bluuebunny/crossref_metadata_2025 huggingface dataset:
Microalgae Polysaccharides: An Overview of Production, Characterization, and Potential Applications
Authors: Costa Jorge Alberto Vieira , Lucas Bárbara Franco , Alvarenga Ana Gabrielle Pires , Moreira Juliana Botelho , de Morais Michele Greque
Published: October 2021

Microalgae and cyanobacteria are photosynthetic microorganisms capable of synthesizing several biocompounds, including polysaccharides with antioxidant, antibacterial, and antiviral properties. At the same time that the accumulation of biomolecules occurs, microalgae can use wastewater and gaseous effluents for their growth, mitigating these pollutants. The increase in the production of polysaccharides by microalgae can be achieved mainly through nutritional limitations, stressful conditions, and/or adverse conditions. These compounds are of commercial interest due to their biological and rheological properties, which allow their application in various sectors, such as pharmaceuticals and foods. Thus, to increase the productivity and competitiveness of microalgal polysaccharides with commercial hydrocolloids, the cultivation parameters and extraction/purification processes have been optimized. In this context, this review addresses an overview of the production, characterization, and potential applications of polysaccharides obtained by microalgae and cyanobacteria. Moreover, the main opportunities and challenges in relation to obtaining these compounds are highlighted.
A Review of Gum Hydrocolloid Polyelectrolyte Complexes (PEC) for Biomedical Applications: Their Properties and Drug Delivery Studies
Authors: Putro Jindrayani Nyoo , Lunardi Valentino Bervia , Soetaredjo Felycia Edi , Yuliana Maria , Santoso Shella Permatasari , Wenten I Gede , Ismadji Suryadi
Published: October 2021

The utilization of natural gum polysaccharides as the vehicle for drug delivery systems and other biomedical applications has increased in recent decades. Their biocompatibility, biodegradability, and price are much cheaper than other materials. It is also renewable and available in massive amounts, which are the main reasons for its use in pharmaceutical applications. Gum can be easily functionalized with other natural polymers to enhance their applications. Various aspects of the utilization of natural gums in the forms of polyelectrolyte complexes (PECs) for drug delivery systems are discussed in this review. The application of different mathematical models were used to represent the drug release mechanisms from PECs; these models include a zero-order equation, first-order equation, Higuchi, simplified Higuchi, Korsmeyer–Peppas, and Peppas–Sahlin.
Composition of Oil after Hydrothermal Treatment of Cabonate-Siliceous and Carbonate Domanic Shale Rocks
Authors: Kayukova Galina P. , Nasyrova Zukhra R. , Mikhailova Anastasiya N. , Kosachev Igor P. , Aliev Firdavs A. , Vakhin Alexey V.
Published: October 2021

The hydrocarbon compositions of shale oils, generated from two different lithological–facial Domanic deposits of the Tatarstan Republic (Russia), were studied under hydrothermal impact with 30% of water addition in a 350 °С and CO2 environment. The samples were extracted from carbonate–siliceous rocks of the Semiluky–Mendym deposits of the Berezovskaya area, and carbonate deposits of the Dankovo–Lebedyan horizon of the Zelenogorskaya area of the Romashkino oil field. The distinctive features of rocks are in the composition and content of organic matter (OM), its thermal stability, as well as the structural-group composition of the shale oil products. The hydrothermal treatment of the rock samples increased the content of saturates and decreased the content of aromatics, resins and asphaltenes in the composition of crude oil. The decomposition of the polymer-like kerogen structure and destruction processes of high-molecular compounds, such as resins and asphaltenes, are accompanied with the formation of substances highly rich in carbons—carbenes and carboids. The contents of n-alkanes and acyclic isoprenoids increase in the composition of saturated hydrocarbons. According to the chemical classification of Al. A. Petrov, the character of the molecular mass distribution of such substances corresponds to oil type A1, which is considered paraffinic. The contents of dibenzothiophene, naphthalene and phenanthrene are increased in the composition of aromatic hydrocarbons, while the contents of tri-methyl-alkyl-benzene and benzothiophene are decreased. The increase in the aryl isoprenoid ratio (AIR = С13–С17/С18–С22) and maturity parameter (4-MDBT/1-MDBT) under the influences of hydrothermal factors indicates the increasing thermal maturity degree of the hydrocarbon system. The differences in the distribution behavior of saturated and aromatic hydrocarbons—biomarkers in rocks of various lithological-facies types, which are reasoned by different conditions of initial organic matter transformation as well as under the impact of hydrothermal factors—were revealed.
Qualitative and Quantitative Evaluation of Different Types of Orthodontic Brackets and Archwires by Optical Microscopy and X-ray Fluorescence Spectroscopy
Authors: D’Andrea Danilo , Milone Dario , Nicita Fabiana , Risitano Giacomo , Santonocito Dario
Published: October 2021

