bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Martelella soudanensis sp. nov., Isolated from a Mine Sediment
Authors: Lee Jung-Yun , Lee Dong-Hun , Kim Dong-Hun
Published: August 2021

Gram-stain-negative, strictly aerobic, non-spore-forming, non-motile, and rod-shaped bacterial strains, designated NC18T and NC20, were isolated from the sediment near-vertical borehole effluent originating 714 m below the subsurface located in the Soudan Iron Mine in Minnesota, USA. The 16S rRNA gene sequence showed that strains NC18T and NC20 grouped with members of the genus Martelella, including M. mediterranea DSM 17316T and M. limonii YC7034T. The genome sizes and G + C content of both NC18T and NC20 were 6.1 Mb and 61.8 mol%, respectively. Average nucleotide identity (ANI), the average amino acid identity (AAI), and digital DNA–DNA hybridization (dDDH) values were below the species delineation threshold. Pan-genomic analysis showed that NC18T, NC20, M. mediterranea DSM 17316T, M. endophytica YC6887T, and M. lutilitoris GH2-6T had 8470 pan-genome orthologous groups (POGs) in total. Five Martelella strains shared 2258 POG core, which were mainly associated with amino acid transport and metabolism, general function prediction only, carbohydrate transport and metabolism, translation, ribosomal structure and biogenesis, and transcription. The two novel strains had major fatty acids (>5%) including summed feature 8 (C18:1 ω7c and/or C18:1 ω6c), C19:0 cyclo ω8c, C16:0, C18:1 ω7c 11-methyl, C18:0, and summed feature 2 (C12:0 aldehyde and/or iso-C16:1 I and/or C14:0 3-OH). The sole respiratory quinone was uniquinone-10 (Q-10). On the basis of polyphasic taxonomic analyses, strains NC18T and NC20 represent novel species of the genus Martelella, for which the name Martelella soudanensis sp. nov. is proposed. The type strain is NC18T (=KTCT 82174T = NBRC 114661T).
Surrounding Rock Stability Control Technology of Roadway in Large Inclination Seam with Weak Structural Plane in Roof
Authors: Wu Peng , Chen Liang , Li Ming , Wang Lan , Wang Xufeng , Zhang Wei
Published: August 2021

The surrounding rock control technology of mining roadways in large inclination seams with a weak structural plane in the roof is one of the most challenging fields in underground roadway support. In view of the serious deformation of the surrounding rock of the transportation roadway in the 1201 working face of a mine, the deformation and failure characteristics and instability mechanism of the surrounding rock of the roadway are analysed. The self-stability mechanical model of the roof block structure of the roadway with a large inclination under the support effect is established, and the support concept of “high pre-stressed asymmetric” and the combined support method of bolts, wire mesh, and cables are proposed. The rationality of the supporting scheme is verified by numerical simulation. The results show that: compared with bolt and wire mesh support, the maximum shear displacement of the roof’s weak layer under the combined support of bolt, wire meshes, and cable before and after mining is reduced by 86.78% and 83%, respectively, and the maximum total displacement of surrounding rock surface is reduced by 49.22% and 37.1%, respectively. The field monitoring results show that the combined support scheme can effectively control the deformation of the surrounding rock.
Capillary Electrophoresis as a Monitoring Tool for Flow Composition Determination
Authors: Kaljurand Mihkel , Saar-Reismaa Piret , Vaher Merike , Gorbatsova Jelena , Mazina-Šinkar Jekaterina
Published: August 2021

Flow analysis is the science of performing quantitative analytical chemistry in flowing streams. Because of its efficiency and speed of analysis, capillary electrophoresis (CE) is a prospective method for the monitoring of a flow composition withdrawn from various processes (e.g., occurring in bioreactors, fermentations, enzymatic assays, and microdialysis samples). However, interfacing CE to a various flow of interest requires further study. In this paper, several ingenious approaches on interfacing flow from various chemical or bioprocesses to a capillary electrophoresis instrument are reviewed. Most of these interfaces can be described as computer-controlled autosamplers. Even though most of the described interfaces waste too many samples, many interesting and important applications of the devices are reported. However, the lack of commercially available devices prevents the wide application of CE for flow analysis. On the contrary, this fact opens up a potential avenue for future research in the field of flow sampling by CE.
Theoretical Encapsulation of Fluorouracil (5-FU) Anti-Cancer Chemotherapy Drug into Carbon Nanotubes (CNT) and Boron Nitride Nanotubes (BNNT)
Authors: Zarghami Dehaghani Maryam , Yousefi Farrokh , Sajadi S. Mohammad , Tajammal Munir Muhammad , Abida Otman , Habibzadeh Sajjad , Mashhadzadeh Amin Hamed , Rabiee Navid , Mostafavi Ebrahim , Saeb Mohammad Reza
Published: August 2021

