bluuebunny/crossref_metadata_2025 huggingface dataset:
Inter- and Intra-Population Variation of Foliage Calcium and Magnesium in Two Chinese Pine Species
Authors: Hu Meng , Yang Yuan , Fan Mingyang , Huang Kexin , Wang Lu , Lv Ting , Yi Xiangui , Chen Lin , Fang Yanming
Published: January 2023

Calcium and magnesium are major nutrient elements of plants, and both play an important role in plant growth and development. Pinus massoniana and P. hwangshanensis are important afforestation tree species in barren mountains in China. However, observation and research on calcium and magnesium nutrition of dominant forest species in China are still limited. This study determined the concentration of calcium and magnesium in needles for two species from five sites in East China by inductively coupled plasma optical emission spectrometry (ICP-OES). We then explored the inter- and intra-population variation pattern of calcium and magnesium and their relationship with environmental factors. There were significant differences in traits among populations. The strongest factors, which impacted the variation of calcium and magnesium concentration, were elevation and individual differences, respectively. Element concentration was correlated to environmental factors such as longitude, latitude, elevation, and mean annual temperature. The results of this study can be helpful for a better understanding of tree growth, population survival, and forest succession.
Cachrys L. Genus: A Comprehensive Review on Botany, Phytochemistry and Biological Properties
Authors: Musolino Vincenzo , Perri Maria Rosaria , Conforti Filomena , Gliozzi Micaela , Marrelli Mariangela , Mollace Vincenzo
Published: January 2023

The Cachrys L. genus belongs to the Apiaceae family and it is widely distributed in the Mediterranean basin, with plant species being endemic to southern Europe, Asia, and northern Africa. Different studies, focused on the phytochemical composition of Cachrys spp. and the biological properties of their phytocomplexes, have been reported. These works mostly focused on the essential oils obtained from these plants, and pointed out that Cachrys species are a rich source of coumarins, mainly furanocoumarins. Other phytochemicals, such as terpenes, fatty acids, phytosterols, and flavonoids have been also identified. Moreover, a number of biological properties such as antioxidant, antimicrobial, anti-inflammatory, cytotoxic, and photocytotoxic effects have been assessed. Nevertheless, a review of the chemical and pharmacological properties of this genus is not available in the literature. The aim of this paper is to provide an overview of the reports concerning the identified phytochemicals and the biological effects reported for Cachrys spp., and to offer a comprehensive understanding of the potential of this genus as a source of bioactive compounds. The current taxonomy, the traditional uses, and the toxicological aspects of plants belonging to this genus are also reported, and the future research directions are discussed.
A Small Set of Nuclear Markers for Reliable Differentiation of the Two Closely Related Oak Species Quercus Robur and Q. Petraea
Authors: Schroeder Hilke , Kersten Birgit
Published: January 2023

Quercus robur and Q. petraea are, in addition to Fagus sylvatica, the main economically used deciduous tree species in Europe. Identification of these two species is crucial because they differ in their ecological demands. Because of a changing climate, foresters must know more than ever which species will perform better under given environmental conditions. The search for differentiating molecular markers between these two species has already lasted for decades. Until now, differentiation has only been possible in approaches with a combination of several molecular markers and a subsequent statistical analysis to calculate the probability of being one or the other species. Here, we used MiSeq Illumina data from pools of Q. robur and Q. petraea specimens and identified nuclear SNPs and small InDels versus the Q. robur reference genome. Selected sequence variants with 100% allele frequency difference between the two pools were further validated in an extended set of Q. robur and Q. petraea specimens, and then the number of markers was deliberately reduced to the smallest possible set for species differentiation. A combination of six markers from four nuclear regions is enough to identify Q. robur, Q. petraea or hybrids between these two species quite well and represents a marker set that is cost-efficient and useable in every laboratory.
Diversity of Citrullus colocynthis (L.) Schrad Seeds Extracts: Detailed Chemical Profiling and Evaluation of Their Medicinal Properties
Authors: Khan Merajuddin , Khan Mujeeb , Al-hamoud Khaleel , Adil Syed Farooq , Shaik Mohammed Rafi , Alkhathlan Hamad Z.
Published: January 2023

