bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Biobased and Hybrid Polyurethane Xerogels from Bacterial Polyester for Potential Biomedical Applications
Authors: Wendels Sophie , de Souza Porto Deyvid , Avérous Luc
Published: December 2021

Organic–inorganic xerogel networks were synthesized from bacterial poly (3-hydroxybutyrate) (PHB) for potential biomedical applications. Since silane-based networks usually demonstrate increased biocompatibility and mechanical properties, siloxane groups have been added onto polyurethane (PU) architectures. In this work, a diol oligomer (oligoPHB-diol) was first prepared from bacterial poly(3-hydroxybutyrate) (PHB) with an environmentally friendly method. Then, hexamethylene diisocyanate or biobased dimeryl diisocyanate was used as diisocyanate to react with the short oligoPHB-diol for the synthesis of different NCO-terminated PU systems in a bulk process and without catalyst. Various PU systems containing increasing NCO/OH molar ratios were prepared. Siloxane precursors were then obtained after reaction of the NCO-terminated PUs with (3-aminopropyl)triethoxysilane, resulting in silane-terminated polymers. These structures were confirmed by different analytical techniques. Finally, four series of xerogels were prepared via a sol–gel process from the siloxane precursors, and their properties were evaluated depending on varying parameters such as the inorganic network crosslinking density. The final xerogels exhibited adequate properties in connection with biomedical applications such as a high in vitro degradation up to 15 wt% after 12 weeks.
Design of Magnetic Hydrogels for Hyperthermia and Drug Delivery
Authors: Ganguly Sayan , Margel Shlomo
Published: December 2021

Hydrogels are spatially organized hydrophilic polymeric systems that exhibit unique features in hydrated conditions. Among the hydrogel family, composite hydrogels are a special class that are defined as filler-containing systems with some tailor-made properties. The composite hydrogel family includes magnetic-nanoparticle-integrated hydrogels. Magnetic hydrogels (MHGs) show magneto-responsiveness, which is observed when they are placed in a magnetic field (static or oscillating). Because of their tunable porosity and internal morphology they can be used in several biomedical applications, especially diffusion-related smart devices. External stimuli may influence physical and chemical changes in these hydrogels, particularly in terms of volume and shape morphing. One of the most significant external stimuli for hydrogels is a magnetic field. This review embraces a brief overview of the fabrication of MHGs and two of their usages in the biomedical area: drug delivery and hyperthermia-based anti-cancer activity. As for the saturation magnetization imposed on composite MHGs, they are easily heated in the presence of an alternating magnetic field and the temperature increment is dependent on the magnetic nanoparticle concentration and exposure time. Herein, we also discuss the mode of different therapies based on non-contact hyperthermia heating.
Effects of Coupling Agent and Thermoplastic on the Interfacial Bond Strength and the Mechanical Properties of Oriented Wood Strand–Thermoplastic Composites
Authors: Shen Ziling , Ye Zhi , Li Kailin , Qi Chusheng
Published: December 2021

Wood–plastic composites (WPC) with good mechanical and physical properties are desirable products for manufacturers and customers, and interfacial bond strength is one of the most critical factors affecting WPC performance. To verify that a higher interfacial bond strength between wood and thermoplastics improves WPC performance, wood veneer–thermoplastic composites (VPC) and oriented strand–thermoplastic composites (OSPC) were fabricated using hot pressing. The effects of the coupling agent (KH550 or MDI) and the thermoplastic (LDPE, HDPE, PP, or PVC) on the interfacial bond strength of VPC, and the mechanical and physical properties of OSPC, were investigated. The results showed that coupling agents KH550 and MDI improved the interfacial bond strength between wood and thermoplastics under dry conditions. MDI was better than KH550 at improving the interfacial bond strength and the mechanical properties of OSPC. Better interfacial bonding between plastic and wood improved the OSPC performance. The OSPC fabricated using PVC film as the thermoplastic and MDI as the coupling agent displayed the highest mechanical properties, with a modulus of rupture of 91.9 MPa, a modulus of elasticity of 10.9 GPa, and a thickness swelling of 2.4%. PVC and MDI are recommended to fabricate WPCs with desirable performance for general applications.
The Potential Role of Nanoparticles as an Anticancer Therapy in the Treatment of Rectal Cancer
Authors: Abbas Mohamed , Alqahtani Mohammed S.
Published: December 2021