Introduction: Chemotherapy with anti-cancer drugs is considered the most common approach for killing cancer cells in the human body. However, some barriers such as toxicity and side effects would limit its usage. In this regard, nano-based drug delivery systems have emerged as cost-effective and efficient for sustained and targeted drug delivery. Nanotubes such as carbon nanotubes (CNT) and boron nitride nanotubes (BNNT) are promising nanocarriers that provide the cargo with a large inner volume for encapsulation. However, understanding the insertion process of the anti-cancer drugs into the nanotubes and demonstrating drug-nanotube interactions starts with theoretical analysis. Methods: First, interactions parameters of the atoms of 5-FU were quantified from the DREIDING force field. Second, the storage capacity of BNNT (8,8) was simulated to count the number of drugs 5-FU encapsulated inside the cavity of the nanotubes. In terms of the encapsulation process of the one drug 5-FU into nanotubes, it was clarified that the drug 5-FU was more rapidly adsorbed into the cavity of the BNNT compared with the CNT due to the higher van der Waals (vdW) interaction energy between the drug and the BNNT. Results: The obtained values of free energy confirmed that the encapsulation process of the drug inside the CNT and BNNT occurred spontaneously with the free energies of −14 and −25 kcal·mol−1, respectively. Discussion: However, the lower value of the free energy in the system containing the BNNT unraveled more stability of the encapsulated drug inside the cavity of the BNNT comparing the system having CNT. The encapsulation of Fluorouracil (5-FU) anti-cancer chemotherapy drug (commercial name: Adrucil®) into CNT (8,8) and BNNT (8,8) with the length of 20 Å in an aqueous solution was discussed herein applying molecular dynamics (MD) simulation.
Silk Fibroin-Coated Liposomes as Biomimetic Nanocarrier for Long-Term Release Delivery System in Cancer Therapy
Authors: Suyamud Chanon , Phetdee Chanita , Jaimalai Thanapak , Prangkio Panchika
Published: August 2021

Despite much progress in cancer therapy, conventional chemotherapy can cause poor biodistribution and adverse side-effects on healthy cells. Currently, various strategies are being developed for an effective chemotherapy delivery system. Silk fibroin (SF) is a natural protein used in a wide range of biomedical applications including cancer therapy due to its biocompatibility, biodegradability, and unique mechanical properties. In this study, SF-coated liposomes (SF-LPs) were prepared as a biomimetic drug carrier. Physicochemical properties of SF-LPs were characterized by Fourier-transform infrared spectroscopy (FTIR), dynamic light scattering, zeta potential measurement, and transmission electron microscopy (TEM). In vitro release of SF-LPs loaded with doxorubicin (DOX-SF-LPs) was evaluated over 21 days. Anticancer activity of DOX-SF-LPs was determined against MCF-7 and MDA-MB231 cells using the MTT assay. SF-LPs containing 1% SF exhibited favorable characteristics as a drug carrier. SF coating modified the kinetics of drug release and reduced the cytotoxic effect against L929 fibroblasts as compared to the uncoated liposomes containing cationic lipid. DOX-SF-LPs showed anticancer activity against breast cancer cells after 48 h or 72 h at 20 μM of DOX. This approach provides a potential platform of long-term release that combines biocompatible SF and phospholipids for cancer therapy, achieving efficient drug delivery and reducing side-effects.
Classification of So-Called Non-Covalent Interactions Based on VSEPR Model
Authors: Grabowski Sławomir J.
Published: August 2021

The variety of interactions have been analyzed in numerous studies. They are often compared with the hydrogen bond that is crucial in numerous chemical and biological processes. One can mention such interactions as the halogen bond, pnicogen bond, and others that may be classified as σ-hole bonds. However, not only σ-holes may act as Lewis acid centers. Numerous species are characterized by the occurrence of π-holes, which also may play a role of the electron acceptor. The situation is complicated since numerous interactions, such as the pnicogen bond or the chalcogen bond, for example, may be classified as a σ-hole bond or π-hole bond; it ultimately depends on the configuration at the Lewis acid centre. The disadvantage of classifications of interactions is also connected with their names, derived from the names of groups such as halogen and tetrel bonds or from single elements such as hydrogen and carbon bonds. The chaos is aggravated by the properties of elements. For example, a hydrogen atom can act as the Lewis acid or as the Lewis base site if it is positively or negatively charged, respectively. Hence names of the corresponding interactions occur in literature, namely hydrogen bonds and hydride bonds. There are other numerous disadvantages connected with classifications and names of interactions; these are discussed in this study. Several studies show that the majority of interactions are ruled by the same mechanisms related to the electron charge shifts, and that the occurrence of numerous interactions leads to specific changes in geometries of interacting species. These changes follow the rules of the valence-shell electron-pair repulsion model (VSEPR). That is why the simple classification of interactions based on VSEPR is proposed here. This classification is still open since numerous processes and interactions not discussed in this study may be included within it.
Native Collagen II Relieves Bone Impairment through Improving Inflammation and Oxidative Stress in Ageing db/db Mice
Authors: Fan Rui , Hao Yuntao , Liu Xinran , Kang Jiawei , Hu Jiani , Mao Ruixue , Liu Rui , Zhu Na , Xu Meihong , Li Yong
Published: August 2021

