bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptome Analysis Reveals Differentially Expressed Genes Involved in Aluminum, Copper and Cadmium Accumulation in Tea ‘Qianmei 419’ and ‘Qianfu 4’
Authors: Yao Xinzhuan , Chen Hufang , Zhang Baohui , Lu Litang
Published: July 2023

Tea, as a global nonalcoholic beverage, is widely consumed due to its economic, health and cultural importance. Polyploids have the ability to solve the problems of low yield, cold resistance and insect resistance in tea tree varieties. However, the response mechanism to aluminum and heavy metal remains unclear. In this study, the content of Al, Cu and Cd were measured in the leaves and roots of ‘Qianmei 419’ and ‘Qianfu 4’, respectively. The content of Al, Cd and Cu in the roots of the ‘Qianmei 419’ tea variety were significantly higher than in ‘Qianfu 4’ roots. Only the content of Cu in the leaves of the ‘Qianmei 419’ tea variety was significantly higher than that in the roots of the ‘Qianfu 4’ tea variety. Moreover, we found that the content of Al, Cu and Cd in the soil around the root of ‘Qianfu 4’ were higher than in the soil around the root of ‘Qianmei 419’. RNA-seq was performed to identify the DEGs involved in the accumulation of Al, Cu and Cd between ‘Qianmei 419’ and ‘Qianfu 4’. A total of 23,813 DEGs were identified in the triploid tea variety, including 16,459 upregulated DEGs and 7354 downregulated DEGs. Among them, by analyzing the expression levels of some metal transporter genes, it was found that most of the metal transporter genes were downregulated in the triploid tea plants. In short, through the analysis of transcriptome data and metal content, it was found that changes in metal transporter gene expression affect the accumulation of metals in tea plants. These results provide candidate genes to enhance multi-metal tolerance through genetic engineering technology.
Foliar Calcium Absorption by Tomato Plants: Comparing the Effects of Calcium Sources and Adjuvant Usage
Authors: Santos Eduardo , Montanha Gabriel Sgarbiero , Agostinho Luís Fernando , Polezi Samira , Marques João Paulo Rodrigues , de Carvalho Hudson Wallace Pereira
Published: July 2023

The deficiency of calcium (Ca) reduces the quality and shelf life of fruits. In this scenario, although foliar spraying of Ca2+ has been used, altogether with soil fertilization, as an alternative to prevent deficiencies, little is known regarding its absorption dynamics by plant leaves. Herein, in vivo microprobe X-ray fluorescence was employed aiming to monitor the foliar absorption of CaCl2, Ca-citrate complex, and Ca3(PO4)2 nanoparticles with and without using adjuvant. We also investigated whether Sr2+ can be employed as Ca2+ proxy in foliar absorption studies. Moreover, the impact of treatments on the cuticle structure was evaluated by scanning electron microscopy. For this study, 45-day-old tomato (Solanum lycopersicum L., cv. Micro-Tom) plants were used as a model species. After 100 h, the leaves absorbed 90, 18, and 4% of aqueous CaCl2, Ca-citrate, and Ca3(PO4)2 nanoparticles, respectively. The addition of adjuvant increased the absorption of Ca-citrate to 28%, decreased that of CaCl2 to 77%, and did not affect Ca3(PO4)2. CaCl2 displayed an exponential decay absorption profile with half-lives of 15 h and 5 h without and with adjuvant, respectively. Ca-citrate and Ca3(PO4)2 exhibited absorption profiles that were closer to a linear behavior. Sr2+ was a suitable Ca2+ tracer because of its similar absorption profiles. Furthermore, the use of adjuvant affected the epicuticular crystal structure. Our findings reveal that CaCl2 was the most efficient Ca2+ source. The effects caused by adjuvant suggest that CaCl2 and Ca-citrate were absorbed mostly through hydrophilic and lipophilic pathways.
Cyclic Hexapeptide from Bouvardia ternifolia (Cav.) Schltdl. and Neuroprotective Effects of Root Extracts
Authors: Lopera Yury Maritza Zapata , Trejo-Tapia Gabriela , González-Cortazar Manasés , Herrera-Ruiz Maribel , Zamilpa Alejandro , Jiménez-Ferrer Enrique
Published: July 2023