Nanotechnology is a rapidly developing science and is applied in a variety of diagnostic and treatment technologies. Colorectal cancer is one of the deadliest human diseases, and hence, wide research is underway regarding its preventative measures. This review demonstrated that “nano” drug delivery systems have successfully transferred pharmaceutical drug particles at the nanoscale as compared to larger particles. Research has shown a higher rate of disease progression among patients who receive conventional drugs compared to those who were given nanoscale drugs. However, the behavior of the cellular components differs from the performance of larger cellular components of the same type; these differences are due to the physical interactions between the nanoparticles (NPs). The review aimed to discuss several recent research studies focused on delivering NPs for the treatment of colorectal cancer (CRC). The reviewed experiments have primarily compared the use of NPs alone or with the addition of an anticancer drug or nanocarriers. These three research methods may help solve past problems and propose new future approaches for colorectal cancer by utilizing the available nanotechnologies. Furthermore, the review illustrated the underlying idea behind NP carriers and stem cell delivery that can be used to create a rapid delivery system for stem cells.
Disinfection By-Products (DBPs) in Seawaters, Sediments and Biota near a Marine Terminal for Regasifying Liquefied Natural Gas (LNG) in the Northern Adriatic Sea (Italy)
Authors: Cacciatore Federica , Amici Marina , Romanelli Giulia , Bernarello Valentina , Franceschini Gianluca , Gabellini Massimo , Virno Lamberti Claudia
Published: December 2021

In 2009, the first Italian offshore LNG terminal, located approximately 12 km from the coast of Italy in the Northern Adriatic Sea, started its operation phase. Even if the active chlorine concentration in the discharged seawater is within limits set by Italian regulations (0.2 mg/L), to verify the environmental impact of disinfection by-products (DBPs) on the ecosystem, a specific monitoring program was scheduled from 2010 to 2015. The present study is the first displaying results of DBPs in marine waters of the Adriatic Sea. During the first two years of monitoring activities, DBPs were slightly above limit of quantifications (LOQs) in all investigated matrices and limited to the nearest area around the terminal. In these surveys, bromoform was the most frequently detected compound in seawaters, while haloacetic acid presence, as well as transplanted mussels and fish fauna, mostly characterized sediments. In the following surveys, levels were mostly negligible in all matrices investigated, with values mostly below the specific LOQs of the different compounds.
Estimation of Shutdown Schedule to Remove Fouling Layers of Heat Exchangers Using Risk-Based Inspection (RBI)
Authors: Elwerfalli Abdelnaser , Alsadaie Salih , Mujtaba Iqbal M.
Published: December 2021

Oil and Gas plants consist of a set of heat exchangers, which are used in recovering the waste heat from product streams to preheat the oil. The heat transfer coefficient of exchangers declines considerably during the operation period due to fouling. Fouling in heat exchangers is a complex phenomenon due to the acceleration of many layers of chemical substances across tubes of heat exchangers resulting from chemical reactions and surface roughness. In this paper, the fouling process was determined as a critical failure in the heat exchanger. Failure is an accelerated fouling layer across the heat exchanger tubes, which can be the reason for the clogging of tubes. Hence, a risk assessment was conducted using the Risk-Based Inspection (RBI) approach to estimate the probability of fouling in heat exchangers. The results showed that the RBI approach can be used successfully to predict the suitable time to shut down the plant and conduct the fouling cleaning process.
Integration of Wind Energy and Desalination Systems: A Review Study
Authors: Greco Francesca , Heijman Sebastiaan , Jarquin-Laguna Antonio
Published: December 2021

Desalination is a well-established technology used all over the world to mitigate freshwater scarcity. Wind-powered reverse osmosis plants are one of the most promising alternatives for renewable energy desalination, particularly for coastal areas and islands. Wind energy can satisfy the high energy consumption of desalination while reducing costs and CO2 emissions. However, the mismatch between the intermittent availability of the wind resource and the desalination’s power demand makes the integration between the two technologies critical. This paper presents a review of wind-powered desalination systems, focusing on the existing topologies and technological advances. An overview of the advantages and disadvantages are analysed based on the theoretical and experimental cases available in the scientific literature. The goal of this work is to show the current status of wind-powered desalination and to present the technical challenges that need to be overcome in order to ensure a sustainable freshwater source.
Towards Continuous Primary Manufacturing Processes—Particle Design through Combined Crystallization and Particle Isolation
Authors: Steenweg Claas , Kufner Anne Cathrine , Habicht Jonas , Wohlgemuth Kerstin
Published: December 2021

Integrated continuous manufacturing processes of active pharmaceutical ingredients (API) provide key benefits concerning product quality control, scale-up capability, and a reduced time-to-market. Thereby, the crystallization step, which is used in approximately 90% of API productions, mainly defines the final API properties. This study focuses on the design and operation of an integrated small-scale process combining a continuous slug flow crystallizer (SFC) with continuous particle isolation using the modular continuous vacuum screw filter (CVSF). By selective adjustment of supersaturation and undersaturation, the otherwise usual blocking could be successfully avoided in both apparatuses. It was shown that, during crystallization in an SFC, a significant crystal growth of particles (Δd50,3≈ 220 µm) is achieved, and that, during product isolation in the CVSF, the overall particle size distribution (PSD) is maintained. The residual moistures for the integrated process ranged around 2% during all experiments performed, ensuring free-flowing particles at the CVSF outlet. In summary, the integrated setup offers unique features, such as its enhanced product quality control and fast start-up behavior, providing a promising concept for integrated continuous primary manufacturing processes of APIs.
A Study on Welding Deformation in Fiber Laser Welding of 9% Nickel Steel through Finite Element Analysis Part I: Implementation of Welding Heat Source Model
Authors: Pyo Changmin , Kim Jaewoong , Kim Du-Song
Published: December 2021

