bluuebunny/crossref_metadata_2025 huggingface dataset:
Regeneration of Osteochondral Defects by Combined Delivery of Synovium-Derived Mesenchymal Stem Cells, TGF-β1 and BMP-4 in Heparin-Conjugated Fibrin Hydrogel
Authors: Sarsenova Madina , Raimagambetov Yerik , Issabekova Assel , Karzhauov Miras , Kudaibergen Gulshakhar , Akhmetkarimova Zhanar , Batpen Arman , Ramankulov Yerlan , Ogay Vyacheslav
Published: December 2022

The regeneration of cartilage and osteochondral defects remains one of the most challenging clinical problems in orthopedic surgery. Currently, tissue-engineering techniques based on the delivery of appropriate growth factors and mesenchymal stem cells (MSCs) in hydrogel scaffolds are considered as the most promising therapeutic strategy for osteochondral defects regeneration. In this study, we fabricated a heparin-conjugated fibrin (HCF) hydrogel with synovium-derived mesenchymal stem cells (SDMSCs), transforming growth factor-β1 (TGF-β1) and bone morphogenetic protein-4 (BMP-4) to repair osteochondral defects in a rabbit model. An in vitro study showed that HCF hydrogel exhibited good biocompatibility, a slow degradation rate and sustained release of TGF-β1 and BMP-4 over 4 weeks. Macroscopic and histological evaluations revealed that implantation of HCF hydrogel with SDMSCs, TGF-β1 and BMP-4 significantly enhanced the regeneration of hyaline cartilage and the subchondral bone plate in osteochondral defects within 12 weeks compared to hydrogels with SDMSCs or growth factors alone. Thus, these data suggest that combined delivery of SDMSCs with TGF-β1 and BMP-4 in HCF hydrogel may synergistically enhance the therapeutic efficacy of osteochondral defect repair of the knee joints.
Trans-Polyisoprene/Poly (Ethylene-co-Vinyl Acetate) Polymer Composites as High-Performance Triple Shape Memory Materials
Authors: Xin Hua , Li Yangfan , Peng Qi
Published: December 2022

The performance and programming conditions of the triple shape memory of crosslinked trans-polyisoprene/poly (ethylene-co-vinyl acetate) (TPI/EVA) composites with different contents of dicumyl peroxide (DCP) were investigated. The effect of triple shape memory in the TPI/EVA composites was studied by tensile loading, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and dynamic thermomechanical analysis (DMA). It was demonstrated that the content of DCP increased, the crystallization temperature of TPI decreased from 55.2 to 38.3 °C, and the crystallization temperature of EVA decreased slightly. The SEM results showed that DCP, as an initiator, could form a graft copolymer of TPI-g-EVA at the interface of the two phases, which could improve the adhesion of the two phases. The DMA showed that the higher the content of DCP, the higher the first-stage shape recovery ratio. Moreover, the composites exhibited favorable shape fixity ratio (Rf) and shape recovery ratio (Rr) with the incorporation of 0.4 phr DCP. At the same time, it was demonstrated that the TPI/EVA composites showed excellent mechanical strength, including tensile strength up to 24.3 MPa, as well as elongation at break reaching 508%.
Preparation and Synergistic Effect of Biomimetic Poly(lactic acid)/Graphene Oxide Composite Scaffolds Loaded with Dual Drugs
Authors: Liu Shuqiong , Li Wanzhu , Xu Zhenyi , Hu Jiapeng , Wu Fangfang , Zheng Yuying
Published: December 2022

To promote the bone repair ability of drug-loaded scaffolds, poly(lactic acid) (PLA)/graphene oxide (GO)/Salvianolic acid B (Sal-B)/aspirin (ASA) dual drug-loaded biomimetic composite scaffolds were prepared. The results showed that the addition of these two drugs delayed the gel formation of the composite system, but a biomimetic nanofiber structure could still be obtained by extending the gel time. The addition of Sal-B increased the hydrophilicity of the scaffold, while an increase in ASA reduced the porosity. Dual drug-loaded scaffolds had good haemocompatibility and synergically promoted the proliferation of MC3T3-E1 cells and enhanced alkaline phosphatase activity. Sustained-release experiments of the two drugs showed that the presence of ASA slowed the cumulative release of Sal-B, while Sal-B promoted the release of ASA. Kinetic modeling showed that the release of both drugs conforms to the Korsmeyer–Peppas model, but Sal-B conforms to the Fick diffusion mechanism and ASA follows Fick diffusion and carrier swelling/dissolution.
Enhancement of Digestion Resistance and Glycemic Control of Corn Starch through Conjugation with Gallic Acid and Quercetin Using the Free Radical Grafting Method
Authors: Wu Tsung-Yen , Sun Nan-Nong , Chan Zu , Chen Chao-Jung , Wu Yi-Ching , Chau Chi-Fai
Published: December 2022

