bluuebunny/crossref_metadata_2025 huggingface dataset:
Mirogabalin—A Novel Selective Ligand for the α2δ Calcium Channel Subunit
Authors: Zajączkowska Renata , Mika Joanna , Leppert Wojciech , Kocot-Kępska Magdalena , Malec-Milewska Małgorzata , Wordliczek Jerzy
Published: February 2021

The efficacy of neuropathic pain control remains unsatisfactory. Despite the availability of a variety of therapies, a significant proportion of patients suffer from poorly controlled pain of this kind. Consequently, new drugs and treatments are still being sought to remedy the situation. One such new drug is mirogabalin, a selective ligand for the α2δ subunits of voltage-gated calcium channels (VGCC) developed by Sankyo group for the management of neuropathic pain. In 2019 in Japan, mirogabalin was approved for peripheral neuropathic pain following the encouraging results of clinical trials conducted with diabetic peripheral neuropathic pain (DPNP) and postherpetic neuralgia (PHN) patients. The ligand selectivity of mirogabalin for α2δ-1 and α2δ-2 and its slower dissociation rate for α2δ-1 than for α2δ-2 subunits of VGCC may contribute to its strong analgesic effects, wide safety margin, and relatively lower incidence of adverse effects compared to pregabalin and gabapentin. This article discusses the mechanism of action of mirogabalin, presents data on its pharmacodynamics and pharmacokinetics, and reviews the available experimental and clinical studies that have assessed the efficacy and safety of the drug in the treatment of selected neuropathic pain syndromes.
Liposomal Bupivacaine (Bupigel) Demonstrates Minimal Local Nerve Toxicity in a Rabbit Functional Model
Authors: Bavli Yaelle , Rabie Malcolm , Fellig Yakov , Nevo Yoram , Barenholz Yechezkel
Published: February 2021

We previously reported the development of a novel formulation of an ultra-long-acting local anesthetic based on bupivacaine encapsulated in large multivesicular liposomes (Bupisomes) embedded in hydrogel. This formulation (Bupigel) prolonged bupivacaine release from the formulation in dissolution-like studies in vitro and analgesia in vivo in mouse, rat, and pig models. In this study we assessed Bupigel neurotoxicity on rabbit sciatic nerve using histopathology and electrophysiologic testing. Sciatic nerves of both hind limbs were injected dropwise with different formulations. Nerve conduction studies and needle electromyography two weeks after perineural administration showed signs of neural damage after injection of free lidocaine and bupivacaine, while there was no sign of neural damage after injection with saline, demonstrating the validity of the method. This test also did not show evidence of motor or sensory nerve damage after injection with liposomal bupivacaine at a dose 10-times higher than free bupivacaine. Histologically, signs of neural damage could be observed with lidocaine. Nerves injected with Bupigel showed mild signs of inflammation and small residues of hydrogel in granulomas, indicating a long residence time of the hydrogel at the site of injection, but no histopathological signs of nerve damage. This demonstrated that early signs of neural damage were detected electrophysiologically, showing the usefulness and sensitivity of electrodiagnostic testing in detection of neural damage from new formulations.
The Topical Nanodelivery of Vismodegib Enhances Its Skin Penetration and Performance In Vitro While Reducing Its Toxicity In Vivo
Authors: Calienni Maria Natalia , Maza Vega Daniela , Temprana C. Facundo , Izquierdo María Cecilia , Ybarra David E. , Bernabeu Ezequiel , Moretton Marcela , Alvira Fernando C. , Chiappetta Diego , Alonso Silvia del Valle , Prieto María Jimena , Montanari Jorge
Published: February 2021

Vismodegib is a first-in-class inhibitor for advanced basal cell carcinoma treatment. Its daily oral doses present a high distribution volume and several side effects. We evaluated its skin penetration loaded in diverse nanosystems as potential strategies to reduce side effects and drug quantities. Ultradeformable liposomes, ethosomes, colloidal liquid crystals, and dendrimers were able to transport Vismodegib to deep skin layers, while polymeric micelles failed at this. As lipidic systems were the most effective, we assessed the in vitro and in vivo toxicity of Vismodegib-loaded ultradeformable liposomes, apoptosis, and cellular uptake. Vismodegib emerges as a versatile drug that can be loaded in several delivery systems for topical application. These findings may be also useful for the consideration of topical delivery of other drugs with a low water solubility.
Comparative Transcriptomic Analysis of Gene Expression Inheritance Patterns Associated with Cabbage Head Heterosis
Authors: Li Shengjuan , Jayasinghege Charitha P. A. , Guo Jia , Zhang Enhui , Wang Xingli , Xu Zhongmin
Published: February 2021