Due to various environmental regulations, the demand for natural gas, i.e., a clean energy, is expected to increase continuously. In terms of efficient storage and transportation of natural gas, liquefied natural gas has an advantageous volume of 1/600 compared to natural gas, but the materials that can be used at a cryogenic temperature of −163 °C are limited. A 9% nickel steel is a material recommended by IMO through IGC. It has excellent mechanical properties compared to other cryogenic materials, but its use has been limited due to its disadvantages in arc welding. Therefore, the main topic of this study is the automatic welding of 9% nickel steel using fiber laser and its purpose is to predict the welding deformation during fiber laser welding. First, an investigation was conducted to find the fiber laser welding heat source. A model that can cover all the models in prior studies such as curve, exponential, conical, conical-conical combination, and conical-cylinder combination models was proposed and the heat source model was constructed in a multi-layer format. Heat transfer analysis was performed using the ratio of a heat source radius and heat energy of each layer as a variable and the pass or failure of a heat source was determined by comparing the analysis results to the experimental results. By changing the variables in conjunction with the optimization algorithm, the main parameters of a passed heat source model were verified in a short period of time. In addition, the tendency of parameters according to the welding speed was checked.
Evaluation of Energy Performance and Thermal Comfort Considering the Heat Storage Capacity and Thermal Conductivity of Biocomposite Phase Change Materials
Authors: Jeong Su-Gwang , Lee Taemin , Lee Jeonghun
Published: December 2021

The application of phase change materials (PCMs) has been verified as an effective strategy for improving energy efficiency and reducing greenhouse gas emissions. Biocomposite PCMs (Bc-PCM) exhibit large latent heat, chemical stability, and a wide temperature range. In this study, thermal conductivity improved Bc-PCM (TBc-PCM) was made via vacuum impregnation with graphene nanoplatelets (GNPs). Chemical stability analysis and thermal performance analyses of the Bc-PCM and TBc-PCM were carried out as well as building energy simulations and thermal comfort analyses. Our results show Bc-PCM showed a higher heat storage capacity and enthalpy value compared to TBc-PCM. TBc-PCM exhibited a 378% increase in thermal conductivity compared to Bc-PCM. Building energy simulation results revealed that annual heating and cooling energy consumption decreased as the thickness of the PCM layer increased. In addition, the Bc-PCM with a larger PCM capacity was more effective in reducing energy consumption during the heating period. On the other hand, the cooling energy reduction effect was greater when TBc-PCM with high thermal conductivity was applied because of the high heat transfer during the cooling period. Thermal comfort evaluation revealed it was more comfortable when PCM was applied.
Death Cults and Dystopian Scenarios: Neo-Nazi Religion and Literature in the USA Today
Authors: Boucher Geoff M.
Published: December 2021

In this article, I investigate the literary representation of the religious convictions and political strategy of neo-Nazi ideologues who are influential in rightwing authoritarian movements in the USA today. The reason that I do this is because in contemporary fascism, the novel has replaced the political manifesto, the military manual and proselytizing testimony, since fiction can evade censorship and avoid prosecution. I read William Luther Pierce’s Turner Diaries and Hunter together with his text on speculative metaphysics and religious belief, Cosmotheism. Then, I turn to Harold Covington’s Northwestern Quintet with The Brigade, reading this with Christian Identity and his own conception of Nazi religious tolerance. Finally, I look at OT Gunnarsson’s Hear the Cradle Song, reading this together with discussions of racism in Californian Odinism. I propose that what this literature shows is that the doctrinal differences between the three main strands of neo-Nazi religion—Cosmotheism, Christian Identity and Odinism—are less significant than their common ideological functions. These are twofold: (1) the sacralization of violence and (2) the sanctification of elites. The dystopian fictions of fascist literature present civil war scenarios whose white nationalist and genocidal outcome is the result of what are, strictly speaking, supremacist death cults.
The Criteria of “Authentically” Catholic Theology: Reading Theology Today a Decade Later
Authors: Regan Ethna
Published: December 2021