The objective of this study was to synthesize different polyphenol–corn starch complexes including gallic acid–starch and quercetin–starch by conjugating corn starch with gallic acid and quercetin using the free radical grafting method. This process was effective in enhancing conjugations of starch molecules with gallic acid and quercetin (5.20 and 5.83 mg GAE/g, respectively) and imparted promising antioxidant capacity to the phenolic–starch complexes. Significant interactions between these phenolic compounds and corn starch molecules were revealed with an ultraperformance liquid chromatography electrospray ionization Q-time-of-flight mass spectrometry assay. It was revealed that significantly higher levels of resistant starch in the above gallic–starch and quercetin–starch complex samples (11.6 and 15.3 g/100 g, respectively) together with an obvious reduction in glycemic response (7.9% and 11.8%, respectively) observed over the control. Complex samples functionalized with gallic acid and quercetin have exerted modified physicochemical properties, particularly reduction in swelling ability (58.7–60.1%), breakdown viscosity (62.5–67.8%), and setback viscosity (37.7–44.5%). In sum, free radical grafting treatment could be a promising method for imparting corn starch with enhanced resistance to enzyme digestion along with changes in pasting properties for specific food applications.
A Novel Method to Detoxify Steam-Exploded Biomass and Produce a Substrate for Biorefinery
Authors: Zimbardi Francesco , Viola Egidio , Arcieri Giuseppe , Valerio Vito , Carnevale Massimo
Published: December 2022

Pre-treatments at relatively high temperatures (range 160 °C–220 °C) are currently used to transform lignocellulosics into biofuels and chemicals. In this step, several molecules with an inhibitory effect in the subsequent fermentation processes are generated. These inhibitors include low-molecular-weight molecules and lignin fragments that can be removed by water washing. However, this procedure also removes valuable soluble carbohydrates which are then difficult to recover from the diluted stream. In this work, a new method to detoxify steam-exploded substrates is reported. The procedure is based on the evaporation of low-weight acids and aldehydes, which leaves all the sugars in the solid matrix, while the cellulose hornification (an irreversible modification of the cellulose fibres that depresses the saccharification yield) is prevented by adding steam to the hot fluidizing flow stream. Two systems were tested: a 0.1 kg/batch oscillating fluidized bed and a continuous fluidized bed dryer operating downstream of a steam explosion plant with a treatment capacity of 150 kg/h. The detoxified substrates were subjected to enzymatic hydrolysis and fermentation to obtain bioethanol, with a yield that was 14% higher than that obtained from substrates detoxified with conventional methods of drying or washing.
Analysis of Voltage Stability of the Slovak Republic’s Power System
Authors: Eleschová Žaneta , Cintula Boris , Cenký Matej , Beláň Anton , Bendík Jozef , Janiga Peter
Published: December 2022

This paper studies the voltage stability of the Slovak Republic’s power system (PS) based on an assessment of the PV curves. The PV curve is a tool for assessing voltage stability, and based on its shape, it is possible to determine weak and strong voltage nodes with the possibility of voltage stability reserve quantification. We present an analysis of the influence of transformers with an automatic voltage regulator (AVR) on the shape of the PV curves and on the magnitude of voltage in the PS. In general, the 400 kV/110 kV transformers equipped with AVRs are critical assets for the PS as they address voltage control in the DS. However, in the case of voltage problems in the TS, the AVR function may worsen the voltage situation across the entire PS. Therefore, we closely analyze the negative effects of the AVR on the PS operation. This impact is clearly proved, and recommendations are given for the transmission system operator (TSO) in order to maintain voltage stability. In addition, the PV curves of the pilot nodes are analyzed very accurately, thereby confirming their importance in the TS in terms of a sufficient reserve of reactive power. The study was conducted in cooperation with the TSO, Slovenská elektrizačná prenosová sústava, a.s.
Diversity-Based Evolutionary Population Dynamics: A New Operator for Grey Wolf Optimizer
Authors: Rezaei Farshad , Safavi Hamid R. , Abd Elaziz Mohamed , Abualigah Laith , Mirjalili Seyedali , Gandomi Amir H.
Published: December 2022

Evolutionary Population Dynamics (EPD) refers to eliminating poor individuals in nature, which is the opposite of survival of the fittest. Although this method can improve the median of the whole population of the meta-heuristic algorithms, it suffers from poor exploration capability to handle high-dimensional problems. This paper proposes a novel EPD operator to improve the search process. In other words, as the primary EPD mainly improves the fitness of the worst individuals in the population, and hence we name it the Fitness-Based EPD (FB-EPD), our proposed EPD mainly improves the diversity of the best individuals, and hence we name it the Diversity-Based EPD (DB-EPD). The proposed method is applied to the Grey Wolf Optimizer (GWO) and named DB-GWO-EPD. In this algorithm, the three most diversified individuals are first identified at each iteration, and then half of the best-fitted individuals are forced to be eliminated and repositioned around these diversified agents with equal probability. This process can free the merged best individuals located in a closed populated region and transfer them to the diversified and, thus, less-densely populated regions in the search space. This approach is frequently employed to make the search agents explore the whole search space. The proposed DB-GWO-EPD is tested on 13 high-dimensional and shifted classical benchmark functions as well as 29 test problems included in the CEC2017 test suite, and four constrained engineering problems. The results obtained by the proposal upon implemented on the classical test problems are compared to GWO, FB-GWO-EPD, and four other popular and newly proposed optimization algorithms, including Aquila Optimizer (AO), Flow Direction Algorithm (FDA), Arithmetic Optimization Algorithm (AOA), and Gradient-based Optimizer (GBO). The experiments demonstrate the significant superiority of the proposed algorithm when applied to a majority of the test functions, recommending the application of the proposed EPD operator to any other meta-heuristic whenever decided to ameliorate their performance.
Cutting Force Prediction for Trochoid Milling of 300M Ultra-High Strength Steel
Authors: Zhou Ke , Zhang Changming , Du Siyuan
Published: December 2022