Bouvardia ternifolia (Cav.) Schltdl. is a shrub that belongs to the Rubiaceae family and is distributed throughout México; it has been used for its antioxidant, neuroprotective, and anti-inflammatory properties. This work aimed to evaluate the protective effects of B. ternifolia root extracts on the blood-brain barrier and the positive regulation of cytokines IL-1β, IL-6, and TNF-α, and the characterization of compounds present in the dichloromethane (BtD) and hexane (BtH) extracts. Male ICR mice were orally administered with B. ternifolia extracts for 5 days before a single injection of LPS. Administration of BtH and BtD significantly decreased Evans blue leakage into brain tissue by 70% and 68%, respectively. Meloxicam (MX) decreased the concentration of IL-1β by 39.6%; BtM by 53.9%; BtAq by 48.4%; BtD by 31.9%, and BtH by 37.7%. BtH was the only treatment that significantly decreased the concentration of IL-6 by 32.2%. The concentration of TNF-α declined with each of the treatments. The chemical composition of BtD and BtH was characterized by GC–MS, and the cyclic hexapeptide was identified by 13C, 1H NMR, and two-dimension techniques. In the BtD extract, seven compounds were found and in BtH 13 compounds were found. The methanolic (BtM) and aqueous (BtAq) extracts were not subjected to chemical analysis, because they did not show a significant difference in the BBB protection activity. Therefore, the results suggested that the extracts BtD and BtH protect the blood-brain barrier, maintaining stable its selective permeability, thereby preventing LPS from entering the brain tissue. Simultaneously, they modulate the production of IL-1β, IL-6, and TNF-α. It is important to note that this research only evaluated the complete extracts.
A Review on Reinforcements and Additives in Starch-Based Composites for Food Packaging
Authors: Muñoz-Gimena Pedro Francisco , Oliver-Cuenca Víctor , Peponi Laura , López Daniel
Published: July 2023

The research of starch as a matrix material for manufacturing biodegradable films has been gaining popularity in recent years, indicating its potential and possible limitations. To compete with conventional petroleum-based plastics, an enhancement of their low resistance to water and limited mechanical properties is essential. This review aims to discuss the various types of nanofillers and additives that have been used in plasticized starch films including nanoclays (montmorillonite, halloysite, kaolinite, etc.), poly-saccharide nanofillers (cellulose, starch, chitin, and chitosan nanomaterials), metal oxides (titanium dioxide, zinc oxide, zirconium oxide, etc.), and essential oils (carvacrol, eugenol, cinnamic acid). These reinforcements are frequently used to enhance several physical characteristics including mechanical properties, thermal stability, moisture resistance, oxygen barrier capabilities, and biodegradation rate, providing antimicrobial and antioxidant properties. This paper will provide an overview of the development of starch-based nanocomposite films and coatings applied in food packaging systems through the application of reinforcements and additives.
Controlling the Fiber Stress Distribution with Variable-Frequency Step Roll for Tunable Spun Yarn Structures
Authors: Peng Zhiyong , Li Wei , Chen Ze , Wang Pinxun , Su Ziyi , Sun Yue , Liu Keshuai , Xu Duo , Xu Weilin
Published: July 2023

The dynamic regulation of fiber stress distribution in the yarn-forming triangle area is critical for controlling variable composite yarn structures, including siro and sirofil composite yarns. In this study, comparison analyses of the variable geometric structure and stress distribution during the yarn-forming process, which involves step rolls with asymmetrical fiber control, have been carried out using ring-spinning technology. The geometric analyses show that partly staple fibers are continuously controlled while other fibers intermittently lack stress restraint, resulting in cyclically changed helical angles and wrapping density in the yarn-forming triangle area. The yarn structure model displayed that periodically distributed staple fibers occur in siro composite yarn, while sirofil composite yarn shows gradual periodic changes with uniform thickness variations, caused by cyclical changes in the stress distribution between filaments, and the strand altered the yarn-forming zone shapes from symmetrical to offset. Then, a systematic comparison of variable composite yarns with different frequencies (high, medium and low frequency) revealed that low-frequency step roll with wider grooves resulted in an intermittent output of staple fibers with less stress restraint, resulting in more pronounced structural variation in the siro and sirofil composite yarns with a slight yarn quality deterioration.
Flow Disturbance Characterization of Highly Filled Thermoset Injection Molding Compounds behind an Obstacle and in a Spiral Flow Part
Authors: Tran Ngoc Tu , Seefried Andreas , Gehde Michael , Hirz Jan , Klaas Dietmar
Published: July 2023

In the injection molding process, weld line regions occur when a molten polymer flow front is first separated and then rejoined. The position, length, and angle of weld lines are dependent on the gate location, injection speed, injection pressure, mold temperature, and, especially, the direction and degree of the polymer melt velocity in the mold-filling process. However, the wall surface velocity of the thermoset melt in the mold-filling process is not zero, which is not found for thermoplastic injection molding. The main reason leading to this difference is the slip phenomenon in the filling phase between the thermoset melt and the wall surface, which is directly affected by the filler content. In this study, commercial thermoset phenolic injection molding compounds with different amounts of filler were employed to investigate not only the mechanism of weld line formation and development behind an obstacle in the injection molding process but also the flow disturbance of the thermoset melt in the spiral flow part. In addition, the effect of the wall slip phenomenon on the flow disturbance characterization and the mechanism of weld lines of selected thermoset materials was carefully considered in this research. Furthermore, the generated material data sheet with the optimal developed reactive viscosity and curing kinetics model was imported into a commercial injection molding tool to predict the weld line formation as well as the mold-filling behavior of selected thermoset injection molding compounds, such as the flow length, cavity pressure profile, temperature distribution, and viscosity variation. The results obtained in this paper provide important academic knowledge about the flow disturbance behavior as well as its influence on the mechanism of weld line formation in the process of thermoset injection molding. Furthermore, the simulated results were compared with the experimental results, which helps provide an overview of the ability of computer simulation in the field of the reactive injection molding process.
Electrical Resistivity of 3D-Printed Polymer Elements
Authors: Stankevich Stanislav , Sevcenko Jevgenijs , Bulderberga Olga , Dutovs Aleksandrs , Erts Donat , Piskunovs Maksims , Ivanovs Valerijs , Ivanov Victor , Aniskevich Andrey
Published: July 2023

