bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethnomedicinal Plants Used in the Health Care System: Survey of the Mid Hills of Solan District, Himachal Pradesh, India
Authors: Kumar Manoj , Radha  , Devi Himani , Prakash Suraj , Rathore Sonia , Thakur Mamta , Puri Sunil , Pundir Ashok , Bangar Sneh Punia , Changan Sushil , Ilakiya Tamilselvan , Samota Mahesh Kumar , Damale Rahul D. , Singh Surinder , Berwal Mukesh K. , Dhumal Sangram , Bhoite Anilkumar G. , Sharma Anshu , Senapathy Marisennayya , Bhushan Bharat , Maurya Vineet Kumar , Asha  , Natta Suman , Amarowicz Ryszard , Mekhemar Mohamed
Published: September 2021

The study was performed in the mid hills of the Dharampur region in Solan district of Himachal Pradesh, India. At the study site, a total of 115 medicinal plants were documented (38 trees, 37 herbs, 34 shrubs, 5 climbers, 1 fern, and 1 grass). In the study region, extensive field surveys were performed between March 2020 and August 2021. Indigenous knowledge of wild medicinal plants was collected through questionnaires, discussions, and personal interviews during field trips. Plants with their correct nomenclature were arranged by botanical name, family, common name, habitat, parts used, routes used, and diseases treated. In the present study, the predominant family was Rosaceae, which represented the maximum number of plant species, 10, followed by Asteraceae and Lamiaceae, which represented 8 plant species. The rural inhabitants of the Dharampur region in the Solan district have been using local plants for primary health care and the treatment of various diseases for a longer time. However, information related to the traditional knowledge of medicinal plants was not documented. The rural inhabitants of the Dharampur region reported that the new generation is not so interested in traditional knowledge of medicinal plants due to modernization in society, so there is an urgent need to document ethnomedicinal plants before such knowledge becomes inaccessible and extinct.
Synergistic Effect of Pressurization Rate and β-Form Nucleating Agent on the Multi-Phase Crystallization of iPP
Authors: Jia Wenxia , Zhuo Ranran , Xu Mingkun , Lin Jiaxiang , Li Xiaoting , Liu Chuntai , Shen Changyu , Shao Chunguang
Published: September 2021

Using a homemade pressure device, we explored the synergistic effect of pressurization rate and β-form nucleating agent (β-NA) on the crystallization of an isotactic polypropylene (iPP) melt. The obtained samples were characterized by combining small angle X-ray scattering and synchrotron wide angle X-ray diffraction. It was found that the synergistic application of pressurization and β-NA enables the preparation of a unique multi-phase crystallization of iPP, including β-, γ- and/or mesomorphic phases. Pressurization rate plays a crucial role on the formation of different crystal phases. As the pressurization rate increases in a narrow range between 0.6–1.9 MPa/s, a significant competitive formation between β- and γ-iPP was detected, and their relative crystallinity are likely to be determined by the growth of the crystal. When the pressurization rate increases further, both β- and γ-iPP contents gradually decrease, and the mesophase begins to emerge once it exceeds 15.0 MPa/s, then mesomorphic, β- and γ- iPP coexist with each other. Moreover, with different β-NA contents, the best pressurization rate for β-iPP growth is the same as 1.9 MPa/s, while more β-NA just promotes the content of β-iPP under the rates lower than 1.9 MPa/s. In addition to inducing the formation of β-iPP, it shows that β-NA can also significantly promote the formation of γ-iPP in a wide pressurization rate range between 3.8 to 75 MPa/s. These results were elucidated by combining classical nucleation theory and the growth theory of different crystalline phases, and a theoretical model of the pressurization-induced crystallization is established, providing insight into understanding the multi-phase structure development of iPP.
Recent Advances in Multimodal Molecular Imaging of Cancer Mediated by Hybrid Magnetic Nanoparticles
Authors: Luengo Morato Yurena , Ovejero Paredes Karina , Lozano Chamizo Laura , Marciello Marzia , Filice Marco
Published: September 2021

Cancer is the second leading cause of death in the world, which is why it is so important to make an early and very precise diagnosis to obtain a good prognosis. Thanks to the combination of several imaging modalities in the form of the multimodal molecular imaging (MI) strategy, a great advance has been made in early diagnosis, in more targeted and personalized therapy, and in the prediction of the results that will be obtained once the anticancer treatment is applied. In this context, magnetic nanoparticles have been positioned as strong candidates for diagnostic agents as they provide very good imaging performance. Furthermore, thanks to their high versatility, when combined with other molecular agents (for example, fluorescent molecules or radioisotopes), they highlight the advantages of several imaging techniques at the same time. These hybrid nanosystems can be also used as multifunctional and/or theranostic systems as they can provide images of the tumor area while they administer drugs and act as therapeutic agents. Therefore, in this review, we selected and identified more than 160 recent articles and reviews and offer a broad overview of the most important concepts that support the synthesis and application of multifunctional magnetic nanoparticles as molecular agents in advanced cancer detection based on the multimodal molecular imaging approach.
High-Strength and Low-Cost Biobased Polyurethane Foam Composites Enhanced by Poplar Wood Powder Liquefaction
Authors: Yang Wanjia , Han Yanming , Zhang Wei , Zhang Derong
Published: September 2021