Trochoid milling can improve the quality of machining of difficult materials as well as the efficiency of machining. However, its complex tool trajectory makes it difficult to predict the instantaneous cutting forces during cutting. Therefore, in this paper, the transient cutting thickness model in the cycloidal milling process was established using numerical combined with analytical methods, and the semi-mechanical cutting force model was established. Experiments were designed to compare the differences between the cutting force coefficients extracted from the slot milling experiments and those extracted from the trochoid milling. Finally, experiments were designed to validate the established cutting force model. The results showed that there was an error of 5–23% between the tangential cutting force coefficients extracted from slot milling and the tangential cutting force coefficients extracted from trochoid milling, while there was an error of 21–35% in the radial cutting force coefficients, indicating that the cutting force coefficients extracted from slot milling cannot be used to predict the cutting force in the trochoid milling process. It was verified that the error of the established cutting force model in predicting the cutting force of trochoid milling was 12%, indicating that the established model has a high accuracy, which provides a theoretical basis for the selection of cutting parameters and parameter optimization in the future.
Fumaric Acid Production by R. arrhizus NRRL 1526 Using Apple Pomace Enzymatic Hydrolysates: Kinetic Modelling
Authors: Martin-Dominguez Victor , Garcia-Montalvo Jorge , Garcia-Martin Alberto , Ladero Miguel , Santos Victoria E.
Published: December 2022

Fumaric acid is one of the most promising biorefinery platform chemicals, fruit residues being a very suitable raw material for its production in second generation biorefineries. In particular, apple pomace is a plentiful residue from the apple juice industry, with apple being the second largest fruit crop in the world, with a production that increased from 46 to 86 Mtons in the 1994–2021 period. With a global apple juice production of more than 4.5 Mtons, a similar amount of apple pomace is produced yearly. In this work, apple pomace hydrolysate has been obtained by enzymatic hydrolysis and further characterized for its content in sugars, phenolics and nitrogen using different analytic methods, based on HPLC and colorimetric techniques. Previous to the use of this hydrolysate (APH), we studied if the addition of fructose to the usual glucose-rich broth could lead to high fumaric acid yields, titers and productivities. Afterwards, APH fermentation was performed and improved using different nitrogen initial amounts, obtaining production yields (0.32 gFumaric acid/gconsumed sugar) similar to those obtained with synthetic media (0.38 gFumaric acid/gconsumed sugar). Kinetic modelling was employed to evaluate, explain, and understand the experimental values and trends of relevant components in the fermentation broth as functions of the bioprocess time, proposing a suitable reaction scheme and a non-structured, non-segregated kinetic model based on it.
Dynamically Triggering Resilient Control for Networked Nonlinear Systems under Malicious Aperiodic DoS Attacks
Authors: Tan Wei , Wang He , Hou Huazhou , Liu Xiaoxu , Zheng Meng
Published: December 2022

Networked nonlinear systems (NNSs) have great potential security threats because of malicious attacks. These attacks will destabilize the networked systems and disrupt the communication to the networked systems, which will affect the stability and performance of the networked control systems. Therefore, this paper aims to deal with the resilient control problem for NNSs with dynamically triggering mechanisms (DTMs) and malicious aperiodic denial-of-service (DoS) attacks. To mitigate the impact from DoS attacks and economize communication resources, a resilient dynamically triggering controller (RDTC) is designed with DTMs evolving an adaptive adjustment auxiliary variable. Thus, the resulting closed-loop system is exponentially stable by employing the piecewise Lyapunov function technique. In addition, according to the minimum inter-event time, the Zeno behavior can be excluded. Finally, the merits of the proposed controllers and theory are corroborated using the well-known nonlinear Chua circuit.
Unforgeable Digital Signature Integrated into Lightweight Encryption Based on Effective ECDH for Cybersecurity Mechanism in Internet of Things
Authors: Ahmed Adel A. , Barukab Omar M.
Published: December 2022

