flax fiber scale, a biochemical alteration of the fiber was observed as the retting increased (a decrease of the soluble fraction from 10.4 ± 0.2 to 4.5 ± 1.2% and an increase of the holocellulose fractions). This finding was associated with the degradation of the middle lamella, favoring the individualization of the flax fibers observed at retting (+). A direct link was established between the biochemical alteration of technical flax fibers and their associated mechanical properties (decrease of the ultimate modulus 69.9 to 43.6 GPa and maximum stress from 702 to 328 MPa). On the flax band scale, the mechanical properties are driven by the interface quality between the technical fibers. The highest maximum stresses were reached at level retting (0) with 26.68 MPa, which is lower compared to technical fiber. On the bio-based composites scale, setup 3 (T = 160 ∘C) and the high retting level (+) are the most relevant for a better mechanical response of flax bio-based materials.
Improvement of the Thermo-Oxidative Stability of Biobased Poly(butylene succinate) (PBS) Using Biogenic Wine By-Products as Sustainable Functional Fillers
Authors: Hiller Benedikt T. , Azzi Julia L. , Rennert Mirko
Published: May 2023

Biobased poly(butylene succinate) (PBS) represents one promising sustainable alternative to petroleum-based polymers. Its sensitivity to thermo-oxidative degradation is one reason for its limited application. In this research, two different varieties of wine grape pomaces (WPs) were investigated as fully biobased stabilizers. WPs were prepared via simultaneous drying and grinding to be used as bio-additives or functional fillers at higher filling rates. The by-products were characterized in terms of composition and relative moisture, in addition to particle size distribution analysis, TGA, and assays to determine the total phenolic content and the antioxidant activity. Biobased PBS was processed with a twin-screw compounder with WP contents up to 20 wt.-%. The thermal and mechanical properties of the compounds were investigated with DSC, TGA, and tensile tests using injection-molded specimens. The thermo-oxidative stability was determined using dynamic OIT and oxidative TGA measurements. While the characteristic thermal properties of the materials remained almost unchanged, the mechanical properties were altered within expected ranges. The analysis of the thermo-oxidative stability revealed WP as an efficient stabilizer for biobased PBS. This research shows that WP, as a low-cost and biobased stabilizer, improves the thermo-oxidative stability of biobased PBS while maintaining its key properties for processing and technical applications.
Design of Photovoltaic Power Generation Servo System Based on Discrete Adaptive Network Dynamic Surface Control Technology
Authors: Xu Xiaowei , Nie Ding , Xu Wenhua , Wang Ke , Chen Shan , Nie Yongjie , Fu Xiao , Xu Wan
Published: May 2023

In recent years, under the development of the dual carbon goal, the energy crisis has become increasingly serious, and China has also experienced serious power rationing. However, the research on dynamic surface control technology in solar tracking systems in nonlinear control systems is mostly based on continuous-time systems, while adaptive dynamic surface control based on discrete-time nonlinear control systems can describe an actual control system more accurately in the production process. It can effectively suppress interference with extremely high stability and safety. To solve the problem of low efficiency in photovoltaic power generation, this research first built a photovoltaic power generation servo system model based on the parameter of uncertainty. Then, a discrete adaptive neural network dynamic surface (DANNDS) controller was designed to solve the problems in the design of the traditional backstepping method. Finally, based on the designed method of a dynamic surface controller, a discrete adaptive neural network quantization controller (DANNQC) for the photovoltaic power generation servo system was designed by introducing external disturbance. The control parameters and their studied ranges were as follows: The reference signals were or1=sin(0.1t) and or2=cos(0.1t). The parameters of the virtual control law and the final control law were m11=0.01, m22=0.01, m12=0.02, m13=0.02, and m23=0.02. The time constant of the low-pass filter was ζ12=ζ13=ζ22=ζ23=0.005. The parameters of the parameter regulation law were ρ12=ρ13=ρ22=ρ23=0.0005 and a12=a13=20, a22=a23=22. The research results show that the MTE, RMSTE, and 2NTE scores of the height angle servo motor of the DANNDS control method were 0.0026, 7.0279 × 10−4, and 0.3552, respectively. The scores for each index of the azimuth servo motor were 0.0028, 8.9237 × 10−4, and 0.4511, respectively. The height angle tracking error for the DANNQC control method was [−0.02,0.022]. The azimuth tracking error was [−0.03,0.03]. In summary, the photovoltaic power generation servo system based on the DANNQC has a better control performance. By controlling the height angle and azimuth angles, it can better track the position of the sun and adjust the position of the photovoltaic panel in real time. The sun’s rays illuminate the photovoltaic panel at an appropriate angle to achieve maximum power generation efficiency, which is of great practical significance for the development of solar technology.
Reimagining Ecumenism for the 21st Century—Stăniloae’s Theology as a Source and Inspiration
Authors: Jemna Dănuț , Mănăstireanu Dănuț
Published: May 2023