In light of the fecundity and diversity of Catholic theology since Vatican II, a 2012 report of the International Theological Commission (ITC) identified perspectives, principles, and criteria—distinctive family traits—of Catholic theology, what Pope Benedict XVI called its “genetic code”: primacy of the Word of God; the faith of the Church as its source, context, and norm; the science of faith; drawing constantly on the canonical witness of Scripture; fidelity to the Apostolic Tradition; attention to the sensus fidelium; responsible adherence to the ecclesiastical magisterium; practiced in collaboration with the whole company of theologians; in dialogue with the world; giving a scientifically and rationally argued presentation of the Christian faith; integration of plurality in the intellectus fidei; and sapiential. This article marks the 10th anniversary of the ITC report by offering a critical commentary on the criteria, examining the possibilities, limitations, and tensions inherent in each, and the ongoing relevance of these criteria for contemporary Catholic theology. It argues that although the aim of the ITC report is not to promote uniformity but to avoid fragmentation, and its framework is an ecclesiology of communion, when the interpretative possibilities of theology are discussed, the report tends to retreat from these possibilities and adopt a restrictive emphasis on conformity. The article then examines what Pope Francis (2013–) says about the characteristics of Catholic theology and the role of theologians in his major documents and his addresses to faculties of theology. It argues that Francis makes a distinctive contribution to consideration of what is “authentically” Catholic theology, and may offer a less restrictive understanding of such theology for the diverse academic, cultural, and ecclesial contexts in which Catholic theologians find themselves.
Latinx Emerging Adults’ Religious Identity, Ethnic Identity, and Psychological Well-Being
Authors: Schiro Isabella Nicole , Barry Carolyn McNamara , Coiro Mary Jo , Quickel Emalee J. W.
Published: December 2021

The current study examined associations among religious and ethnic identity exploration and commitment, and psychological well-being (PWB) among 683 Latinx emerging adults. A subset of data collected in the Multi-Site University Study of Identity and Culture was analyzed, focusing on three measures: (a) Multigroup Ethnic Identity Measure (MEIM), (b) Religious Identity Measure (adapted from MEIM), and (c) Scales of Psychological Well-Being–Short Form. Correlations indicated that PWB was positively related to religious and ethnic identity commitment, not exploration. Regression analyses indicated that commitment to religious or ethnic identity were positively associated with PWB, while exploration of religious or ethnic identity were not associated with PWB. In addition, religious identity exploration moderated the relation between ethnic identity exploration and commitment and PWB. These findings have implications for efforts to support the development of ethnic and religious identity among Latinx emerging adults.
Synergy of Sentinel-1 and Sentinel-2 Imagery for Early Seasonal Agricultural Crop Mapping
Authors: Valero Silvia , Arnaud Ludovic , Planells Milena , Ceschia Eric
Published: December 2021

The exploitation of the unprecedented capacity of Sentinel-1 (S1) and Sentinel-2 (S2) data offers new opportunities for crop mapping. In the framework of the SenSAgri project, this work studies the synergy of very high-resolution Sentinel time series to produce accurate early seasonal binary cropland mask and crop type map products. A crop classification processing chain is proposed to address the following: (1) high dimensionality challenges arising from the explosive growth in available satellite observations and (2) the scarcity of training data. The two-fold methodology is based on an S1-S2 classification system combining the so-called soft output predictions of two individually trained classifiers. The performances of the SenSAgri processing chain were assessed over three European test sites characterized by different agricultural systems. A large number of highly diverse and independent data sets were used for validation experiments. The agreement between independent classification algorithms of the Sentinel data was confirmed through different experiments. The presented results assess the interest of decision-level fusion strategies, such as the product of experts. Accurate crop map products were obtained over different countries in the early season with limited training data. The results highlight the benefit of fusion for early crop mapping and the interest of detecting cropland areas before the identification of crop types.
Performance Analysis of Ocean Eddy Detection and Identification by L-Band Compact Polarimetric Synthetic Aperture Radar
Authors: Shu Sijing , Yang Ji , Yang Chuanxun , Hu Hongda , Jing Wenlong , Hu Yiqiang , Li Yong
Published: December 2021

The automatic detection and analysis of ocean eddies has become a popular research topic in physical oceanography during the last few decades. Compact polarimetric synthetic aperture radar (CP SAR), an emerging polarimetric SAR system, can simultaneously acquire richer polarization information of the target and achieve large bandwidth observations. It has inherent advantages in ocean observation and is bound to become an ideal data source for ocean eddy observation and research. In this study, we simulated the CP data with L-band ALOS PALSAR fully polarimetric data. We assessed the detection and classification potential of ocean eddies from CP SAR by analyzing 50 CP features for 2 types of ocean eddies (“black”and “white”) based on the Euclidean distance and further carried out eddy detection and eddy information extraction experiments. The results showed that among the 50 CP features, the dihedral component power (Pd), shannon entropy (SEI), double bounce (Dbl), Stokes parameters (g0 and g3), eigenvalue (l1), lambda, RVoG parameter (ms), shannon entropy (SE), surface scattering component (Ps), and σHH all performed better for detecting “white” eddies. Moreover, the H-A combination parameter (1mHA), entropy, shannon entropy (SEP, SEI, and SE), probability (p2), polarization degree (m), anisotropy, probability (p1), double bounce (Dbl), H-A combination parameter (H1mA), circular polarization ratio (CPR), and σVV were better CP features for detecting “black” eddies.
Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers
Authors: Paugam Ronan , Wooster Martin J. , Mell William E. , Rochoux Mélanie C. , Filippi Jean-Baptiste , Rücker Gernot , Frauenberger Olaf , Lorenz Eckehard , Schroeder Wilfrid , Main Bruce , Govender Navashni
Published: December 2021