An environmentally friendly liquefaction of wood powder was prepared by atmospheric pressure liquefaction technology to replace the non-renewable petroleum polyols in the preparation of polyurethane foam composites. The liquefaction time varied from 0 min to 140 min. The composition of liquefied products and the effects of liquefaction time on the morphology, apparent density and mechanical properties of polyurethane foam composites were investigated. The results showed that the optimal process time for the preparation of wood powder liquefaction products, which could replace traditional petroleum polyols, was 110 min. At this time, polyether polyols are the main liquefaction products, with an average molecular weight in Mn reaching 237 and average molecular weight in Mw reaching 246. The functional group of the liquefied product consisted mainly of hydroxyl, with the highest content of 1042 mg KOH/g and the lowest acid number of 1.6 mg KOH/g. In addition, the surface of the polyurethane foam based on poplar wood is dominated by closed cell foam; thus its foam has good heat insulation and heat preservation properties. At 110 min liquefaction time, the apparent density of polyurethane foam is 0.164 g/cm3 and the compression strength is 850 kPa, which is higher than that of traditional polyurethane foam (768 kPa), which is without wood powder modification. Replacing petroleum polyol with renewable wood powder liquefaction products to prepare biomass-based polyurethane foam composite materials, researching complex chemical changes in different liquefaction stages, and finding the best liquefaction conditions are of great significance to optimize the performance of polyurethane, address the shortage of resources and reduce environmental pollution.
Hydrophobic Modification of Biopolymer Aerogels by Cold Plasma Coating
Authors: Schroeter Baldur , Jung Isabella , Bauer Katharina , Gurikov Pavel , Smirnova Irina
Published: September 2021

The aim of this work was to evaluate the potential of cold plasma polymerization as a simple, fast and versatile technique for deposition of protective hydrophobic and oleophobic polymer layers on hydrophilic biopolymer aerogels. Polymerization of different fluorinated monomers (octafluorocyclobutane C4F8 and perfluoro-acrylates PFAC-6 and PFAC-8) on aerogel monoliths derived from alginate, cellulose, whey protein isolate (WPI) and potato protein isolate (PPI) resulted in fast and significant surface hydrophobization after short process times of 5 min and led to superhydrophobic surfaces with static water contact angles up to 154° after application of poly-C4F8 coatings. Simultaneous introduction of hydro- and oleophobicity was possible by deposition of perfluoro-acrylates. While the porous structure of aerogels stayed intact during the process, polymerization inside the aerogels pores led to the generation of new porous moieties and resulted therefore in significant increase in the specific surface area. The magnitude of the effect depended on the individual process settings and on the overall porosity of the substrates. A maximization of specific surface area increase (+179 m2/g) was obtained by applying a pulsed wave mode in the C4F8-coating of alginate aerogels.
External Marginal Gap Variation and Residual Fracture Resistance of Composite and Lithium-Silicate CAD/CAM Overlays after Cyclic Fatigue over Endodontically-Treated Molars
Authors: Baldi Andrea , Comba Allegra , Michelotto Tempesta Riccardo , Carossa Massimo , Pereira Gabriel Kalil Rocha , Valandro Luiz Felipe , Paolone Gaetano , Vichi Alessandro , Goracci Cecilia , Scotti Nicola
Published: September 2021

The purpose of this in vitro study was to evaluate the external marginal gap variation with a 3D quantitative method and the residual fracture resistance after cyclic fatigue in endodontically treated molars restored with overlays of different materials, with and without fiber posts-supported buildups. Forty-eight human maxillary molars were selected, endodontically treated, prepared with standardized MOD cavities and randomly allocated into 6 study groups considering the “core strategy” (build-up with composite resin; build-up with composite resin supported by a fiber post); and the “restorative material” of the indirect adhesive overlay (GrandioBlocks, Voco; Cerasmart, GC; CeltraDuo, Dentsply). All procedures were executed according with manufacturers guidelines. Micro-CT analysis prior and after cyclic fatigue were executed, followed by scanning electron microscope analysis and fracture resistance test. The Two-Way ANOVA analysis showed that interfacial gap progression was significantly influenced by the “core strategy” (p < 0.01) but not of “restorative material” (p = 0.59). Concerning fracture resistance, “restorative material” was statistically significant (p < 0.01), while “core strategy” (p = 0.63) and the interaction (p = 0.84) were not. In conclusion, the fiber post presence within the build-up promoted a lower interfacial gap opening after fatigue, evaluated through micro-CT scans. In terms of fracture resistance, teeth restored with Cerasmart and Celtra Duo were statistically similar, but superior to GrandioBlocks.
Dielectric Permittivity, AC Electrical Conductivity and Conduction Mechanism of High Crosslinked-Vinyl Polymers and Their Pd(OAc)2 Composites
Authors: Elbayoumy Elsayed , El-Ghamaz Nasser A. , Mohamed Farid Sh. , Diab Mostafa A. , Nakano Tamaki
Published: September 2021