There are many competent voices who estimate that in recent years ecumenism has been going through a crisis. Concern for ecumenical dialogue is becoming secondary for many theologians or members of the clergy, including hierarchs, who are preoccupied almost exclusively with addressing the problems facing their local and confessional communities. As a result, receptivity to ecumenical dialogue and cooperation is even lower among the faithful, who are preoccupied with assessing their own Christian identity in a socio-cultural context marked by rapid change and unprecedented challenges, of which secularism is only one of many. The disappointing assessment of the state of contemporary ecumenism, has led some ecumenists to an effort of identifying solutions for reimagining interconfessional dialogue in an ever-changing world. Theologians from all Christian traditions seek to contribute to identifying ways to unblock the current situation and to propose concrete approaches for rethinking ecumenism for future generations of believers. One of the ways suggested in the literature is to think of ecumenism less in terms of theological agreements, and more in terms of a process of mutual learning, considering that we can receive and offer our gifts in a mutual process, being aware of the need for each community to be open to such a perspective. In this paper, we argue that the constant receptivity to Fr. Dumitru Stăniloae’s theology, and to his anthropology in particular, that exists in Western traditions can be an opportunity for revitalising the ecumenical dialogue through the gift exchange model described above. We start from the premise that Fr. Stăniloae’s work represents an important gift not just for the Orthodox, but also for many Protestant and Catholic theologians, and we suggest that this direction can produce a reciprocal effect on Orthodox theologians to open up and receive the gifts of Western theology.
Ocean Clutter Characterization Based on PolSAR Data and Second-Order Statistics of Elementary Scatterers
Authors: Koukiou Georgia , Anastassopoulos Vassilis
Published: May 2023

New features are proposed for sea clutter characterization when PolSAR data are employed. Cameron coherent target decomposition is applied to characterize each SAR pixel by means of the 8 basic elementary scatterers obtained by this decomposition. Since the examined SAR pixel does not match exactly to a specific ideal elementary scatterer, the closest scatterer is assigned to this pixel along with its distance (closeness) from the ideal one. The features proposed are (a) the percentage of each elementary scatterer in the investigated region; (b) the distribution of the closeness of each declared elementary scattering mechanism to its ideal counterpart; (c) the co-occurrence of the same scattering mechanism, taking into consideration its distance from the ideal one; and (d) The co-occurrence of the different scattering mechanisms in pairs, taking again into consideration their distance from the ideal ones. Simultaneously, the skewness and the kurtosis and their 2D versions of the previously mentioned probabilities are employed to further improve ocean clutter characterization. The above features correspond to the sea state condition in each separate region, i.e., the wave height and the wind speed. A clear correspondence between the proposed features and the sea state conditions is established. Data were available from RADARSAT-2 and ALOS-1 PALSAR systems for four different ocean regions on Earth.
Using Imagery Collected by an Unmanned Aerial System to Monitor Cyanobacteria in New Hampshire, USA, Lakes
Authors: Bunyon Christine L. , Fraser Benjamin T. , McQuaid Amanda , Congalton Russell G.
Published: May 2023