Ageing-related bone impairment due to exposure to hyperglycemic environment is scarcely researched. The aim was to confirm the improvement effects of undenatured type II collagen (UC II) on bone impairment in ageing db/db mice, and the ageing model was established by normal feeding for 48-week-old. Then, the ageing db/db mice were randomly assigned to UC II intervention, the ageing model, and the chondroitin sulfate + glucosamine hydrochloride control groups. After 12 weeks of treatment, femoral microarchitecture and biomechanical parameters were observed, biomarkers including bone metabolism, inflammatory cytokines, and oxidative stress were measured, and the gastrocnemius function and expressions of interleukin (IL) 1β, receptor activator of nuclear factor (NF)-κB ligand (RANKL), and tartrate-resistant acid phosphatase (TRAP) were analyzed. The results showed that the mice in the UC II intervention group showed significantly superior bone and gastrocnemius properties than those in the ageing model group, including bone mineral density (287.65 ± 72.77 vs. 186.97 ± 32.2 mg/cm3), gastrocnemius index (0.46 ± 0.07 vs. 0.18 ± 0.01%), muscle fiber diameter (0.0415 ± 0.005 vs. 0.0330 ± 0.002 mm), and cross-sectional area (0.0011 ± 0.00007 vs. 0.00038 ± 0.00004 mm2). The UC II intervention elevated bone mineralization and formation and decreased bone resorption, inflammatory cytokines, and the oxidative stress. In addition, lower protein expression of IL-1β, RANKL, and TRAP in the UC II intervention group was observed. These findings suggested that UC II improved bones impaired by T2DM during ageing, and the likely mechanism was partly due to inhibition of inflammation and oxidative stress.
Vitamin D and Hashimoto’s Thyroiditis: Observations from CROHT Biobank
Authors: Cvek Maja , Kaličanin Dean , Barić Ana , Vuletić Marko , Gunjača Ivana , Torlak Lovrić Vesela , Škrabić Veselin , Punda Ante , Boraska Perica Vesna
Published: August 2021

The aims of this study were to evaluate: (1) associations of vitamin D with the presence/severity of Hashimoto’s thyroiditis (HT) and (2) correlations of vitamin D with thyroid-related phenotypes. Total 25(OH)D (vitamin D in the text) was measured from stored serum samples of 461 HT patients and 176 controls from a Croatian Biobank of HT patients (CROHT). (1) Vitamin D levels, and proportions of vitamin D deficiency, were compared between HT cases and controls. HT patients were additionally divided into two groups (MILD and OVERT) to take into account HT severity. (2) Correlations between vitamin D and 10 clinical phenotypes in all HT patients and two subgroups of HT patients were tested using the Spearman correlation test. Our analyses were adjusted for age, gender, BMI, smoking status and seasonality of blood sampling. (1) No significant differences in vitamin D levels, or proportions of vitamin D deficiency, were detected between HT patients of all disease stages and controls. However, a nominally significant difference in vitamin D levels between MILD and OVERT subgroups (OR = 1.038, p = 0.023) was observed. Proportions of individuals with vitamin D deficiency during winter–spring were high: all HT cases (64.69%), MILD (60.64%), OVERT (68.7%), controls (60.79%). (2) A nominally significant negative correlation between vitamin D and TSH in all HT patients (r = −0.113, p = 0.029) and a positive correlation between vitamin D and systolic blood pressure in OVERT HT patients (r = 0.205, p = 0.025) were identified. Our study indicates that there is no association between vitamin D and HT; however, there may be a subtle decrease in vitamin D levels associated with overt hypothyroidism.
An Experimental Medicine Investigation of the Effects of Subacute Pramipexole Treatment on Emotional Information Processing in Healthy Volunteers
Authors: Martens Marieke Annie Gerdine , Kaltenboeck Alexander , Halahakoon Don Chamith , Browning Michael , Cowen Philip J. , Harmer Catherine J.
Published: August 2021

Treatment with the dopamine D2/D3 receptor agonist pramipexole has demonstrated promising clinical effects in patients with depression. However, the mechanisms through which pramipexole might alleviate depressive symptoms are currently not well understood. Conventional antidepressant drugs are thought to work by biasing the processing of emotional information in favour of positive relative to negative appraisal. In this study, we used an established experimental medicine assay to explore whether pramipexole treatment might have a similar effect. Employing a double-blind, parallel-group design, 40 healthy volunteers (aged 18 to 43 years, 50% female) were randomly allocated to 12 to 15 days of treatment with either pramipexole (at a peak daily dose of 1.0 mg pramipexole salt) or placebo. After treatment was established, emotional information processing was assessed on the neural level by measuring amygdala activity in response to positive and negative facial emotional expressions, using functional magnetic resonance imaging (MRI). In addition, behavioural measures of emotional information processing were collected at baseline and on drug, using an established computerized task battery, tapping into different cognitive domains. As predicted, pramipexole-treated participants, compared to those receiving placebo, showed decreased neural activity in response to negative (fearful) vs. positive (happy) facial expressions in bilateral amygdala. Contrary to our predictions, however, pramipexole treatment had no significant antidepressant-like effect on behavioural measures of emotional processing. This study provides the first experimental evidence that subacute pramipexole treatment in healthy volunteers modifies neural responses to emotional information in a manner that resembles the effects of conventional antidepressant drugs.
Electroactive Polymers Obtained by Conventional and Non-Conventional Technologies
Authors: Kanaan Akel F. , Pinho Ana C. , Piedade Ana P.
Published: August 2021