Semiconductor materials based on metal high crosslinked-vinyl polymer composites were prepared through loading of Pd(OAc)2 on both Poly(ethylene-1,2-diyl dimethacrylate) (poly(EDMA)) and poly(ethylene-1,2-diyl dimethacrylate-co-methyl methacrylate) (Poly(EDMA-co-MMA)). The thermochemical properties for both poly(EDMA) and poly(EDMA-co-MMA) were investigated by thermal gravimetric analysis TGA technique. The dielectric permittivity, AC electrical conductivity and conduction mechanism for all the prepared polymers and their Pd(OAc)2 composites were studied. The results showed that the loading of polymers with Pd(OAc)2 led to an increase in the magnitudes of both the dielectric permittivity and AC electrical conductivity (σac). The value of σac increased from 1.38 × 10−5 to 5.84 × 10−5 S m−1 and from 6.40 × 10−6 to 2.48 × 10−5 S m−1 for poly(EDMA) and poly(EDMA-co-MMA), respectively, at 1 MHz and 340 K after loading with Pd(OAc)2. Additionally, all the prepared polymers and composites were considered as semiconductors at all the test frequencies and in the temperature range of 300–340 K. Furthermore, it seems that a conduction mechanism for all the samples could be Quantum Mechanical Tunneling (QMT).
Surface Morphology and Mechanical Properties of Polyether Ether Ketone (PEEK) Nanocomposites Reinforced by Nano-Sized Silica (SiO2) for Prosthodontics and Restorative Dentistry
Authors: Abd El-Fattah Ahmed , Youssef Heba , Gepreel Mohamed Abdel Hady , Abbas Rafik , Kandil Sherif
Published: September 2021

In the field of orthopedics and traumatology, polyether ether ketone (PEEK) serves a significant role as a suitable alternative to traditional metal-based implants like titanium. PEEK is being used more commonly to replace traditional dental products. For bonding with various adhesive agents and preserved teeth, the surface alteration of PEEK was investigated. The aim of this research was to understand how different types and contents of nano-sized silica (SiO2) fillers influenced the surface and mechanical properties of PEEK nanocomposites used in prosthodontics. In this work, PEEK based nanocomposites containing hydrophilic or hydrophobic nano-silica were prepared by a compression molding technique. The influence of nano-SiO2 type and content (10, 20 and 30% wt) on surface properties of the resultant nanocomposites was investigated by the use of scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), surface roughness analysis, and contact angle measurement. The crystalline structures of PEEK/SiO2 nanocomposites were examined by X-ray diffraction (XRD) spectroscopy. Mechanical properties were measured by microhardness, elastic compression modulus, and flexural strength. All nanocomposites showed increased surface roughness compared to pure PEEK. SEM images revealed that nanocomposites filled with low content hydrophobic nano-SiO2 showed uniform dispersion within the PEEK matrix. The introduction of 10 wt% of hydrophobic nano-SiO2 to the PEEK matrix improved elastic modulus, flexural strength, and microhardness, according to the findings. The addition of nano-SiO2 fillers in a higher weight percentage, over 10%, significantly damages the mechanical characteristics of the resultant nanocomposite. On the basis of the obtained results, PEEK/SiO2 nanocomposites loaded with low content hydrophobic nano-SiO2 are recommended as promising candidates for orthopedic and prosthodontics materials.
Conjugated Mass Transfer of CO2 Absorption through Concentric Circular Gas–Liquid Membrane Contactors
Authors: Ho Chii-Dong , Chang Hsuan , Chen Yih-Hang , Lim Jun-Wei , Liou Jing-Wei
Published: September 2021

A new design of gas absorption that winds the permeable membrane onto an inner concentric tube to conduct a concentric circular gas–liquid membrane module has been studied theoretically in the fully developed region. An analytical formulation, referred to as conjugated Graetz problems, is developed to predict the concentration distribution and Sherwood numbers for the absorbent fluid flowing in the shell side and CO2/N2 gas mixture flowing in the tube side under various designs and operating parameters. The analytical solutions to the CO2 absorption efficiency were developed by using a two-dimensional mathematical modeling, and the resultant conjugated partial differential equations were solved analytically using the method of separation variables and eigen-function expansion in terms of power series. The predictions of CO2 absorption rate by using Monoethanolamide (MEA) solution in concentric circular membrane contactors under both concurrent- and countercurrent-flow operations are developed theoretically and confirmed with the experimental results. Consistency in both a good qualitative and quantitative sense is achieved between the theoretical predictions and experimental results. The advantage of the present mathematical treatment provides a concise expression for the chemical absorption of CO2 by MEA solution to calculate the absorption rate, absorption efficiency, and average Sherwood number. The concentration profiles with the mass-transfer Graetz number, inlet CO2 concentration, and both gas feed and absorbent flow rates are also emphasized. Both theoretical predictions and experimental results show that the device performance of the countercurrent-flow operation is better than that of the concurrent-flow device operation. The availability of such simplified expressions of the absorption rate and averaged Sherwood as developed directly from the analytical solutions is the value of the present study.
Influence of Cellulose Characteristics on Pyrolysis Suitability
Authors: Eugenio María E. , Ruiz-Montoya Mercedes , Martín-Sampedro Raquel , Ibarra David , Díaz Manuel J.
Published: September 2021