With the increasing occurrence of cyanobacteria blooms, it is crucial to improve our ability to monitor impacted lakes accurately, efficiently, and safely. Cyanobacteria are naturally occurring in many waters globally. Some species can release neurotoxins which cause skin irritations, gastrointestinal illness, pet/livestock fatalities, and possibly additional complications after long-term exposure. Using a DJI M300 RTK Unmanned Aerial Vehicle equipped with a MicaSense 10-band dual camera system, six New Hampshire lakes were monitored from May to September 2022. Using the image spectral data coupled with in situ water quality data, a random forest classification algorithm was used to predict water quality categories. The analysis yielded very high overall classification accuracies for cyanobacteria cell (93%), chlorophyll-a (87%), and phycocyanin concentrations (92%). The 475 nm wavelength, normalized green-blue difference index—version 4 (NGBDI_4), and normalized green-red difference index—version 4 (NGRDI_4) indices were the most important features for these classifications. Logarithmic regressions illuminated relationships between single bands/indices with water quality data but did not perform as well as the classification algorithm approach. Ultimately, the UAS multispectral data collected in this study successfully classified cyanobacteria cell, chlorophyll-a, and phycocyanin concentrations in the studied NH lakes.
The Importance of Spatial Resolution in the Modeling of Methane Emissions from Natural Wetlands
Authors: Albuhaisi Yousef A. Y. , van der Velde Ype , Houweling Sander
Published: May 2023

An important uncertainty in the modeling of methane (CH4) emissions from natural wetlands is the wetland area. It is difficult to model wetlands’ CH4 emissions because of several factors, including its spatial heterogeneity on a large range of scales. In this study, we investigate the impact of model resolution on the simulated wetland methane emission for the Fennoscandinavian Peninsula. This is carried out using a high-resolution wetland map (100 × 100 m2) and soil carbon map (250 × 250 m2) in combination with a highly simplified CH4 emission model that is coarsened in five steps from 0.005° to 1°. We find a strong relation between wetland emissions and resolution, which is sensitive, however, to the sub-grid treatment of the wetland fraction. In our setup, soil carbon and soil moisture are positively correlated at a high resolution, with the wetland location leading to increasing CH4 emissions with increasing resolution. Keeping track of the wetland fraction reduces the impact of resolution. However, uncertainties in CH4 emissions remain high because of the large uncertainty in the representation of wetland the area, as demonstrated using the output of the WetChimp intercomparison over our study domain. Because of wetland mapping uncertainties, existing models are unlikely to realistically represent the correlation between soil moisture and soil carbon availability. The correlation is positive in our simplified model but may be different in more complex models depending on their method of representing substrate availability. Therefore, depending on the correlation, CH4 emissions may be over- or underestimated. As increasing the model resolution is an effective approach to mitigate the problem of accounting for the correlation between soil moisture and soil carbon and to improve the accuracy of models, the main message of this study is that increasing the resolution of global wetland models, and especially the input datasets that are used, should receive high priority.
Validation of Himawari-8 Sea Surface Temperature Retrievals Using Infrared SST Autonomous Radiometer Measurements
Authors: Zhang Haifeng , Beggs Helen , Griffin Christopher , Govekar Pallavi Devidas
Published: May 2023