The wear behaviour and chemical composition of orthodontic components influence the mechanical characteristics of a fixed orthodontic treatment. The purpose of this paper is to evaluate the surface alterations of different types of brackets (aesthetic, metallic, and conventional self-ligating) and archwires (superelastic and thermal) subjected to wear tests through optical microscopy and, subsequently, to identify the chemical elements of accessories by X-ray fluorescence. The cycles (5000 for each bracket and 10,000 for each wire) of the tribological test were carried out in dry conditions inside a machine that allows alternating sliding. The results of the study highlighted different wear behaviours even within the same type of brackets and archwires. The monocrystalline sapphire brackets maintain their aesthetic properties despite traces of wear inside the slots and contain minimal amounts of nickel. Superelastic NiTi archwires have a better overall rating than thermal wires, as they do not show significant surface wear alterations.
Open Access Publishing Probabilities Based on Gender and Authorship Structures in Vietnam
Authors: Nguyen Huyen Thanh T. , Nguyen Minh-Hoang , Le Tam-Tri , Ho Manh-Toan , Vuong Quan-Hoang
Published: October 2021

Open access (OA) publishing is beneficial for researchers to improve recognition, representation, and visibility in academia. However, few studies have been conducted for studying the association between gender and OA publishing likelihood. Therefore, the current study explores the impacts of gender-based authorship structures on OA publishing in Vietnamese social sciences and humanities. Bayesian analysis was performed on a dataset of 3122 publications in social sciences and humanities. We found that publications with mixed-gender authorship were most likely to be published under Gold Access terms (26.31–31.65%). In contrast, the likelihood of publications with the solely male or female author(s) was lower. It is also notable that if female researcher(s) held the first-author position in an article of mixed-gender authorship, the publication would be less likely to be published under Gold Access terms (26.31% compared to 31.65% of male-first-author structure). In addition, publications written by a solo female author (14.19%) or a group of female authors (10.72%) had lower OA publishing probabilities than those written by a solely male author(s) (17.14%). These findings hint at the possible advantage of gender diversity and the disadvantage of gender homophily (especially female-only authorship) on OA publishing likelihood. Moreover, they show there might be some negative impacts of gender inequality on OA publishing. As a result, the notion of gender diversity, financial and policy supports are recommended to promote the open science movement.
The Stegodon Bonebed of the Middle Pleistocene Archaeological Site Mata Menge (Flores, Indonesia): Taphonomic Agents in Site Formation
Authors: Powley Meagan J. , Sutisna Indra , Mikac Katarina M. , Wibowo Unggul Prasetyo , van den Bergh Gerrit D.
Published: October 2021

The Middle Pleistocene fluvial channel site of the Upper Fossil-bearing Interval at Mata Menge in the So’a Basin, Flores, Indonesia, has yielded the earliest fossil evidence for Homo floresiensis in association with stone artefacts and fossils of highly endemic insular fauna, including Stegodon, giant rats, crocodiles, Komodo dragons, and various birds. A preliminary taphonomic review of the fossil material here aimed to provide additional context for the hominin remains in this bonebed. Analysis was performed on two subsets of material from the same fluvial sandstone layer. Subset 1 comprised all material from two adjacent one-metre square quadrants (n = 91), and Subset 2 all Stegodon long limb bones excavated from the same layer (n = 17). Key analytical parameters included species and skeletal element identification; fossil size measurements and fragmentation; weathering stages; bone fracture characteristics; and other biological and geological bone surface modifications. Analysis of Subset 1 material identified a highly fragmented assemblage with a significant bias towards Stegodon. A large portion of these bones were likely fractured by trampling prior to entering the fluvial channel and were transported away from the death-site, undergoing surface modification causing rounding. Subset 2 material was less likely to have been transported far based on its limited susceptibility to fluvial transport. There was no significant difference in weathering for the long limb bones and fragments, with the highest portion exhibiting Stage 2 weathering, indicating that prior to final burial, all material was exposed to prolonged periods of surface exposure. Approximately 10% of all material have characteristics of fracturing on fresh bone, contributing to the taphonomic context for this bonebed; however insufficient evidence was found for anthropogenic modification.
High-Shear De-Gassing and De-Ironing of an Aluminum Casting Alloy Made Directly from Aluminum End-of-Life Vehicle Scrap
Authors: Al-Helal Kawther , Lazaro-Nebreda Jaime , Patel Jayesh B. , Scamans Geoff M.
Published: October 2021

High-shear melt conditioning (HSMC) technology was used for degassing and de-ironing of an aluminum alloy recovered from the Zorba cast fraction of the non-ferrous scrap from shredded end-of-life vehicles. The results showed that the recovery of aluminum alloys from the Zorba cast fraction was more than 80%. High-shear melt conditioning improved the degassing process during melt treatment in comparison with the adding of degassing tablets. The efficiency of the de-ironing process using HSMC increased by up to 24% after, increasing the Mn content to 0.8% in the melt. Adding Mn to Zorba melt enhanced the de-ironing process and eliminated the formation of β-AlFeSi intermetallic particles, which have a detrimental effect on both the mechanical and corrosion properties of the alloy.
Introduction to the Special Issue Art, Shamanism and Animism
Authors: Wallis Robert J. , Carocci Max
Published: October 2021

Art, shamanism and animism are mutable, contested terms which, when brought together, present a highly charged package [...]
Becoming a Confucian in Contemporary Singapore: The Case of Nanyang Confucian Association
Authors: Ong Chang Woei , Koh Khee Heong
Published: October 2021