Seeds and fruits of Citrullus colocynthis have been reported to possess huge potential for the development of phytopharmaceuticals with a wide range of biological activities. Thus, in the current study, we are reporting the potential antimicrobial and anticancer properties of C. colocynthis seeds extracted with solvents of different polarities, including methanol (M.E.), hexane (H.E.), and chloroform (C.E.). Antimicrobial properties of C. colocynthis seeds extracts were evaluated on Gram-positive and Gram-negative bacteria, whereas, anticancer properties were tested on four different cell lines, including HepG2, DU145, Hela, and A549. All the extracts have demonstrated noteworthy antimicrobial activities with a minimum inhibitory concentration (MIC) ranging from 0.9–62.5 µg/mL against Klebsiella planticola and Staphylococcus aureus; meanwhile, they were found to be moderately active (MIC 62.5–250 µg/mL) against Escherichia coli and Micrococcus luteus strains. Hexane extracts have demonstrated the highest antimicrobial activity against K. planticola with an MIC value of 0.9 µg/mL, equivalent to that of the standard drug ciprofloxacin used as positive control in this study. For anticancer activity, all the extracts of C. colocynthis seeds were found to be active against all the tested cell lines (IC50 48.49–197.96 µg/mL) except for the chloroform extracts, which were found to be inactive against the HepG2 cell line. The hexane extract was found to possess the most prominent anticancer activity when compared to other extracts and has demonstrated the highest anticancer activity against the DU145 cell line with an IC50 value of 48.49 µg/mL. Furthermore, a detailed phytoconstituents analysis of all the extracts of C. colocynthis seeds were performed using GC–MS and GC–FID techniques. Altogether, 43 phytoconstituents were identified from the extracts of C. colocynthis seeds, among which 21, 12, and 16 components were identified from the H.E., C.E., and M.E. extracts, respectively. Monoterpenes (40.4%) and oxygenated monoterpenes (41.1%) were the most dominating chemical class of compounds from the hexane and chloroform extracts, respectively; whereas, in the methanolic extract, oxygenated aliphatic hydrocarbons (77.2%) were found to be the most dominating chemical class of compounds. To the best of our knowledge, all the phytoconstituents identified in this study are being reported for the first time from the C. colocynthis.
Hybrid Hydrogels for Neomycin Delivery: Synergistic Effects of Natural/Synthetic Polymers and Proteins
Authors: Bercea Maria , Plugariu Ioana-Alexandra , Gradinaru Luiza Madalina , Avadanei Mihaela , Doroftei Florica , Gradinaru Vasile Robert
Published: January 2023

This paper reports new physical hydrogels obtained by the freezing/thawing method. They include pullulan (PULL) and poly(vinyl alcohol) (PVA) as polymers, bovine serum albumin (BSA) as protein, and a tripeptide, reduced glutathione (GSH). In addition, a sample containing PULL/PVA and lysozyme was obtained in similar conditions. SEM analysis evidenced the formation of networks with porous structure. The average pore size was found to be between 15.7 μm and 24.5 μm. All samples exhibited viscoelastic behavior typical to networks, the hydrogel strength being influenced by the protein content. Infrared spectroscopy analysis revealed the presence of intermolecular hydrogen bonds and hydrophobic interactions (more pronounced for BSA content between 30% and 70%). The swelling kinetics investigated in buffer solution (pH = 7.4) at 37 °C evidenced a quasi-Fickian diffusion for all samples. The hydrogels were loaded with neomycin trisulfate salt hydrate (taken as a model drug), and the optimum formulations (samples containing 10–30% BSA or 2% lysozyme) proved a sustained drug release over 480 min in simulated physiological conditions. The experimental data were analyzed using different kinetic models in order to investigate the drug release mechanism. Among them, the semi-empirical Korsmeyer–Peppas and Peppas–Sahlin models were suitable to describe in vitro drug release mechanism of neomycin sulfate from the investigated hybrid hydrogels. The structural, viscoelastic, and swelling properties of PULL/PVA/protein hybrid hydrogels are influenced by their composition and preparation conditions, and they represent important factors for in vitro drug release behavior.
Physicochemical and Structural Properties of Gluten-Konjac glucomannan Conjugates Prepared by Maillard Reaction
Authors: Song Yukang , Huang Danping , Guo Wanchun , Gao Yiqing , Xue Feng , Xiong Xiaohui , Li Chen
Published: January 2023

Gluten (Glu) is important to wheat products by forming a three-dimensional matrix. This study aimed to investigate the physicochemical and structural properties of gluten after conjugation with konjac glucomannan (KGM) through the Maillard reaction. The study revealed that the degree of graft increased with the prolonged reaction time. The Glu-KGM conjugates were possessed of increased β-sheet but decreased α-helix and β-turn, as well as unfolding and loose tertiary structures as the reaction proceeded. Among three different proportions, the Glu-KGM 1:1 conjugate was proved to have the most excellent foaming and emulsifying properties, and could form more rigid and firm gelation structures, which could be related to the decreased particle size and increased zeta potential of the conjugate. Overall, the physicochemical and structural properties of gluten were significantly related to the KGM ratios as well as the reaction period.
Fabrication of Ordered Porous Polyimide Films Templated by (AB)m Type of Diblock Copolymer
Authors: Huo Mengwei , Wang Yibo , Wang Xinbo
Published: January 2023

Ordered porous polyimide films were fabricated from (AB)m type of diblock copolymer polyimide-b-polystyrene (PI-b-PS). An increase in PS volume fraction (f VPS) is beneficial to decrease the relative dielectric constants and water contact angles of the obtained porous PI films: the relative dielectric constant decreases to 1.89 and water contact angle decreases to 43° when f VPS is 0.36, indicating porous PI films can be used as low-κ material and have good wettability. The solvent uptake of the porous PI films increases with increasing f VPS. A net-like morphology appears when f VPS reaches 0.36. The net-like porous PI film reaches equilibrium uptake of water within approximately 2.5 h, with a final equilibrium uptake ratio of 17.5%, and reaches equilibrium uptake of toluene within approximately 8 h, with a final equilibrium uptake ratio of 15.4%, displaying the highest and fastest solvent uptake compared with other microstructured porous PI films, which is ascribed to the specific characteristic of the interconnecting porous channels derived from the self-assembly of PI-b-PS with f VPS 0.36. Introducing thermally degradable segments to PI-based block copolymer is an effective method to prepare porous PI films and can enhance some of their properties.
Selected Biopolymers’ Processing and Their Applications: A Review
Authors: Flórez María , Cazón Patricia , Vázquez Manuel
Published: January 2023