To pursue the development and validation of coupled fire-atmosphere models, the wildland fire modeling community needs validation data sets with scenarios where fire-induced winds influence fire front behavior, and with high temporal and spatial resolution. Helicopter-borne infrared thermal cameras have the potential to monitor landscape-scale wildland fires at a high resolution during experimental burns. To extract valuable information from those observations, three-step image processing is required: (a) Orthorectification to warp raw images on a fixed coordinate system grid, (b) segmentation to delineate the fire front location out of the orthorectified images, and (c) computation of fire behavior metrics such as the rate of spread from the time-evolving fire front location. This work is dedicated to the first orthorectification step, and presents a series of algorithms that are designed to process handheld helicopter-borne thermal images collected during savannah experimental burns. The novelty in the approach lies on its recursive design, which does not require the presence of fixed ground control points, hence relaxing the constraint on field of view coverage and helping the acquisition of high-frequency observations. For four burns ranging from four to eight hectares, long-wave and mid infra red images were collected at 1 and 3 Hz, respectively, and orthorectified at a high spatial resolution (<1 m) with an absolute accuracy estimated to be lower than 4 m. Subsequent computation of fire radiative power is discussed with comparison to concurrent space-borne measurements.
Estimated Biomass Loss Caused by the Vaia Windthrow in Northern Italy: Evaluation of Active and Passive Remote Sensing Options
Authors: Vaglio Laurin Gaia , Puletti Nicola , Tattoni Clara , Ferrara Carlotta , Pirotti Francesco
Published: December 2021

Windstorms are a major disturbance factor for European forests. The 2018 Vaia storm, felled large volumes of timber in Italy causing serious ecological and financial losses. Remote sensing is fundamental for primary assessment of damages and post-emergency phase. An explicit estimation of the timber loss caused by Vaia using satellite remote sensing was not yet undertaken. In this investigation, three different estimates of timber loss were compared in two study sites in the Alpine area: pre-existing local growing stock volume maps based on lidar data, a recent national-level forest volume map, and an novel estimation of AGB values based on active and passive remote sensing. The compared datasets resemble the type of information that a forest manager might potentially find or produce. The results show a significant disagreement in the different biomass estimates, related to the methods used to produce them, the study areas characteristics, and the size of the damaged areas. These sources of uncertainty highlight the difficulty of estimating timber loss, unless a unified national or regional European strategy to improve preparedness to forest hazards is defined. Considering the frequent impacts on forest resources that occurred in the last years in the European Union, remote sensing-based surveys targeting forests is urgent, particularly for the many European countries that still lack reliable forest stocks data.
Automatic Extraction of Indoor Structural Information from Point Clouds
Authors: Cheng Dongyang , Zhang Junchao , Zhao Dangjun , Chen Jianlai , Tian Di
Published: December 2021

We propose an innovative method with which to extract building interior structure information automatically, including ceiling, floor, and wall. Our approach outperforms previous methods in the following respects. First, we propose an approach based on principal component analysis (PCA) to find the ground plane, which is regarded as the new Cartesian plane. Second, to reduce the complexity of data processing, the data are projected into two dimensions and transformed into a binary image via the operation of an improved radius outlier removal (ROR) filter. Third, a traditional thinning algorithm is adopted to extract the image skeleton. Then, we propose a method for calculating slope through the nearest neighbor point. Moreover, the line is represented with the slopes to obtain information pertaining to the interior planes. Finally, the outline of the line is restored to a three-dimensional structure. The proposed method is evaluated in multiple scenarios, and the results show that the method is accurate (the maximum error of 0.03 m was in three scenarios) in indoor environments.
Managing Flood Hazard in a Complex Cross-Border Region Using Sentinel-1 SAR and Sentinel-2 Optical Data: A Case Study from Prut River Basin (NE Romania)
Authors: Cîmpianu Cătălin I. , Mihu-Pintilie Alin , Stoleriu Cristian C. , Urzică Andrei , Huţanu Elena
Published: December 2021