Using the Nanyang Confucian Association (NCA) as a case study, this paper explores the multi-faceted processes through which a segment of Singapore’s Chinese community constructs its self-identity based on an understanding of Confucianism that dismisses its religious attributes while underscoring the ethnic and cultural dimensions. Tracing the history of the association since its formation in 1914, the paper hopes to contribute to recent overseas Chinese studies on the rethinking of the notion of the Chinese diaspora within the context of the formation, circulation, and contest of a global Chinese identity by asking the following questions: Does identifying with the Confucian tradition necessarily require one to acknowledge their connection with China? Would a self-proclaimed Confucian be perceived as someone who looks to China for ethnic and cultural affiliation and thus appears less local? The authors argue that, while still acknowledging the spatial–temporal centrality of China as the origin of Confucianism and Chinese civilization, leaders of the NCA clearly intended to simultaneously position the NCA at the center of global Confucian activism. What emerges from the processes initiated by the NCA in constructing its identity is a complex overlay of history, geography, and culture that gives rise to a vision of multiple centers.
NMR Spectroscopy-Based Metabolomics of Platelets to Analyze Brain Tumors
Authors: Pudakalakatti Shivanand , Audia Alessandra , Mukhopadhyay Anirudh , Enriquez José S. , Bourgeois Dontrey , Tayob Nabihah , Zacharias Niki M. , Millward Steven W. , Carson Daniel , Farach-Carson Mary C. , Lang Frederick F. , Heimberger Amy B. , Bhat Krishna P. , Bhattacharya Pratip K.
Published: October 2021

“Tumor-educated platelets” have recently generated substantial interest for the diagnosis of cancer. We hypothesized that tumor educated platelets from patients with brain tumors will reflect altered metabolism compared to platelets from healthy volunteers. Here, in a pilot study, we have employed nuclear magnetic resonance (NMR) spectroscopy in platelets from brain tumor patients to demonstrate altered metabolism compared to the platelets obtained from healthy volunteers.
A Case Report of a Solitary Fibrous Tumor of the Maxillary Sinus
Authors: Di Bartolomeo Mattia , Negrello Sara , Pellacani Arrigo , Cesinaro Anna Maria , Vallone Stefano , Presutti Livio , Chiarini Luigi , Anesi Alexandre
Published: October 2021

A solitary fibrous tumor (SFT) is a benign neoplasm, firstly described as a mesenchymal tumor of the pleura. Its incidence range in the head and neck region is about 5–27%, but only rarely does it affect paranasal sinuses. The differential diagnosis is challenging, owing to its erosive growth pattern and immuno-histochemical features. SFTs have an aggressive behavior and an important recurrence potential. Therefore, a radical surgical excision is the gold standard therapeutic procedure. A rare SFT originating from the right maxillary sinus is reported here. The 37-year-old patient presented to the outpatient clinic with a painful expansive lesion in the whole right maxillary region. The overlying skin was inflamed and the patient had no epistaxis episodes. The 1.5 dentary element tested negative for vitality; however, a puncture of the lesion led to a hematic spill and no purulent discharge. An endoscopic-guided biopsy was suggestive either of SFT or hemangioperictoma, excluding a malignant neoplasm. A multi-equipe surgical team was activated. The lesion was embolized in order to achieve a good hemostatic control and, after 48 h, the neoplasm was radically excised with a combined open and endoscopic approach. The patient was disease-free at 12-month radiological and clinical follow-up. Given the rarity of this lesion and the delicacy required in addressing head and neck neoplasms, we believe that the present case report might be of help in further understanding how to approach cranio-facial SFTs.
A Suite of Robotic Solutions for Nuclear Waste Decommissioning
Authors: Vitanov Ivan , Farkhatdinov Ildar , Denoun Brice , Palermo Francesca , Otaran Ata , Brown Joshua , Omarali Bukeikhan , Abrar Taqi , Hansard Miles , Oh Changjae , Poslad Stefan , Liu Chen , Godaba Hareesh , Zhang Ketao , Jamone Lorenzo , Althoefer Kaspar
Published: October 2021

Dealing safely with nuclear waste is an imperative for the nuclear industry. Increasingly, robots are being developed to carry out complex tasks such as perceiving, grasping, cutting, and manipulating waste. Radioactive material can be sorted, and either stored safely or disposed of appropriately, entirely through the actions of remotely controlled robots. Radiological characterisation is also critical during the decommissioning of nuclear facilities. It involves the detection and labelling of radiation levels, waste materials, and contaminants, as well as determining other related parameters (e.g., thermal and chemical), with the data visualised as 3D scene models. This paper overviews work by researchers at the QMUL Centre for Advanced Robotics (ARQ), a partner in the UK EPSRC National Centre for Nuclear Robotics (NCNR), a consortium working on the development of radiation-hardened robots fit to handle nuclear waste. Three areas of nuclear-related research are covered here: human–robot interfaces for remote operations, sensor delivery, and intelligent robotic manipulation.
Atmospheric Anomaly Analysis Related to Ms > 6.0 Earthquakes in China during 2020–2021
Authors: Xu Xitong , Chen Shengbo , Yu Yan , Zhang Sen
Published: October 2021