The molecular mechanism of heterosis or hybrid vigor, where F1 hybrids of genetically diverse parents show superior traits compared to their parents, is not well understood. Here, we studied the molecular regulation of heterosis in four F1 cabbage hybrids that showed heterosis for several horticultural traits, including head size and weight. To examine the molecular mechanisms, we performed a global transcriptome profiling in the hybrids and their parents by RNA sequencing. The proportion of genetic variations detected as single nucleotide polymorphisms and small insertion–deletions as well as the numbers of differentially expressed genes indicated a larger role of the female parent than the male parent in the genetic divergence of the hybrids. More than 86% of hybrid gene expressions were non-additive. More than 81% of the genes showing divergent expressions showed dominant inheritance, and more than 56% of these exhibited maternal expression dominance. Gene expression regulation by cis-regulatory mechanisms appears to mediate most of the gene expression divergence in the hybrids; however, trans-regulatory factors appear to have a higher effect compared to cis-regulatory factors on parental expression divergence. These observations bring new insights into the molecular mechanisms of heterosis during the cabbage head development.
Accumulation of Silicon and Changes in Water Balance under Drought Stress in Brassica napus var. napus L.
Authors: Saja-Garbarz Diana , Ostrowska Agnieszka , Kaczanowska Katarzyna , Janowiak Franciszek
Published: February 2021

The aim of this study was to investigate the accumulation of silicon in oilseed rape and to characterize the changes in chosen water balance parameters in response to drought. The following parameters were estimated: water content, osmotic and water potential, evapotranspiration, stomatal conductance and abscisic acid level under optimal and drought conditions. It was shown that oilseed rape plants accumulate silicon after its supplementation to the soil, both in the case of silicon alone and silicon together with iron. It was revealed that silicon (without iron) helps maintain constant water content under optimal conditions. While no silicon influence on osmotic regulation was observed, a transpiration decrease was detected under optimal conditions after silicon application. Under drought, a reduction in stomatal conductance was observed, but it was similar for all plants. The decrease in leaf water content under drought was accompanied by a significant increase in abscisic acid content in leaves of control plants and those treated with silicon together with iron. To sum up, under certain conditions, silicon is accumulated even in non-accumulator species, such as oilseed rape, and presumably improves water uptake under drought stress.
The Effect of Stacking Sequence and Ply Orientation on the Mechanical Properties of Pineapple Leaf Fibre (PALF)/Carbon Hybrid Laminate Composites
Authors: Hashim Mohd Khairul Rabani , Abdul Majid Mohd Shukry , Jamir Mohd Ridzuan Mohd , Kasim Farizul Hafiz , Sultan Mohamed Thariq Hameed
Published: February 2021

In this paper, the effects of stacking sequence and ply orientation on the mechanical properties of pineapple leaf fibre (PALF)/carbon hybrid laminate composites were investigated. The hybrid laminates were fabricated using a vacuum infusion technique in which the stacking sequences and ply orientations were varied, which were divided into the categories of cross-ply symmetric, angle-ply symmetric, and symmetric quasi-isotropic. The results of tensile and flexural tests showed that the laminate with interior carbon plies and ply orientation [0°, 90°] exhibited the highest tensile strength (187.67 MPa) and modulus (5.23 GPa). However, the highest flexural strength (289.46 MPa) and modulus (4.82 GPa) were recorded for the laminate with exterior carbon plies and the same ply orientation. The fracture behaviour of the laminates was determined by using scanning electron microscopy, and the results showed that failure usually initiated at the weakest PALF layer. The failure modes included fibre pull-out, fibre breaking, matrix crack, debonding, and delamination.
Processability of Different Polymer Fractions Recovered from Mixed Wastes and Determination of Material Properties for Recycling
Authors: Möllnitz Selina , Feuchter Michael , Duretek Ivica , Schmidt Gerald , Pomberger Roland , Sarc Renato
Published: February 2021