This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Australian Bureau of Meteorology (Bureau) against shipborne radiometer SST measurements obtained from the Infrared SST Autonomous Radiometer (ISAR) onboard research vessel RV Investigator. Before being used, all data sets employed in this study have gone through careful quality control, and only the most trustworthy measurements are retained. With a large matchup database (31,871 collocations in total, including 16,418 during daytime and 15,453 during night-time), it is found that the Bureau H8 SST product is of good quality, with a mean bias ± standard deviation (SD) of −0.12 °C ± 0.47 °C for the daytime and −0.04 °C ± 0.37 °C for the night-time. The performance of the H8 data under different environmental conditions, determined by the observations obtained concurrently from RV Investigator, is examined. Daytime and night-time satellite data behave slightly differently. During the daytime, a cold bias can be seen under almost all environmental conditions, including for most values of wind speed, SST, and relative humidity. On the other hand, the performance of the night-time H8 SST product is consistently more stable under most meteorological conditions with the mean bias usually close to zero.
A Novel Method to Improve the Estimation of Ocean Tide Loading Displacements for K1 and K2 Components with GPS Observations
Authors: Pan Haidong , Xu Xiaoqing , Zhang Huayi , Xu Tengfei , Wei Zexun
Published: May 2023

The accurate estimation of ocean tide loading displacements is essential and necessary for geodesy, oceanic and geophysical studies. It is common knowledge that K1 and K2 tidal constituents estimated from Global Positioning System (GPS) observations are unsatisfactory because their tidal periods are nearly same to the revisit cycle or orbital period of GPS constellation. To date, this troublesome problem is not fully solved. In this paper, we revisit this important issue and develop a novel method based on the unique characteristic of tidal waves to separate GPS-system errors from astronomical K1/K2 tides. The well-known credo of smoothness indicates that tidal admittances of astronomical constituents in a narrow band can be expressed as smooth functions of tidal frequencies, while the interference of GPS-system errors seriously damages the smooth nature of observed tidal admittances. Via quadratic fitting, smooth functions of tidal frequencies for tidal admittances can be determined, thus, astronomical K1 and K2 tides can be interpolated using fitted quadratic functions. Three GPS stations are selected to demonstrate our method because of their typicality in terms of poor estimates of K1/K2 tidal parameters related to GPS-system errors. After removing GPS-systematical contributions based on our method, corrected K1/K2 tides at three GPS stations are much closer to the modeled K1/K2 tides from FES2014, which is one of the most accurate tide models. Furthermore, the proposed method can be easily applied to other areas to correct GPS-system errors because their smooth nature is valid for global tidal signals.
Comparison of Three Active Microwave Models of Forest Growing Stock Volume Based on the Idea of the Water Cloud Model
Authors: Zhang Tian , Sun Hao , Xu Zhenheng , Xu Huanyu , Wu Dan , Wu Ling
Published: May 2023

Forest growing stock volume (GSV) is an essential aspect of ecological carbon stock monitoring. The successive launches of spaceborne microwave satellites have provided a broader way to use microwave remote sensing to monitor forest accumulation. Currently, the inversion parameterization models of active microwave remote sensing stock volume mainly include the interferometric water cloud (IWCM), BIOMASAR, and Siberia. Among them, the IWCM introduces backscattering and coherence, the BIOMASAR model only introduces backscattering, and the Siberia model only introduces coherence. Although these three models combine the backscatter coefficient and coherence of SAR to estimate volume accumulation, the performance of the models has not been evaluated at the same time in the same area. Therefore, this article starts from the perspective of the three combinations of coherence and backscattering, relies on three models that do not require measured data, and evaluates the accuracy of the models’ overall inversion of GSV. In addition, we combine precipitation meteorological information, vegetation types, and seasonal variation to separately explore model performance. The comparison results show that the IWCM model is relatively stable in the process of stock volume inversion and is more sensitive to the vegetation types of coniferous and deciduous forests. The influence of seasons and precipitation on the model is weak, and the accuracy of the multi-time-series model is slightly improved. The Siberia model has a good storage volume inversion effect in this study area, but the multiple time series did not improve the model accuracy. The BIOMASAR model is simple, and its performance was slightly inferior in this study area. Precipitation can negatively affect BIOMASAR. The model results for multiple time series outperform those for single time. In summary, the stability of IWCM is more suitable for research with unknown information. The BIOMASAR model is simple, does not require coherence calculations, and is ideal for the estimation of large-scale national or world-level storage distributions. The Siberian model performs better in small regions and smaller spatiotemporal baselines.
Land Subsidence Monitoring and Building Risk Assessment Using InSAR and Machine Learning in a Loess Plateau City—A Case Study of Lanzhou, China
Authors: Xu Yuanmao , Wu Zhen , Zhang Huiwen , Liu Jie , Jing Zhaohua
Published: May 2023