During this study, the resistivity of electrically conductive structures 3D-printed via fused filament fabrication (FFF) was investigated. Electrical resistivity characterisation was performed on various structural levels of the whole 3D-printed body, starting from the single traxel (3D-printed single track element), continuing with monolayer and multilayer formation, finalising with hybrid structures of a basic nonconductive polymer and an electrically conductive one. Two commercial conductive materials were studied: Proto-Pasta and Koltron G1. It was determined that the geometry and resistivity of a single traxel influenced the resistivity of all subsequent structural elements of the printed body and affected its electrical anisotropy. In addition, the results showed that thermal postprocessing (annealing) affected the resistivity of a standalone extruded fibre (extruded filament through a printer nozzle in freefall) and traxel. The effect of Joule heating and piezoresistive properties of hybrid structures with imprinted conductive elements made from Koltron G1 were investigated. Results revealed good thermal stability within 70 °C and considerable piezoresistive response with a gauge factor of 15–25 at both low 0.1% and medium 1.5% elongations, indicating the potential of such structures for use as a heat element and strain gauge sensor in applications involving stiff materials and low elongations.
Modification of Starches and Flours by Acetylation and Its Dual Modifications: A Review of Impact on Physicochemical Properties and Their Applications
Authors: Subroto Edy , Cahyana Yana , Indiarto Rossi , Rahmah Tiara Aray
Published: July 2023

Various modification treatments have been carried out to improve the physicochemical and functional properties of various types of starch and flour. Modification by acetylation has been widely used to improve the quality and stability of starch. This review describes the effects of acetylation modification and its dual modifications on the physicochemical properties of starch/flour and their applications. Acetylation can increase swelling power, swelling volume, water/oil absorption capacity, and retrogradation stability. The dual modification of acetylation with cross-linking or hydrothermal treatment can improve the thermal stability of starch/flour. However, the results of the modifications may vary depending on the type of starch, reagents, and processing methods. Acetylated starch can be used as an encapsulant for nanoparticles, biofilms, adhesives, fat replacers, and other products with better paste stability and clarity. A comparison of various characteristics of acetylated starches and their dual modifications is expected to be a reference for developing and applying acetylated starches/flours in various fields and products.
EW-YOLOv7: A Lightweight and Effective Detection Model for Small Defects in Electrowetting Display
Authors: Zheng Zihan , Chen Ningxia , Wu Jianhao , Xv Zhixuan , Liu Shuangyin , Luo Zhijie
Published: July 2023

In order to overcome the shortcomings of existing electrowetting display defect detection models in terms of computational complexity, structural complexity, detection speed, and detection accuracy, this article proposes an improved YOLOv7-based electrowetting display defect detection model. The model effectively optimizes the detection performance of display defects, especially small target defects, by integrating GhostNetV2 modules, Acmix attention mechanisms, and NGWD (Normalized Gaussian Wasserstein Distance) Loss. At the same time, it reduces the parameter size of the network model and improves the inference efficiency of the network. This article evaluates the performance of an improved model using a self-constructed electrowetting display defect dataset. The experimental results show that the proposed improved model achieves an average detection rate (mAP) of 89.5% and an average inference time of 35.9 ms. Compared to the original network, the number of parameters and computational costs are reduced by 19.2% and 64.3%, respectively. Compared with current state-of-the-art detection network models, the proposed EW-YOLOv7 exhibits superior performance in detecting electrowetting display defects. This model helps to solve the problem of defect detection in industrial production of electrowetting display and assists the research team in quickly identifying the causes and locations of defects.
Facile Electrochemical Biosensing Platform Based on Laser Induced Graphene/Laccase Electrode for the Effective Determination of Gallic Acid
Authors: Lin Xi , Zhou Yuchen , Lei Zhenfeng , Chen Rui , Chen Wanchun , Meng Xiangying , Li Yanxia
Published: July 2023

In this study, a facile electrochemical biosensing platform was fabricated with Laccase (Lac) immobilized on laser-induced graphene (LIG) electrode by glutaraldehyde covalently binding for the effective determination of gallic acid (GA). The patterned graphene for the LIG electrode was prepared by a one-step laser direct writing on the polyimide film in ambient air. The sheet layer and spatial mesh structures of LIG give the prepared LIG electrode a large specific surface area and good conductivity. The oxygen enrichment and good hydrophilicity cause LIG to favor covalent crosslinking with laccase through glutaraldehyde. The electrochemical sensor of GA on the prepared electrode was determined by chronoamperometry. Results show that the current signals of the laccase electrodes had an excellent linear relationship with GA in the concentration range of 0.1–20 mmol/L with a detection limit of 0.07 mmol/L under optimized experimental conditions. The prepared GA sensor with good selectivity, regeneration, and stability can be applied to biological samples such as sweat, urine and serum without needing sample pretreatment.
Neuro-Fuzzy Based High-Voltage DC Model to Optimize Frequency Stability of an Offshore Wind Farm
Authors: Bhutta Muhammad Shoaib , Xuebang Tang , Faheem Muhammad , Almasoudi Fahad M. , Alatawi Khaled Saleem S. , Guo Huali
Published: July 2023