Electroactive polymers (EAPs), materials that present size/shape alteration in response to an electrical stimulus, are currently being explored regarding advanced smart devices, namely robotics, valves, soft actuators, artificial muscles, and electromechanical sensors. They are generally prepared through conventional techniques (e.g., solvent casting and free-radical polymerization). However, non-conventional processes such as those included in additive manufacturing (AM) are emerging as a novel approach to tune and enhance the electromechanical properties of EAPs to expand the scope of areas for this class of electro-responsive material. This review aims to summarize the published work (from the last five years) in developing EAPs either by conventional or non-conventional polymer processing approaches. The technology behind each processing technique is discussed as well as the main mechanism behind the electromechanical response. The most common polymer-based materials used in the design of current EAPs are reviewed. Therefore, the main conclusions and future trends regarding EAPs obtained by conventional and non-conventional technologies are also given.
Conformation, Self-Organization and Thermoresponsibility of Polymethacrylate Molecular Brushes with Oligo(ethylene glycol)-block-oligo(propylene glycol) Side Chains
Authors: Simonova Maria , Kamorin Denis , Kazantsev Oleg , Nepomnyashaya Maria , Filippov Alexander
Published: August 2021

Polymethacrylic molecular brushes with oligo(ethylene glycol)-block-oligo(propylene glycol) side chains were investigated by static and dynamic light scattering and viscometry. The solvents used were acetonitrile, tetrahydrofuran, chloroform, and water. The grafted copolymers were molecularly dispersed and dissolved in tetrahydrofuran and acetonitrile. In these solvents, the molar masses of copolymers were determined. In thermodynamically good solvents, namely tetrahydrofuran and acetonitrile, investigated copolymers have a high intramolecular density and the shape of their molecules resembles a star-shaped macromolecule. In chloroform and water, the micelle-like aggregates were formed. Critical micelle concentrations decreased with the lengthening of the hydrophobic block. Molecular brushes demonstrated thermosensitive behavior in aqueous solutions. The phase separation temperatures reduced with an increase in the content of the oligo(propylene glycol) block.
Bioactivity and Bone Cell Formation with Poly-ε-Caprolactone/Bioceramic 3D Porous Scaffolds
Authors: Juan Po-Kai , Fan Fang-Yu , Lin Wei-Chun , Liao Pei-Bang , Huang Chiung-Fang , Shen Yung-Kang , Ruslin Muhammad , Lee Chen-Han
Published: August 2021

This study applied poly-ε-caprolactone (PCL), a biomedical ceramic powder as an additive (nano-hydroxyapatite (nHA) or β-tricalcium diphosphate (β-TCP)), and sodium chloride (NaCl) and ammonium bicarbonate ((NH4)HCO3) as porogens; these stuffs were used as scaffold materials. An improved solvent-casting/particulate-leaching method was utilized to fabricate 3D porous scaffolds. In this study we examined the physical properties (elastic modulus, porosity, and contact angle) and degradation properties (weight loss and pH value) of the 3D porous scaffolds. Both nHA and β-TCP improved the mechanical properties (elastic modulus) of the 3D porous scaffolds. The elastic modulus (0.15~1.865 GPa) of the various composite scaffolds matched that of human cancellous bone (0.1~4.5 GPa). Osteoblast-like (MG63) cells were cultured, a microculture tetrazolium test (MTT) was conducted and alkaline phosphatase (ALP) activity of the 3D porous scaffolds was determined. Experimental results indicated that both nHA and β-TCP powder improved the hydrophilic properties of the scaffolds. The degradation rate of the scaffolds was accelerated by adding nHA or β-TCP. The MTT and ALP activity tests indicated that the scaffolds with a high ratio of nHA or β-TCP had excellent properties of in vitro biocompatibility (cell attachment and proliferation).
Direct Writing Corrugated PVC Gel Artificial Muscle via Multi-Material Printing Processes
Authors: Luo Bin , Zhong Yiding , Chen Hualing , Zhu Zicai , Wang Yanjie
Published: August 2021

Electroactive PVC gel is a new artificial muscle material with good performance that can mimic the movement of biological muscle in an electric field. However, traditional manufacturing methods, such as casting, prevent the broad application of this promising material because they cannot achieve the integration of the PVC gel electrode and core layer, and at the same time, it is difficult to create complex and diverse structures. In this study, a multi-material, integrated direct writing method is proposed to fabricate corrugated PVC gel artificial muscle. Inks with suitable rheological properties were developed for printing four functional layers, including core layers, electrode layers, sacrificial layers, and insulating layers, with different characteristics. The curing conditions of the printed CNT/SMP inks under different applied conditions were also discussed. The structural parameters were optimized to improve the actuating performance of the PVC gel artificial muscle. The corrugated PVC gel with a span of 1.6 mm had the best actuating performance. Finally, we printed three layers of corrugated PVC gel artificial muscle with good actuating performance. The proposed method can help to solve the inherent shortcomings of traditional manufacturing methods of PVC gel actuators. The printed structures have potential applications in many fields, such as soft robotics and flexible electronic devices.
Remote Sensing of Ecosystem Structure—Part 2: Initial Findings of Ecosystem Functioning through Intra- and Inter-Annual Comparisons with Earth Observation Data
Authors: Peters Daniel L. , Niemann K. Olaf , Skelly Robert
Published: August 2021