As a representative city located in the Loess Plateau region of China, Lanzhou is affected by various environmental and engineering factors, such as precipitation, earthquake subsidence, and building construction, which all lead to frequent geological disasters. Obtaining information on land subsidence over a long time series helps us grasp the patterns of change in various types of ground hazard. In this paper, we present the results of using Interferometric Synthetic Aperture Radar (InSAR) to monitor land subsidence in the main urban area of Lanzhou from 26 October 2014 to 12 December 2021. The main influential factors leading to subsidence were analyzed and combined via machine learning simulation to assess the land subsidence risk grade distribution of a building unit. The results show that the annual average deformation rate in Lanzhou ranged from −18.74 to 12.78 mm/yr. Linear subsidence dominated most subsidence areas in Lanzhou during the monitoring period. The subsidence areas were mainly distributed along the Yellow River, the railway, and villages and towns on the edges of urban areas. The main areas where subsidence occurred were the eastern part of Chengguan District, the railway line in Anning District, and the southern parts of Xigu District and Qilihe urban area, accounting for 38.8, 43.5, 32.5, and 51.8% of the area of their respective administrative districts, respectively. The random forest model analysis results show that the factors influencing surface subsidence in Lanzhou were, in order of importance, precipitation, the distribution of faults, the lithology of strata, high-rise buildings, and the distance to the river and railway. Lanzhou experienced excessive groundwater drainage in some areas from 2015 to 2017, with a 1 m drop in groundwater and 14.61 mm surface subsidence in the most critical areas. At the same time, extensive subsidence occurred in areas with highly compressible loess ground and most railway sections, reaching a maximum of −11.68 mm/yr. More than half of the super-tall building areas also showed settlement funnels. The area at a very high risk of future subsidence in Lanzhou covers 22.02 km2, while the high-subsidence-risk area covers 54.47 km2. The areas at greatest risk of future subsidence are Chengguan District and Qilihe District. The city contains a total of 51,163 buildings in the very high-risk area, including about 44.57% of brick-and-timber houses, 51.36% of old housing, and 52.78% of super-tall buildings, which are at especially high risk of subsidence, threatening the lives and properties of the population. The deformation results reveal poor building safety in Lanzhou, providing an essential basis for future urban development and construction.
PPA-Net: Pyramid Pooling Attention Network for Multi-Scale Ship Detection in SAR Images
Authors: Tang Gang , Zhao Hongren , Claramunt Christophe , Zhu Weidong , Wang Shiming , Wang Yide , Ding Yuehua
Published: May 2023

In light of recent advances in deep learning and Synthetic Aperture Radar (SAR) technology, there has been a growing adoption of ship detection models that are based on deep learning methodologies. However, the efficiency of SAR ship detection models is significantly impacted by complex backgrounds, noise, and multi-scale ships (the number of pixels occupied by ships in SAR images varies significantly). To address the aforementioned issues, this research proposes a Pyramid Pooling Attention Network (PPA-Net) for SAR multi-scale ship detection. Firstly, a Pyramid Pooled Attention Module (PPAM) is designed to alleviate the influence of background noise on ship detection while its parallel component favors the processing of multiple ship sizes. Different from the previous attention module, the PPAM module can better suppress the background noise in SAR images because it considers the saliency of ships in SAR images. Secondly, an Adaptive Feature Balancing Module (AFBM) is developed, which can automatically balance the conflict between ship semantic information and location information. Finally, the detection capabilities of the ship detection model for multi-scale ships are further improved by introducing the Atrous Spatial Pyramid Pooling (ASPP) module. This innovative module enhances the detection model’s ability to detect ships of varying scales by extracting features from multiple scales using atrous convolutions and spatial pyramid pooling. PPA-Net achieved detection accuracies of 95.19% and 89.27% on the High-Resolution SAR Images Dataset (HRSID) and the SAR Ship Detection Dataset (SSDD), respectively. The experimental results demonstrate that PPA-Net outperforms other ship detection models.
Slight Aware Enhancement Transformer and Multiple Matching Network for Real-Time UAV Tracking
Authors: Deng Anping , Han Guangliang , Chen Dianbin , Ma Tianjiao , Liu Zhichao
Published: May 2023