Lack of synchronization between high voltage DC systems linking offshore wind farms and the onshore grid is a natural consequence owing to the stochastic nature of wind energy. The poor synchronization results in increased system disturbances, grid contingencies, power loss, and frequency instability. Emphasizing frequency stability analysis, this research investigates a dynamic coordination control technique for a Double Fed Induction Generator (DFIG) consisting of OWFs integrated with a hybrid multi-terminal HVDC (MTDC) system. Line commutated converters (LCC) and voltage source converters (VSC) are used in the suggested control method in order to ensure frequency stability. The adaptive neuro-fuzzy inference approach is used to accurately predict wind speed in order to further improve frequency stability. The proposed HVDC system can integrate multiple distributed OWFs with the onshore grid system, and the control strategy is designed based on this concept. In order to ensure the transient stability of the HVDC system, the DFIG-based OWF is regulated by a rotor side controller (RSC) and a grid side controller (GSC) at the grid side using a STATCOM. The devised HVDC (MTDC) is simulated in MATLAB/SIMULINK, and the performance is evaluated in terms of different parameters, such as frequency, wind power, rotor and stator side current, torque, speed, and power. Experimental results are compared to a conventional optimal power flow (OPF) model to validate the performance.
Hydrocarbon Generation History of the Eocene Source Rocks in the Fushan Depression, South China Sea: Insights from a Basin Modeling Study
Authors: Zeng Bang , Lu Zhenghuan , Yang Taotao , Shi Yang , Guo Hao , Wang Xin , Liao Feiyan , Li Meijun
Published: July 2023

Reconstruction of hydrocarbon generation history is essential to understanding the petroleum system. In this study, basin modeling was employed to investigate the primary source rocks in the Fushan Depression (FD), a significant oil-bearing basin situated in the South China Sea. The research findings indicate that different tectonic zones within the FD underwent distinct hydrocarbon generation stages. The step-fault zone and the central sag zone experienced one hydrocarbon generation stage at 10–0 Ma and 30–0 Ma, respectively. The slope zone, on the other hand, experienced two hydrocarbon generation stages, 40–23.5 Ma and 10–0 Ma, controlled by tectonic movements and heat flow variations. Furthermore, critical times for the process of the petroleum system have been determined based on this work and previous literature. The slope zone in the eastern FD is considered a favorable area for conventional hydrocarbon exploration due to the high maturity of source rocks promoted by volcanic heating and two significant oil charges. The central sag zone is identified as an excellent prospect for unconventional resources because of the substantial retention of hydrocarbons in in-source unconventional reservoirs long after hydrocarbon generation. These findings provide a valuable guide for further exploration.
Research on the Disassembly Process and Model of Waste Mobile Phone Circuit Board Components
Authors: Jiang Yuxuan , Zhao Min , Zhao Litao , Chen Qin , Huang Qing , Song Xiaolong , Zhang Chenglong , Wang Jingwei
Published: July 2023

Dismantling the waste printed circuit boards (WPCBs) of obsolete mobile phones is essential for resource recycling and environmental protection. An automated WPCB disassembly equipment based on the hot-vibration process was designed and applied, with optimized process conditions of a heating temperature of 250 °C and an equipment amplitude of >3.66 mm. The dismantling rate for electronic components and metal shields was 98%, but disassembly of components with underfill was less effective. Both simulation and actual measurement results of the equipment’s thermal field showed that the temperature inside the disassembly bin was uniform, with a maximum temperature difference of 6–8 °C. The area of the low-temperature region accounted for approximately 5% of the total area. The acceleration ranged from 2.11 to 8.28 g when using the disassembly force model. This equipment and process can be applied to disassemble large quantities of WPCBs.
Thousands of Glittering Shards: Spirituality as Resonance in the Lives of People with Intellectual Disabilities
Authors: Dow Keith
Published: July 2023

In the Kabbalah creation myth, God creates the universe by “stepping back”, releasing ten holy vessels with his light—only to have those vessels shatter with shards of divine light, or “shards” scattered throughout the earth. In a parallel approach, this paper suggests that the sacred must be sought in diverse encounters within everyday life and professional practice. In counseling or other therapeutic support, the definition of and search for spiritual dimensions must be broadened to thoughtfully incorporate the diverse experiences and expressions of people with intellectual disabilities. Similarly, those who seek to understand people’s relationship with the divine and support meaning in their lives must welcome a wide range of “artistic” engagements, an approach exemplified in grief and loss intervention. This article concludes by pointing towards resonance as a helpful concept to reconceptualize accessible spirituality in future work.
Type Synthesis of 5-DOF Hybrid (Parallel-Serial) Manipulators Designed from Open Kinematic Chains
Authors: Antonov Anton , Fomin Alexey , Glazunov Victor , Petelin Daniil , Filippov Gleb
Published: July 2023