This study examines the response of a cold-regions deltaic wetland ecosystem in northwestern Canada to two separate and differing seasonal wetting cycles. The goal of this paper was to examine the nature of reflected electromagnetic energy measured by earth observation (EO) satellites, and to assess whether seasonal wetland hydroperiod and episodic flooding events impact the information retrieved by the Sentinel-2 sensors. The year 2018 represents a year characterized by a large spring freshet and ice-jam flooding, while 2019 represents a year characterized more by summer open-water flooding. We applied the Modified Normalized Difference Wetness Index (MNDWI) to address the effects of the wetting cycles. The response of the vegetative cover was tracked using the fraction of the absorbed photosynthetically active radiation (fAPAR) and the Leaf Area Index (LAI). All three indices were viewed through the lens of cover classes as derived through a previously published study by the authors. The study provides a framework for designing longer-term studies where multiple intra- and inter-annual hydrological cycles can be accessed via EO data. Future studies will enable the examination of lag times inherent in the response to the various water sources applied to spectral response and incorporate this EO approach into a monitoring framework.
Hyperspectral and Multispectral Image Fusion by Deep Neural Network in a Self-Supervised Manner
Authors: Gao Jianhao , Li Jie , Jiang Menghui
Published: August 2021

Compared with multispectral sensors, hyperspectral sensors obtain images with high- spectral resolution at the cost of spatial resolution, which constrains the further and precise application of hyperspectral images. An intelligent idea to obtain high-resolution hyperspectral images is hyperspectral and multispectral image fusion. In recent years, many studies have found that deep learning-based fusion methods outperform the traditional fusion methods due to the strong non-linear fitting ability of convolution neural network. However, the function of deep learning-based methods heavily depends on the size and quality of training dataset, constraining the application of deep learning under the situation where training dataset is not available or of low quality. In this paper, we introduce a novel fusion method, which operates in a self-supervised manner, to the task of hyperspectral and multispectral image fusion without training datasets. Our method proposes two constraints constructed by low-resolution hyperspectral images and fake high-resolution hyperspectral images obtained from a simple diffusion method. Several simulation and real-data experiments are conducted with several popular remote sensing hyperspectral data under the condition where training datasets are unavailable. Quantitative and qualitative results indicate that the proposed method outperforms those traditional methods by a large extent.
A Satellite-USV System for Persistent Observation of Mesoscale Oceanographic Phenomena
Authors: Dallolio Alberto , Quintana-Diaz Gara , Honoré-Livermore Evelyn , Garrett Joseph L. , Birkeland Roger , Johansen Tor A.
Published: August 2021

Traditional tools and methodologies for mesoscale observation of oceanographic phenomena are limited by under-sampling and data latency. In this article we evaluate three different scenario variants of an architecture for how heterogeneous sensor nodes can be integrated with satellite remote sensing. Independent space and marine sensing platforms are interconnected either directly or by means of a ground-based mission control center responsible for data processing, relay, and coordination of the assets. A wave-propelled unmanned surface vehicle (USV) persistently collects in situ data of the targeted phenomenon. In two variants of the architecture, a dedicated small satellite acts as a sensor node, a data processing facility and a communication node. We have used a System-of-Systems (SoS) modeling approach coupled with operational simulations in different locations on Earth, in order to support the proposed methodology and investigate quantitatively the reduction the data latency to end-users. Through a combination of field experiments and simulations we estimate how the different scenarios perform with respect to providing remote sensing data that are used to create a measurement and navigation plan for the autonomous vessel.
A Time-Domain Simulation System of MICAP L-Band Radiometer for Pre-Launch RFI Processing Study
Authors: Guo Tianshu , Guo Xi , Zhang Cheng , Han Donghao , Niu Lijie , Liu Hao , Wu Ji
Published: August 2021

Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been approved to be taken onbord the Chinese Ocean Salinity Mission. The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). Since radio frequency interference (RFI) is reported as a serious threat to L-band radiometry, the RFI detection and mitigation techniques must be carefully designed before launch. However, these techniques need to be developed based on the knowledge of how RFI affects complex correlation, visibility function, and reconstructed brightness temperature. This paper presents a time-domain signal modeling method for the simulation of interferometric measurement under RFI’s presences, and a simulation system for L-Rad is established accordingly. Several RFI cases are simulated with different RFI types, parameters, and positions; and the RFI characteristics upon L-Rad’s measurement are discussed. The proposed simulation system will be further dedicated to the design of RFI processing strategy onboard MICAP.
Improved Attitude and Heading Accuracy with Double Quaternion Parameters Estimation and Magnetic Disturbance Rejection
Authors: Wondosen Assefinew , Jeong Jin-Seok , Kim Seung-Ki , Debele Yisak , Kang Beom-Soo
Published: August 2021

