bluuebunny/crossref_metadata_2025 huggingface dataset:
Scientific Advances in the Last Decade on the Recovery, Characterization, and Functionality of Bioactive Compounds from the Araticum Fruit (Annona crassiflora Mart.)
Authors: Arruda Henrique Silvano , Borsoi Felipe Tecchio , Andrade Amanda Cristina , Pastore Glaucia Maria , Marostica Junior Mario Roberto
Published: April 2023

Araticum (Annona crassiflora Mart.) is a native and endemic species to Brazilian Cerrado whose fruits have high sensorial, nutritional, bioactive, and economic potential. Its use in local folk medicine, associated with recent scientific findings, has attracted growing interest from different industrial sectors. Therefore, understanding the scientific advances achieved so far and identifying gaps to be filled is essential to direct future studies and transform accumulated knowledge into innovative technologies and products. In this review, we summarize the phytochemical composition, bioactivities, and food products from araticum fruit that have been reported in the scientific literature over the past 10 years. The compiled data showed that araticum fruit parts contain a wide range of bioactive compounds, particularly phenolic compounds, alkaloids, annonaceous acetogenins, carotenoids, phytosterols, and tocols. These phytochemicals contribute to different biological activities verified in araticum fruit extracts/fractions, including antioxidant, anti-inflammatory, anti-Alzheimer, anticancer, antidiabetic, anti-obesity, antidyslipidemic, antinociceptive, hepatoprotective, healing of the cutaneous wound, antibacterial, and insecticide effects. Despite the promising findings, further studies—particularly toxicological (especially, with byproducts), pre-clinical, and clinical trials—must be conducted to confirm these biological effects in humans and assure the safety and well-being of consumers.
An Insight into In Vitro Antioxidant, Antimicrobial, Cytotoxic, and Apoptosis Induction Potential of Mangiferin, a Bioactive Compound Derived from Mangifera indica
Authors: Yehia Ramy S. , Altwaim Sarah A.
Published: April 2023

Due to their low cost, toxicity, and health risks, medicinal plants have come to be seen as useful products and sources of biologically active compounds. Mangifera indica L., a medicinal plant with a long history, has a high bioactive metabolites content. Mangiferin (C19H18O11) is primary isolated from M. indica’s leaves, which has many pharmacological benefits. In this investigation, ultrasonic-assisted extraction with ethanol as the extraction solvent was applied to obtain mangiferin from a local type of M. indica leaves. HPLC was performed after a dichloromethane-ethyl acetate liquid–liquid fractionation method. Further, UV–vis, FTIR, and NMR spectroscopy were utilized to elucidate the structure. Interestingly, purified mangiferin displayed promising antimicrobial efficacy against a diverse variety of fungal and bacterial pathogens with MICs of 1.95–62.5 and 1.95–31.25 µg/mL, respectively. Time–kill patterns also showed that mangiferin had both bactericidal and fungicidal action. Furthermore, it exhibited strong radical dosage-dependent scavenging activity (IC50 = 17.6 μg/mL) compared to vitamin C (Vc, IC50 = 11.9 μg/mL), suggesting it could be developed into a viable antioxidant agent. To our delight, the IC50 values of mangiferin for the MCF-7 and HeLa cell lines were 41.2 and 44.7 μg/mL, respectively, from MTT cell viability testing, and it was less harmful when tested against the noncancerous cell line. Notably, it significantly induced cell apoptosis in MCF-7 cells by 62.2–83.4% using annexin V-FITC/PI labeling. Hence, our findings suggest that mangiferin can be used in the medical industry to create therapeutic interventions and medication delivery systems for society.
Caffeine Release from Magneto-Responsive Hydrogels Controlled by External Magnetic Field and Calcium Ions and Its Effect on the Viability of Neuronal Cells
Authors: Frachini Emilli C. G. , Selva Jéssica S. G. , Falcoswki Paula C. , Silva Jean B. , Cornejo Daniel R. , Bertotti Mauro , Ulrich Henning , Petri Denise F. S.
Published: April 2023

Caffeine (CAF) is a psychostimulant present in many beverages and with rapid bioabsorption. For this reason, matrices that effectuate the sustained release of a low amount of CAF would help reduce the intake frequency and side effects caused by high doses of this stimulant. Thus, in this study, CAF was loaded into magnetic gelatin/alginate (Gel/Alg/MNP) hydrogels at 18.5 mg/ghydrogel. The in vitro release of CAF was evaluated in the absence and presence of an external magnetic field (EMF) and Ca2+. In all cases, the presence of Ca2+ (0.002 M) retarded the release of CAF due to favorable interactions between them. Remarkably, the release of CAF from Gel/Alg/MNP in PBS/CaCl2 (0.002 M) at 37 °C under an EMF was more sustained due to synergic effects. In PBS/CaCl2 (0.002 M) and at 37 °C, the amounts of CAF released after 45 min from Gel/Alg and Gel/Alg/MNP/EMF were 8.3 ± 0.2 mg/ghydrogel and 6.1 ± 0.8 mg/ghydrogel, respectively. The concentration of CAF released from Gel/Alg and Gel/Alg/MNP hydrogels amounted to ~0.35 mM, thereby promoting an increase in cell viability for 48 h. Gel/Alg and Gel/Alg/MNP hydrogels can be applied as reservoirs to release CAF at suitable concentrations, thus forestalling possible side effects and improving the viability of SH-SY5Y cells.
Morphology and Selected Properties of Modified Potato Thermoplastic Starch
Authors: Jeziorska Regina , Szadkowska Agnieszka , Studzinski Maciej , Chmielarek Michal , Spasowka Ewa
Published: April 2023