Cellulose is the most abundant component of biomass and the one that requires the most activation energy (Ea) for pyrolysis. In this study, the dependence of Ea on the intrinsic cellulose characteristics, such as the degree of polymerization (DP), crystallinity, and crystal size, was studied in different cellulose samples, including samples from Eucalyptus globulus, Ulmus minor, Linun usitatissimum, Olea europaea, Robinia pseudoacacia, and Populus alba. Then, to describe the pyrolytic degradation of cellulose, the Ozawa–Flynn–Wall kinetic method was the most appropriate among the isoconversional models studied. An acceptable quadratic relationship of R2 > 0.9 between the Ea values of the different cellulose samples with their corresponding DP, crystallinity index, and crystal size values was found. Therefore, low crystallinity and low-to-medium crystal size values are desired to obtain lower Ea values for cellulose pyrolysis. On the other hand, DP did not present a clear effect on Ea in the studied DP range.
Counter-Current Suspension Extraction Process of Lignocellulose in Biorefineries to Reach Low Water Consumption, High Extraction Yields, and Extract Concentrations
Authors: Conrad Marc , Smirnova Irina
Published: September 2021

The processing of large quantities of water in biorefining processes can lead to immense costs for heating, evaporation, and wastewater disposal. These costs may prohibit the exploitation of alternative products, e.g., xylooligosaccharides from straw, which are regarded as too costly. A new counter-current extractions method is proposed that aims at low solvent (water) consumption, as well as high yields and extract concentrations. This process was evaluated with suspension extraction experiments with steam pretreated wheat straw and the process window analysis based on a mass balance for a washing and a leaching scenario. The latter was conducted with two other suspension extraction processes as a comparison. The equilibration time was found to be well below 10 min. While the suspension extraction with and without recycling need to be designed to achieve a high yield or a high concentration and low solvent consumption, the proposed extraction method can reach all three simultaneously. Thus, this new process is evaluated as a potential method to spare water and downstream costs and allow new processing pathways in second-generation biorefineries.
The Influence of Annealing Atmosphere, Blending Ratio, and Molecular Weight on the Phase Behavior of Blend Materials
Authors: Liu Weichen , Zhang Libin , Wei Yayi
Published: September 2021

In the study of block copolymers, many parameters need to be adjusted to obtain good phase separation results. Based on block copolymer polystyrene-b-polycarbonate and homopolymer polystyrene, the effects of the annealing atmosphere, blending ratio, and molecular weight on phase separation were studied. The results show that annealing in air can inhibit the occurrence of phase separation. In addition, snowflake patterns are formed during phase separation. The blending ratio affects the quality of the pattern. The molecular weight affects the size of the pattern, and the size increases as the molecular weight increases. In this article, the influence of process conditions and materials on phase separation was discussed, which has laid a solid foundation for the development of block copolymer self-assembly in the future.
Protective Effect of Salvianolic Acid B in Acetic Acid-Induced Experimental Colitis in a Mouse Model
Authors: Govindarasu Mydhili , Ansari Mohammad Azam , Alomary Mohammad N. , AlYahya Sami , Alghamdi Saad , Bannunah Azzah M. , Almehmadi Mazen , Abirami Pari , Gayathiri Ekambaram , Palani Mariyappan , Rajakumar Govindasamy , Thiruvengadam Muthu , Vaiyapuri Manju
Published: September 2021

In its prominent experimental studies salvianolic acid B (Sal B) is novel because of its well-defined, common physiological effects, which include anti-inflammatory, anti-depressant, cardioprotective, DNA protective, neuroprotective and hepatoprotective activity in experimental animals. Initially, Sal B was studied for its anti-inflammatory properties, used as a remedy for a wide range of disease conditions, but its specific efficacy on inflammatory bowel disease is still unclear. The aim of this current study was to understand the therapeutic potential of Sal B in an acetic acid (AA)—triggered experimental mouse colitis model. Colitis was triggered by intrarectal injection of 5% AA, and then laboratory animals were given Sal B (10, 20 and 40 μg/kg) for seven days. The ulcerated colonic mucosa was assessed by clinical experiment, macroscopical, biological and histopathological analysis. The results showed depleted SOD, CAT, GSH levels and consequential elevated MPO and MDA levels and aberrant crypt foci and mast cells were seen in the AA-induced colonic mucosa of experimental animals. The data obtained from this study demonstrate that a dose of 40 µg/kg showed an efficacious anti-ulcer effect against AA-induced experimental colitis. Based on its antioxidant efficacy, Sal B may therefore be useful as a therapeutic approach for ulcerative colitis.
Synthesis of Palladium and Copper Nanoparticles Supported on TiO2 for Oxidation Solvent-Free Aerobic Oxidation of Benzyl Alcohol
Authors: Alshammari Hamed M.
Published: September 2021