Cybersecurity protocols enable several levels of protection against cyberattacks (digital attacks) that spread across network devices, platform programs, and network applications. On the Internet of Things (IoT), cyberattacks are generally intended to access and change/destroy sensitive information, which may reduce IoT benefits. Moreover, recent IoT systems are experiencing a critical challenge in designing a lightweight and robust cybersecurity mechanism on resource-constrained IoT devices. The cybersecurity challenges facing the IoT that should be taken into consideration are identifying compromised devices, data/service protection, and identifying impacted IoT users. This paper proposes an unforgeable digital signature integrated into an effective lightweight encryption (ELCD) mechanism that utilizes the secure key distribution in an elliptic curve Diffie–Hellman (ECDH) and resolves the weak bit problem in the shared secret key due to the Diffie–Hellman exchange. The ELCD mechanism proposes a secure combination between the digital signature and encryption, and it uses fast hash functions to confidentially transfer a shared secret key among IoT devices over an insecure communication channel. Furthermore, the ELCD mechanism checks the true identity of the sender with certainty through the proposed digital signature, which works based on a hash function and three steps of curve-point inspection. Furthermore, the security of ELCD was mathematically proven using the random oracle and IoT adversary models. The findings of the emulation results show the effectiveness of ELCD in terms of CPU execution time, storage cost, and power consumption that are less by 53.8%, 33–17%, and 68.7%, respectively, compared to the baseline cryptographic algorithms.
Mindfulness Interventions for Attention Deficit Hyperactivity Disorder: A Systematic Review and Meta-Analysis
Authors: Kretschmer Clara R. , Göz Tebrizcik Burcu , Dommett Eleanor J.
Published: December 2022

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental condition impacting children and adults. Current treatments are limited and there is increasing interest in the use of mindfulness, which is growing in popularity. Previous systematic reviews have typically focused on specific ages, outcome measures or interventions. The current review aimed to take a more comprehensive approach. Title and abstract searches were performed in five databases for randomized and non-randomized controlled trials or pre-post studies with participants with an ADHD diagnosis or a score above a clinically relevant cut-off on a validated ADHD measure. Studies had to measure symptoms of ADHD, global or social functioning. Extraction of key information including participant status (i.e., diagnosis, scale scores, comorbidities, medication use), study design, and outcome measures was conducted. Effect sizes (Hedge’s g) were calculated and where a measure had been used in at least three studies with the same population, meta-analyses were considered. Twenty-nine studies were initially identified, with seven deemed poor quality and removed from further analysis leaving, 22 studies containing data from 1237 children and adults with ADHD along with data from 525 family members. The data indicate possible benefits of mindfulness on self-compassion, quality of life, wellbeing, depression, and anxiety. The findings also suggest that mindfulness may also improve ADHD symptoms, executive function, problematic behaviours, and emotional dysregulation, although results vary by age of patient and measures used. Parent stress and parenting style have received limited attention, highlighting the need for more studies in these areas. Whilst the data presented suggest that mindfulness may be beneficial, the evidence base is not as strong as the popularity of the approach. Many of the studies lacked blind assessment, adequate randomization, or suitable control conditions. As such high-quality controlled studies considering medication, other psychosocial interventions, use of active and in active controls and comorbidity as well as longer follow-up periods, are needed to confirm this.
Buddhist Environmentalism as Seen through Religious Change
Authors: Lin Nan Kathy
Published: December 2022

This article considers the disagreement between scholars of Buddhism around whether the tradition is or is not amenable to environmental concerns. It identifies the gap between the two sides as arising from a problem in how historical-critical methods divorce moral concepts from materiality in the study of religious history. This paper considers paticca-samuppada as a central moral concept in Buddhist tradition, one that has indeed changed via translation over the course of Buddhist history. This is the moral concept that leads directly into current environmentalist discourse, in its translation as interdependence. The paper first considers the translation of paticca-samuppada in historical tradition as well as in the hands of environmentalist authors. It then considers why paticca-samuppada as interdependence is a context-appropriate contribution, in settings of industrial political economy heavily directed by an abstract, mathematical concept of capital in connection with the moral concept of unlimited growth. The paper concludes by suggesting that contemporary Buddhist environmentalism be understood as a case of religious change. It concludes that the Buddhist eco-critical position is untenable, in light of processes of change in religious traditions, and suggests that the study of religious history should better account for how it is that religious change occurs.
Idealist Individualism or Indigenous Cosmology; Finding Entanglement across Species and Strata
Authors: Irwin Ruth
Published: December 2022

Science and technology have been associated with modern Enlightenment, in a manner that elevated the rational mind over emotions and the body, a separation of the subjective mind from the object of observation, universal categories, objective observation, and linear causality. These assumptions, consolidated by Descartes and then Kant, have underpinned the philosophies of science, economics, policy, and political theory. They have shaped the modern world and enabled corporate freedom to exploit all ‘resources’ in the name of consumerism and global trade. Idealism has alienated subjective rationality from an idealised universal created world. In contrast, ancient indigenous ways of knowing are emerging as better exemplars of the interrelationship between individuals, communities, and organic and anorganic life forms. Celtic shapeshifters and praise poems forge an interwoven dance of geology, weather, plants, animals, and humanity with wisdom and politics. The Māori concept of whakapapa is the kin relations of everything, tied into complex claves as a taxonomy of familial ties. Animism was understood as pagan misidentification by modernity, but if the alienation set out by modern linear physics is severed, then the intra and inter-relationship of strata, atmosphere, ocean, and species are better relayed by indigenous philosophy than by outdated, colonial, modern assumptions. Celtic and Māori pantheism show us how entangled we are, and how special relationships are in place that last across generations.
All-Weather and Superpixel Water Extraction Methods Based on Multisource Remote Sensing Data Fusion
Authors: Chen Xiaopeng , Gao Fang , Li Yingye , Wang Bin , Li Xiaojie
Published: December 2022