To achieve future recycling targets and CO2 and waste reduction, the transfer of plastic contained in mixed waste from thermal recovery to mechanical recycling is a promising option. This requires extensive knowledge of the necessary processing depth of mixed wastes to enrich plastics and their processability in polymer processing machines. Also, the selection of a suitable processing method and product application area requires appropriate material behaviour. This paper investigates these aspects for a commercial processed, mixed waste, and two different mixed polyolefin fractions. The wastes are processed at different depths (e.g., washed/not washed, sorted into polyethylene, polypropylene, polyethylene terephthalate, polystyrene/unsorted) and then either homogenised in the extruder in advance or processed heterogeneously in the compression moulding process into plates. The produced recyclates in plate form are then subjected to mechanical, thermal, and rheological characterisation. Most investigated materials could be processed with simple compression moulding. The results show that an upstream washing process improves the achievable material properties, but homogenisation does not necessarily lead to an improvement. It was also found that a higher treatment depth (recovery of plastic types) is not necessary. The investigations show that plastic waste recovery with simple treatment from mixed, contaminated wastes into at least downcycling products is possible.
Morphology-Mechanical Performance Relationship at the Micrometrical Level within Molded Polypropylene Obtained with Non-Symmetric Mold Temperature Conditioning
Authors: Liparoti Sara , Sorrentino Andrea , Speranza Vito
Published: February 2021

The control of the structural properties of a polymeric material at the micro and nano-metrical scale is strategic to obtaining parts with high performance, durability and free from sudden failures. The characteristic skin-core morphology of injection molded samples is intimately linked to the complex shear flow, pressure and temperature evolutions experienced by the polymer chains during processing. An accurate analysis of this morphology can allow for the assessment of the quality and confidence of the process. Non-symmetric mold temperature conditions are imposed to produce complex morphologies in polypropylene parts. Morphological and micromechanical characterizations of the samples are used to quantify the effects of the processing conditions on the part performance. Asymmetric distribution of temperatures determines asymmetric distribution of both morphology and mechanical properties. The inhomogeneity degree depends on the time that one side of the cavity experiences high temperatures. The spherulites, which cover the thickest of the parts obtained with high temperatures at one cavity side, show smaller values of elastic modulus than the fibrils. When the polymer molecules experience high temperatures for long periods, the solid-diffusion and the partial melting and recrystallization phenomena determine a better structuring of the molecules with a parallel increase of the elastic modulus.
Energy Saving for Tissue Paper Mills by Energy-Efficiency Scheduling under Time-of-Use Electricity Tariffs
Authors: Zeng Zhiqiang , Chen Xiaobin , Wang Kaiyao
Published: February 2021

Environmental concerns and soaring energy prices have brought huge pressure of energy saving and emission reduction to tissue paper mills. Electricity is one of the main energy sources of tissue paper mills. The production characteristics of tissue paper mills make it easy to decrease energy cost by using time-of-use (TOU) electricity tariffs. This study investigates the bi-objective energy-efficiency scheduling of tissue paper mills under time-of-use electricity tariffs, the objectives of which are makespan and energy cost. First, considering the processing energy cost, setup energy cost, and transportation energy cost, an energy cost model of a tissue paper mill under TOU electricity tariffs is established. Second, the energy-efficiency scheduling model under TOU electricity tariffs is built based on the energy cost model. Finally, on the basis of decomposition and teaching–learning optimization, this study proposes a novel multi-objective evolutionary algorithm and further combined with the variable neighborhood search to solve the problem. The case study results demonstrate that our study of tissue paper mill energy saving is feasible, and the proposed method has better performance than the existing methods.
Black Soldier Fly Larval Valorization Benefitting from Ex-Situ Fungal Fermentation in Reducing Coconut Endosperm Waste
Authors: Wong Chung Yiin , Kiatkittipong Kunlanan , Kiatkittipong Worapon , Ntwampe Seteno K. O. , Lam Man Kee , Goh Pei Sean , Cheng Chin Kui , Bashir Mohammed J. K. , Lim Jun Wei
Published: February 2021

Oftentimes, the employment of entomoremediation to reduce organic wastes encounters ubiquitous shortcomings, i.e., ineffectiveness to valorize recalcitrant organics in wastes. Considering the cost-favorability, a fermentation process can be employed to facilitate the degradation of biopolymers into smaller organics, easing the subsequent entomoremediation process. However, the efficacy of in situ fermentation was found impeded by the black soldier fly larvae (BSFL) in the current study to reduce coconut endosperm waste (CEW). Indeed, by changing into ex situ fermentation, in which the fungal Rhizopus oligosporus was permitted to execute fermentation on CEW prior to the larval feeding, the reduction of CEW was significantly enhanced. In this regard, the waste reduction index of CEW by BSFL was almost doubled as opposed to in situ fermentation, even with the inoculation of merely 0.5 wt % of Rhizopus oligosporus. Moreover, with only 0.02 wt % of fungal inoculation size to execute the ex situ fermentation on CEW, it could spur BSFL growth by about 50%. Finally, from the statistical correlation study using principal component analysis, the presence of Rhizopus oligosporus in a range of 0.5–1.0 wt % was regarded as optimum to ferment CEW via ex situ mode, prior to the valorization by BSFL in reducing the CEW.
Evaluation of a Full-Scale Suspended Sludge Deammonification Technology Coupled with an Hydrocyclone to Treat Thermal Hydrolysis Dewatering Liquors
Authors: Ochs Pascal , Martin Benjamin D. , Germain Eve , Wu Zhuoying , Lee Po-Heng , Stephenson Tom , van Loosdrecht Mark , Soares Ana
Published: February 2021