The use of metal oxides as supports for palladium and copper (Pd–Cu) nanoalloys constitutes a new horizon for improving new active catalysts in very important reactions. From the literatures, Pd-based bimetallic nanostructures have great properties and active catalytic performance. In this work, nanostructures of titanium dioxide (TiO2) were used as supports for Pd–Cu nanoparticles catalysts. Palladium and copper were deposited on these supports using the sol-immobilisation method. The composite nanoalloys were characterized using transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). The catalyst was evaluated for the oxidation of benzyl alcohol. The effect of the Cu–Pd ratio using sol-immobilization methods supported on TiO2 was investigated. The results show that monometallic Cu/TiO2 was observed to have a low activity. However, as soon as the catalyst contained any palladium, the activity increased with a significant increase in the selectivity towards isomerization products. The influence of support and temperature were investigated. Furthermore, the catalyst reusability was also tested for oxidation of benzyl alcohol reactions, by repeatedly performing the same reaction using the recovered catalyst. The Pd–Cu/TiO2 catalyst displayed better reusability even after several reactions
Smart Home Gateway Based on Integration of Deep Reinforcement Learning and Blockchain Framework
Authors: Shahbazi Zeinab , Byun Yung-Cheol , Kwak Ho-Young
Published: September 2021

The development of information and communication technology in terms of sensor technologies cause the Internet of Things (IoT) step toward smart homes for prevalent sensing and management of resources. The gateway connections contain various IoT devices in smart homes representing the security based on the centralized structure. To address the security purposes in this system, the blockchain framework is considered a smart home gateway to overcome the possible attacks and apply Deep Reinforcement Learning (DRL). The proposed blockchain-based smart home approach carefully evaluated the reliability and security in terms of accessibility, privacy, and integrity. To overcome traditional centralized architecture, blockchain is employed in the data store and exchange blocks. The data integrity inside and outside of the smart home cause the ability of network members to authenticate. The presented network implemented in the Ethereum blockchain, and the measurements are in terms of security, response time, and accuracy. The experimental results show that the proposed solution contains a better outperform than recent existing works. DRL is a learning-based algorithm which has the most effective aspects of the proposed approach to improve the performance of system based on the right values and combining with blockchain in terms of security of smart home based on the smart devices to overcome sharing and hacking the privacy. We have compared our proposed system with the other state-of-the-art and test this system in two types of datasets as NSL-KDD and KDD-CUP-99. DRL with an accuracy of 96.9% performs higher and has a stronger output compared with Artificial Neural Networks with an accuracy of 80.05% in the second stage, which contains 16% differences in terms of improving the accuracy of smart homes.
Liturgy and Apophaticism
Authors: Turcan Nicolae
Published: September 2021

The Orthodox liturgy is a religious phenomenon that can be analyzed phenomenologically and theologically alike, given the emphasis that both phenomenology and Orthodox theology place on experience. By proposing the Kingdom of God instead of the natural world without being able to annihilate the latter in the name of the former, the liturgy seeks divine-human communion. Through the dialogue of prayer, through symbolic and iconic openings, as well as through apophatic theology, the liturgy emphasizes the horizon of mystery as a horizon essential to the way man positions himself before God. The present text attempts to demonstrate that apophaticism, understood as an experience of the mysterious presence of God, is one of the crucial dimensions of the Orthodox liturgy; and that this apophatic presence of God reveals a way of thinking which does not become onto-theology, not even when using concepts borrowed from metaphysics. The overcoming of onto-theology is achieved here not by abandoning concepts such as “being” and “cause” but by placing the language game in the field of prayer and apophatic theology.
Introduction
Authors: Winings Kathy
Published: September 2021

Education is a very diverse field [...]
Patch-Wise Semantic Segmentation for Hyperspectral Images via a Cubic Capsule Network with EMAP Features
Authors: Sun Le , Song Xiangbo , Guo Huxiang , Zhao Guangrui , Wang Jinwei
Published: September 2021

In order to overcome the disadvantages of convolution neural network (CNN) in the current hyperspectral image (HSI) classification/segmentation methods, such as the inability to recognize the rotation of spatial objects, the difficulty to capture the fine spatial features and the problem that principal component analysis (PCA) ignores some important information when it retains few components, in this paper, an HSI segmentation model based on extended multi-morphological attribute profile (EMAP) features and cubic capsule network (EMAP–Cubic-Caps) was proposed. EMAP features can effectively extract various attributes profile features of entities in HSI, and the cubic capsule neural network can effectively capture complex spatial features with more details. Firstly, EMAP algorithm is introduced to extract the morphological attribute profile features of the principal components extracted by PCA, and the EMAP feature map is used as the input of the network. Then, the spectral and spatial low-layer information of the HSI is extracted by a cubic convolution network, and the high-layer information of HSI is extracted by the capsule module, which consists of an initial capsule layer and a digital capsule layer. Through the experimental comparison on three well-known HSI datasets, the superiority of the proposed algorithm in semantic segmentation is validated.
Quality Evaluation of Digital Twins Generated Based on UAV Photogrammetry and TLS: Bridge Case Study
Authors: Mohammadi Masoud , Rashidi Maria , Mousavi Vahid , Karami Ali , Yu Yang , Samali Bijan
Published: September 2021