Potato thermoplastic starch (TPS) containing 1 wt.% of pure halloysite (HNT), glycerol-modified halloysite (G-HNT) or polyester plasticizer-modified halloysite (PP-HNT) was prepared by melt-extrusion. Halloysites were characterized by FTIR, SEM, TGA, and DSC. Interactions between TPS and halloysites were studied by FTIR, SEM, and DMTA. The Vicat softening temperature, tensile, and flexural properties were also determined. FTIR proved the interactions between halloysite and the organic compound as well as between starch, plasticizers and halloysites. Pure HNT had the best thermal stability, but PP-HNT showed better thermal stability than G-HNT. The addition of HNT and G-HNT improved the TPS’s thermal stability, as evidenced by significantly higher T5%. Modified TPS showed higher a Vicat softening point, suggesting better hot water resistance. Halloysite improved TPS stiffness due to higher storage modulus. However, TPS/PP-HNT had the lowest stiffness, and TPS/HNT the highest. Halloysite increased Tα and lowered Tβ due to its simultaneous reinforcing and plasticizing effect. TPS/HNT showed an additional β-relaxation peak, suggesting the formation of a new crystalline phase. The mechanical properties of TPS were also improved in the presence of both pure and modified halloysites.
Preparation of Crosslinked Poly(acrylic acid-co-acrylamide)-Grafted Deproteinized Natural Rubber/Silica Composites as Coating Materials for Controlled Release of Fertilizer
Authors: Inphonlek Supharat , Jarukumjorn Kasama , Chumsamrong Pranee , Ruksakulpiwat Chaiwat , Ruksakulpiwat Yupaporn
Published: April 2023

The crosslinked poly(acrylic acid-co-acrylamide)-grafted deproteinized natural rubber/silica ((PAA-co-PAM)-DPNR/silica) composites were prepared and applied as coating materials for fertilizer in this work. The crosslinked (PAA-co-PAM)-DPNR was prepared via emulsion graft copolymerization in the presence of MBA as a crosslinking agent. The modified DPNR was mixed with various contents of silica (10 to 30 phr) to form the composites. The existence of crosslinked (PAA-co-PAM) after modification provided a water adsorption ability to DPNR. The swelling degree values of composites were found in the range of 2217.3 ± 182.0 to 8132.3 ± 483.8%. The addition of silica in the composites resulted in an improvement in mechanical properties. The crosslinked (PAA-co-PAM)-DPNR with 20 phr of silica increased its compressive strength and compressive modulus by 1.61 and 1.55 times compared to the unloaded silica sample, respectively. There was no breakage of samples after 80% compression strain. Potassium nitrate, a model fertilizer, was loaded into chitosan beads with a loading percentage of 40.55 ± 1.03% and then coated with the modified natural rubber/silica composites. The crosslinked (PAA-co-PAM)-DPNR/silica composites as the outer layers had the ability of holding water in their structure and retarded the release of fertilizer. These composites could be promising materials for controlled release and water retention that would have potential for agricultural application.
Fabrication and Assessment of Orodispersible Tablets Loaded with Cubosomes for the Improved Anticancer Activity of Simvastatin against the MDA-MB-231 Breast Cancer Cell Line
Authors: Zaki Randa Mohammed , El Sayeh Abou El Ela Amal , Almurshedi Alanood S. , Aldosari Basmah Nasser , Aldossari Abdullah A. , Ibrahim Mohamed A.
Published: April 2023