The attention towards links of atmospheric parameter variation and earthquakes has increased exponentially by utilizing new methods and more accurate observations. Persistent research makes it possible to gain insight into the precursor mechanism of earthquakes. In this paper, we studied the universality of detecting atmospheric anomalies associated with earthquakes based on tidal force fluctuation in China for earthquakes of Ms > 6.0, and explored the influence of tidal force on tectonic stress. The data of air temperature, geopotential height, ozone mixing ratio, and relative humidity from the National Center for Environmental Prediction (NCEP) were analyzed to reveal the spatiotemporal variation of atmospheric anomalies at multiple isobaric surfaces. Furthermore, the coupling of atmospheric parameters was investigated. The results showed that continuous solicitation exerted by tidal forces could change the strength of tectonic stress that causes earthquakes. The evolution pattern of air temperature, geopotential height, and relative humidity could be supported by atmospheric thermal vertical diffusion, while the anomalies of ozone mixing ratio was not evident. This verified the feasibility of detecting multi-parameter atmospheric anomalies associated with earthquakes based on tidal force fluctuation. Our results provide more evidence for understanding the atmospheric precursor characteristics of earthquakes.
A New Analysis of Caldera Unrest through the Integration of Geophysical Data and FEM Modeling: The Long Valley Caldera Case Study
Authors: Pulvirenti Fabio , Silverii Francesca , Battaglia Maurizio
Published: October 2021

The Long Valley Caldera, located at the eastern edge of the Sierra Nevada range in California, has been in a state of unrest since the late 1970s. Seismic, gravity and geodetic data strongly suggest that the source of unrest is an intrusion beneath the caldera resurgent dome. However, it is not clear yet if the main contribution to the deformation comes from pulses of ascending high-pressure hydrothermal fluids or low viscosity magmatic melts. To characterize the nature of the intrusion, we developed a 3D finite element model which includes topography and crust heterogeneities. We first performed joint numerical inversions of uplift and Electronic Distance Measurement baseline length change data, collected during the period 1985–1999, to infer the deformation-source size, position, and overpressure. Successively, we used this information to refine the source overpressure estimation, compute the gravity potential and infer the intrusion density from the inversion of deformation and gravity data collected in 1982–1998. The deformation source is located beneath the resurgent dome, at a depth of 7.5 ± 0.5 km and a volume change of 0.21 ± 0.04 km3. We assumed a rhyolite compressibility of 0.026 ± 0.0011 GPa−1 (volume fraction of water between 0% and 30%) and estimated a reservoir compressibility of 0.147 ± 0.037 GPa−1. We obtained a density of 1856 ± 72 kg/m3. This density is consistent with a rhyolite melt, with 20% to 30% of dissolved hydrothermal fluids.
Dielectric Properties of Lunar Materials at the Chang’e-4 Landing Site
Authors: Lai Jialong , Cui Feifei , Xu Yi , Liu Chaofei , Zhang Ling
Published: October 2021

On January 3rd 2019, the Chang’e-4 mission successfully landed in the Von Kármán Crater inside the South Pole-Aitken (SPA) basin and achieved the first soft landing on the farside of the Moon. Lunar penetrating radar (LPR) equipped on the rover measured the shallow subsurface structure along the motion path for more than 700 m. LPR data could be used to obtain the dielectric properties of the materials beneath the exploration area, providing important clues as to the composition and source of the materials. Although the properties of the upper fine-grained regolith have been studied using various methods, the underlying coarse-grained materials still lack investigation. Therefore, this paper intends to estimate the loss tangent of the coarse-grained materials at depth ranges of ~12 and ~28 m. Stochastic media models with different rock distributions for the LPR finite-difference time-domain (FDTD) simulation are built to evaluate the feasibility of the estimation method. Our results show that the average loss tangent value of coarse-grained materials is 0.0104±0.0027, and the abundance of FeOT+TiO2 is 20.08 wt.%, which is much higher than the overlying fine-grained regolith, indicating different sources.
Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data
Authors: Zhao Liya , Yang Qi , Zhao Qiang , Wu Jingwei
Published: October 2021