Petroleum-based polymers are used in a multitude of products in the commercial world, but their high degree of contamination and non-biodegradability make them unattractive. The development and use of polymers derived from nature offer a solution to achieve an environmentally friendly and green alternative and reduce waste derived from plastics. This review focuses on showing an overview of the most widespread production methods for the main biopolymers. The parameters affecting the development of the technique, the most suitable biopolymers, and the main applications are included. The most studied biopolymers are those derived from polysaccharides and proteins. These biopolymers are subjected to production methods that improve their properties and modify their chemical structure. Process factors such as temperature, humidity, solvents used, or processing time must be considered. Among the most studied production techniques are solvent casting, coating, electrospinning, 3D printing, compression molding, and graft copolymerization. After undergoing these production techniques, biopolymers are applied in many fields such as biomedicine, pharmaceuticals, food packaging, scaffold engineering, and others.
A Novel Fault Detection Method Based on One-Dimension Convolutional Adversarial Autoencoder (1DAAE)
Authors: Wang Jian , Li Yakun , Han Zhiyan
Published: January 2023

Fault detection is an important and demanding problem in industry. Recently, many researchers have addressed the use of deep learning architectures for fault detection applications such as an autoencoder. Traditional methods based on an autoencoder usually complete fault detection by comparing reconstruction errors, and ignore a lot of useful information about the distribution of latent variables. To deal with this problem, this paper proposes a novel unsupervised fault detection method named one-dimension convolutional adversarial autoencoder (1DAAE), which introduces two new ideas: one-dimension convolution layers for the encoder to obtain better features and the adversarial thought to impose the latent variable z to cluster into a prior distribution. The proposed method not only has powerful feature representation ability than the traditional autoencoder, but has also enhanced the discrimination ability by imposing a prior distribution of the latent variables to cluster. Then, two anomaly scores for 1DAAE were proposed to detect fault samples, one based on reconstruction errors, and the other based on latent variable distribution. Finally, it was shown by the experiments that the proposed method outperformed the autoencoder-based, adversarial autoencoder-based, one-dimension convolutional autoencoder-based and generative adversarial network-based algorithms on the Tennessee Eastman process. Through the experiments, we found that the both one-dimension convolution layers and the latent vector distribution are helpful for fault detection.
Research on the Interdependence and Interaction between Sacred Space and Religious Personality—Centered on the Political and Religious Image of Wanhui 萬回 (632–712)
Authors: Zheng Jiajia
Published: January 2023

As a famous “miraculous monk” dating from the Tang Dynasty, Wanhui (632–712) was favored by four emperors, Gaozong (r. 649–683), Empress Wu (regency: 684–690; reign: 690–705), Zhongzong (r. 683–684, r. 705–710) and Ruizong (r. 684–690, r. 710–712). Relying on his special religious status as a Buddhist palace chaplain, he was alleged to have created religious momentum and to have advocated political opinions to maintain the “legitimacy” of the Li-Tang imperial family, but he was unfailingly able to avoid political persecution. Although there have been some academic publications on Wanhui and the group of “miraculous monks” and “mad monks” in the Tang Dynasty, there are still ambiguities in the understanding of Wanhui’s political and religious image. This article firstly conducts textual research on the interdependence and interaction between the sacred space of the Tang Buddhist palace chapel on the one hand and religious personality as represented by Wanhui on the other. The former gave the latter a rich religious sacredness, mystical charm and strong political support; while the latter, in turn, strengthened the religious and political functions of the unique Buddhist institution in the service of imperial power, manifesting itself in the consolidation and elevation of the former. Secondly, by investigating the reasons for shaping the political and religious images of Wanhui in monastic biography and Buddhist hagiography, this article argues that this was a conscious arrangement due to the political purposes or religious intentions of the compilers. Finally, by exploring how Wanhui exerted various subtle political and religious impacts on the Tang emperors by virtue of his status as a miraculous Buddhist palace chaplain—partly imparted by sacredness of the Buddhist palace chapel—this article attempts to shed new light on several key aspects of the complicated state–saṃgha relationship during this special period of the Tang Dynasty.
Extending the HIRS Data Record with IASI Measurements
Authors: Inamdar Anand K. , Shi Lei , Lee Hai-Tien , Jackson Darren L. , Matthews Jessica L.
Published: January 2023