In this study, an alternative solution for flood risk management in complex cross-border regions is presented. In these cases, due to different flood risk management legislative approaches, there is a lack of joint cooperation between the involved countries. As a main consequence, LiDAR-derived digital elevation models and accurate flood hazard maps obtained by means of hydrological and hydraulic modeling are missing or are incomplete. This is also the case for the Prut River, which acts as a natural boundary between European Union (EU) member Romania and non-EU countries Ukraine and Republic of Moldova. Here, flood hazard maps were developed under the European Floods Directive (2007/60/EC) only for the Romanian territory and only for the 1% exceeding probability (respectively floods that can occur once every 100 years). For this reason, in order to improve the flood hazard management in the area and consider all cross-border territories, a fully remote sensing approach was considered. Using open-source SAR Sentinel-1 and Sentinel-2 data characterized by an improved temporal resolution, we managed to capture the maximum spatial extent of a flood event that took place in the aforementioned river sector (middle Prut River course) during the 24 and 27 June 2020. Moreover, by means of flood frequency analysis, the development of a transboundary flood hazard map with an assigned probability, specific to the maximum flow rate recorded during the event, was realized.
GNSS Imaging of Strain Rate Changes and Vertical Crustal Motions over the Tibetan Plateau
Authors: Xiang Yunfei , Wang Hao , Chen Yuanyuan , Xing Yin
Published: December 2021

In this paper, we perform a comprehensive analysis of contemporary three-dimensional crustal deformations over the Tibetan Plateau. Considering that the coverage of continuous GNSS sites in the Tibetan Plateau is sparse, a newly designed method that mainly contains Spatial Structure Function (SSF) construction and Median Spatial Filtering (MSF) is adopted to conduct GNSS imaging of point-wise velocities, which can well reveal the spatial pattern of vertical crustal motions. The result illustrates that the Himalayan belt bordering Nepal appears significant uplift at the rates of ~3.5 mm/yr, while the low-altitude regions of Nepal and Bhutan near the Tibetan Plateau are undergoing subsidence. The result suggests that the subduction of the Indian plate is the driving force of the uplift and subsidence in the Himalayan belt and its adjacent regions. Similarly, the thrusting of the Tarim Basin is the main factor of the slight uplift and subsidence in the Tianshan Mountains and Tarim Basin, respectively. In addition, we estimate the strain rate changes over the Tibetan Plateau using high-resolution GNSS horizontal velocities. The result indicates that the Himalayan belt and southeastern Tibetan Plateau have accumulated a large amount of strain rate due to the Indian-Eurasian plate collision and blockage of the South China block, respectively.
Characteristics of Spatiotemporal Changes in the Occurrence of Forest Fires
Authors: Kim Taehee , Hwang Suyeon , Choi Jinmu
Published: December 2021

The purpose of this study is to understand the characteristics of the spatial distribution of forest fire occurrences with the local indicators of temporal burstiness in Korea. Forest fire damage data were produced in the form of areas by combining the forest fire damage ledger information with VIIRS-based forest fire occurrence data. Then, detrended fluctuation analysis and the local indicator of temporal burstiness were applied. In the results, the forest fire occurrence follows a self-organized criticality mechanism, and the temporal irregularities of fire occurrences exist. When the forest fire occurrence time series in Gyeonggi-do Province, which had the highest value of the local indicator of temporal burstiness, was checked, it was found that the frequency of forest fires was increasing at intervals of about 10 years. In addition, when the frequencies of forest fires and the spatial distribution of the local indicators of forest fire occurrences were compared, it was found that there were spatial differences in the occurrence of forest fires. This study is meaningful in that it analyzed the time series characteristics of the distribution of forest fires in Korea to understand that forest fire occurrences have long-term temporal correlations and identified areas where the temporal irregularities of forest fire occurrences are remarkable with the local indicators of temporal burstiness.
Revise-Net: Exploiting Reverse Attention Mechanism for Salient Object Detection
Authors: Hussain Rukhshanda , Karbhari Yash , Ijaz Muhammad Fazal , Woźniak Marcin , Singh Pawan Kumar , Sarkar Ram
Published: December 2021

Recently, deep learning-based methods, especially utilizing fully convolutional neural networks, have shown extraordinary performance in salient object detection. Despite its success, the clean boundary detection of the saliency objects is still a challenging task. Most of the contemporary methods focus on exclusive edge detection modules in order to avoid noisy boundaries. In this work, we propose leveraging on the extraction of finer semantic features from multiple encoding layers and attentively re-utilize it in the generation of the final segmentation result. The proposed Revise-Net model is divided into three parts: (a) the prediction module, (b) a residual enhancement module, and (c) reverse attention modules. Firstly, we generate the coarse saliency map through the prediction modules, which are fine-tuned in the enhancement module. Finally, multiple reverse attention modules at varying scales are cascaded between the two networks to guide the prediction module by employing the intermediate segmentation maps generated at each downsampling level of the REM. Our method efficiently classifies the boundary pixels using a combination of binary cross-entropy, similarity index, and intersection over union losses at the pixel, patch, and map levels, thereby effectively segmenting the saliency objects in an image. In comparison with several state-of-the-art frameworks, our proposed Revise-Net model outperforms them with a significant margin on three publicly available datasets, DUTS-TE, ECSSD, and HKU-IS, both on regional and boundary estimation measures.
A Novel 4D Track-before-Detect Approach for Weak Targets Detection in Clutter Regions
Authors: Yan Bo , Zhang Hua , Xu Luping , Chen Yu , Lu Hongmin
Published: December 2021