Salinization in arid or semiarid regions with water logging limits cropland yield, threatening food security. The highest level of farmland salinization, that is, abandoned salinized farmland, is a tradeoff between inadequate drainage facilities and sustainable farming. The evolution of abandoned salinized farmlands is closely related to the development of cropping systems. However, detecting abandoned salinized farmland using time-series remote sensing data has not been investigated well by previous studies. In this study, a novel approach was proposed to detect the dynamics of abandoned salinized farmland using time-series multispectral and thermal imagery. Thirty-two years of temporal Landsat imagery (from 1988 to 2019) was used to assess the evolution of salinization in Hetao, a two-thousand-year-old irrigation district in northern China. As intermediate variables of the proposed method, the crop-specific planting area was retrieved via its unique temporal vegetation index (VI) pattern, in which the shape-model-fitting technology and the K-means cluster algorithm were used. The desert area was stripped from the clustered non-vegetative area using its distinct features in the thermal band. Subsequently, the abandoned salinized farmland was distinguished from the urban area by the threshold-based saline index (SI). In addition, a regression model between electrical conductance (EC) and SI was established, and the spatial saline degree was evaluated by the SI map in uncropped and unfrozen seasons. The results show that the cropland has constantly been expanding in recent decades (from 4.7 × 105 ha to 7.1 × 105 ha), while the planting area of maize and sunflower has grown and the area of wheat has decreased. Significant desalinization progress was observed in Hetao, where both the area of salt-affected land (salt-free area increased approximately 4 × 105 ha) and the abandoned salinized farmland decreased (reduced from 0.45 × 105 ha to 0.19 × 105 ha). This could be mainly attributed to three reasons: the popularization of water-saving irrigation technology, the construction of artificial drainage facilities, and a shift in cropping patterns. The decrease in irrigation and the increase in drainage have deepened the groundwater table in Hetao, which weakens the salt collection capacity of the abandoned salinized farmland. The results demonstrate the promising possibility of reutilizing abandoned salinized farmland via a leaching campaign where the groundwater table is sufficiently deep to stop salinization.
BDS Satellite Clock Prediction Considering Periodic Variations
Authors: Zhao Lin , Li Nan , Li Hui , Wang Renlong , Li Menghao
Published: October 2021

The periodic noise exists in BeiDou navigation satellite system (BDS) clock offsets. As a commonly used satellite clock prediction model, the spectral analysis model (SAM) typically detects and identifies the periodic terms by the Fast Fourier transform (FFT) according to long-term clock offset series. The FFT makes an aggregate assessment in frequency domain but cannot characterize the periodic noise in a time domain. Due to space environment changes, temperature variations, and various disturbances, the periodic noise is time-varying, and the spectral peaks vary over time, which will affect the prediction accuracy of the SAM. In this paper, we investigate the periodic noise and its variations present in BDS clock offsets, and improve the clock prediction model by considering the periodic variations. The periodic noise and its variations over time are analyzed and quantified by short time Fourier transform (STFT). The results show that both the amplitude and frequency of the main periodic term in BDS clock offsets vary with time. To minimize the impact of periodic variations on clock prediction, a time frequency analysis model (TFAM) based on STFT is constructed, in which the periodic term can be quantified and compensated accurately. The experiment results show that both the fitting and prediction accuracy of TFAM are better than SAM. Compared with SAM, the average improvement of the prediction accuracy using TFAM of the 6 h, 12 h, 18 h and 24 h is in the range of 6.4% to 10% for the GNSS Research Center of Wuhan University (WHU) clock offsets, and 11.1% to 14.4% for the Geo Forschungs Zentrum (GFZ) clock offsets. For the satellites C06, C14, and C32 with marked periodic variations, the prediction accuracy is improved by 26.7%, 16.2%, and 16.3% for WHU clock offsets, and 29.8%, 16.0%, 21.0%, and 9.0% of C06, C14, C28, and C32 for GFZ clock offsets.
SS-MLP: A Novel Spectral-Spatial MLP Architecture for Hyperspectral Image Classification
Authors: Meng Zhe , Zhao Feng , Liang Miaomiao
Published: October 2021

Convolutional neural networks (CNNs) are the go-to model for hyperspectral image (HSI) classification because of the excellent locally contextual modeling ability that is beneficial to spatial and spectral feature extraction. However, CNNs with a limited receptive field pose challenges for modeling long-range dependencies. To solve this issue, we introduce a novel classification framework which regards the input HSI as a sequence data and is constructed exclusively with multilayer perceptrons (MLPs). Specifically, we propose a spectral-spatial MLP (SS-MLP) architecture, which uses matrix transposition and MLPs to achieve both spectral and spatial perception in global receptive field, capturing long-range dependencies and extracting more discriminative spectral-spatial features. Four benchmark HSI datasets are used to evaluate the classification performance of the proposed SS-MLP. Experimental results show that our pure MLP-based architecture outperforms other state-of-the-art convolution-based models in terms of both classification performance and computational time. When comparing with the SSSERN model, the average accuracy improvement of our approach is as high as 3.03%. We believe that our impressive experimental results will foster additional research on simple yet effective MLP-based architecture for HSI classification.
The 2019 Eruptive Activity at Stromboli Volcano: A Multidisciplinary Approach to Reveal Hidden Features of the “Unexpected” 3 July Paroxysm
Authors: Mattia Mario , Di Lieto Bellina , Ganci Gaetana , Bruno Valentina , Romano Pierdomenico , Ciancitto Francesco , De Martino Prospero , Gambino Salvatore , Aloisi Marco , Sciotto Mariangela , Scarpa Roberto , Ferlito Carmelo
Published: October 2021