The article proposes an approach for synthesizing hybrid (parallel-serial) manipulators with five degrees of freedom (5-DOF) using open kinematic chains. The method idea consists in taking an open kinematic chain, selecting a subchain within it, and replacing the subchain with a parallel mechanism. The article considers 5-DOF open chains and 3-DOF subchains, substituted for 3-DOF parallel mechanisms with the same motion pattern as the subchain. Thus, synthesized hybrid manipulators have a 3-DOF parallel part and a 2-DOF serial part. First, we grouped 26 structures of open chains with revolute and prismatic joints into five types and 78 subtypes. Next, for each type, we selected one subtype and presented several hybrid mechanisms that can correspond to it. We considered hybrid manipulators that included 3-DOF parallel mechanisms with planar, spherical, and other commonly used motion types. The suggested synthesis method is intuitive for a designer, and it does not need any mathematical formulations like screw theory or group theory approaches.
Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico
Authors: Portillo-Quintero Carlos , Hernandez-Stefanoni Jose Luis , Dupuy Juan Manuel
Published: July 2023

The Puuc Biocultural State Reserve (PBSR) is a unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on maintaining low-impact productive activities coordinated by multiple communal and private landowners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and their relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000–2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (±19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000–2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing changed over the years after the creation of the PBSR in 2011. However, an emergent hotspot analysis shows that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012–2021 period was less common than prior to 2011, and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, the results show that landowners outside the PBSR often clear forests with lower carbon density and species diversity than those inside the PBSR. This suggests that, compared to landowners outside the PBSR, landowners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012–2021 period, minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend continuing efforts to provide alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. Combining these models with continuous change detection datasets will allow for underlying ecological processes to be revealed and the generation of information better adapted to forest governance scales.
Comparison of Different Important Predictors and Models for Estimating Large-Scale Biomass of Rubber Plantations in Hainan Island, China
Authors: Li Xin , Wang Xincheng , Gao Yuanfeng , Wu Jiuhao , Cheng Renxi , Ren Donghao , Bao Qing , Yun Ting , Wu Zhixiang , Xie Guishui , Chen Bangqian
Published: July 2023

Rubber (Hevea brasiliensis Muell.) plantations are among the most critical agricultural ecosystems in tropical regions, playing a vital role in regional carbon balance. Accurate large-scale biomass estimation for these plantations remains a challenging task due to the severe signal saturation problem. Recent advances in remote sensing big data, cloud platforms, and machine learning have facilitated the precise acquisition of key physiological variables, such as stand age (A) and canopy height (H), which are critical parameters for biomass estimation but have been underutilized in prior studies. Using Hainan Island—the second-largest rubber planting base in China—as a case study, we integrated extensive ground surveys, maps of stand age and canopy height, remote sensing indicators (RSIs), and geographical and climate indicators (ECIs) to ascertain the optimal method for estimating rubber plantation biomass. We compared different inputs and estimation approaches (direct and indirect) using the random forest algorithm and analyzed the spatiotemporal characteristics of rubber plantation biomass on Hainan Island. The results indicated that the traditional model (RSIs + ECIs) had low accuracy and significant estimation bias (R2 = 0.24, RMSE = 38.36 mg/ha). The addition of either stand age or canopy height considerably enhance model accuracy (R2 = 0.77, RMSE ≈ 21.12 mg/ha). Moreover, incorporating the DBH obtained through indirect inversion yielded even greater predictive accuracy (R2 = 0.97, RMSE = 7.73 mg/ha), outperforming estimates derived from an allometric equation model input with the DBH (R2 = 0.67, RMSE = 25.43 mg/ha). However, augmenting the model with stand age, canopy height, or their combination based on RSIs, ECIs, and DBH only marginally improved the accuracy. Consequently, it is not recommended in scenarios with limited data and computing resources. Employing the optimal model, we generated biomass maps of rubber plantations on Hainan Island for 2016 and 2020, revealing that the spatiotemporal distribution pattern of the biomass is closely associated with the establishment year of the rubber plantations. While average biomass in a few areas has undergone slight decreases, total biomass has exhibited significant growth, reaching 5.46 × 107 mg by the end of 2020, underscoring its considerable value as a carbon sink.
Multiscale Representation of Radar Echo Data Retrieved through Deep Learning from Numerical Model Simulations and Satellite Images
Authors: Zhu Mingming , Liao Qi , Wu Lin , Zhang Si , Wang Zifa , Pan Xiaole , Wu Qizhong , Wang Yangang , Su Debin
Published: July 2023