The High-Resolution Infrared Radiation Sounder (HIRS) on the NOAA and the MetOp satellite series have provided global sounding measurements since the late 1970s, spanning over 40 years. These measurements have been useful in climate change detection, numerical weather prediction, and development of long-term climate data records of profiles of atmospheric temperature and humidity, cloud climatology, upper tropospheric water vapor, outgoing longwave radiation, etc. However, the HIRS instrument is being replaced by the new generation of sounders such as the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on recently launched satellites. In order to continue and extend the HIRS record, we use IASI measurements to simulate and derive HIRS-like data for the 12 HIRS longwave channels. The MetOp satellite operated by EUMETSAT carries both the HIRS and the hyper-spectral IASI instrument with accurate spectral and radiometric calibration, providing a great opportunity to consistently calibrate the measurements. The IASI radiances are convolved with the HIRS spectral response functions to produce IASI-simulated HIRS (IHIRS) for the longwave channels. In the present work, IHIRS data are collocated and compared with HIRS observed radiances on the same satellite to develop a calibration table for each of the ascending/descending orbits and cloudy and clear categories. The resulting inter-instrument calibrated IHIRS data was found to agree with HIRS brightness temperatures within 0.05 K for all longwave channels.
Assessment and Correction of View Angle Dependent Radiometric Modulation due to Polarization for the Cross-Track Infrared Sounder (CrIS)
Authors: Taylor Joe K. , Revercomb Henry E. , Tobin David C. , Knuteson Robert O. , Loveless Michelle L. , Malloy Rebecca , Suwinski Lawrence , Iturbide-Sanchez Flavio , Chen Yong , White Glen , Predina Joe , Johnson David G.
Published: January 2023

The Cross-track Infrared Sounder (CrIS) is an infrared Fourier-transform spectrometer that measures the Earth’s infrared radiance at high spectral resolution and high accuracy. The potential for polarization errors contributing significantly to the radiometric uncertainty of infrared remote sounders has been well recognized and documented, particularly due to polarization-dependent scene select mirrors operated in conjunction with grating-based instruments. The issue is equally applicable to FTS-based sensors. While the CrIS sensor utilizes an unprotected gold scene select mirror which has extremely low polarization in the infrared and the angle of incidence at the mirror is maintained for all calibration and Earth scene views, the radiometric bias due to polarization effects was determined to be non-negligible for cold scenes. A model for the polarization-induced calibration bias and the associated correction is presented for the CrIS instrument, along with details of the model parameter determination, and the impact of the correction on the calibrated radiances for a range of scene temperatures and types.
Towards Digital Twinning on the Web: Heterogeneous 3D Data Fusion Based on Open-Source Structure
Authors: La Guardia Marcello , Koeva Mila
Published: January 2023

Recent advances in Computer Science and the spread of internet connection have allowed specialists to virtualize complex environments on the web and offer further information with realistic exploration experiences. At the same time, the fruition of complex geospatial datasets (point clouds, Building Information Modelling (BIM) models, 2D and 3D models) on the web is still a challenge, because usually it involves the usage of different proprietary software solutions, and the input data need further simplification for computational effort reduction. Moreover, integrating geospatial datasets acquired in different ways with various sensors remains a challenge. An interesting question, in that respect, is how to integrate 3D information in a 3D GIS (Geographic Information System) environment and manage different scales of information in the same application. Integrating a multiscale level of information is currently the first step when it comes to digital twinning. It is needed to properly manage complex urban datasets in digital twins related to the management of the buildings (cadastral management, prevention of natural and anthropogenic hazards, structure monitoring, etc.). Therefore, the current research shows the development of a freely accessible 3D Web navigation model based on open-source technology that allows the visualization of heterogeneous complex geospatial datasets in the same virtual environment. This solution employs JavaScript libraries based on WebGL technology. The model is accessible through web browsers and does not need software installation from the user side. The case study is the new building of the University of Twente—Faculty of Geo-Information (ITC), located in Enschede (the Netherlands). The developed solution allows switching between heterogeneous datasets (point clouds, BIM, 2D and 3D models) at different scales and visualization (indoor first-person navigation, outdoor navigation, urban navigation). This solution could be employed by governmental stakeholders or the private sector to remotely visualize complex datasets on the web in a unique visualization, and take decisions only based on open-source solutions. Furthermore, this system can incorporate underground data or real-time sensor data from the IoT (Internet of Things) for digital twinning tasks.
Fused Thermal and RGB Imagery for Robust Detection and Classification of Dynamic Objects in Mixed Datasets via Pre-Trained High-Level CNN
Authors: Ben-Shoushan Ravit , Brook Anna
Published: January 2023