A 4D TBD approach is developed here for closely weak extended target tracking and overcoming heterogeneous clutter background and various clutter regions. The 4D measurements in this work are the points containing three positional information in spatial space and corresponding timestamp. The proposed method is mainly designed to address two issues. The first one is the dilemma between the weak target detection and difficult computation originating from the high dimensions of measurement. The second issue is the suppression of inhomogeneous background clutter and various clutter regions. The extension experiment using synthetic data showcases that no false alarm track would be built in the clutter regions, and the detection rate of close targets exceeds 94%. The experiments using real 3D radar also prove that the method works well in tracking closely maneuvering extended targets even if a clutter region exists.
Analysis of Hypersonic Platform-Borne SAR Imaging: A Physical Perspective
Authors: Song Lihao , Bai Bowen , Li Xiaoping , Niu Gezhao , Liu Yanming , Zhao Liang , Zhou Hui
Published: December 2021

The usage of a hypersonic platform for remote sensing application has promising prospects, especially for hypersonic platform-borne synthetic aperture radar (SAR) imaging. However, the high-speed of hypersonic platform will lead to extreme friction between the platform and air, which will cause the ionization of air. The ionized gas forms the plasma sheath wrapped around the hypersonic platform. The plasma sheath will severely affect the propagation of SAR signal and further affect the SAR imaging. Therefore, hypersonic platform-borne SAR imaging should be studied from a physical perspective. In this paper, hypersonic platform-borne SAR imaging under plasma sheath is analyzed. The SAR signal propagation in plasma sheath is computed using scatter matrix method. The proposed SAR signal model is verified by using a ground experiment system. Moreover, the effect of attenuation caused by plasma sheath on SAR imaging is studied under different SAR parameters and plasma sheath. The result shows that attenuation caused by plasma sheath will degrade the SAR imaging quality and even cause the point and area targets to be submerged into the noise. The real SAR images under plasma sheath also illustrate this phenomenon. Furthermore, by studying imaging results under different SAR and plasma parameters, it can be concluded that the severe degradation of SAR imaging quality appears at condition of high plasma sheath electron density and low SAR carrier frequency. The work in this paper will be beneficial for the study of hypersonic platform-borne SAR imaging and design of hypersonic SAR imaging systems in the future.
A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs
Authors: Galarza Christian E. , Palma Jonathan M. , Morais Cecilia F. , Utria Jaime , Carvalho Leonardo P. , Bustos Daniel , Oliveira Ricardo C. L. F.
Published: December 2021

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.
Real-Time Semantic Segmentation with Dual Encoder and Self-Attention Mechanism for Autonomous Driving
Authors: Chang Yu-Bang , Tsai Chieh , Lin Chang-Hong , Chen Poki
Published: December 2021

As the techniques of autonomous driving become increasingly valued and universal, real-time semantic segmentation has become very popular and challenging in the field of deep learning and computer vision in recent years. However, in order to apply the deep learning model to edge devices accompanying sensors on vehicles, we need to design a structure that has the best trade-off between accuracy and inference time. In previous works, several methods sacrificed accuracy to obtain a faster inference time, while others aimed to find the best accuracy under the condition of real time. Nevertheless, the accuracies of previous real-time semantic segmentation methods still have a large gap compared to general semantic segmentation methods. As a result, we propose a network architecture based on a dual encoder and a self-attention mechanism. Compared with preceding works, we achieved a 78.6% mIoU with a speed of 39.4 FPS with a 1024 × 2048 resolution on a Cityscapes test submission.
Synthetic Generation of Passive Infrared Motion Sensor Data Using a Game Engine
Authors: Stefansson Petter , Karlsson Fredrik , Persson Magnus , Olsson Carl Magnus
Published: December 2021

Quantifying the number of occupants in an indoor space is useful for a wide variety of applications. Attempts have been made at solving the task using passive infrared (PIR) motion sensor data together with supervised learning methods. Collecting a large labeled dataset containing both PIR motion sensor data and ground truth people count is however time-consuming, often requiring one hour of observation for each hour of data gathered. In this paper, a method is proposed for generating such data synthetically. A simulator is developed in the Unity game engine capable of producing synthetic PIR motion sensor data by detecting simulated occupants. The accuracy of the simulator is tested by replicating a real-world meeting room inside the simulator and conducting an experiment where a set of choreographed movements are performed in the simulated environment as well as the real room. In 34 out of 50 tested situations, the output from the simulated PIR sensors is comparable to the output from the real-world PIR sensors. The developed simulator is also used to study how a PIR sensor’s output changes depending on where in a room a motion is carried out. Through this, the relationship between sensor output and spatial position of a motion is discovered to be highly non-linear, which highlights some of the difficulties associated with mapping PIR data to occupancy count.
A Flexible Chemosensor Based on Colorimetric and Fluorescent Dual Modes for Rapid and Sensitive Detection of Hypochlorite Anion
Authors: Wu Qin , Tao Tao , Zhao Yunxia , Huang Wei
Published: December 2021