Suspended sludge deammonification technologies are frequently applied for sidestream ammonia removal from dewatering liquors resulting from a thermal hydrolysis anaerobic digestion (THP/AD) process. This study aimed at optimizing the operation, evaluate the performance and stability of a full-scale suspended sludge continuous stirred tank reactor (S-CSTR) with a hydrocyclone for anaerobic ammonia oxidizing bacteria (AMX) biomass separation. The S-CSTR operated at a range of nitrogen loading rates of 0.08–0.39 kg N m−3 d−1 displaying nitrogen removal efficiencies of 75–89%. The hydrocyclone was responsible for retaining 56–83% of the AMX biomass and the washout of ammonia oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) was two times greater than AMX. The solid retention time (SRT) impacted on NOB washout, that ranged from 0.02–0.07 d−1. Additionally, it was demonstrated that an SRT of 11–13 d was adequate to wash-out NOB. Microbiome analysis revealed a higher AMX abundance (Candidatus scalindua) in the reactor through the action of the hydrocyclone. Overall, this study established the optimal operational envelope for deammonification from THP/AD dewatering liquors and the role of the hydrocyclone towards maintaining AMX in the S-CSTR and hence obtain process stability.
Coarse-Grain DEM Modelling in Fluidized Bed Simulation: A Review
Authors: Di Renzo Alberto , Napolitano Erasmo , Di Maio Francesco
Published: February 2021

In the last decade, a few of the early attempts to bring CFD-DEM of fluidized beds beyond the limits of small, lab-scale units to larger scale systems have become popular. The simulation capabilities of the Discrete Element Method in multiphase flow and fluidized beds have largely benefitted by the improvements offered by coarse graining approaches. In fact, the number of real particles that can be simulated increases to the point that pilot-scale and some industrially relevant systems become approachable. Methodologically, coarse graining procedures have been introduced by various groups, resting on different physical backgrounds. The present review collects the most relevant contributions, critically proposing them within a unique, consistent framework for the derivations and nomenclature. Scaling for the contact forces, with the linear and Hertz-based approaches, for the hydrodynamic and cohesive forces is illustrated and discussed. The orders of magnitude computational savings are quantified as a function of the coarse graining degree. An overview of the recent applications in bubbling, spouted beds and circulating fluidized bed reactors is presented. Finally, new scaling, recent extensions and promising future directions are discussed in perspective. In addition to providing a compact compendium of the essential aspects, the review aims at stimulating further efforts in this promising field.
Exosome-Derived Mediators as Potential Biomarkers for Cardiovascular Diseases: A Network Approach
Authors: Moreira-Costa Liliana , Barros António S. , Lourenço André P. , Leite-Moreira Adelino F. , Nogueira-Ferreira Rita , Thongboonkerd Visith , Vitorino Rui
Published: February 2021

Cardiovascular diseases (CVDs) are widely recognized as the leading cause of mortality worldwide. Despite the advances in clinical management over the past decades, the underlying pathological mechanisms remain largely unknown. Exosomes have drawn the attention of researchers for their relevance in intercellular communication under both physiological and pathological conditions. These vesicles are suggested as complementary prospective biomarkers of CVDs; however, the role of exosomes in CVDs is still not fully elucidated. Here, we performed a literature search on exosomal biogenesis, characteristics, and functions, as well as the different available exosomal isolation techniques. Moreover, aiming to give new insights into the interaction between exosomes and CVDs, network analysis on the role of exosome-derived mediators in coronary artery disease (CAD) and heart failure (HF) was also performed to incorporate the different sources of information. The upregulated exosomal miRNAs miR-133a, miR-208a, miR-1, miR-499-5p, and miR-30a were described for the early diagnosis of acute myocardial infarction, while the exosome-derived miR-192, miR-194, miR-146a, and miR-92b-5p were considered as potential biomarkers for HF development. In CAD patients, upregulated exosomal proteins, including fibrinogen beta/gamma chain, inter-alpha-trypsin inhibitor heavy chain, and alpha-1 antichymotrypsin, were assessed as putative protein biomarkers. From downregulated proteins in CAD patients, albumin, clusterin, and vitamin D-binding protein were considered relevant to assess prognosis. The Vesiclepedia database included miR-133a of exosomal origin upregulated in patients with CAD and the exosomal miR-192, miR-194, and miR-146a upregulated in patients with HF. Additionally, Vesiclepedia included 5 upregulated and 13 downregulated exosomal proteins in patients in CAD. The non-included miRNAs and proteins have not yet been identified in exosomes and can be proposed for further research. This report highlights the need for further studies focusing on the identification and validation of miRNAs and proteins of exosomal origin as biomarkers of CAD and HF, which will enable, using exosomal biomarkers, the guiding of diagnosis/prognosis in CVDs.
Development of Pulsed TEM Equipped with Nitride Semiconductor Photocathode for High-Speed Observation and Material Nanofabrication
Authors: Yasuda Hidehiro , Nishitani Tomohiro , Ichikawa Shuhei , Hatanaka Shuhei , Honda Yoshio , Amano Hiroshi
Published: February 2021