Smart vehicles with embedded Autonomous Vehicle (AV) technologies are currently equipped with different types of mounted sensors, aiming to ensure safe movement for both passengers and other road users. The sensors’ ability to capture and gather data to be synchronically interpreted by neural networks for a clear understanding of the surroundings is influenced by lighting conditions, such as natural lighting levels, artificial lighting effects, time of day, and various weather conditions, such as rain, fog, haze, and extreme temperatures. Such changing environmental conditions are also known as complex environments. In addition, the appearance of other road users is varied and relative to the vehicle’s perspective; thus, the identification of features in a complex background is still a challenge. This paper presents a pre-processing method using multi-sensorial RGB and thermal camera data. The aim is to handle issues arising from the combined inputs of multiple sensors, such as data registration and value unification. Foreground refinement, followed by a novel statistical anomaly-based feature extraction prior to image fusion, is presented. The results met the AV challenges in CNN’s classification. The reduction of the collected data and its variation level was achieved. The unified physical value contributed to the robustness of input data, providing a better perception of the surroundings under varied environmental conditions in mixed datasets for day and night images. The method presented uses fused images, robustly enriched with texture and feature depth and reduced dependency on lighting or environmental conditions, as an input for a CNN. The CNN was capable of extracting and classifying dynamic objects as vehicles and pedestrians from the complex background in both daylight and nightlight images.
MINDED-FBA: An Automatic Remote Sensing Tool for the Estimation of Flooded and Burned Areas
Authors: Oliveira Eduardo R. , Disperati Leonardo , Alves Fátima L.
Published: January 2023

This paper presents the MINDED-FBA, a remote-sensing-based tool for the determination of both flooded and burned areas. The tool, freely distributed as a QGIS plugin, consists of an adaptation and development of the previously published Multi Index Image Differencing methods (MINDED and MINDED-BA). The MINDED-FBA allows the integration and combination of a wider diversity of satellite sensor datasets, now including the synthetic aperture radar (SAR), in addition to optical multispectral data. The performance of the tool is evaluated for six case studies located in Portugal, Australia, Pakistan, Italy, and the USA. The case studies were chosen for representing a wide range of conditions, such as type of hazardous event (i.e., flooding or fire), scale of application (i.e., local or regional), site specificities (e.g., climatic conditions, morphology), and available satellite data (optical multispectral and SAR). The results are compared in respect to reference delineation datasets (mostly from the Copernicus EMS). The application of the MINDED-FBA tool with SAR data is particularly effective to delineate flooding, while optical multispectral data resulted in the best performances for burned areas. Nonetheless, the combination of both types of remote sensing data (data fusion approach) also provides high correlations with the available reference datasets. The MINDED-FBA tool could represent a new near-real-time solution, capable of supporting emergency response measures.
Post Mining Ground Deformations Transition Related to Coal Mines Closure in the Campine Coal Basin, Belgium, Evidenced by Three Decades of MT-InSAR Data
Authors: Declercq Pierre-Yves , Dusar Michiel , Pirard Eric , Verbeurgt Jeffrey , Choopani Atefe , Devleeschouwer Xavier
Published: January 2023

Spatio-temporal ground-movement measurements and mappings have been carried out in the Campine coalfield in Belgian Limburg since the closure of the mines to document post-mining effects. MT-InSAR measurements are compared to groundwater head changes in the overburden and to height data from the closest GNSS stations. Radar interferometry is used to estimate the extension and the velocity of ground movements. In particular, the MT-InSAR technique has been applied to SAR acquisitions of the satellites ERS-1/2 (1991–2005), ENVISAT (2003–2010), COSMO-SkyMed (2011–2014), and Sentinel-1A (2014–2022). The images were processed and used to highlight a switch from subsidence to uplift conditions in the western part of the coal basin, while the eastern part had already been affected by a rebound since the beginning of the ERS-1/2 acquisitions. Following the closure of the last active colliery of Zolder in 1992 and the subsequent cease of mine-water pumping, a recharge of mine-water aquifers occurred in the western part of the basin. This process provoked the change from subsidence to uplift conditions that was recorded during the ENVISAT period. In the center of the coal-mining area, measured uplift velocities reached a maximum of 18 mm/year during the ENVISAT period, while they subsided at −12 mm/year during the ERS-1/2 period. Mean velocities in the western and eastern parts of the coalfield area have decreased since the last MT-InSAR measurements were performed using Sentinel-1A, while the Zolder coal mine continues to rise at a faster-than-average rate of a maximum of 16 mm/year. The eastern part of the coalfield is still uplifting, while its rate has been reduced from 18 mm/year (ERS-1/2) to 9 mm/year (Sentinel-1A) since the beginning of the radar–satellite observations. Time-series data from the two GNSS stations present in the study area were used for a local comparison with the evolution of ground movements observed by MT-InSAR. Two leveling campaigns (2000, 2013) were also used to make comparisons with the MT-InSAR data. The station’s measurements and the leveling data were in line with the MT-InSAR data. Overall, major ground movements are obviously limited to an extension of the actual underground-mining works and rapidly diminish outside of them.
Back-Projection Imaging for Synthetic Aperture Radar with Topography Occlusion
Authors: Chen Zhanye , Zeng Zhiqiang , Fu Dongning , Huang Yan , Li Qiang , Zhang Xin , Wan Jun
Published: January 2023