Radar reflectivity data snapshot fine-grained atmospheric variations that cannot be represented well by numerical weather prediction models or satellites, which poses a limit for nowcasts based on model–data fusion techniques. Here, we reveal a multiscale representation (MSR) of the atmosphere by reconstructing the radar echoes from the Weather Research and Forecasting (WRF) model simulations and the Himawari-8 satellite products using U-Net deep networks. Our reconstructions generated the echoes well in terms of patterns, locations, and intensities with a root mean square error (RMSE) of 5.38 dBZ. We find stratified features in this MSR, with small-scale patterns such as echo intensities sensitive to the WRF-simulated dynamic and thermodynamic variables and with larger-scale information about shapes and locations mainly captured from satellite images. Such MSRs with physical interpretations may inspire innovative model–data fusion methods that could overcome the conventional limits of nowcasting.
Infrared Image-Enhancement Algorithm for Weak Targets in Complex Backgrounds
Authors: Li Yingchao , Ma Lianji , Yang Shuai , Fu Qiang , Sun Hongyu , Wang Chao
Published: July 2023

Infrared small-target enhancement in complex contexts is one of the key technologies for infrared search and tracking systems. The effect of enhancement directly determines the reliability of the monitoring equipment. To address the problem of the low signal-to-noise ratio of small infrared moving targets in complex backgrounds and the poor effect of traditional enhancement algorithms, an accurate enhancement method for small infrared moving targets based on two-channel information is proposed. For a single frame, a modified curvature filter is used in the A channel to weaken the background while an improved PM model is used to enhance the target, and a modified band-pass filter is used in the B channel for coarse enhancement followed by a local contrast algorithm for fine enhancement, based on which a weighted superposition algorithm is used to extract a single-frame candidate target. The results of the experimental data analysis prove that the method has a good enhancement effect and robustness for small IR motion target enhancement in complex backgrounds, and it outperforms other advanced algorithms by about 43.7% in ROC.
Towards Topology-Free Programming for Cyber-Physical Systems with Process-Oriented Paradigm
Authors: Zyubin Vladimir E. , Garanina Natalia O. , Anureev Igor S. , Staroletov Sergey M.
Published: July 2023

The paper proposes a topology-free specification of distributed control systems by means of a process-oriented programming paradigm. The proposed approach was characterized, on the one hand, by a topologically independent specification of the control algorithm and, on the other hand, by the possibility of using existing formal verification methods by preserving the semantics of a centralized process-oriented program. The paper discusses the advantages of a topologically independent specification of distributed control systems, outlines the features of control software, argues why the use of a process-oriented approach to the development of the automation of cyber-physical systems is suitable for solving these problems, describes a general scheme for implementing a distributed control system according to a process-oriented specification, and proposes a formal heuristic algorithm for partitioning a sequential process-oriented program into independent clusters. We illustrate our algorithm with bottle-filling and sluice case studies.
Acoustic Lung Imaging Utilized in Continual Assessment of Patients with Obstructed Airway: A Systematic Review
Authors: Lee Chang-Sheng , Li Minghui , Lou Yaolong , Abbasi Qammer H. , Imran Muhammad Ali
Published: July 2023

Smart respiratory therapy is enabled by continual assessment of lung functions. This systematic review provides an overview of the suitability of equipment-to-patient acoustic imaging in continual assessment of lung conditions. The literature search was conducted using Scopus, PubMed, ScienceDirect, Web of Science, SciELO Preprints, and Google Scholar. Fifteen studies remained for additional examination after the screening process. Two imaging modalities, lung ultrasound (LUS) and vibration imaging response (VRI), were identified. The most common outcome obtained from eleven studies was positive observations of changes to the geographical lung area, sound energy, or both, while positive observation of lung consolidation was reported in the remaining four studies. Two different modalities of lung assessment were used in eight studies, with one study comparing VRI against chest X-ray, one study comparing VRI with LUS, two studies comparing LUS to chest X-ray, and four studies comparing LUS in contrast to computed tomography. Our findings indicate that the acoustic imaging approach could assess and provide regional information on lung function. No technology has been shown to be better than another for measuring obstructed airways; hence, more research is required on acoustic imaging in detecting obstructed airways regionally in the application of enabling smart therapy.
Evaluating the Performance of Pre-Trained Convolutional Neural Network for Audio Classification on Embedded Systems for Anomaly Detection in Smart Cities
Authors: Lamrini Mimoun , Chkouri Mohamed Yassin , Touhafi Abdellah
Published: July 2023

Environmental Sound Recognition (ESR) plays a crucial role in smart cities by accurately categorizing audio using well-trained Machine Learning (ML) classifiers. This application is particularly valuable for cities that analyzed environmental sounds to gain insight and data. However, deploying deep learning (DL) models on resource-constrained embedded devices, such as Raspberry Pi (RPi) or Tensor Processing Units (TPUs), poses challenges. In this work, an evaluation of an existing pre-trained model for deployment on Raspberry Pi (RPi) and TPU platforms other than a laptop is proposed. We explored the impact of the retraining parameters and compared the sound classification performance across three datasets: ESC-10, BDLib, and Urban Sound. Our results demonstrate the effectiveness of the pre-trained model for transfer learning in embedded systems. On laptops, the accuracy rates reached 96.6% for ESC-10, 100% for BDLib, and 99% for Urban Sound. On RPi, the accuracy rates were 96.4% for ESC-10, 100% for BDLib, and 95.3% for Urban Sound, while on RPi with Coral TPU, the rates were 95.7% for ESC-10, 100% for BDLib and 95.4% for the Urban Sound. Utilizing pre-trained models reduces the computational requirements, enabling faster inference. Leveraging pre-trained models in embedded systems accelerates the development, deployment, and performance of various real-time applications.
Intelligent Drone Positioning via BIC Optimization for Maximizing LPWAN Coverage and Capacity in Suburban Amazon Environments
Authors: Ferreira Flávio Henry Cunha da Silva , Neto Miércio Cardoso de Alcântara , Barros Fabrício José Brito , Araújo Jasmine Priscyla Leite de
Published: July 2023