The high spatial and temporal resolution of water body data offers valuable guidance for disaster monitoring and assessment. These data can be employed to quickly identify water bodies, especially small water bodies, and to accurately locate affected areas, which is significant for protecting people’s lives and property. However, the application of optical remote sensing is often limited by clouds and fog during actual floods. In this paper, water extraction methods of the multisource data fusion model (MDFM) and superpixel water extraction model (SWEM) are proposed, in which the MDFM fuses optical and synthetic aperture radar (SAR) images, and all-weather water extraction is achieved by using spectral information of optical images, texture information and the good penetration performance of SAR images. The SWEM further improves the accuracy of the water boundary with superpixel decomposition for extracted water boundaries using the fully constrained least squares (FCLS) method. The results show that the correlation coefficient (r) and area accuracy (Parea) of the MDFM and SWEM are improved by 2.22% and 9.20% (without clouds), respectively, and 3.61% and 18.99% (with clouds), respectively, compared with the MDFM, and 41.54% and 85.09% (without clouds), respectively, and 32.31% and 84.31% (with clouds), respectively, compared with the global surface water product of the European Commission Joint Research Centre’s Global Surface Water Explorer (JRC-GSWE). The MDFM and SWEM can extract water bodies with all weather and superpixel and improve the temporal and spatial resolution of water extraction, which has obvious advantages.
Improved Dempster–Shafer Evidence Theory for Tunnel Water Inrush Risk Analysis Based on Fuzzy Identification Factors of Multi-Source Geophysical Data
Authors: Ding Yulin , Yang Binru , Xu Guangchun , Wang Xiaoyong
Published: December 2022

Water inrush is one of the most important risk factors in tunnel construction because of its abruptness and timeliness. Various geophysical data used in actual construction contain useful information related to groundwater development. However, the existing approaches with such data from multiple sources and sensors are generally independent and cannot integrate this information, leading to inaccurate projections. In addition, existing tunnel advanced geological forecast reports for risk projections interpreted by human operators generally contain no quantitative observations or measurements, but only consist of ambiguous and uncertain qualitative descriptions. To surmount the problems above, this paper proposes a tunnel water inrush risk analysis method by fusing multi-source geophysical observations with fuzzy identification factors. Specifically, the membership function of the fuzzy set is used to solve the difficulty in determining the basic probability assignment function in the improved Dempster–Shafer evidence theory. The prediction model of effluent conditions fuses seismic wave reflection data, ground penetrating radar data, and transient electromagnetic data. Therefore, quantitative evaluations of the effluent conditions are achieved, including the strand water, linear water, seepage and dripping water, and anhydrous. Experimental evaluations with a typical tunnel section were conducted, in which the state of the groundwater from a series of geological sketch reports in this sectionpaper were used as ground truth for verification. The experimental results revealed that the proposed method not only has high accuracy and robustness but also aligns well with different evidence effectively that generally contradicts manual interpretation reports. The results from 12 randomly selected tunnel sections also demonstrate the generalization abilities of the proposed method.
Assessing Vegetation Phenology across Different Biomes in Temperate China—Comparing GIMMS and MODIS NDVI Datasets
Authors: Xiao Jiangtao , Huang Ke , Lin Yang , Ren Ping , Zu Jiaxing
Published: December 2022

Assessing vegetation phenology is very important for better understanding the impact of climate change on the ecosystem, and many vegetation index datasets from different remote sensors have been used to quantify vegetation phenology from a regional to global perspective. This study mainly analyzes the similarities and differences in phenology derived from GIMMS NDVI3g and MODIS NDVI datasets across different biomes throughout temperate China. We applied three commonly used methods to extract the start and end of the growing season (SOS and EOS) from two datasets between 2000 and 2015, and analyzed the spatio-temporal characteristics and trends of key phenological parameters between these two datasets in temperate China. Results showed that the multi-year mean GIMMS NDVI was higher than MODIS NDVI throughout most of temperate China, and the consistencies between GIMMS NDVI and MODIS NDVI for all biomes in the senescence phase were better than those in the green-up phase. NDVI differences between GIMMS and MODIS resulted in some distinctions between phenology derived from the two datasets. The results of SOS and EOS for three methods also showed wide discrepancies in spatial patterns, especially in SOS. For different biomes, differences of SOS in forests were obviously less than that in shrublands, grasslands-IM, grasslands-QT and meadows, whereas the differences of EOS in forests were relatively greater than that in SOS. Moreover, large differences of phenological trends were found between GIMMS and MODIS datasets from 2000 to 2015 in entire region and different biomes, and it is particularly noteworthy that both SOS and EOS showed a low proportion of the identical significant trends. The results suggested NDVI datasets obtained from GIMMS and MODIS sensors could induce the differences of the inversion of vegetation phenology in some degree due to the differences of instrumental characteristics between these two sensors. These findings highlighted that inter-calibrate datasets derived from different satellite sensors for some biomes (e.g., grasslands) should be needed when analyzing land surface phenology and their trends, and also provided baseline information for choosing different NDVI datasets in subsequent studies on vegetation patterns and dynamics.
Dynamic Evolution Modeling of a Lake-Terminating Glacier in the Western Himalayas Using a Two-Dimensional Higher-Order Flowline Model
Authors: Yan Zhan , Zhang Tong , Wang Yuzhe , Leng Wei , Ding Minghu , Zhang Dongqi , Xiao Cunde
Published: December 2022