Various factors limit the use of simvastatin as an anticancer drug. Therefore, this study aimed to analyse simvastatin (SIM)-loaded cubosome efficacy against breast cancer. SIM-loaded cubosomes were prepared using the emulsification method using different glyceryl monooleate, Pluronic F127 (PF-127), and polyvinyl alcohol (PVA) ratios. The best cubosomal formula was subjected to an in vitro cytotoxicity analysis using the human breast cancer cell line, MDA-MB-231 (MDA) (ATCC, HTB-26), and formulated as oral disintegrating tablets through direct compression. PF-127 and PVA positively affected drug loading, and the entrapment efficiency percentage of different SIM-cubosomal formulations ranged from 33.52% to 80.80%. Vesicle size ranged from 181.9 ± 0.50 to 316.6 ± 1.25 nm. PF-127 enhanced in vitro SIM release from cubosome formulations due to its solubilising action on SIM. The in vitro dissolution analysis indicated that SIM exhibited an initial dissolution of 10.4 ± 0.25% within the first 5 min, and 63.5 ± 0.29% of the loaded drug was released after 1 h. Moreover, cubosome formula F3 at 25 and 50 µg/mL doses significantly decreased MDA cell viability compared to the 12.5 µg/mL dose. The untreated SIM suspension and drug-free cubosomes at all doses had no significant influence on MDA cell viability compared to the control.
Modelling and Scaling-Up of a Supercritical Fluid Extraction of Emulsions Process
Authors: Tirado Diego F. , Cabañas Albertina , Calvo Lourdes
Published: April 2023

Supercritical CO2 (scCO2) is utilized in the supercritical fluid extraction of emulsions (SFEE) to swiftly extract the organic phase (O) from an O/W emulsion. The dissolved substances in the organic phase precipitate into small particles and remain suspended in the water (W) with the aid of a surfactant. The process can be continuously conducted using a packed column in a counter-current flow of the emulsion and scCO2, at moderate pressure (8–10 MPa) and temperature (37–40 °C). To ensure the commercial viability of this technique, the organic solvent must be separated from the CO2 to facilitate the recirculation of both streams within the process while minimizing environmental impact. Thus, the aim of this work was to design a plant to produce submicron materials using SFEE, integrating the recovery of both solvents. First, experimental equilibrium data of the ternary system involved (CO2/ethyl acetate/water) were fitted with a proper thermodynamic model. Then, simulations of the whole integrated process at different scales were carried out using Aspen Plus®, along with economical evaluations. This work proposes the organic solvent separation with a distillation column. Thus, the two solvents can be recovered and recycled to the process in almost their entirety. Furthermore, the particles in the aqueous raffinate are produced free of solvents and sterilized for further safe use. The costs showed an important economy scale-up. This work could ease the transfer of the SFEE technology to the industry.
Application of Wearable Gloves for Assisted Learning of Sign Language Using Artificial Neural Networks
Authors: Kim Hyeon-Jun , Baek Soo-Whang
Published: April 2023

This study proposes the design and application of wearable gloves that can recognize sign language expressions from input images via long short-term memory (LSTM) network models and can learn sign language through finger movement generation and vibration motor feedback. It is difficult for nondisabled people who do not know sign language to express sign language accurately. Therefore, we suggest the use of wearable gloves for sign language education to help nondisabled people learn and accurately express sign language. The wearable glove consists of a direct current motor, a link (finger exoskeleton) that can generate finger movements, and a flexible sensor that recognizes the degree of finger bending. When the coordinates of the hand move in the input image, the sign language motion is fed back through the vibration motor attached to the wrist. The proposed wearable glove can learn 20 Korean sign language words, and the data used for learning are configured to represent the joint coordinates and joint angles of both the hands and body for these 20 sign language words. Prototypes were produced based on the design, and it was confirmed that the angle of each finger could be adjusted. Through experiments, a sign language recognition model was selected, and the validity of the proposed method was confirmed by comparing the generated learning results with the data sequence. Finally, we compared and verified the accuracy and learning loss using a recurrent neural network and confirmed that the test results of the LSTM model showed an accuracy of 85%.
Statistical Investigation of Rotary Fluidized Bed Agglomeration Process with Tangential Spray and In-Line Particle Size Measurement for PAT Process Control
Authors: Langner Marcel , Zhou Biwen , Priese Florian , Wolf Bertram
Published: April 2023

A statistical design of experiments for a rotary fluidized bed agglomeration process is performed to improve both the knowledge of the process and the influence of the process parameters. Agglomerates of a pharmaceutical formulation are manufactured in a laboratory fluidized bed rotor apparatus with a tangential spray nozzle. Particle size is measured in-line over the entire agglomeration process with a spatial filter velocimetry probe installed directly in the process chamber and off-line with dynamic image analysis for comparison. The influence of the process parameters spray rate, spray pressure, rotor speed, and process air temperature on the fluidized bed is investigated using a central composite design. In-line measurement of particle size is possible over the entire rotor process. Spray pressure, spray rate, square of process air temperature, and some interactions proved to be statistically significant. Particle size measured with spatial filter velocimetry and dynamic image analysis indicates good agreement and a similar trend. The successful application of particle size measurement in a fluidized bed rotor agglomeration at a laboratory scale using spatial filter velocimetry to improve process control and reduce the risk of failed batches serves as the basis for transferring to a production scale.
Continuous-Flow Hydrogenation of Nitroaromatics in Microreactor with Mesoporous Pd@SBA-15
Authors: Chai Kejie , Shen Runqiu , Qi Tingting , Chen Jianli , Su Weike , Su An
Published: April 2023