This paper aims to provide a metaheuristic approach to drone array optimization applied to coverage area maximization of wireless communication systems, with unmanned aerial vehicle (UAV) base stations, in the context of suburban, lightly to densely wooded environments present in cities of the Amazon region. For this purpose, a low-power wireless area network (LPWAN) was analyzed and applied. LPWAN are systems designed to work with low data rates but keep, or even enhance, the extensive area coverage provided by high-powered networks. The type of LPWAN chosen is LoRa, which operates at an unlicensed spectrum of 915 MHz and requires users to connect to gateways in order to relay information to a central server; in this case, each drone in the array has a LoRa module installed to serve as a non-fixated gateway. In order to classify and optimize the best positioning for the UAVs in the array, three concomitant bioinspired computing (BIC) methods were chosen: cuckoo search (CS), flower pollination algorithm (FPA), and genetic algorithm (GA). Positioning optimization results are then simulated and presented via MATLAB for a high-range IoT-LoRa network. An empirically adjusted propagation model with measurements carried out on a university campus was developed to obtain a propagation model in forested environments for LoRa spreading factors (SF) of 8, 9, 10, and 11. Finally, a comparison was drawn between drone positioning simulation results for a theoretical propagation model for UAVs and the model found by the measurements.
Eye-Gaze Controlled Wheelchair Based on Deep Learning
Authors: Xu Jun , Huang Zuning , Liu Liangyuan , Li Xinghua , Wei Kai
Published: July 2023

In this paper, we design a technologically intelligent wheelchair with eye-movement control for patients with ALS in a natural environment. The system consists of an electric wheelchair, a vision system, a two-dimensional robotic arm, and a main control system. The smart wheelchair obtains the eye image of the controller through a monocular camera and uses deep learning and an attention mechanism to calculate the eye-movement direction. In addition, starting from the relationship between the trajectory of the joystick and the wheelchair speed, we establish a motion acceleration model of the smart wheelchair, which reduces the sudden acceleration of the smart wheelchair during rapid motion and improves the smoothness of the motion of the smart wheelchair. The lightweight eye-movement recognition model is transplanted into an embedded AI controller. The test results show that the accuracy of eye-movement direction recognition is 98.49%, the wheelchair movement speed is up to 1 m/s, and the movement trajectory is smooth, without sudden changes.
Monitoring and Analysis of the Collapse Process in Blasting Demolition of Tall Reinforced Concrete Chimneys
Authors: Huang Xiaowu , Xie Xianqi , Sun Jinshan , Zhong Dongwang , Yao Yingkang , Tu Shengwu
Published: July 2023

Aiming at the problem of displacement of collapse direction caused by the impact of the high-rise reinforced concrete chimney in the process of blasting demolition, combined with the monitoring methods such as high-speed photography observation, piezoelectric ceramic sensor, and blasting vibration monitor, the impact process of the 180 m high chimney was comprehensively analyzed. The results show that the chimney will experience multiple ‘weight loss’ and ‘overweight’ effects during the sit-down process, inducing compressive stress waves in the chimney. When the sit-down displacement is large, the broken reinforced concrete at the bottom can play a significant buffering effect, and the ‘overweight’ effect gradually weakens until the sit-down stops. The stress of the inner and outer sides of the chimney wall is obviously different in the process of collapsing and touching the ground. The waveform of the monitoring point of the piezoelectric ceramic sensor is divided into three stages, which specifically characterizes the evolution process of the explosion load and the impact of the chimney. The vibration induced by explosive explosion is mainly high-frequency vibration above 50 Hz, the vibration induced by chimney collapse is mainly low-frequency vibration below 10 Hz, and the vibration characteristics are obviously different. In the process of blasting demolition and collapse of high-rise reinforced concrete chimney, due to the impact of sitting down, the wall of the support tube is subjected to uneven force, resulting in the deviation of the collapse direction. In practical engineering, the control measures of chimney impact, blasting vibration, and collapse touchdown vibration should be fully strengthened to ensure the safety of the protection target around the blasting demolition object.
A Wearable Multi-Sensor Array Enables the Recording of Heart Sounds in Homecare
Authors: Giordano Noemi , Rosati Samanta , Balestra Gabriella , Knaflitz Marco
Published: July 2023