To better understand the future evolution of Jiemayangzong Glacier (JMYZG), the headstream of the Yarlung Zangbo River, we simulated its future ice thickness evolution using a two-dimensional higher-order numerical flowline model. Due to the sparsity of in situ observational data, we used a combination of field observations and inversion models of velocity and ice thickness to initialize the model parameters. We validated the parametrizations of the calving scheme by comparing the modeled and observed glacier terminus retreats. To estimate the response of JMYZG to climate change, the ice flow model was forced with different climate scenarios. We found that the JMYZG will retreat under different climate scenarios. By 2100, the volume loss of JMYZG will be approximately 34%, 67% and 81% under SSP1-2.6, SSP3-7.0 and SSP5-8.5, respectively.
Regional Spatiotemporal Patterns of Fire in the Eurasian Subarctic Based on Satellite Imagery
Authors: Zhou Yikang , Ji Shunping , Warner Timothy A.
Published: December 2022

The fire risks in the vast Eurasian Subarctic are increasing, raising concerns for both local and global climate systems. Although some studies have addressed this problem, their conclusions only draw from relatively lower resolution data, and the sub-regional analysis of fire patterns in this area is lacking. In this paper, using a huge amount of multi-temporal and multi-resolution remotely sensed data, derived products, and weather data between the period 2001 and 2021, we reveal several novel and recent findings concerning regional and overall fire patterns in the Eurasian Subarctic. First, we discovered that fire occurrence over the period 2001 and 2021 varied by sub-region within the Eurasian Subarctic, with perennial low fire incidence in the East European and West Siberian Plain, increasing fire incidence in the Central Siberian Plateau, and marked periodicity of fire in the East Siberian Highlands. Second, we reveal the larger scale of individual fires in the Eurasian Subarctic compared to the adjacent region to the south, with fires of longer duration (13 vs. 8 days), larger daily expansion area (7.5 vs. 3.0 km2/d), and faster propagation (442 vs. 280 m/d). Third, the northern limit of fire has extended poleward approximately 1.5° during the study period. Fourth, the start dates of fire seasons in Eurasian Subarctic, dominated by the Central Siberian Plateau, has advanced at a rate of 1.4 days per year. We also analyzed the factors resulting in the regional patterns of fire incidence including weather, human activity, land cover, and landscape structure. Our findings not only increase the knowledge of regional fire patterns and trends in Eurasian Subarctic but also will benefit the design of special fire management policies.
Consensus Tracking of Nonlinear Agents Using Distributed Nonlinear Dynamic Inversion with Switching Leader-Follower Connection
Authors: Mondal Sabyasachi , Tsourdos Antonios
Published: December 2022

In this paper, a consensus tracking protocol for nonlinear agents is presented, which is based on the Nonlinear Dynamic Inversion (NDI) technique. Implementation of such a technique is new in the context of the consensus tracking problem. The tracking capability of nonlinear dynamic inversion (NDI) is exploited for a leader-follower multi-agent scenario. We have provided all the mathematical details to establish its theoretical foundation. Additionally, a convergence study is provided to show the efficiency of the proposed controller. The performance of the proposed controller is evaluated in the presence of both (a) random switching topology among the agents and (b) random switching of leader–follower connections, which is realistic and not reported in the literature. The follower agents track various trajectories generated by a dynamic leader, which describes the tracking capability of the proposed controller. The results obtained from the simulation study show how efficiently this controller can handle the switching topology and switching leader-follower connections.
Surface Functionalization Strategies of Polystyrene for the Development Peptide-Based Toxin Recognition
Authors: Debela Ahmed M. , Gonzalez Catherine , Pucci Monica , Hudie Shemsia M. , Bazin Ingrid
Published: December 2022