The hydrogenation of nitroaromatics to prepare aromatic amines plays a crucial role in the chemical industry. Traditional hydrogenation has the risk of hydrogen leakage from the equipment, and its catalyst has the disadvantage of being easily deactivated and difficult to recover. In this study, we designed an efficient and stable mesoporous catalyst, Pd@SBA-15, which was constructed by impregnating the nanopores of the mesoporous material SBA-15 with palladium nanoparticles. The catalyst was then filled in a micro-packed-bed reactor (MPBR) for continuous flow hydrogenation. The designed continuous flow hydrogenation system has two distinctive features. First, we used mesoporous Pd@SBA-15 instead of the traditional bulk Pd/C as the hydrogenation catalyst, which is more suitable for exposing the active sites of metal Pd and reducing the agglomeration of nanometals. The highly ordered porous structure enhances hydrogen adsorption and thus hydrogenation efficiency. Secondly, the continuous flow system allows for precise detection and control of the reaction process. The highly efficient catalysts do not require complex post-treatment recovery, which continues to operate for 24 h with barely any reduction in activity. Due to the high catalytic activity, the designed mesoporous Pd@SBA-15 showed excellent catalytic performance as a hydrogenation catalyst in a continuous flow system with 99% conversion of nitroaromatics in 1 min. This work provides insights into the rational design of hydrogenation systems in the chemical industry.
Numerical Estimation of Gas Release and Dispersion from a Submarine Pipeline
Authors: Yang Mingjun , Jiang Rui , Wu Xinyuan , Hu Zhongzhi
Published: April 2023

Submarine pipeline gas releases and dispersions can cause safety concerns such as fire and explosion, which can cause serious casualties and property losses. There are many existing studies on the impacts of the horizontal diffusion distances of natural gas leakages from subsea pipelines, but there is a lack of research on the impact of influencing factors on vertical diffusion distances. Therefore, a diffusion model of natural gas leakage from a submarine pipeline is established by using the computational fluid dynamics method (CFD). The influence law and degrees of factors such as water depth at the leakage point, leak orifice size, leak pressure and the ocean current’s velocity on the leakages and vertical diffusion distances of natural gases from submarine pipelines are systematically investigated. The results show that the leaked natural gas jet enters the sea water to form an air mass, which rises continuously under the action of the pressure in the pipe and the buoyancy of the sea water. The gas mass breaks into smaller bubbles affected by the interaction between the gas–liquid two phases and continues to float up and diffuse to the overflow surface. It is also found that the ocean current’s velocity will affect the offset of leakage gas along the current direction; the depth of the leakage water, the pressure in the pipe and the leakage aperture will affect the time when the gas reaches the sea surface and the release area after a submarine pipeline’s leakage. The research results would help to support risk assessments and response planning of potential subsea gas release accidents.
Oxidative Stress Induced Dysfunction of Protein Synthesis in 661W Mice Photoreceptor Cells
Authors: Deng Liting , Gupta Vivek , Abyadeh Morteza , Chitranshi Nitin , Pushpitha Kanishka , Wu Yunqi , Gupta Veer , You Yuyi , Paulo Joao A. , Graham Stuart L. , Mirzaei Mehdi , Haynes Paul A.
Published: April 2023

Photoreceptor cells are highly susceptible to oxidative-stress-induced damage due to their high metabolic rate. Oxidative stress plays a key role in driving pathological events in several different ocular diseases, which lead to retinal degeneration and ultimately blindness. A growing number of studies have been performed to understand downstream events caused by ROS induced oxidative stress in photoreceptor cells; however, the underlying mechanisms of ROS toxicity are not fully understood. To shed light on ROS induced downstream pathological events, we employed a tandem mass tag (TMT) labelling-based quantitative mass-spectrometric approach to determine proteome changes in 661W photoreceptor cells following oxidative stress induction via the application of different concentrations of H2O2 at different time points. Overall, 5920 proteins were identified and quantified, and 450 differentially expressed proteins (DEPs) were identified, which were altered in a dose and time dependent manner in all treatment groups compared to the control group. These proteins were involved in several biological pathways, including spliceosome and ribosome response, activated glutathione metabolism, decreased ECM-receptor interaction, oxidative phosphorylation, abnormally regulated lysosome, apoptosis, and ribosome biogenesis. Our results highlighted ECM receptor interaction, oxidative phosphorylation and spliceosome pathways as the major targets of oxidative stress that might mediate vascular dysfunction and cellular senescence.
Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype
Authors: Neagu Anca-Narcisa , Whitham Danielle , Seymour Logan , Haaker Norman , Pelkey Isabella , Darie Costel C.
Published: April 2023