When synthetic aperture radar (SAR) is conducting remote sensing or terrain mapping, its radar beam is inevitably occluded by the variations in the under-test topography. Although back-projection algorithm (BPA) can theoretically directly solve the imaging problems of topography variations that most current SAR imaging algorithms cannot handle, these BPAs only solve the phase focusing of SAR echo signal, and do not consider the mismatch of SAR imaging results caused by topography occlusion. To solve the mis-imaging issue of the occluded area generated by BPA under the case of topography variation, a topography-based BPA (Topo-BPA) is proposed in this paper. Firstly, a new beam occlusion judgment algorithm based on spherical wave assumption is proposed, and its core is depression angle interpolation and depression angle updating. Then, the proposed Topo-BPA embeds the proposed beam occlusion judgment algorithm before the classical BPA, which not only did not reduce the focus depth of BPA, but improved the imaging accuracy of classical BPA. Finally, numerical experiments have demonstrated the superiority of the Topo-BPA’s performance in comparison with classical BPA.
A Hybrid Convolutional Neural Network and Random Forest for Burned Area Identification with Optical and Synthetic Aperture Radar (SAR) Data
Authors: Sudiana Dodi , Lestari Anugrah Indah , Riyanto Indra , Rizkinia Mia , Arief Rahmat , Prabuwono Anton Satria , Sri Sumantyo Josaphat Tetuko
Published: January 2023

Forest and land fires are disasters that greatly impact various sectors. Burned area identification is needed to control forest and land fires. Remote sensing is used as common technology for rapid burned area identification. However, there are not many studies related to the combination of optical and synthetic aperture radar (SAR) remote sensing data for burned area detection. In addition, SAR remote sensing data has the advantage of being a technology that can be used in various weather conditions. This research aims to evaluate the burned area model using a hybrid of convolutional neural network (CNN) as a feature extractor and random forest (CNN-RF) as classifiers on Sentinel-1 and Sentinel-2 data. The experiment uses five test schemes: (1) using optical remote sensing data; (2) using SAR remote sensing data; (3) a combination of optical and SAR data with VH polarization only; (4) a combination of optical and SAR data with VV polarization only; and (5) a combination of optical and SAR data with dual VH and VV polarization. The research was also carried out on the CNN, RF, and neural network (NN) classifiers. On the basis of the overall accuracy on the part of the region of Pulang Pisau Regency and Kapuas Regency, Central Kalimantan, Indonesia, the CNN-RF method provided the best results in the tested schemes, with the highest overall accuracy reaching 97% using Satellite pour l’Observation de la Terre (SPOT) images as reference data. This shows the potential of the CNN-RF method to identify burned areas, mainly in increasing precision value. The estimated result of the burned area at the research site using a hybrid CNN-RF method is 48,824.59 hectares, and the accuracy is 90% compared with MCD64A1 burned area product data.
Mobility and Location of Drainage Divides Affected by Tilting Uplift in Sado Island, Japan
Authors: Sakashita Akimasa , Endo Noritaka
Published: January 2023

Drainage divide is a dynamic feature that migrates in response to tectonic activity. The asymmetric uplift between two adjacent basins causes the divide migration from a slower to faster uplift area. Sado Island, Japan, has been affected by southeastward tilting uplift for ca. 300k years. Despite the faster uplift on the northwest, the main divides have existed on the southeast side of the geometric center of the island, with no other feature suggesting tectonic inversion of the tilting direction. In this study, we conducted a digital elevation model (DEM) based investigation that focused on divide migration. A spectrum from very inactive to active divide migration in the northwest. Regardless of their position, actively migrating divides are comprehensible, but inactive divides located in a relatively slow uplift area remain unclear. We concluded that some divides slowed down owing to the local balance of erosion rates across the divides, which does not imply balance between uplift and river erosion at the basin scale, reflecting disequilibrium in river longitudinal profiles. The main divides of Sado have presumably continued to slowly migrate toward the area of faster uplift; however, they are most likely to have never overcome the moving geometric center owing to land expansion at the seacoast due to asymmetric uplift.
Cushioned Footwear Effect on Pain and Gait Characteristics of Individuals with Knee Osteoarthritis: A Double-Blinded 3 Month Intervention Study
Authors: Schwartz Isabella , Ofran Yonah , Bernovsky Svetlana , Kandel Leonid , Rivkin Gurion , Karniel Naama , Seyres Martin , Portnoy Sigal
Published: January 2023

One of the recommendations for individuals with knee osteoarthritis (OA) is the use of specific footwear, such as sturdy or cushioned shoes. However, the long-term use effects of using cushioned shoes on the pain and spatiotemporal gait parameters in individuals with knee OA are yet to be reported. We therefore aimed to compare the efficacy of cushioned sport footwear versus sham shoes on motor functions, pain and gait characteristics of individuals with knee OA who used the shoes for 3 months. In a double-blinded study, we provided 26 individuals with knee OA with cushioned sport shoes and 12 individuals with knee OA with similar sport shoes without cushioning for 3 months. The gait analysis, the timed up and go (TUG) test and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) were conducted and the pain levels were measured at the baseline, 1 month, and 3 months after the baseline. We found that the cushioned shoes reduce the amount of pain (based on WOMAC) in the affected knee and increase functionality in the research group, but not in the control group. Gait velocity and cadence were increased in both groups. Gait spatiotemporal parameters and their symmetry were unaffected during the intervention. We conclude that the use of cushioned shoes should be recommended to individuals with knee OA for alleviating pain.
A Survey on Low-Latency DNN-Based Speech Enhancement
Authors: Drgas Szymon
Published: January 2023