In July and August 2019, Stromboli volcano underwent two dangerous paroxysms previously considered “unexpected” because of the absence of significant changes in usually monitored parameters. We applied a multidisciplinary approach to search for signals able to indicate the possibility of larger explosive activity and to devise a model to explain the observed variations. We analysed geodetic data, satellite thermal data, images from remote cameras and seismic data in a timespan crossing the eruptive period of 2019 to identify precursors of the two paroxysms on a medium-term time span (months) and to perform an in-depth analysis of the signals recorded on a short time scale (hours, minutes) before the paroxysm. We developed a model that explains the observations. We call the model “push and go” where the uppermost feeding system of Stromboli is made up of a lower section occupied by a low viscosity, low density magma that is largely composed of gases and a shallower section occupied by the accumulated melt. We hypothesize that the paroxysms are triggered when an overpressure in the lower section is built up; the explosion will occur at the very moment such overpressure overcomes the confining pressure of the highly viscous magma above it.
Three-Dimensional Convolutional Neural Network Model for Early Detection of Pine Wilt Disease Using UAV-Based Hyperspectral Images
Authors: Yu Run , Luo Youqing , Li Haonan , Yang Liyuan , Huang Huaguo , Yu Linfeng , Ren Lili
Published: October 2021

As one of the most devastating disasters to pine forests, pine wilt disease (PWD) has caused tremendous ecological and economic losses in China. An effective way to prevent large-scale PWD outbreaks is to detect and remove the damaged pine trees at the early stage of PWD infection. However, early infected pine trees do not show obvious changes in morphology or color in the visible wavelength range, making early detection of PWD tricky. Unmanned aerial vehicle (UAV)-based hyperspectral imagery (HI) has great potential for early detection of PWD. However, the commonly used methods, such as the two-dimensional convolutional neural network (2D-CNN), fail to simultaneously extract and fully utilize the spatial and spectral information, whereas the three-dimensional convolutional neural network (3D-CNN) is able to collect this information from raw hyperspectral data. In this paper, we applied the residual block to 3D-CNN and constructed a 3D-Res CNN model, the performance of which was then compared with that of 3D-CNN, 2D-CNN, and 2D-Res CNN in identifying PWD-infected pine trees from the hyperspectral images. The 3D-Res CNN model outperformed the other models, achieving an overall accuracy (OA) of 88.11% and an accuracy of 72.86% for detecting early infected pine trees (EIPs). Using only 20% of the training samples, the OA and EIP accuracy of 3D-Res CNN can still achieve 81.06% and 51.97%, which is superior to the state-of-the-art method in the early detection of PWD based on hyperspectral images. Collectively, 3D-Res CNN was more accurate and effective in early detection of PWD. In conclusion, 3D-Res CNN is proposed for early detection of PWD in this paper, making the prediction and control of PWD more accurate and effective. This model can also be applied to detect pine trees damaged by other diseases or insect pests in the forest.
A Study of Terahertz-Wave Cylindrical Super-Oscillatory Lens for Industrial Applications
Authors: Iba Ayato , Ikeda Makoto , Agulto Verdad C. , Mag-usara Valynn Katrine , Nakajima Makoto
Published: October 2021

This paper describes the design and development of a cylindrical super-oscillatory lens (CSOL) for applications in the sub-terahertz frequency range, which are especially ideal for industrial inspection of films using terahertz (THz) and millimeter waves. Product inspections require high resolution (same as inspection with visible light), long working distance, and long depth of focus (DOF). However, these are difficult to achieve using conventional THz components due to diffraction limits. Here, we present a numerical approach in designing a 100 mm × 100 mm CSOL with optimum properties and performance for 0.1 THz (wavelength λ = 3 mm). Simulations show that, at a focal length of 70 mm (23.3λ), the focused beam by the optimized CSOL is a thin line with a width of 2.5 mm (0.84λ), which is 0.79 times the diffraction limit. The DOF of 10 mm (3.3λ) is longer than that of conventional lenses. The results also indicate that the generation of thin line-shaped focal beam is dominantly influenced by the outer part of the lens.
A Cascaded Model Based on EfficientDet and YOLACT++ for Instance Segmentation of Cow Collar ID Tag in an Image
Authors: Zhao Kaixuan , Zhang Ruihong , Ji Jiangtao
Published: October 2021

In recent years, many imaging systems have been developed to monitor the physiological and behavioral status of dairy cows. However, most of these systems do not have the ability to identify individual cows because the systems need to cooperate with radio frequency identification (RFID) to collect information about individual animals. The distance at which RFID can identify a target is limited, and matching the identified targets in a scenario of multitarget images is difficult. To solve the above problems, we constructed a cascaded method based on cascaded deep learning models, to detect and segment a cow collar ID tag in an image. First, EfficientDet-D4 was used to detect the ID tag area of the image, and then, YOLACT++ was used to segment the area of the tag to realize the accurate segmentation of the ID tag when the collar area accounts for a small proportion of the image. In total, 938 and 406 images of cows with collar ID tags, which were collected at Coldstream Research Dairy Farm, University of Kentucky, USA, in August 2016, were used to train and test the two models, respectively. The results showed that the average precision of the EfficientDet-D4 model reached 96.5% when the intersection over union (IoU) was set to 0.5, and the average precision of the YOLACT++ model reached 100% when the IoU was set to 0.75. The overall accuracy of the cascaded model was 96.5%, and the processing time of a single frame image was 1.92 s. The performance of the cascaded model proposed in this paper is better than that of the common instance segmentation models, and it is robust to changes in brightness, deformation, and interference around the tag.
InterNet+: A Light Network for Hand Pose Estimation
Authors: Liu Yang , Jiang Jie , Sun Jiahao , Wang Xianghan
Published: October 2021