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70–80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of “6P” medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC–MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein–protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with “proteome point sampling” methods that allow for proteomic profiling by in vivo “proteome point characterization”, or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC–MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.
Controlled Combustion and Pyrolysis of Waste Plastics: A Comparison Based on Human Health Risk Assessment
Authors: Moranda Arianna , Paladino Ombretta
Published: April 2023

Increasing conditions of economic and social well-being have led to an increase in waste production. Among the waste products, a significant portion consists of plastic materials that are popular in the components of consumer goods. For this reason, the conversion of plastic to energy via controlled combustion and plastic to fuel via thermal/catalytic pyrolysis or gasification can be proposed to treat the residual heterogeneous mixed plastics that cannot be recovered as individual polymers. The quality and type of fuels that are possible to obtain from these processes are different, as is the quality of their emissions, which generally contain VOCs, PCBs, dioxins, PAHs, and heavy metals. In this work, we propose a methodology based on human health risk assessment to compare controlled combustion and catalytic pyrolysis. Many pathways are analyzed, and pollutant concentrations are computed in the atmosphere, water, vegetables, fish, and food. Exposure is evaluated for inhalation and ingestion routes by taking into account uncertainties. Our results show that the risk profile of catalytic pyrolysis is low. Controlled combustion remains an interesting process, but even if Best Available Technologies (BAT) are adopted, the cancer risk due to PAHs contained in particulate is around the threshold for people living near the plant if a long period of operation is considered.
Skole and Historia: A Role for the Study of History in a Catholic School of Leisure
Authors: Seeley Andrew
Published: April 2023

Josef Pieper hoped to persuade his contemporaries to rebuild European society into a civilization of leisure. Catholic schools can make themselves into schools of leisure, and the approach they take to the study of history can facilitate this. In this essay, after looking to Pieper’s “Leisure, the Basis of Culture” for educational principles that would guide a school of leisure, I explore the educational plan of one Catholic school that has embodied them. The study of history fills the primary integrating and formative role in this school, so I look to The Religious Dimension of Education and contemporary Catholic teachers of history to see how the study of history can be formative while remaining true to the principles of its discipline. Finally, I suggest that studying history from a Catholic perspective performs an important service for the Church as a whole.
The Mandorla Symbol in Byzantine and Post-Byzantine Iconography of the Dormition: Function and Meaning
Authors: Todorova Rostislava Georgieva
Published: April 2023

The present study examines the use of the mandorla symbol in Byzantine and post-Byzantine iconography of the Dormition. The research aims to outline the reasons for the adoption of the mandorla in the iconographic scheme of the subject as a means of visualizing the heavenly Eden and the Glory of God’s presence. It traces the main stages in the development of the Dormition iconography and the creation of its principal models, highlighting the diversity of the patterns in the post-Byzantine art in the Balkans.
Design and Evaluation of an Intuitive Haptic Teleoperation Control System for 6-DoF Industrial Manipulators
Authors: Dekker Ivo , Kellens Karel , Demeester Eric
Published: April 2023

Industrial robots are capable of performing automated tasks repeatedly, reliably and accurately. However, in some scenarios, human-in-the-loop control is required. In this case, having an intuitive system for moving the robot within the working environment is crucial. Additionally, the operator should be aided by sensory feedback to obtain a user-friendly robot control system. Haptic feedback is one way of achieving such a system. This paper designs and assesses an intuitive teleoperation system for controlling an industrial 6-DoF robotic manipulator using a Geomagic Touch haptic interface. The system utilises both virtual environment-induced and physical sensor-induced haptic feedback to provide the user with both a higher amount of environmental awareness and additional safety while manoeuvering the robot within its working area. Different tests show that the system is capable of fully stopping the manipulator without colliding with the environment, and preventing it from entering singularity states with Cartesian end effector velocities of up to 0.25 m/s. Additionally, an operator is capable of executing low-tolerance end effector positioning tasks (∼0.5 mm) with high-frequency control of the robot (∼100 Hz). Fourteen inexperienced volunteers were asked to perform a typical object removal and writing task to gauge the intuitiveness of the system. It was found that when repeating the same test for a second time, the participants performed 22.2% faster on average. The results for the second attempt also became significantly more consistent between participants, as the inter quartile range dropped by 82.7% (from 52 s on the first attempt to 9 s on the second).
Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters
Authors: Luo Cong , Ba Jing , Guo Qiang
Published: April 2023