This paper presents recent advances in low-latency, single-channel, deep neural network-based speech enhancement systems. The sources of latency and their acceptable values in different applications are described. This is followed by an analysis of the constraints imposed on neural network architectures. Specifically, the causal units used in deep neural networks are presented and discussed in the context of their properties, such as the number of parameters, the receptive field, and computational complexity. This is followed by a discussion of techniques used to reduce the computational complexity and memory requirements of the neural networks used in this task. Finally, the techniques used by the winners of the latest speech enhancement challenges (DNS, Clarity) are shown and compared.
A Study on the Impact of Integrating Reinforcement Learning for Channel Prediction and Power Allocation Scheme in MISO-NOMA System
Authors: Gaballa Mohamed , Abbod Maysam , Aldallal Ammar
Published: January 2023

In this study, the influence of adopting Reinforcement Learning (RL) to predict the channel parameters for user devices in a Power Domain Multi-Input Single-Output Non-Orthogonal Multiple Access (MISO-NOMA) system is inspected. In the channel prediction-based RL approach, the Q-learning algorithm is developed and incorporated into the NOMA system so that the developed Q-model can be employed to predict the channel coefficients for every user device. The purpose of adopting the developed Q-learning procedure is to maximize the received downlink sum-rate and decrease the estimation loss. To satisfy this aim, the developed Q-algorithm is initialized using different channel statistics and then the algorithm is updated based on the interaction with the environment in order to approximate the channel coefficients for each device. The predicted parameters are utilized at the receiver side to recover the desired data. Furthermore, based on maximizing the sum-rate of the examined user devices, the power factors for each user can be deduced analytically to allocate the optimal power factor for every user device in the system. In addition, this work inspects how the channel prediction based on the developed Q-learning model, and the power allocation policy, can both be incorporated for the purpose of multiuser recognition in the examined MISO-NOMA system. Simulation results, based on several performance metrics, have demonstrated that the developed Q-learning algorithm can be a competitive algorithm for channel estimation when compared to different benchmark schemes such as deep learning-based long short-term memory (LSTM), RL based actor-critic algorithm, RL based state-action-reward-state-action (SARSA) algorithm, and standard channel estimation scheme based on minimum mean square error procedure.
Speeding up Smartphone-Based Dew Computing: In Vivo Experiments Setup Via an Evolutionary Algorithm
Authors: Yannibelli Virginia , Hirsch Matías , Toloza Juan , Majchrzak Tim A. , Zunino Alejandro , Mateos Cristian
Published: January 2023

Dew computing aims to minimize the dependency on remote clouds by exploiting nearby nodes for solving non-trivial computational tasks, e.g., AI inferences. Nowadays, smartphones are good candidates for computing nodes; hence, smartphone clusters have been proposed to accomplish this task and load balancing is frequently a subject of research. Using the same real—i.e., in vivo—testbeds to evaluate different load balancing strategies based on energy utilization is challenging and time consuming. In principle, test repetition requires a platform to control battery charging periods between repetitions. Our Motrol hard-soft device has such a capability; however, it lacks a mechanism to assure and reduce the time in which all smartphone batteries reach the level required by the next test. We propose an evolutionary algorithm to execute smartphone battery (dis)charging plans to minimize test preparation time. Charging plans proposed by the algorithm include charging at different speeds, which is achieved by charging at maximum speed while exercising energy hungry components (the CPU and screen). To evaluate the algorithm, we use various charging/discharging battery traces of real smartphones and we compare the time-taken for our method to collectively prepare a set of smartphones versus that of individually (dis)charging all smartphones at maximum speed.
Optimization of an Impact-Based Frequency Up-Converted Piezoelectric Vibration Energy Harvester for Wearable Devices
Authors: Aceti Pietro , Rosso Michele , Ardito Raffaele , Pienazza Nicola , Nastro Alessandro , Baù Marco , Ferrari Marco , Rouvala Markku , Ferrari Vittorio , Corigliano Alberto
Published: January 2023

This work presents a novel development of the impact-based mechanism for piezoelectric vibration energy harvesters. More precisely, the effect of an impacting mass on a cantilever piezoelectric transducer is studied both in terms of the tip mass value attached to the cantilever and impact position to find an optimal condition for power extraction. At first, the study is carried out by means of parametric analyses at varying tip mass and impact position on a unimorph MEMS cantilever, and a suitable physical interpretation of the associated electromechanical response is given. The effect of multiple impacts is also considered. From the analysis, it emerges that the most effective configuration, in terms of power output, is an impact at the cantilever tip without a tip mass. By changing the value of the tip mass, a sub-optimal impact position along the beam axis can also be identified. Moreover, the effect of a tip mass is deleterious on the power performance, contrary to the well-known case of a resonant energy harvester. A mesoscale prototype with a bimorph transducer is fabricated and tested to validate the computational models. The comparison shows a good agreement between numerical models and the experiments. The proposed approach is promising in the field of consumer electronics, such as wearable devices, in which the impact-based device moves at the frequencies of human movement and is much lower than those of microsystems.
DPO: Direct Planar Odometry with Stereo Camera
Authors: Lins Filipe C. A. , Rosa Nicolas S. , Grassi Valdir , Medeiros Adelardo A. D. , Alsina Pablo J.
Published: January 2023