The use of unmanned aerial vehicle (UAV) applications has grown rapidly over the past decade with the introduction of low-cost microelectromechanical system (MEMS)-based sensors that measure angular velocity, gravity, and magnetic field, which are important for an object orientation determination. However, the use of low-cost sensors has also been limited because their readings are easily distorted by unwanted internal and/or external noise signals such as environmental magnetic disturbance, which lead to errors in attitude and heading estimation results. In an extended Kalman filter (EKF) process, this study proposes a method for mitigating the effect of magnetic disturbance on attitude determination by using a double quaternion parameters for representation of orientation states, which decouples the magnetometer from attitude computation. Additionally, an online measurement error covariance matrix tuning system was implemented to reject the impact of magnetic disturbance on the heading estimation. Simulation and experimental tests were conducted to verify the performance of the proposed methods in resolving the magnetic noise effect on attitude and heading. The results showed that the proposed method performed better than complimentary, gradient descent, and single quaternion-based EKF.
Application of Photo Texture Analysis and Weather Data in Assessment of Air Quality in Terms of Airborne PM10 and PM2.5 Particulate Matter
Authors: Chuchro Monika , Sarlej Wojciech , Grzegorczyk Marta , Nurzyńska Karolina
Published: August 2021

The study was undertaken in Krakow, which is situated in Lesser Poland Voivodeship, where bad PM10 air-quality indicators occurred on more than 100 days in the years 2010–2019. Krakow has continuous air quality measurement in seven locations that are run by the Province Environmental Protection Inspectorate. The research aimed to create regression and classification models for PM10 and PM2.5 estimation based on sky photos and basic weather data. For this research, one short video with a resolution of 1920 × 1080 px was captured each day. From each film, only five frames were used, the information from which was averaged. Then, texture analysis was performed on each averaged photo frame. The results of the texture analysis were used in the regression and classification models. The regression models’ quality for the test datasets equals 0.85 and 0.73 for PM10 and 0.63 for PM2.5. The quality of each classification model differs (0.86 and 0.73 for PM10, and 0.80 for PM2.5). The obtained results show that the created classification models could be used in PM10 and PM2.5 air quality assessment. Moreover, the character of the obtained regression models indicates that their quality could be enhanced; thus, improved results could be obtained.
Estimation of Knee Joint Angle Using Textile Capacitive Sensor and Artificial Neural Network Implementing with Three Shoe Types at Two Gait Speeds: A Preliminary Investigation
Authors: Chhoeum Vantha , Kim Young , Min Se-Dong
Published: August 2021

The lower limb joints might be affected by different shoe types and gait speeds. Monitoring joint angles might require skill and proper technique to obtain accurate data for analysis. We aimed to estimate the knee joint angle using a textile capacitive sensor and artificial neural network (ANN) implementing with three shoe types at two gait speeds. We developed a textile capacitive sensor with a simple structure design and less costly placing in insole shoes to measure the foot plantar pressure for building the deep learning models. The smartphone was used to video during walking at each condition, and Kinovea was applied to calibrate the knee joint angle. Six ANN models were created; three shoe-based ANN models, two speed-based ANN models, and one ANN model that used datasets from all experiment conditions to build a model. All ANN models at comfortable and fast gait provided a high correlation efficiency (0.75 to 0.97) with a mean relative error lower than 15% implement for three testing shoes. And compare the ANN with A convolution neural network contributes a similar result in predict the knee joint angle. A textile capacitive sensor is reliable for measuring foot plantar pressure, which could be used with the ANN algorithm to predict the knee joint angle even using high heel shoes.
Pulmonary COVID-19: Learning Spatiotemporal Features Combining CNN and LSTM Networks for Lung Ultrasound Video Classification
Authors: Barros Bruno , Lacerda Paulo , Albuquerque Célio , Conci Aura
Published: August 2021

Deep Learning is a very active and important area for building Computer-Aided Diagnosis (CAD) applications. This work aims to present a hybrid model to classify lung ultrasound (LUS) videos captured by convex transducers to diagnose COVID-19. A Convolutional Neural Network (CNN) performed the extraction of spatial features, and the temporal dependence was learned using a Long Short-Term Memory (LSTM). Different types of convolutional architectures were used for feature extraction. The hybrid model (CNN-LSTM) hyperparameters were optimized using the Optuna framework. The best hybrid model was composed of an Xception pre-trained on ImageNet and an LSTM containing 512 units, configured with a dropout rate of 0.4, two fully connected layers containing 1024 neurons each, and a sequence of 20 frames in the input layer (20×2018). The model presented an average accuracy of 93% and sensitivity of 97% for COVID-19, outperforming models based purely on spatial approaches. Furthermore, feature extraction using transfer learning with models pre-trained on ImageNet provided comparable results to models pre-trained on LUS images. The results corroborate with other studies showing that this model for LUS classification can be an important tool in the fight against COVID-19 and other lung diseases.
Effect of Dispersion-Enhanced Sensitivity in a Two-Mode Optical Waveguide with an Asymmetric Diffraction Grating
Authors: Tsarev Andrei
Published: August 2021

Analysis of trends in the development of silicon photonics shows the high efficiency regarding the creation of optical sensors. The concept of bimodal sensors, which suggests moving away from the usual paradigm based only on single-mode waveguides and using the inter-mode interaction of guided optical waves in a two-mode optical waveguide, is developed in the present paper. In this case, the interaction occurs in the presence of an asymmetric periodic perturbation of the refractive index above the waveguide surface. Such a system has unique dispersion properties that lead to the implementation of collinear Bragg diffraction with the mode number transformation, in which there is an extremely high dependence of the Bragg wavelength on the change in the refractive index of the environment. This is called the “effect of dispersion-enhanced sensitivity”. In this paper, it is shown by numerical calculation methods that the effect can be used to create optical sensors with the homogeneous sensitivity higher than 3000 nm/RIU, which is many times better than that of sensors in single-mode waveguide structures.
Automated Cyber and Privacy Risk Management Toolkit
Authors: Gonzalez-Granadillo Gustavo , Menesidou Sofia Anna , Papamartzivanos Dimitrios , Romeu Ramon , Navarro-Llobet Diana , Okoh Caxton , Nifakos Sokratis , Xenakis Christos , Panaousis Emmanouil
Published: August 2021