A flexible chemosensor has been developed based on colorimetric and fluorescent dual modes using tetraphenylethylene-centered tetraaniline (TPE4A) for rapid and sensitive detection of hypochlorite anion. The fluorescent probe TPE4A exhibits a unique aggregation-induced emission (AIE) character which is proved by a blue shift of the fluorescent peak from 544 to 474 nm with the water equivalents increasing. With the addition of hypochlorite in solution, the absorbance of the probe changes and the responding fluorescence color can be observed to change from light green to purple. The detection limit of hypochlorite is 1.80 × 10−4 M in solution, and the visual detection limit is 1.27 µg/cm2 with the naked eye for the flexible paper-based chemosensor. The proposed flexible chemosensors show a good selectivity and sensitivity which has great potential for effective detection of hypochlorite anions without any spectroscopic instrumentation.
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative Study
Authors: Naushad Raoof , Kaur Tarunpreet , Ghaderpour Ebrahim
Published: December 2021

Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide significant value in land use and land cover (LULC) classification. The new advances in remote sensing and deep learning technologies have facilitated the extraction of spatiotemporal information for LULC classification. Moreover, diverse disciplines of science, including remote sensing, have utilised tremendous improvements in image classification involving convolutional neural networks (CNNs) with transfer learning. In this study, instead of training CNNs from scratch, the transfer learning was applied to fine-tune pre-trained networks Visual Geometry Group (VGG16) and Wide Residual Networks (WRNs), by replacing the final layers with additional layers, for LULC classification using the red–green–blue version of the EuroSAT dataset. Moreover, the performance and computational time are compared and optimised with techniques such as early stopping, gradient clipping, adaptive learning rates, and data augmentation. The proposed approaches have addressed the limited-data problem, and very good accuracies were achieved. The results show that the proposed method based on WRNs outperformed the previous best results in terms of computational efficiency and accuracy, by achieving 99.17%.
Graphene-Based Sensor for Detection of Bacterial Pathogens
Authors: Pandit Santosh , Li Mengyue , Chen Yanyan , Rahimi Shadi , Mokkapati Vrss , Merlo Alessandra , Yurgens August , Mijakovic Ivan
Published: December 2021

Microbial colonization to biomedical surfaces and biofilm formation is one of the key challenges in the medical field. Recalcitrant biofilms on such surfaces cause serious infections which are difficult to treat using antimicrobial agents, due to their complex structure. Early detection of microbial colonization and monitoring of biofilm growth could turn the tide by providing timely guidance for treatment or replacement of biomedical devices. Hence, there is a need for sensors, which could generate rapid signals upon bacterial colonization. In this study, we developed a simple prototype sensor based on pristine, non-functionalized graphene. The detection principle is a change in electrical resistance of graphene upon exposure to bacterial cells. Without functionalization with specific receptors, such sensors cannot be expected to be selective to certain bacteria. However, we demonstrated that two different bacterial species can be detected and differentiated by our sensor due to their different growth dynamics, adherence pattern, density of adhered bacteria and microcolonies formation. These distinct behaviors of tested bacteria depicted distinguishable pattern of resistance change, resistance versus gate voltage plot and hysteresis effect. This sensor is simple to fabricate, can easily be miniaturized, and can be effective in cases when precise identification of species is not needed.
Factors Influencing Nursing Students’ Immersive Virtual Reality Media Technology-Based Learning
Authors: Kim Young-Ju , Ahn Sung-Yun
Published: December 2021

Background/objectives: This study aims to identify the effects of cognitive and emotional variables related to immersive virtual reality media technology on learning for nursing students. Methods/Statistical analysis: The subjects of this study were 121 nursing students from a university in area D. After experiential learning with virtual reality from 6–8 June 2019, data was collected through questionnaires. For virtual reality learning, VIVE’s hTC VIVE ECO CE model was used. The collected data was analyzed using the IBM SPSS 26.0 program. Multiple Regression Analysis was used to analyze the factors influencing the subject’s virtual reality learning effects. Findings: The learning effects of the virtual reality medium had a statistically significant positive correlation with the virtual reality technology recognition, sensory immersion, realism, learning satisfaction, learning necessity, and continuous use intention (p < 0.001) scores. In personality traits, only Openness, Extraversion (p < 0.01), and Conscientiousness (p < 0.05) had a statistically significant positive correlation. As a result of regression analysis, the explanatory power of the learning effect of the virtual reality medium was 63.9% (F = 53.61, p < 0.001), with learning satisfaction, sensory immersion, continuous use intention, and Extraversion being significant influencing factors (p < 0.05). Improvements/Applications: This study is meaningful in the sense that it provided strategic implications for the teaching and learning method of virtual reality technology-based learning by considering the insights necessary to develop a learning program using virtual reality technology, according to the characteristics of virtual reality technology, and the learner’s cognitive and psychological variables.