Hand pose estimation from RGB images has always been a difficult task, owing to the incompleteness of the depth information. Moon et al. improved the accuracy of hand pose estimation by using a new network, InterNet, through their unique design. Still, the network still has potential for improvement. Based on the architecture of MobileNet v3 and MoGA, we redesigned a feature extractor that introduced the latest achievements in the field of computer vision, such as the ACON activation function and the new attention mechanism module, etc. Using these modules effectively with our network, architecture can better extract global features from an RGB image of the hand, leading to a greater performance improvement compared to InterNet and other similar networks.
Ultrasound Assessment of Honey Using Fast Fourier Transform
Authors: Rufo Montaña , Jiménez Antonio , Paniagua Jesús M. , González-Mohíno Alberto
Published: October 2021

Ultrasound inspection permits the characteristics of some foodstuffs to be determined easily and cheaply. This experimental study included the determination of various ultrasound parameters provided by the fast Fourier transform (FFT) which had not previously been considered in testing the physical properties of different varieties of honey. These parameters are practically independent of the criteria adopted for their calculation, unlike other ultrasound variables such as pulse velocity or attenuation whose determination can vary depending on those criteria. The study was carried out on four varieties of honey (Eucalyptus, Heather, Thyme, and Thousand Flowers) using 500-kHz transducers. A simultaneously performed honey texture analysis (Texture Profile Analysis-TPA) showed significant linear correlations between the ultrasound variables provided by FFT and the texture parameters. The FFT parameters distinguished between each of the four honey varieties studied.
A Sparse Algorithm for Computing the DFT Using Its Real Eigenvectors
Authors: Thomas Rajesh , DeBrunner Victor , DeBrunner Linda S.
Published: October 2021

Direct computation of the discrete Fourier transform (DFT) and its FFT computational algorithms requires multiplication (and addition) of complex numbers. Complex number multiplication requires four real-valued multiplications and two real-valued additions, or three real-valued multiplications and five real-valued additions, as well as the requisite added memory for temporary storage. In this paper, we present a method for computing a DFT via a natively real-valued algorithm that is computationally equivalent to a N=2k-length DFT (where k is a positive integer), and is substantially more efficient for any other length, N. Our method uses the eigenstructure of the DFT, and the fact that sparse, real-valued, eigenvectors can be found and used to advantage. Computation using our method uses only vector dot products and vector-scalar products.
Purpose Adequacy as a Basis for Sustainable Building Design: A Post-Occupancy Evaluation of Higher Education Classrooms
Authors: López-Chao Vicente , López-Pena Vicente
Published: October 2021

Building design is one of the essential elements to consider for maximizing the sustainability of construction. Prior studies on energy and resource consumption and on indoor environmental quality indicators (IEQs) are increasingly frequent; however, attention has not been focused on design as supporting the function performed within architecture. Educational buildings have specific conditions related to teaching methodologies, including activating students and promoting participation and interaction in the classroom. This manuscript aims to explore whether the social dimension of physical space in educational settings can explain a student’s academic outcome. For this, the Learning Environment and Social Interaction Scale was designed and validated and applied to 796 undergraduate students at the University of Coruña, and multiple linear regression analysis was applied to the academic results. The results display a structure comprising five factors; these include novelties such as the division of conventional IEQs into two groups: the workspace and the classroom environment. In addition, place attachment, the design of the classroom as a facilitator of social interaction, the learning value of social interaction, and the satisfaction of the IEQ demonstrated their influence on the academic result.
Education for a Sustainable Future: Strategies for Holistic Global Competence Development at Engineering Institutions
Authors: Kjellgren Björn , Richter Tanja
Published: October 2021

Higher education institutions (HEIs) must ensure that their graduates possess not only professional know-how, but also the global competence to address the challenges posed in the UN’s 2030 Agenda. This is especially relevant in engineering education, which plays an important role in sustainable development. These competencies are typically thought to be developed in relation to institutions’ internationalisation efforts, but reports on how this is supposed to happen are often vague or built on wishful thinking. In this article, we describe a mixed-methods investigation into how holistic global competence development as a crucial aspect of sustainable education can be systematically enhanced in higher engineering education. Following a design-based research approach, connecting theoretical and practical insights from experts and stakeholders, we present here four dimensions of such an approach. Firstly, we discuss the setup, contents, and implementation of institutional guidelines as the crucial starting point of any internationalisation strategy aiming at integrating sustainable development education and global competence development. Secondly, we stress the role of institutional diversity, and show how institutions can foster inclusive and welcoming environments. Thirdly, we suggest strategies and approaches for global competence training for students, faculty, and staff, and highlight important background considerations for enabling global competence development. Fourthly, we emphasise the importance of assessing efforts to ensure that they live up to their potential and deliver the desired outcomes. The recommendations based on the investigation summarise key considerations that all HEIs—not just those focused on engineering education—must take into account as they strive for holistic global competence development, which is a key aspect of education for sustainable development.
Developing Eighth-Grade Students’ Computational Thinking with Critical Reflection
Authors: He Zhenzhen , Wu Xuemei , Wang Qiyun , Huang Changqin
Published: October 2021