Addressing cyber and privacy risks has never been more critical for organisations. While a number of risk assessment methodologies and software tools are available, it is most often the case that one must, at least, integrate them into a holistic approach that combines several appropriate risk sources as input to risk mitigation tools. In addition, cyber risk assessment primarily investigates cyber risks as the consequence of vulnerabilities and threats that threaten assets of the investigated infrastructure. In fact, cyber risk assessment is decoupled from privacy impact assessment, which aims to detect privacy-specific threats and assess the degree of compliance with data protection legislation. Furthermore, a Privacy Impact Assessment (PIA) is conducted in a proactive manner during the design phase of a system, combining processing activities and their inter-dependencies with assets, vulnerabilities, real-time threats and Personally Identifiable Information (PII) that may occur during the dynamic life-cycle of systems. In this paper, we propose a cyber and privacy risk management toolkit, called AMBIENT (Automated Cyber and Privacy Risk Management Toolkit) that addresses the above challenges by implementing and integrating three distinct software tools. AMBIENT not only assesses cyber and privacy risks in a thorough and automated manner but it also offers decision-support capabilities, to recommend optimal safeguards using the well-known repository of the Center for Internet Security (CIS) Controls. To the best of our knowledge, AMBIENT is the first toolkit in the academic literature that brings together the aforementioned capabilities. To demonstrate its use, we have created a case scenario based on information about cyber attacks we have received from a healthcare organisation, as a reference sector that faces critical cyber and privacy threats.
Development and Evaluation of a Virtual Environment to Assess Cycling Hazard Perception Skills
Authors: van Paridon Kjell , Timmis Matthew A. , Sadeghi Esfahlani Shabnam
Published: August 2021

Safe cycling requires situational awareness to identify and perceive hazards in the environment to react to and avoid dangerous situations. Concurrently, tending to external distractions leads to a failure to identify hazards or to respond appropriately in a time-constrained manner. Hazard perception training can enhance the ability to identify and react to potential dangers while cycling. Although cycling on the road in the presence of driving cars provides an excellent opportunity to develop and evaluate hazard perception skills, there are obvious ethical and practical risks, requiring extensive resources to facilitate safety, particularly when involving children. Therefore, we developed a Cycling and Hazard Perception virtual reality (VR) simulator (CHP-VR simulator) to create a safe environment where hazard perception can be evaluated and/or trained in a real-time setting. The player interacts in the virtual environment through a stationary bike, where sensors on the bike transfer the player’s position and actions (speed and road positioning) into the virtual environment. A VR headset provides a real-world experience for the player, and a procedural content generation (PCG) algorithm enables the generation of playable artifacts. Pilot data using experienced adult cyclists was collected to develop and evaluate the VR simulator through measuring gaze behavior, both in VR and in situ. A comparable scene (cycling past a parked bus) in VR and in situ was used. In this scenario, cyclists fixated 20% longer at the bus in VR compared to in situ. However, limited agreement identified that the mean differences fell within 95% confidence intervals. The observed differences were likely attributed to a lower number of concurrently appearing elements (i.e., cars) in the VR environment compared with in situ. Future work will explore feasibility testing in young children by increasing assets and incorporating a game scoring system to direct attention to overt and covert hazards.
High Accurate Environmental Sound Classification: Sub-Spectrogram Segmentation versus Temporal-Frequency Attention Mechanism
Authors: Qiao Tianhao , Zhang Shunqing , Cao Shan , Xu Shugong
Published: August 2021

In the important and challenging field of environmental sound classification (ESC), a crucial and even decisive factor is the feature representation ability, which can directly affect the accuracy of classification. Therefore, the classification performance often depends to a large extent on whether the effective representative features can be extracted from the environmental sound. In this paper, we firstly propose a sub-spectrogram segmentation with score level fusion based ESC classification framework, and we adopt the proposed convolutional recurrent neural network (CRNN) for improving the classification accuracy. By evaluating numerous truncation schemes, we numerically figure out the optimal number of sub-spectrograms and the corresponding band ranges, and, on this basis, we propose a joint attention mechanism with temporal and frequency attention mechanisms and use the global attention mechanism when generating the attention map. Finally, the numerical results show that the two frameworks we proposed can achieve 82.1% and 86.4% classification accuracy on the public environmental sound dataset ESC-50, respectively, which is equivalent to more than 13.5% improvement over the traditional baseline scheme.
Effectiveness of a Cool Bed Linen for Thermal Comfort and Sleep Quality in Air-Conditioned Bedroom under Hot-Humid Climate
Authors: Zaki Sheikh Ahmad , Rosli Mohamad Faizal , Rijal Hom Bahadur , Sadzli Farah Nurhanis Hassan , Hagishima Aya , Yakub Fitri
Published: August 2021