Based on the versatility and effectiveness of the siamese neural network, the technology of unmanned aerial vehicle visual object tracking has found widespread application in various fields including military reconnaissance, intelligent transportation, and visual positioning. However, due to complex factors, such as occlusions, viewpoint changes, and interference from similar objects during UAV tracking, most existing siamese neural network trackers struggle to combine superior performance with efficiency. To tackle this challenge, this paper proposes a novel SiamSTM tracker that is based on Slight Aware Enhancement Transformer and Multiple matching networks for real-time UAV tracking. The SiamSTM leverages lightweight transformers to encode robust target appearance features while using the Multiple matching networks to fully perceive response map information and enhance the tracker’s ability to distinguish between the target and background. The results are impressive: evaluation results based on three UAV tracking benchmarks showed superior speed and precision. Moreover, SiamSTM achieves over 35 FPS on NVIDIA Jetson AGX Xavier, which satisfies the real-time requirements in engineering.
The Changes in Dominant Driving Factors in the Evolution Process of Wetland in the Yellow River Delta during 2015–2022
Authors: Wei Cuixia , Guo Bing , Lu Miao , Zang Wenqian , Yang Fei , Liu Chuan , Wang Baoyu , Huang Xiangzhi , Liu Yifeng , Yu Yang , Li Jialin , Xu Mei
Published: May 2023

Most of the previous studies exploring the changing patterns of wetland in the Yellow River Delta (YRD) were conducted based on sparse time-series images, which ignored its severe environmental gradient and rapid evolution process of the wetland. The changes in the dominant factors in the evolution of the wetland in the YRD are not clear. This study used the dense time-series Sentinel-2 images to establish a wetland database of the YRD, and then analyzed the spatial distribution characteristics of, and temporal changes in, the wetland during 2015–2022. Finally, the dominant factors of the spatio-temporal evolutions of the wetland were explored and revealed. The results showed the following. (1) During 2015–2022, the wetland in the YRD was dominated by artificial wetland, accounting for 54.02% of the total wetland area in the study area. In 2015–2022, the total wetland area increased by 309.90 km2, including an increase of 222.63 km2 in natural wetlands and 87.27 km2 in artificial wetlands. In the conversion between wetland types, 218.73 km2 of artificial wetlands were converted into natural wetlands, and 75.18 km2 of natural wetlands were converted into artificial wetlands. The patch density of rivers, swamps, and salt pans increased, showing a trend of fragmentation. However, the overall degree of landscape fragmentation in wetlands weakened. The trend of changes in the number of patches and landscape shape index was the same, while the trend of changes in Shannon’s diversity index and Contagion index was completely opposite. (2) Natural factors, such as precipitation (0.51, 2015; 0.65, 2016), DEM (0.57, 2017; 0.47, 2018; 0.49, 2020; 0.46, 2021), vegetation coverage (0.59, 2019), and temperature (0.48, 2022), were the dominant influencing factors of wetland changes in the YRD. The dominant single factor causing the changes in artificial wetlands was vegetation coverage, while socio-economic factors had lower explanatory power, with the average q value of 0.18. (3) During 2015–2022, the interactions between the natural and artificial factors of the wetland changes were mostly nonlinear and showed double-factor enhancement. The interactions between temperature and sunshine hours had the largest explanatory power for natural wetland change, while interactions between precipitation and vegetation coverage, and between temperature and vegetation coverage, had large contribution rates for artificial wetland change. The interactions among natural factors had the greatest impacts on wetland change, followed by interactions between natural factors and socio-economic factors, while interactions among socio-economic factors had more slight impacts on wetland change. The results can provide a scientific basis for regional wetland protection and management.
On the Consistency between a Classical Definition of the Geoid-to-Quasigeoid Separation and Helmert Orthometric Heights
Authors: Tenzer Robert , Nsiah Ababio Albertini
Published: May 2023