As an important geophysical data processing technique, seismic inversion estimates subsurface rock properties with seismic observations. However, anisotropic inversion, intended for a vertical transverse isotropy (VTI) media that primarily describes shale gas/oil resources, suffers from high nonlinearity. Simulated annealing is a widely used global optimization algorithm for solving nonlinear seismic inverse problems, but it involves multiple optimization parameters (e.g., initial temperature, search limit, and perturbation range). The importance of such parameters has been proven whilst the relevant analysis is limited in seismic inversion studies. This work hereby proposes a sequential anisotropic inversion method for VTI media, wherein we combine Bayesian linear and simulated annealing nonlinear inversion schemes. The simulated annealing is featured by adaptive optimization parameters aided by the linear result. Rather than the conventional method, the adaptive setting can be implemented trace by trace for complex reservoirs, which endows the method with enhanced stability and extended applicability. Synthetic tests and practical application demonstrate the validity of the method, wherein the obtained stiffness parameters facilitate the characterization of potential shale reservoirs with an improved accuracy.
3D Indoor Mapping and BIM Reconstruction Editorial
Authors: Bassier Maarten , Poux Florent , Nikoohemat Shayan
Published: April 2023

This Special Issue gathers papers reporting research on various aspects of the use of low-cost photogrammetric and lidar sensors for indoor building reconstruction. It includes contributions presenting improvements in the alignment of mobile mapping systems with and without a prior 3D BIM model, the interpretation of both imagery and lidar data of indoor scenery and finally the reconstruction and enrichment of existing 3D point clouds and meshes with BIM information. Concretely, the publications showcase methods and experiments for the Reconstruction of Indoor Navigation Elements for Point Cloud of Buildings with Occlusions and Openings by Wall Segment Restoration from Indoor Context Labeling, Two-Step Alignment of Mixed Reality Devices to Existing Building Data, Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption, A Robust Rigid Registration Framework of 3D Indoor Scene Point Clouds Based on RGB-D Information, 3D Point Cloud Semantic Augmentation for Instance Segmentation of 360° Panoramas by Deep Learning Techniques and the Symmetry-Based Coarse Registration of Smartphone’s Colorful Point Clouds with CAD Drawings (RegARD) for Low-Cost Digital Twin Buildings.
A Modified Temperature Vegetation Dryness Index (mTVDI) for Agricultural Drought Assessment Based on MODIS Data: A Case Study in Northeast China
Authors: Dai Rui , Chen Shengbo , Cao Yijing , Zhang Yufeng , Xu Xitong
Published: April 2023

Satellite-based drought indices have been shown to be effective and convenient in detecting drought conditions. The temperature vegetation dryness index (TVDI) is one of the most frequently used drought indices; however, it is not suitable for areas with high fractional vegetation cover (FVC). In this study, a modified temperature vegetation dryness index (mTVDI) was constructed by using the multispectral vegetation dryness index (MVDI) proposed by a PROSAIL simulation and water stress experiments which was based on the theory of the TVDI and utilized MODIS data. Compared with the TVDI, the mTVDI presents a more triangular feature space, as well as obviously increased R2 values for dry and wet edges (from 0.37–0.90 to 0.53–0.91 for dry edges and from 0.00–0.77 to 0.24–0.80 for wet edges). The mTVDI was evaluated using standardized precipitation evapotranspiration indices (SPEIs), precipitation, potential evapotranspiration (PET), and the crop water deficit index (CWDI), and the results confirmed that the mTVDI can better reflect the actual spatial changes, compared to the TVDI, under high FVC, as well as presenting an increased Pearson correlation coefficient (by 0.06–0.10) when compared with SPEIs. Moreover, the good performance of the mTVDI in major drought events indicates its reliability and accuracy for drought monitoring. Overall, the mTVDI is a reliable and accurate satellite-based dryness index suitable for high FVC conditions.
An Overview of the Special Issue on “Precision Agriculture Using Hyperspectral Images”
Authors: Avola Giovanni , Matese Alessandro , Riggi Ezio
Published: April 2023

In precision agriculture systems, remote sensing has played an essential role in crop and environment monitoring, and hyperspectral imaging is a particularly effective tool in this regard [...]
An Effective and Efficient Approach for 3D Recovery of Human Motion Capture Data
Authors: Yasin Hashim , Ghani Saba , Krüger Björn
Published: April 2023

In this work, we propose a novel data-driven approach to recover missing or corrupted motion capture data, either in the form of 3D skeleton joints or 3D marker trajectories. We construct a knowledge-base that contains prior existing knowledge, which helps us to make it possible to infer missing or corrupted information of the motion capture data. We then build a kd-tree in parallel fashion on the GPU for fast search and retrieval of this already available knowledge in the form of nearest neighbors from the knowledge-base efficiently. We exploit the concept of histograms to organize the data and use an off-the-shelf radix sort algorithm to sort the keys within a single processor of GPU. We query the motion missing joints or markers, and as a result, we fetch a fixed number of nearest neighbors for the given input query motion. We employ an objective function with multiple error terms that substantially recover 3D joints or marker trajectories in parallel on the GPU. We perform comprehensive experiments to evaluate our approach quantitatively and qualitatively on publicly available motion capture datasets, namely CMU and HDM05. From the results, it is observed that the recovery of boxing, jumptwist, run, martial arts, salsa, and acrobatic motion sequences works best, while the recovery of motion sequences of kicking and jumping results in slightly larger errors. However, on average, our approach executes outstanding results. Generally, our approach outperforms all the competing state-of-the-art methods in the most test cases with different action sequences and executes reliable results with minimal errors and without any user interaction.
Constrained IoT-Based Machine Learning for Accurate Glycemia Forecasting in Type 1 Diabetes Patients
Authors: Rodríguez-Rodríguez Ignacio , Campo-Valera María , Rodríguez José-Víctor , Frisa-Rubio Alberto
Published: April 2023

Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest.
Performance Assessment of Heartbeat Detection Algorithms on Photoplethysmograph and Functional NearInfrared Spectroscopy Signals
Authors: Bizzego Andrea , Esposito Gianluca
Published: April 2023

With wearable sensors, the acquisition of physiological signals has become affordable and feasible in everyday life. Specifically, Photoplethysmography (PPG), being a low-cost and highly portable technology, has attracted notable interest for measuring and diagnosing cardiac activity, one of the most important physiological and autonomic indicators. In addition to the technological development, several specific signal-processing algorithms have been designed to enable reliable detection of heartbeats and cope with the lower quality of the signals. In this study, we compare three heartbeat detection algorithms: Derivative-Based Detection (DBD), Recursive Combinatorial Optimization (RCO), and Multi-Scale Peak and Trough Detection (MSPTD). In particular, we considered signals from two datasets, namely, the PPG-DALIA dataset (N = 15) and the FANTASIA dataset (N = 20) which differ in terms of signal characteristics (sampling frequency and length) and type of acquisition devices (wearable and medical-grade). The comparison is performed both in terms of heartbeat detection performance and computational workload required to execute the algorithms. Finally, we explore the applicability of these algorithms on the cardiac component obtained from functional Near InfraRed Spectroscopy signals (fNIRS).The results indicate that, while the MSPTD algorithm achieves a higher F1 score in cases that involve body movements, such as cycling (MSPTD: Mean = 74.7, SD = 14.4; DBD: Mean = 54.4, SD = 21.0; DBD + RCO: Mean = 49.5, SD = 22.9) and walking up and down the stairs (MSPTD: Mean = 62.9, SD = 12.2; DBD: Mean = 50.5, SD = 11.9; DBD + RCO: Mean = 45.0, SD = 14.0), for all other activities the three algorithms perform similarly. In terms of computational complexity, the computation time of the MSPTD algorithm appears to grow exponentially with the signal sampling frequency, thus requiring longer computation times in the case of high-sampling frequency signals, where the usage of the DBD and RCO algorithms might be preferable. All three algorithms appear to be appropriate candidates for exploring the applicability of heartbeat detection on fNIRS data.
Non-Linear Conductivity Response of Graphene on Thin-Film PET Characterized by Transmission and Reflection Air-Plasma THz-TDS
Authors: Zhou Binbin , Rasmussen Mattias , Whelan Patrick Rebsdorf , Ji Jie , Shivayogimath Abhay , Bøggild Peter , Jepsen Peter Uhd
Published: April 2023

We demonstrate that the conductivity of graphene on thin-film polymer substrates can be accurately determined by reflection-mode air-plasma-based THz time-domain spectroscopy (THz-TDS). The phase uncertainty issue associated with reflection measurements is discussed, and our implementation is validated by convincing agreement with graphene electrical properties extracted from more conventional transmission-mode measurements. Both the reflection and transmission THz-TDS measurements reveal strong non-linear and instantaneous conductivity depletion across an ultra-broad bandwidth (1–9 THz) under relatively high incident THz electrical field strengths (up to 1050 kV/cm).
Assessing Technology Implementation Success for Highway Construction and Asset Management
Authors: Tripathi Amit , Dadi Gabriel B. , Nassereddine Hala , Sturgill Roy E. , Mitchell Alexa
Published: April 2023

The increasing demand for safe, reliable, and higher-quality infrastructure systems has led to more complex transportation construction and maintenance projects. This, coupled with the declining staff levels at many transportation agencies, requires a more comprehensive evaluation of technology implementation to compensate for these challenges. With a focus on effective technology implementation, this research goes beyond simply evaluating technologies to investigate technology implementation with personnel and policies at departments of transportation (DOTs). The study methodology involved a comprehensive literature review, a survey of all 50 state DOTs, and an in-person workshop of 18 DOT experts to validate the survey results and preliminary research findings. The findings support the need for those implementing technologies to understand people, processes, and technology maturity for their improved chances of implementation success. Using the approach presented, the DOTs can assess themselves and identify pathways to higher maturity levels in the areas of their people, processes, and technologies. This study also highlighted six factors that are important considerations for technology implementation and thus determined the relative importance of people, processes, and technology for these factors. The objective of this study was to assess the importance of people, processes, and technology that DOTs should prioritize to enhance the likelihood of successfully implementing technologies. The framework presented herein can be extended to any new or existing technology implementation initiatives at a DOT, including automatic identification and data capture (AIDC), emerging sensing and wireless technologies, safety technologies, and others.
Grand Theft Auto-Based Cycling Simulator for Cognitive Enhancement Technologies in Dangerous Traffic Situations
Authors: Schöning Julius , Kettler Jan , Jäger Milena I. , Gunia Artur
Published: April 2023