Comfort temperature and sleep quality involving 20 participants were determined in two cases: Case A (arbitrary, controlled air-conditioner setting) and Case B (adjustment of 3 °C higher than the setting of Case A with cool bed linen). Data of indoor thermal comfort and electricity consumption were collected every night throughout the measurement period. Questionnaires on thermal comfort and sleep quality were distributed twice a night for a duration of three nights for each case; the first night was for respondents’ adaptation and the following two nights were for measurement. The sleep quality of the respondents was objectively measured using a commercially available activity tracker. Results found that most respondents were thermally comfortable in both cases, with 39% lower energy consumption reported for Case B compared to Case A. The thermal conditions of Case B were found to be more tolerable than those of Case A. Most respondents reported to have a calm and satisfied sleep for both cases. Comfort temperature and Sleep Efficiency Index (SEI) were found to be maintained in both cases.
Alliance Management Practices for Higher Trust, Commitment and Inter-Organizational Relationship Performance: Evidence from Travel Companies in Vietnam
Authors: Nguyen Phuong Thi Minh , Mai Khuong Ngoc , Nguyen Phuong Ngoc Duy
Published: August 2021

Vietnam tourism experienced impressive growth from 2008–2019, but it has weakened due to the impact of the pandemic up to the present. So, what should the travel companies and their partners do to overcome the crisis caused by the COVID-19 pandemic? This paper aims to identify what alliance management practices (AMP) factors help improve the inter-organizational relationship performance (IORP) between travel companies and their partners through the mediating roles of trust and commitment. A quantitative approach was applied with data collection from representatives of 319 SMEs of travel companies and the PLS-SEM was used to test the hypotheses. The findings indicated that trust, commitment, coordination, and frequency of interaction directly affect IORP, and simultaneously, communication and participation have indirect impacts on IORP. This study provides suggestions for all tourism companies to be aware of the need to form relationships with other partners to sustainably survive and develop together.
Earth Observation for Monitoring, Reporting, and Verification within Environmental Land Management Policy
Authors: Andries Ana , Murphy Richard J. , Morse Stephen , Lynch Jim
Published: August 2021

The main aim of the new agricultural scheme, Environmental Land Management, in England is to reward landowners based on their provision of ‘public goods’ while achieving the goals of the 25 Year Environment Plan and commitment to net zero emission by 2050. Earth Observation (EO) satellites appear to offer an unprecedented opportunity in the process of monitoring, reporting, and verification (MRV) of this scheme. In this study, we worked with ecologists to determine the habitat–species relationships for five wildlife species in the Surrey Hills ‘Area of Outstanding Natural Beauty’ (AONB), and this information was used to examine the extent to which EO satellite imagery, particularly very high resolution (VHR) imagery, could be used for habitat assessment, via visual interpretation and automated methods. We show that EO satellite products at 10 m resolution and other geospatial datasets enabled the identification and location of broadly suitable habitat for these species and the use of VHR imagery (at 1–4 m spatial resolution) allowed valuable insights for remote assessment of habitat qualities and quantity. Hence, at a fine scale, we obtained additional habitats such as scrub, hedges, field margins, woodland and tree characteristics, and agricultural practices that offer an effective source of information for sustainable land management. The opportunities and limitations of this study are discussed, and we conclude that there is considerable scope for it to offer valuable information for land management decision-making and as support and evidence for MRV for incentive schemes.
The Critical Role of the Construction Industry in Achieving the Sustainable Development Goals (SDGs): Delivering Projects for the Common Good
Authors: Fei Wenmei , Opoku Alex , Agyekum Kofi , Oppon James Anthony , Ahmed Vian , Chen Charles , Lok Ka Leung
Published: August 2021

In 2015, the United Nations (UN) adopted the 2030 agenda for Sustainable Development, which set out 17 Sustainable Development Goals (SDGs), 169 targets and 231 unique indicators as a significant initiative towards socio-economic development. The SDGs provide the construction industry with a new lens through which global needs and desires can be translated into business solutions. This paper explores the role of the construction industry in achieving the 2030 Sustainable Development Goals. The paper uses an explanatory sequential design with an initial quantitative instrument phase, followed by a qualitative data collection phase. Following a comparative review of the literature on the 17 SDGs, a questionnaire was designed and administered among 130 respondents, and 105 responses were received. These data were then validated through semi-structured interviews with 16 sustainable construction experts. Data obtained from the semi-structured validation interviews were analysed through side-by-side comparisons of the qualitative data with the quantitative data. The findings show that the construction industry has a critical role in achieving almost all the 17 SDGs. The roles were, however, prevalent in 10 key SDGs, namely: sustainable cities and communities (SDG 11); climate action (SDG 13); clean water and sanitation (SDG 6); responsible consumption and production (SDG 12); industry, innovation and infrastructure (SDG 9); life on land (biodiversity) (SDG 15); gender equality (SDG 5); good health and well-being (SDG 3); affordable and clean energy (SDG 7); decent work and economic growth (SDG 8). The study confirmed the role played by the construction industry in achieving these SDGs. The findings from this study provide further insights into the ever-increasing state-of-the-art regarding the construction industry’s role in achieving Sustainable Development Goals.