It is acknowledged that a classical definition of the geoid-to-quasigeoid separation as a function of the simple planar Bouguer gravity anomaly is compatible with Helmert’s definition of orthometric heights. According to Helmert, the mean actual gravity along the plumbline between the geoid and the topographic surface in the definition of orthometric height is computed approximately from the measured surface gravity by applying the Poincaré-Prey gravity reduction. This study provides theoretical proof and numerical evidence that this assumption is valid. We demonstrate that differences between the normal and (Helmert) orthometric corrections are equivalent to the geoid-to-quasigeoid separation differences computed for individual levelling segments. According to our theoretical estimates, maximum differences between these 2 quantities should be less than ±1 mm. By analogy, differences between the Molodensky normal and Helmert orthometric heights at levelling benchmarks should be equivalent to the geoid-to-quasigeoid separation computed from the Bouguer gravity data. Both theoretical findings are inspected numerically by using levelling and gravity data along selected closed levelling loops of the vertical control network in Hong Kong. Results show that values of the geoid-to-quasigeoid separation at levelling benchmarks differ less than ±0.1 mm from differences between the normal and orthometric corrections. Relatively large differences (slightly exceeding 2 mm) between values of the geoid-to-quasigeoid separation and differences between the normal and (Helmert) orthometric heights at levelling benchmarks are explained by errors in levelling measurements rather than by inconsistencies in computed values of the geoid-to-quasigeoid separation and (Helmert) orthometric correction.
Temperature Effects Removal from Non-Stationary Bridge–Vehicle Interaction Signals for ML Damage Detection
Authors: Niyozov Sardorbek , Domaneschi Marco , Casas Joan R. , Delgadillo Rick M.
Published: May 2023

Bridges are vital components of transport infrastructures, and therefore, it is of utmost importance that they operate safely and reliably. This paper proposes and tests a methodology for detecting and localizing damage in bridges under both traffic and environmental variability considering non-stationary vehicle-bridge interaction. In detail, the current study presents an approach to temperature removal in the case of forced vibrations in the bridge using principal component analysis, with detection and localization of damage using an unsupervised machine learning algorithm. Due to the difficulty in obtaining real data on undamaged and later damaged bridges that are simultaneously influenced by traffic and temperature changes, the proposed method is validated using a numerical bridge benchmark. The vertical acceleration response is derived from a time-history analysis with a moving load under different ambient temperatures. The results show how machine learning algorithms applied to bridge damage detection appear to be a promising technique to efficiently solve the problem’s complexity when both operational and environmental variability are included in the recorded data. However, the example application still shows some limitations, such as the use of a numerical bridge and not a real bridge due to the lack of vibration data under health and damage conditions, and with varying temperatures; the simple modeling of the vehicle as a moving load; and the crossing of only one vehicle present in the bridge. This will be considered in future studies.
PT-Symmetric LC Passive Wireless Sensing
Authors: Chen Dong-Yan , Dong Lei , Huang Qing-An
Published: May 2023