Nowadays, state-of-the-art direct visual odometry (VO) methods essentially rely on points to estimate the pose of the camera and reconstruct the environment. Direct Sparse Odometry (DSO) became the standard technique and many approaches have been developed from it. However, only recently, two monocular plane-based DSOs have been presented. The first one uses a learning-based plane estimator to generate coarse planes as input for optimization. When these coarse estimates are too far from the minimum, the optimization may fail. Thus, the entire system result is dependent on the quality of the plane predictions and restricted to the training data domain. The second one only detects planes in vertical and horizontal orientation as being more adequate to structured environments. To the best of our knowledge, we propose the first Stereo Plane-based VO inspired by the DSO framework. Differing from the above-mentioned methods, our approach purely uses planes as features in the sliding window optimization and uses a dual quaternion as pose parameterization. The conducted experiments showed that our method presents a similar performance to Stereo DSO, a point-based approach.
Fuzzy Logic Controlled Simulation in Regulating Thermal Comfort and Indoor Air Quality Using a Vehicle Heating, Ventilation, and Air-Conditioning System
Authors: Rajeswari Subramaniam Konguvel , Cheng Chi-Tsun , Pang Toh Yen
Published: January 2023

Conventional heating ventilation and air-conditioning (HVAC) controllers have been designed to mainly control the temperature of a confined compartment, such as a room or a cabin of a vehicle. Other important parameters related to the thermal comfort and indoor air quality (IAQ) of the confined compartment have often been ignored. In this project, IAQ in the vehicle cabin was represented by its carbon dioxide (CO2) concentration, and the occupants’ thermal comfort levels were estimated with the predicted mean vote (PMV) index. A new fuzzy logic controller (FLC) was designed and developed using the MATLAB fuzzy logic toolbox and Simulink to provide a nonlinear mapping between the measured values, i.e., PMV, temperature, CO2, and control parameters (recirculation flaps, blower’s speed, and refrigerant mass flow rate) of a vehicle HVAC system. The new FLC aimed to regulate both in-cabin PMV and CO2 values without significantly increasing overall energy consumption. To evaluate the effectiveness of the proposed FLC, a cabin simulator was used to mimic the effects of different HVAC variables and indoor/outdoor environmental settings, which represented the in-cabin PMV and IAQ readings. Results demonstrated that the new FLC was effective in regulating the in-cabin PMV level and CO2 concentration, at desirable levels, by adaptively controlling the opening and closing of the recirculation flap based on in-cabin temperature and CO2 readings, while maintaining an average-to-good energy consumption level. The proposed FLC could be applied to a large variety of HVAC systems by utilizing low-cost sensors, without the need to significantly modify the internal design of the HVAC system.
Stable Heteroclinic Channel Networks for Physical Human–Humanoid Robot Collaboration
Authors: Brecelj Tilen , Petrič Tadej
Published: January 2023

Human–robot collaboration is one of the most challenging fields in robotics, as robots must understand human intentions and suitably cooperate with them in the given circumstances. But although this is one of the most investigated research areas in robotics, it is still in its infancy. In this paper, human–robot collaboration is addressed by applying a phase state system, guided by stable heteroclinic channel networks, to a humanoid robot. The base mathematical model is first defined and illustrated on a simple three-state system. Further on, an eight-state system is applied to a humanoid robot to guide it and make it perform different movements according to the forces exerted on its grippers. The movements presented in this paper are squatting, standing up, and walking forwards and backward, while the motion velocity depends on the magnitude of the applied forces. The method presented in this paper proves to be a suitable way of controlling robots by means of physical human-robot interaction. As the phase state system and the robot movements can both be further extended to make the robot execute many other tasks, the proposed method seems to provide a promising way for further investigation and realization of physical human–robot interaction.
Smart Streets as a Cyber-Physical Social Platform: A Conceptual Framework
Authors: Lynn Theo , Wood Charles
Published: January 2023

Streets perform a number of important functions and have a wide range of activities performed in them. There is a small but growing focus on streets as a more generalisable, atomised, and therefore more manageable unit of development and analysis than cities. Despite the public realm being one of the largest physical spaces on streets, the impact and potential of digitalisation projects on this realm is rarely considered. In this article, the smartness of a street is derived from the cyber-physical social infrastructure in the public realm, including data obtained from sensors, the interconnection between different services, technologies and social actors, intelligence derived from analysis of the data, and optimisation of operations within a street. This article conceptualises smart streets as basic units of urban space that leverage cyber-physical social infrastructure to provide and enable enhanced services to and between stakeholders, and through stakeholders’ use of the street, generate data to optimise its services, capabilities, and value to stakeholders. A proposed conceptual framework is used to identify and explore how streets can be augmented and create value through cyber-physical social infrastructure and digital enhancements. We conclude with a discussion of future avenues of research.