The development of a robust surface functionalization method is indispensable in controlling the efficiency, sensitivity, and stability of a detection system. Polystyrene (PS) has been used as a support material in various biomedical fields. Here, we report various strategies of polystyrene surface functionalization using siloxane derivative, divinyl sulfone, cyanogen bromide, and carbonyl diimidazole for the immobilization of biological recognition elements (peptide developed to detect ochratoxin A) for a binding assay with ochratoxin A (OTA). Our objective is to develop future detection systems that would use polystyrene cuvettes such as immobilization support of biological recognition elements. The goal of this article is to demonstrate the proof of concept of this immobilization support. The results obtained reveal the successful modification of polystyrene surfaces with the coupling agents. Furthermore, the immobilization of biological recognition elements, for the OTA binding assay with horseradish peroxidase conjugated to ochratoxin A (OTA-HRP) also confirms that the characteristics of the functionalized peptide immobilized on polystyrene retains its ability to bind to its ligand. The presented strategies on the functionalization of polystyrene surfaces will offer alternatives to the possibilities of immobilizing biomolecules with excellent order- forming monolayers, due to their robust surface chemistries and validate a proof of concept for the development of highly efficient, sensitive, and stable future biosensors for food or water pollution monitoring.
Learning for Data Synthesis: Joint Local Salient Projection and Adversarial Network Optimization for Vehicle Re-Identification
Authors: Chen Yanbing , Ke Wei , Zhang Wei , Wang Cui , Sheng Hao , Xiong Zhang
Published: December 2022

The problem of vehicle re-identification in surveillance scenarios has grown in popularity as a research topic. Deep learning has been successfully applied in re-identification tasks in the last few years due to its superior performance. However, deep learning approaches require a large volume of training data, and it is particularly crucial in vehicle re-identification tasks to have a sufficient amount of varying image samples for each vehicle. To collect and construct such a large and diverse dataset from natural environments is labor intensive. We offer a novel image sample synthesis framework to automatically generate new variants of training data by augmentation. First, we use an attention module to locate a local salient projection region in an image sample. Then, a lightweight convolutional neural network, the parameter agent network, is responsible for generating further image transformation states. Finally, an adversarial module is employed to ensure that the images in the dataset are distorted, while retaining their structural identities. This adversarial module helps to generate more appropriate and difficult training samples for vehicle re-identification. Moreover, we select the most difficult sample and update the parameter agent network accordingly to improve the performance. Our method draws on the adversarial networks strategy and the self-attention mechanism, which can dynamically decide the region selection and transformation degree of the synthesis images. Extensive experiments on the VeRi-776, VehicleID, and VERI-Wild datasets achieve good performance. Specifically, our method outperforms the state-of-the-art in MAP accuracy on VeRi-776 by 2.15%. Moreover, on VERI-Wil, a significant improvement of 7.15% is achieved.
Analysis and Correction of Measurement Error of Spherical Capacitive Sensor Caused by Assembly Error of the Inner Frame in the Aeronautical Optoelectronic Pod
Authors: Ma Tianxiang , Yang Shengqi , Xu Yongsen , Liu Dachuan , Hou Jinghua , Liu Yunqing
Published: December 2022

The ball joint is a multi-degree-of-freedom transmission pair, if it can replace the inner frame in the aviation photoelectric pod to carry the optical load, which will greatly simplify the system structure of the photoelectric pod and reduce the space occupied by the inner frame. However, installation errors in ball joint siting introduce nonlinear errors that are difficult to correct and two degree of freedom angular displacement of the ball joint is difficult to detect, which limits application in the precision control of two degrees of freedom systems. Studies of spherical capacitive sensors to date have not tested sensors for use in an inner frame stabilisation mechanism nor have they analysed the influence of installation error on sensor output. A two-axis angular experimental device was designed to measure the performance of a ball joint capacitive sensor in a frame stabilisation mechanism in an aeronautical optoelectronic pod, and a mathematical model to compensate for ball joint capacitive sensor installation error was created and tested. The experimental results show that the resolution of the capacitive sensor was 0.02° in the operating range ±4°, the repeatability factor was 0.86%, and the pulse response time was 39 μs. The designed capacitive sensor has a simple structure, high measurement accuracy, and strong robustness, and it can be integrated into ball joint applications in the frames of aeronautical photoelectric pods.
Investigation of EEG-Based Biometric Identification Using State-of-the-Art Neural Architectures on a Real-Time Raspberry Pi-Based System
Authors: Benomar Mohamed , Cao Steven , Vishwanath Manoj , Vo Khuong , Cao Hung
Published: December 2022

Despite the growing interest in the use of electroencephalogram (EEG) signals as a potential biometric for subject identification and the recent advances in the use of deep learning (DL) models to study neurological signals, such as electrocardiogram (ECG), electroencephalogram (EEG), electroretinogram (ERG), and electromyogram (EMG), there has been a lack of exploration in the use of state-of-the-art DL models for EEG-based subject identification tasks owing to the high variability in EEG features across sessions for an individual subject. In this paper, we explore the use of state-of-the-art DL models such as ResNet, Inception, and EEGNet to realize EEG-based biometrics on the BED dataset, which contains EEG recordings from 21 individuals. We obtain promising results with an accuracy of 63.21%, 70.18%, and 86.74% for Resnet, Inception, and EEGNet, respectively, while the previous best effort reported accuracy of 83.51%. We also demonstrate the capabilities of these models to perform EEG biometric tasks in real-time by developing a portable, low-cost, real-time Raspberry Pi-based system that integrates all the necessary steps of subject identification from the acquisition of the EEG signals to the prediction of identity while other existing systems incorporate only parts of the whole system.
Moving-Target Defense in Depth: Pervasive Self- and Situation-Aware VM Mobilization across Federated Clouds in Presence of Active Attacks
Authors: Magdy Yousra , Azab Mohamed , Hamada Amal , Rizk Mohamed R. M. , Sadek Nayera
Published: December 2022