Parity–time (PT) symmetry challenges the long-held theoretical basis that only Hermitian operators correspond to observable phenomena in quantum mechanics. Non-Hermitian Hamiltonians satisfying PT symmetry also have a real-valued energy spectrum. In the field of inductor–capacitor (LC) passive wireless sensors, PT symmetry is mainly used for improving performance in terms of multi-parameter sensing, ultrahigh sensitivity, and longer interrogation distance. For example, the proposal of both higher-order PT symmetry and divergent exceptional points can utilize a more drastic bifurcation process around exceptional points (EPs) to accomplish a significantly higher sensitivity and spectral resolution. However, there are still many controversies regarding the inevitable noise and actual precision of the EP sensors. In this review, we systematically present the research status of PT-symmetric LC sensors in three working areas: exact phase, exceptional point, and broken phase, demonstrating the advantages of non-Hermitian sensing concerning classical LC sensing principles.
A Microstrip Transmission Line Biosensor to Measure the Interaction between Microliter Aqueous Solutions and 1.0–17.0 GHz Radio Frequencies
Authors: Godfrey Mary , Ewert Daniel , Striker Ryan , Braaten Benjamin
Published: May 2023

Radio frequency (RF) biosensors are an expanding field of interest because of the ability to design noninvasive, label-free, low-production-cost sensing devices. Previous works identified the need for smaller experimental devices, requiring nanoliter to milliliter sampling volumes and increased capability of repeatable and sensitive measurement capability. The following work aims to verify a millimeter-sized, microstrip transmission line biosensor design with a microliter well operating on a broadband radio frequency range of 1.0–17.0 GHz. Three successive experiments were performed to provide evidence for (1) repeatability of measurements after loading/unloading the well, (2) sensitivity of measurement sets, and (3) methodology verification. Materials under test (MUTs) loaded into the well included deionized water, Tris-EDTA buffer, and lambda DNA. S-parameters were measured to determine interaction levels between the radio frequencies and MUTs during the broadband sweep. MUTs increasing in concentration were repeatably detected and demonstrated high measurement sensitivity, with the highest error value observed being 0.36%. Comparing Tris-EDTA buffer versus lambda DNA suspended in Tris-EDTA buffer suggests that introducing lambda DNA into the Tris-EDTA buffer repeatably alters S-parameters. The innovative aspect of this biosensor is that it can measure interactions of electromagnetic energy and MUTs in microliter quantities with high repeatability and sensitivity.
Anti-Fouling Strategies of Electrochemical Sensors for Tumor Markers
Authors: Song Ge , Han Hongliang , Ma Zhanfang
Published: May 2023

The early detection and prognosis of cancers require sensitive and accurate detection methods; with developments in medicine, electrochemical biosensors have been developed that can meet these clinical needs. However, the composition of biological samples represented by serum is complex; when substances undergo non-specific adsorption to an electrode and cause fouling, the sensitivity and accuracy of the electrochemical sensor are affected. In order to reduce the effects of fouling on electrochemical sensors, a variety of anti-fouling materials and methods have been developed, and enormous progress has been made over the past few decades. Herein, the recent advances in anti-fouling materials and strategies for using electrochemical sensors for tumor markers are reviewed; we focus on new anti-fouling methods that separate the immunorecognition and signal readout platforms.
MSTA-SlowFast: A Student Behavior Detector for Classroom Environments
Authors: Zhang Shiwen , Liu Hong , Sun Cheng , Wu Xingjin , Wen Pei , Yu Fei , Zhang Jin
Published: May 2023

Detecting students’ classroom behaviors from instructional videos is important for instructional assessment, analyzing students’ learning status, and improving teaching quality. To achieve effective detection of student classroom behavior based on videos, this paper proposes a classroom behavior detection model based on the improved SlowFast. First, a Multi-scale Spatial-Temporal Attention (MSTA) module is added to SlowFast to improve the ability of the model to extract multi-scale spatial and temporal information in the feature maps. Second, Efficient Temporal Attention (ETA) is introduced to make the model more focused on the salient features of the behavior in the temporal domain. Finally, a spatio-temporal-oriented student classroom behavior dataset is constructed. The experimental results show that, compared with SlowFast, our proposed MSTA-SlowFast has a better detection performance with mean average precision (mAP) improvement of 5.63% on the self-made classroom behavior detection dataset.