In the current modern era of information and technology, emerging remote advancements have been widely established for detailed virtual inspections and assessments of infrastructure assets, especially bridges. These technologies are capable of creating an accurate digital representation of the existing assets, commonly known as the digital twins. Digital twins are suitable alternatives to in-person and on-site based assessments that can provide safer, cheaper, more reliable, and less distributive bridge inspections. In the case of bridge monitoring, Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are among the most common advanced technologies that hold the potential to provide qualitative digital models; however, the research is still lacking a reliable methodology to evaluate the generated point clouds in terms of quality and geometric accuracy for a bridge size case study. Therefore, this paper aims to provide a comprehensive methodology along with a thorough bridge case study to evaluate two digital point clouds developed from an existing Australian heritage bridge via both UAV-based photogrammetry and TLS. In this regard, a range of proposed approaches were employed to compare point clouds in terms of points’ distribution, level of outlier noise, data completeness, surface deviation, and geometric accuracy. The comparative results of this case study not only proved the capability and applicability of the proposed methodology and approaches in evaluating these two voluminous point clouds, but they also exhibited a higher level of point density and more acceptable agreements with as-is measurements in TLS-based point clouds subjected to the implementation of a precise data capture and a 3D reconstruction model.
Lost Landscape: A Combination of LiDAR and APSFR Data to Locate and Contextualize Archaeological Sites in River Environments
Authors: Rodríguez González Esther , Paniego Díaz Pablo , Celestino Pérez Sebastián
Published: September 2021

Over the last few decades, river landscapes have been significantly transformed as a result of increased human impact. This transformation is evident in areas such as the middle Guadiana basin, where the impact of both agricultural and hydraulic infrastructures has led to the decontextualization of archaeological sites, resulting in a disconnection between archaeological sites and their own physical environment. In order to analyse the location and geographic contexts of sites from the first Iron Age in the middle Guadiana basin and to detect the existence of human settlement patterns, we designed a methodological approach that combines LiDAR and APSFR data (areas with potential significant flood risk). The main purpose of this method is to detect flood areas and assess the relationship between them and archaeological sites. The result allowed us to obtain a clearer understanding of these societies, their knowledge of the physical environment, and the causes and reasons behind their occupation of certain sites. The validation of the results demonstrated the versatility of this methodological approach, which can be extrapolated to analysing other regions and historical periods.
Detection of Collapsed Bridges from Multi-Temporal SAR Intensity Images by Machine Learning Techniques
Authors: Liu Wen , Maruyama Yoshihisa , Yamazaki Fumio
Published: September 2021

Bridges are an important part of road networks in an emergency period, as well as in ordinary times. Bridge collapses have occurred as a result of many recent disasters. Synthetic aperture radar (SAR), which can acquire images under any weather or sunlight conditions, has been shown to be effective in assessing the damage situation of structures in the emergency response phase. We investigate the backscattering characteristics of washed-away or collapsed bridges from the multi-temporal high-resolution SAR intensity imagery introduced in our previous studies. In this study, we address the challenge of building a model to identify collapsed bridges using five change features obtained from multi-temporal SAR intensity images. Forty-four bridges affected by the 2011 Tohoku-oki earthquake, in Japan, and forty-four bridges affected by the 2020 July floods, also in Japan, including a total of 21 collapsed bridges, were divided into training, test, and validation sets. Twelve models were trained, using different numbers of features as input in random forest and logistic regression methods. Comparing the accuracies of the validation sets, the random forest model trained with the two mixed events using all the features showed the highest capability to extract collapsed bridges. After improvement by introducing an oversampling technique, the F-score for collapsed bridges was 0.87 and the kappa coefficient was 0.82, showing highly accurate agreement.
The Impacts of Farmland Loss on Regional Food Self-Sufficiency in Yangtze River Delta Urban Agglomeration over Last Two Decades
Authors: Duan Xuelin , Meng Qingxiang , Fei Xufeng , Lin Meng , Xiao Rui
Published: September 2021

Food security is essential for human survival and sustainable development. Due to rapid urbanization and industrialization, the farmland loss in Yangtze River Delta Urban Agglomeration (YRDUA) has threatened food security. Thus, this study intended to quantify the farmland loss and assess its impacts on food security in the YRDUA from 2000 to 2020 at three scales based on the Google Earth Engine platform. Our results show that the area of farmland in YRDUA is decreasing at a rather high speed in the past 20 years and the trend is getting worse. At the urban agglomeration scale, there was a farmland deficit of 0.44 million ha in 2000, followed by larger farmland deficits in 2010 and 2020. At the city scale, Shanghai had the largest scarcity of farmland. At the urban subgroup scale, Subgroup I in the west and Subgroup II in the north always maintained an oversupply of farmland, while Subgroup III in the east and Subgroup IV in the south faced serious food security problems. Our study suggests that farmland must be protected in YRDUA in order to ensure food self-sufficiency and promote regional sustainability.
Land Degradation and Development Processes and Their Response to Climate Change and Human Activity in China from 1982 to 2015
Authors: Kang Jianfang , Zhang Yaonan , Biswas Asim
Published: September 2021