The home monitoring of patients affected by chronic heart failure (CHF) is of key importance in preventing acute episodes. Nevertheless, no wearable technological solution exists to date. A possibility could be offered by Cardiac Time Intervals extracted from simultaneous recordings of electrocardiographic (ECG) and phonocardiographic (PCG) signals. Nevertheless, the recording of a good-quality PCG signal requires accurate positioning of the stethoscope over the chest, which is unfeasible for a naïve user as the patient. In this work, we propose a solution based on multi-source PCG. We designed a flexible multi-sensor array to enable the recording of heart sounds by inexperienced users. The multi-sensor array is based on a flexible Printed Circuit Board mounting 48 microphones with a high spatial resolution, three electrodes to record an ECG and a Magneto-Inertial Measurement Unit. We validated the usability over a sample population of 42 inexperienced volunteers and found that all subjects could record signals of good to excellent quality. Moreover, we found that the multi-sensor array is suitable for use on a wide population of at-risk patients regardless of their body characteristics. Based on the promising findings of this study, we believe that the described device could enable the home monitoring of CHF patients soon.
A Fast Algorithm for Intra-Frame Versatile Video Coding Based on Edge Features
Authors: Zhao Shuai , Shang Xiwu , Wang Guozhong , Zhao Haiwu
Published: July 2023

Versatile Video Coding (VVC) introduces many new coding technologies, such as quadtree with nested multi-type tree (QTMT), which greatly improves the efficiency of VVC coding. However, its computational complexity is higher, which affects the application of VVC in real-time scenarios. Aiming to solve the problem of the high complexity of VVC intra coding, we propose a low-complexity partition algorithm based on edge features. Firstly, the Laplacian of Gaussian (LOG) operator was used to extract the edges in the coding frame, and the edges were divided into vertical and horizontal edges. Then, the coding unit (CU) was equally divided into four sub-blocks in the horizontal and vertical directions to calculate the feature values of the horizontal and vertical edges, respectively. Based on the feature values, we skipped unnecessary partition patterns in advance. Finally, for the CUs without edges, we decided to terminate the partition process according to the depth information of neighboring CUs. The experimental results show that compared with VTM-13.0, the proposed algorithm can save 54.08% of the encoding time on average, and the BDBR (Bjøntegaard delta bit rate) only increases by 1.61%.
A Survey on Autism Care, Diagnosis, and Intervention Based on Mobile Apps: Focusing on Usability and Software Design
Authors: Liu Xiongyi , Zhao Wenbing , Qi Quan , Luo Xiong
Published: July 2023

This article presents a systematic review on autism care, diagnosis, and intervention based on mobile apps running on smartphones and tablets. Here, the term “intervention” means a carefully planned set of activities with the objective of improving autism symptoms. We guide our review on related studies using five research questions. First, who benefits the most from these mobile apps? Second, what are the primary purposes of these mobile apps? Third, what mechanisms have been incorporated in these mobiles apps to improve usability? Fourth, what guidelines have been used in the design and implementation of these mobile apps? Fifth, what theories and frameworks have been used as the foundation for these mobile apps to ensure the intervention effectiveness? As can be seen from these research questions, we focus on the usability and software development of the mobile apps. Informed by the findings of these research questions, we propose a taxonomy for the mobile apps and their users. The mobile apps can be categorized into autism support apps, educational apps, teacher training apps, parental support apps, and data collection apps. The individuals with autism spectrum disorder (ASD) are the primary users of the first two categories of apps. Teachers of children with ASD are the primary users of the teacher training apps. Parents are the primary users of the parental support apps, while individuals with ASD are usually the primary users of the data collection apps and clinicians and autism researchers are the beneficiaries. Gamification, virtual reality, and autism-specific mechanisms have been used to improve the usability of the apps. User-centered design is the most popular approach for mobile app development. Augmentative and alternative communication, video modeling, and various behavior change practices have been used as the theoretical foundation for intervention efficacy.
The Design and Optimization of an Acoustic and Ambient Sensing AIoT Platform for Agricultural Applications
Authors: Alzuhair Ahmed , Alghaihab Abdullah
Published: July 2023

The use of technology in agriculture has been gaining significant attention recently. By employing advanced tools and automation and leveraging the latest advancements in the Internet of Things (IoT) and artificial intelligence (AI), the agricultural sector is witnessing improvements in its crop yields and overall efficiency. This paper presents the design and performance analysis of a machine learning (ML) model for agricultural applications involving acoustic sensing. This model is integrated into an efficient Artificial Intelligence of Things (AIoT) platform tailored for agriculture. The model is then used in the design of a communication network architecture and for determining the distribution of the computing load between edge devices and the cloud. The study focuses on the design, analysis, and optimization of AI deployment for reliable classification models in agricultural applications. Both the architectural level and hardware implementation are taken into consideration when designing the radio module and computing unit. Additionally, the study encompasses the design and performance analysis of the hardware used to implement the sensor node specifically developed for sound classification in agricultural applications. The novelty of this work lies in the optimization of the integrated sensor node, which combines the proposed ML model and wireless network, resulting in an agricultural-specific AIoT platform. This co-design enables significant improvements in the performance and efficiency for acoustic and ambient sensing applications.