As computer science has become a vital power in facilitating the rapid and sustainable development of various fields, equipping everyone with computational thinking (CT) has been recognized as one of the core pillars supporting the sustainable development of individuals and our digital world. However, it remains challenging for secondary school students to assimilate CT. Recently, critical reflection has been proposed as a useful metacognitive strategy for regulating students’ thinking to solve current and future problems. In this study, a quasi-experiment was conducted to investigate the role of critical reflection in advancing eighth-grade students’ CT. The participants were 95 eighth-grade students, comprising an experimental group (n = 49) and a control group (n = 46). The students’ CT was evaluated based on their learning performance in computational concepts, computational practices, and computational perspectives. The results showed that critical reflection, compared with traditional instruction from teachers, could significantly advance eighth-grade students’ CT. Interestingly, the two groups showed significantly different learning performance in computational practices during the learning process. Furthermore, interaction with peers and instructors played an essential role in helping students engage as active agents in critical reflection. The results of this study emphasize the need to develop students’ CT by practicing critical reflection in eighth-grade education.
Power Quality Improvement Using Distributed Power Flow Controller with BWO-Based FOPID Controller
Authors: Goud B. Srikanth , Reddy Ch. Rami , Bajaj Mohit , Elattar Ehab E. , Kamel Salah
Published: October 2021

The integration of hybrid renewable energy sources (HRESs) into the grid is currently being encouraged to meet the increasing demand for electric power and reduce fossil fuels which are causing environmental-related problems. Integration of HRESs into the grid can create some power quality (PQ) problems. To mitigate PQ problems and improve the performance of grid-connected HRESs some flexible devices should be used. This paper presents a distributed power flow controller (DPFC), as a type of flexible device to mitigate some PQ problems, including voltage sag, swell, disruptions, and eliminating the harmonics in a hybrid power system (HPS). The HPS presented in this work comprises a photo voltaic (PV) system, wind turbine (WT) and battery energy storage system (BESS). As a result, black widow optimization (BWO) with DPFC with real and reactive power (DPFC-PQ) is built in this paper to solve the PQ issues in HRES systems. The main aim of the work is to mitigate PQ problems and compensate for load demand in the HRES scheme. The controller used to drive this DPFC-PQ is a fractional-order PID (FOPID) controller optimized by the black widow optimization (BWO) technique. To assess the capability of BWO in fine-tuning the FOPID controller parameters, twelve optimization techniques were presented: P&O, PSO, Cuckoo, GA, GSA, BBO, Whale, ESA, RFA, ASO, and EVORFA. Additionally, a comparison between the FOPID controller and the classical PI controller is introduced. The results showed that the proposed BWO-FOPID controller for DFPC had mitigated the PQ problems in grid-connected HRESs. The system’s performance with the presented BWO-FOPID controller is compared with eleven optimization techniques used to optimize the FOPID controller and also compared with the conventional PI controller. The design of the proposed system is implemented in the MATLAB/Simulink platform and performances were analyzed.
Citizens’ or Government’s Will? Exploration of Why Indonesia’s Local Governments Adopt Technologies for Open Government
Authors: Adnan Hafizh Rafizal , Hidayanto Achmad Nizar , Kurnia Sherah
Published: October 2021

Web 2.0 is a technology that enables collaboration between citizens and the government to actualise the concept of open government. The adoption of technology in the public sector is known to have positive impacts in fostering public sector innovation, including in developing countries with various problems that require collaboration between citizens and the government. However, currently studies concerning open government technology adoption in developing countries are limited. Indonesia as an example of a developing and democratic country provides a suitable context to explore this phenomenon. Moreover, there are many local government institutions in Indonesia, especially on Java Island, that have implemented Web 2.0 to support open government initiatives. Therefore, this research aims to explore key factors influencing the adoption of the Web 2.0 platform by local government institutions in Indonesia. Multiple theories are combined to guide the exploration of the influencing factors related to technology, organisations, management, and the environment. Based on a multiple case study involving five local government institutions in Indonesia, we identified fifteen factors affecting the adoption of Web 2.0 technology. This study offers both research and practical implications that can be considered by government and other key stakeholders to optimise public participation and information access through the adoption of open government initiatives.
Natural Capital Accounting Informing Water Management Policies in Europe
Authors: Souliotis Ioannis , Voulvoulis Nikolaos
Published: October 2021

In the European Union, the Water Framework Directive provides a roadmap for achieving good water status and sustainable water usage, and a framework for the information, types of analysis, and interventions required by the Member States. Lack of previous knowledge in, and understanding of, interdisciplinary approaches across European countries has led to applications of corrective measures that have yielded less than favourable results. The natural capital paradigm, the assessment and monitoring of the value of natural capital, has the potential to convey information on the use of water resources and improve the connection between implemented measures and changes in the status of the resources, thus enhancing the effectiveness of policy interventions. In this paper, we present the natural capital accounting methodology, adapted to the requirements of the Directive, and demonstrate its application in two European catchments. Using economic methods, the asset value of two ecosystem services was estimated and associated with changes in water status due to policy instruments. Findings demonstrate that the asset value of water for residential consumption and recreational purposes fluctuates from year to year, influenced by current and future uses. Consequently, managing authorities should consider both current and emerging pressures when designing interventions to manage water resource sustainably.