Land degradation and development (LDD) has become an urgent global issue. Quick and accurate monitoring of LDD dynamics is key to the sustainability of land resources. By integrating normalized difference vegetation index (NDVI) and net primary productivity (NPP) based on the Euclidean distance method, a LDD index (LDDI) was introduced to detect LDD processes, and to explore its quantitative relationship with climate change and human activity in China from 1985 to 2015. Overall, China has experienced significant land development, about 45% of China’s mainland, during the study period. Climate change (temperature and precipitation) played limited roles in the affected LDD, while human activity was the dominant driving force. Specifically, LDD caused by human activity accounted for about 58% of the total, while LDD caused by climate change only accounted for 0.34% of the total area. Results from the present study can provide insight into LDD processes and their driving factors and promote land sustainability in China and around the world.
SVG-Loop: Semantic–Visual–Geometric Information-Based Loop Closure Detection
Authors: Yuan Zhian , Xu Ke , Zhou Xiaoyu , Deng Bin , Ma Yanxin
Published: September 2021

Loop closure detection is an important component of visual simultaneous localization and mapping (SLAM). However, most existing loop closure detection methods are vulnerable to complex environments and use limited information from images. As higher-level image information and multi-information fusion can improve the robustness of place recognition, a semantic–visual–geometric information-based loop closure detection algorithm (SVG-Loop) is proposed in this paper. In detail, to reduce the interference of dynamic features, a semantic bag-of-words model was firstly constructed by connecting visual features with semantic labels. Secondly, in order to improve detection robustness in different scenes, a semantic landmark vector model was designed by encoding the geometric relationship of the semantic graph. Finally, semantic, visual, and geometric information was integrated by fuse calculation of the two modules. Compared with art-of-the-state methods, experiments on the TUM RBG-D dataset, KITTI odometry dataset, and practical environment show that SVG-Loop has advantages in complex environments with varying light, changeable weather, and dynamic interference.
Analysis of Temporal and Spatial Variability of Fronts on the Amery Ice Shelf Automatically Detected Using Sentinel-1 SAR Data
Authors: Zhu Tingting , Cui Xiangbin , Zhang Yu
Published: September 2021

The Amery Ice Shelf (AIS) dynamics and mass balance caused by iceberg calving and basal melting are significant in the ocean climate system. Using satellite imagery from Sentinel-1 SAR, we monitored the temporal and spatial variability of the frontal positions on the Amery Ice Shelf, Antarctica, from 2015 to 2021. In this paper, we propose an automatic algorithm based on the SO-CFAR strategy and a profile cumulative method for frontal line extraction. To improve the accuracy of the extracted frontal lines, we developed a framework combining the Constant False Alarm Rate (CFAR) and morphological image-processing strategies. A visual comparison between the proposed algorithm and state-of-the-art algorithm shows that our algorithm is effective in these cases including rifts, icebergs, and crevasses as well as ice-shelf surface structures. We present a detailed analysis of the temporal and spatial variability of fronts on AIS that we find, an advance of the AIS frontal line before the D28 calving event, and a continuous advance after the event. The study reveals that the AIS extent has been advanced at the rate of 1015 m/year. Studies have shown that the frontal location of AIS has continuously expanded. From March 2015 to May 2021, the frontal location of AIS expanded by 6.5 km; while the length of the AIS frontal line is relatively different after the D28 event, the length of the frontal line increased by about 7.5% during 2015 and 2021 (255.03 km increased to 273.5 km). We found a substantial increase in summer advance rates and a decrease in winter advance rates with the seasonal characteristics. We found this variability of the AIS frontal line to be in good agreement with the ice flow velocity.
Fog Season Risk Assessment for Maritime Transportation Systems Exploiting Himawari-8 Data: A Case Study in Bohai Sea, China
Authors: Du Pei , Zeng Zhe , Zhang Jingwei , Liu Lu , Yang Jianchang , Qu Chuanping , Jiang Li , Liu Shanwei
Published: September 2021

Sea fog is a disastrous marine phenomenon for ship navigation. Sea fog reduces visibility at sea and has a great impact on the safety of ship navigation, which may lead to catastrophic accidents. Geostationary orbit satellites such as Himawari-8 make it possible to monitor sea fog over large areas of the sea. In this paper, a framework for marine navigation risk evaluation in fog seasons is developed based on Himawari-8 satellite data, which includes: (1) a sea fog identification method for Himawari-8 satellite data based on multilayer perceptron; (2) a navigation risk evaluation model based on the CRITIC objective weighting method, which, along with the sea fog identification method, allows us to obtain historical sea fog data and marine environmental data, such as properties related to wind, waves, ocean currents, and water depth to evaluate navigation risks; and (3) a way to determine shipping routes based on the Delaunay triangulation method to carry out risk analyses of specific navigation areas. This paper uses global information system mapping technology to get navigation risk maps in different seasons in Bohai Sea and its surrounding waters. The proposed sea fog identification method is verified by CALIPSO vertical feature mask data, and the navigation risk evaluation model is verified by historical accident data. The probability of detection is 81.48% for sea fog identification, and the accident matching rate of the navigation risk evaluation model is 80% in fog seasons.
Monocular Pedestrian 3D Localization for Social Distance Monitoring
Authors: Niu Yiru , Xu Zhihua , Xu Ershuai , Li Gongwei , Huo Yuan , Sun Wenbin
Published: September 2021