Federated clouds are interconnected cooperative cloud infrastructures offering vast hosting capabilities, smooth workload migration and enhanced reliability. However, recent devastating attacks on such clouds have shown that such features come with serious security challenges. The oblivious heterogeneous construction, management, and policies employed in federated clouds open the door for attackers to induce conflicts to facilitate pervasive coordinated attacks. In this paper, we present a novel proactive defense that aims to increase attacker uncertainty and complicate target tracking, a critical step for successful coordinated attacks. The presented systemic approach acts as a VM management platform with an intrinsic multidimensional hierarchical attack representation model (HARM) guiding a dynamic, self and situation-aware VM live-migration for moving-target defense (MtD). The proposed system managed to achieve the proposed goals in a resource-, energy-, and cost-efficient manner.
Flexible UWB and MIMO Antennas for Wireless Body Area Network: A Review
Authors: Jhunjhunwala Vikash Kumar , Ali Tanweer , Kumar Pramod , Kumar Praveen , Kumar Pradeep , Shrivastava Sakshi , Bhagwat Arnav Abhijit
Published: December 2022

In recent years, there has been a surge of interest in the field of wireless communication for designing a monitoring system to observe the activity of the human body remotely. With the use of wireless body area networks (WBAN), chronic health and physical activity may be tracked without interfering with routine lifestyle. This crucial real-time data transmission requires low power, high speed, and broader bandwidth communication. Ultrawideband (UWB) technology has been explored for short-range and high-speed applications to cater to these demands over the last decades. The antenna is a crucial component of the WBAN system, which lowers the overall system’s performance. The human body’s morphology necessitates a flexible antenna. In this article, we comprehensively survey the relevant flexible materials and their qualities utilized to develop the flexible antenna. Further, we retrospectively investigate the design issues and the strategies employed in designing the flexible UWB antenna, such as incorporating the modified ground layer, including the parasitic elements, coplanar waveguide, metamaterial loading, etc. To improve isolation and channel capacity in WBAN applications, the most recent decoupling structures proven in UWB MIMO technology are presented.
Design and Modeling of a Fully Integrated Microring-Based Photonic Sensing System for Liquid Refractometry
Authors: Voronkov Grigory , Zakoyan Aida , Ivanov Vladislav , Iraev Dmitry , Stepanov Ivan , Yuldashev Roman , Grakhova Elizaveta , Lyubopytov Vladimir , Morozov Oleg , Kutluyarov Ruslan
Published: December 2022

The design of a refractometric sensing system for liquids analysis with a sensor and the scheme for its intensity interrogation combined on a single photonic integrated circuit (PIC) is proposed. A racetrack microring resonator with a channel for the analyzed liquid formed on the top is used as a sensor, and another microring resonator with a lower Q-factor is utilized to detect the change in the resonant wavelength of the sensor. As a measurement result, the optical power at its drop port is detected in comparison with the sum of the powers at the through and drop ports. Simulations showed the possibility of registering a change in the analyte refractive index with a sensitivity of 110 nm per refractive index unit. The proposed scheme was analyzed with a broadband source, as well as a source based on an optoelectronic oscillator using an optical phase modulator. The second case showed the fundamental possibility of implementing an intensity interrogator on a PIC using an external typical single-mode laser as a source. Meanwhile, additional simulations demonstrated an increased system sensitivity compared to the conventional interrogation scheme with a broadband or tunable light source. The proposed approach provides the opportunity to increase the integration level of a sensing device, significantly reducing its cost, power consumption, and dimensions.
Validity and Reliability of Wearable Motion Sensors for Clinical Assessment of Shoulder Function in Brachial Plexus Birth Injury
Authors: Grip Helena , Källströmer Anna , Öhberg Fredrik
Published: December 2022

The modified Mallet scale (MMS) is commonly used to grade shoulder function in brachial plexus birth injury (BPBI) but has limited sensitivity and cannot grade scapulothoracic and glenohumeral mobility. This study aims to evaluate if the addition of a wearable inertial movement unit (IMU) system could improve clinical assessment based on MMS. The system validity was analyzed with simultaneous measurements with the IMU system and an optical camera system in three asymptomatic individuals. Test–retest and interrater reliability were analyzed in nine asymptomatic individuals and six BPBI patients. IMUs were placed on the upper arm, forearm, scapula, and thorax. Peak angles, range of motion, and average joint angular speed in the shoulder, scapulothoracic, glenohumeral, and elbow joints were analyzed during mobility assessments and MMS tasks. In the validity tests, clusters of reflective markers were placed on the sensors. The validity was high with an error standard deviation below 3.6°. Intraclass correlation coefficients showed that 90.3% of the 69 outcome scores showed good-to-excellent test–retest reliability, and 41% of the scores gave significant differences between BPBI patients and controls with good-to-excellent test–retest reliability. The interrater reliability was moderate to excellent, implying that standardization is important if the patient is followed-up longitudinally.