While developing traffic-based cognitive enhancement technology (CET), such as bike accident prevention systems, it can be challenging to test and evaluate them properly. After all, the real-world scenario could endanger the subjects’ health and safety. Therefore, a simulator is needed, preferably one that is realistic yet low cost. This paper introduces a way to use the video game Grand Theft Auto V (GTA V) and its sophisticated traffic system as a base to create such a simulator, allowing for the safe and realistic testing of dangerous traffic situations involving cyclists, cars, and trucks. The open world of GTA V, which can be explored on foot and via various vehicles, serves as an immersive stand-in for the real world. Custom modification scripts of the game give the researchers control over the experiment scenario and the output data to be evaluated. An off-the-shelf bicycle equipped with three sensors serves as a realistic input device for the subject’s movement direction and speed. The simulator was used to test two early-stage CET concepts enabling cyclists to sense dangerous traffic situations, such as trucks approaching from behind the cyclist. Thus, this paper also presents the user evaluation of the cycling simulator and the CET used by the subjects to sense dangerous traffic situations. With the knowledge of the first iteration of the user-centered design (UCD) process, this paper concludes by naming improvements for the cycling simulator and discussing further research directions for CET that enable users to sense dangerous situations better.
Seismic Signal Analysis Based on Variational Mode Decomposition and Hilbert Transform for Ground Intrusion Activity Classification
Authors: Sun Yuan , Qian Dongdong , Zheng Jing , Liu Yuting , Liu Cen
Published: April 2023

The identification of ground intrusion is a key and important technology in the national public security field. In this paper, a novel variational mode decomposition (VMD) and Hilbert transform (HT) is proposed for the classification of seismic signals generated by ground intrusion activities using a seismic sensing system. Firstly, the representative seismic data, including bicycles, vehicles, footsteps, excavations, and environmental noises, were collected through the designed experiment. Secondly, each original datum is decomposed through VMD and five Band-limited intrinsic mode functions (BIMF) are obtained, respectively, which will be used to generate a corresponding marginal spectrum that can reflect the actual frequency component of the signal accurately by HT. Then, three features related to the marginal spectrum, including marginal spectrum energy, marginal spectrum entropy, and marginal spectrum dominant frequency, are extracted for the analysis of the multi-classification using the support vector machine (SVM) classifier with the LIBSVM library. For the sake of testing and verifying the effectiveness of the proposed variational mode decomposition and Hilbert transform (VMD-HT) technique, the evaluation indicators including accuracy, precision, recall, and F1-Score are used and the results are compared with the time domain, frequency domain, ensemble empirical mode decomposition (EEMD), and empirical wavelet transform (EWT) combined with the HT analysis method. The performance of the VMD-HT method for ground intrusion activity classification provides an average value of 99.50%, 98.76%, 98.76%, and 98.75% for the four evaluation indicators, which are higher than all the other contrasted methods.
Sensor Fusion of GNSS and IMU Data for Robust Localization via Smoothed Error State Kalman Filter
Authors: Yin Yuming , Zhang Jinhong , Guo Mengqi , Ning Xiaobin , Wang Yuan , Lu Jianshan
Published: April 2023

High−precision and robust localization is critical for intelligent vehicle and transportation systems, while the sensor signal loss or variance could dramatically affect the localization performance. The vehicle localization problem in an environment with Global Navigation Satellite System (GNSS) signal errors is investigated in this study. The error state Kalman filtering (ESKF) and Rauch–Tung–Striebel (RTS) smoother are integrated using the data from Inertial Measurement Unit (IMU) and GNSS sensors. A segmented RTS smoothing algorithm is proposed in order to estimate the error state, which is typically close to zero and mostly linear, which allows more accurate linearization and improved state estimation accuracy. The proposed algorithm is evaluated using simulated GNSS signals with and without signal errors. The simulation results demonstrate its superior accuracy and stability for state estimation. The designed ESKF algorithm yielded an approximate 3% improvement in long straight line and turning scenarios compared to classical EKF algorithm. Additionally, the ESKF−RTS algorithm exhibited a 10% increase in the localization accuracy compared to the ESKF algorithm. In the double turning scenarios, the ESKF algorithm resulted in an improvement of about 50% in comparison to the EKF algorithm, while the ESKF−RTS algorithm improved by about 50% compared to the ESKF algorithm. These results indicated that the proposed ESKF−RTS algorithm is more robust and provides more accurate localization.