Social distancing protocols have been highly recommended by the World Health Organization (WHO) to curb the spread of COVID-19. However, one major challenge to enforcing social distancing in public areas is how to perceive people in three dimensions. This paper proposes an innovative pedestrian 3D localization method using monocular images combined with terrestrial point clouds. In the proposed approach, camera calibration is achieved based on the correspondences between 2D image points and 3D world points. The vertical coordinates of the ground plane where pedestrians stand are extracted from the point clouds. Then, using the assumption that the pedestrian is always perpendicular to the ground, the 3D coordinates of the pedestrian’s feet and head are calculated iteratively using collinear equations. This allows the three-dimensional localization and height determination of pedestrians using monocular cameras, which are widely distributed in many major cities. The performance of the proposed method was evaluated using two different datasets. Experimental results show that the pedestrian localization error of the proposed approach was less than one meter within tens of meters and performed better than other localization techniques. The proposed approach uses simple and efficient calculations, obtains accurate location, and can be used to implement social distancing rules. Moreover, since the proposed approach also generates accurate height values, exclusionary schemes to social distancing protocols, particularly the parent-child exemption, can be introduced in the framework.
Medium-Sized Highly Coupled Planar Arrays with Maximum Aperture Efficiency
Authors: Pourmohammadi Peyman , Volski Vladimir , Vandenbosch Guy A. E.
Published: September 2021

This paper presents a technique to design strongly coupled planar arrays with very high aperture efficiency. The key innovation is that, based on an irregular 2 × 1 array, very compact medium-sized arrays of size 2 × 2, 2 × 4, and 2 × 6 are constructed with very strong and constructive mutual coupling between the elements. In this way, a maximum aperture efficiency is reached for a given footprint of the array. The occupied space of the antenna in comparison with conventional linear patch arrays is studied. A prototype 2 × 4 array operating around 5.8 GHz is designed, fabricated, built, and measured. The results show a large bandwidth of 20% and a very high aperture efficiency of 100%, which is the largest found in the literature for similarly sized arrays. These results are important in view of the future Internet of Things, where small and medium-sized arrays are planned to be mounted on numerous devices where a very limited physical area is available.
Human–Machine Integration in Processes within Industry 4.0 Management
Authors: Villalba-Diez Javier , Ordieres-Meré Joaquín
Published: September 2021

The aim of this work is to use IIoT technology and advanced data processing to promote integration strategies between these elements to achieve a better understanding of the processing of information and thus increase the integrability of the human–machine binomial, enabling appropriate management strategies. Therefore, the major objective of this paper is to evaluate how human–machine integration helps to explain the variability associated with value creation processes. It will be carried out through an action research methodology in two different case studies covering different sectors and having different complexity levels. By covering cases from different sectors and involving different value stream architectures, with different levels of human influence and organisational requirements, it will be possible to assess the transparency increases reached as well as the benefits of analysing processes with higher level of integration between them.
An NB-IoT-Based Edge-of-Things Framework for Energy-Efficient Image Transfer
Authors: Khan Sikandar Zulqarnain , Le Moullec Yannick , Alam Muhammad Mahtab
Published: September 2021

Machine Learning (ML) techniques can play a pivotal role in energy efficient IoT networks by reducing the unnecessary data from transmission. With such an aim, this work combines a low-power, yet computationally capable processing unit, with an NB-IoT radio into a smart gateway that can run ML algorithms to smart transmit visual data over the NB-IoT network. The proposed smart gateway utilizes supervised and unsupervised ML algorithms to optimize the visual data in terms of their size and quality before being transmitted over the air. This relaxes the channel occupancy from an individual NB-IoT radio, reduces its energy consumption and also minimizes the transmission time of data. Our on-field results indicate up to 93% reductions in the number of NB-IoT radio transmissions, up to 90.5% reductions in the NB-IoT radio energy consumption and up to 90% reductions in the data transmission time.
Use of Thermally Assisted Hydrolysis and Methylation (THM-GC-MS) to Unravel Influence of Pottery Production and Post-Depositional Processes on the Molecular Composition of Organic Matter in Sherds from a Complex Coastal Settlement
Authors: Kaal Joeri , Castro González María Guadalupe , Martínez Cortizas Antonio , Prieto Martínez María Pilar
Published: September 2021

Ceramic fragments from the Islet of Guidoiro Areoso (NW Spain), covering a wide range of cultural periods (Neolithic to Late Bronze Age), have been studied by color analysis, elemental analysis of carbon (C) and nitrogen (N), and molecular analysis (thermally assisted hydrolysis and methylation, THM-GC-MS), in order to identify the organic matter (OM) in the prehistoric pottery and reveal information on ceramic production techniques, food remains and post-depositional effects. Results showed that the strong marine influence (sherds recovered from coastal deposits) and microbial activity (recovery from waste deposits, “cuncheiros”) had a profound effect on C/N ratio and molecular composition (N-rich protein and chitin structures). Other organic ingredients originated from the material used for creating the ware (detected as pyrogenic OM) and possibly food remains (fatty acid fingerprints). Dark-colored ware was enriched in both pyrogenic OM from incomplete combustion and non-bacterial fatty acids. Fatty acid patterns could not be related to possible vessel use, and markers of aquatic resources were scarce, or absent. It is argued that THM-GC-MS of pottery fragments is useful for understanding how an archaeological deposit developed in time, what kinds of OM are present, and possibly to make a pre-selection of samples with high potential for more cost-demanding dietary molecular assessments.