The development of pulsed electron sources is applied to electron microscopes or electron beam lithography and is effective in expanding the functions of such devices. The laser photocathode can generate short pulsed electrons with high emittance, and the emittance can be increased by changing the cathode substrate from a metal to compound semiconductor. Among the substrates, nitride-based semiconductors with a negative electron affinity (NEA) have good advantages in terms of vacuum environment and cathode lifetime. In the present study, we report the development of a photocathode electron gun that utilizes photoelectron emission from a NEA-InGaN substrate by pulsed laser excitation, and the purpose is to apply it to material nanofabrication and high-speed observation using a pulsed transmission electron microscope (TEM) equipped with it.
Effect of Changing Amounts of Promoters and Base Fe Metal in a Multicomponent Catalyst Supported on Coal-Based Activated Carbon for Fischer–Tropsch Synthesis
Authors: Gujjar Soumya J. , Karre Avinashkumar V. , Kababji Alaa , Dadyburjor Dady B.
Published: February 2021

The effect of varying the amounts of metals Fe, Cu, K, and Mo was studied on a catalyst supported on activated carbon (AC), which is an item of novelty of this paper. The base-case catalyst contains 16% Fe, 0.9% K, 6% Mo, and 0.8% Cu relative to the AC support. For all of the catalysts used, alcohol production is small. The production of hydrocarbons depends upon the amount of Fe and other promoters used. The amount of Fe was increased from 0% to 32% on the catalyst containing base-case amounts of the other materials. While 0% Fe shows no activity towards Fischer–Tropsch synthesis (FTS), 32% Fe shows a marginal increase in FTS activity when compared with 16% Fe. Furthermore, the amount of K was increased from 0% to 1.8%, with the other metals in their base-case amounts. The selectivity of C1–C4 decreases with the addition of K, while the selectivity of C5+ increases. Analogously, the amount of Mo was increased from 0% to 12%. A small amount of Mo results in an increase in FTS activity but decreases with the addition of more Mo. Cu on the catalyst was increased from 0% to 1.6%, with 0.8% Cu proving optimum for FTS.
Issues and Challenges Confronting the Achievement of Zero Plastic Waste in Victoria, Australia
Authors: Ng Anne W. M. , Ly Srenghang , Muttil Nitin , Nguyen Cuong Ngoc
Published: February 2021

Despite the increase in popularity of the zero waste (ZW) concept, the successful implementation of this concept in waste management is still facing many challenges. The plastic recycling rate in Australia is at only about 9.4% (in 2017–2018). The state of Victoria (in Australia) has proposed an ambitious 10-year plan to upgrade its waste and recycling system and to divert about 80% of waste from landfills by 2030. The aim of this research is to study this currently proposed waste management plan and to develop a simulation model to assess the feasibility of achieving 80% diversion rate by 2030. The feasibility of achieving zero plastic waste by 2035 has also been assessed. In this direction, the existing knowledge of global ZW implementation has been reviewed to gain understanding of the challenges, obstacles, and uncertainties in achieving the ZW target. A simulation model is established using a method called double baselines. This method was developed to address the limitation of data availability for the model development. The model was run in 4 scenarios including one for Victoria’s current 10-year plan. Outcomes from the model are produced using six key considerations, including the rate of plastic consumption, waste to landfill, diversion rate, recycling rate, relative accumulative effort, and cost. The findings of this study point out that Victoria’s current plan for achieving an 80% diversion rate by 2030 is possible. On the other hand, the study results also suggest that achieving zero plastic waste by 2035 is less likely to happen. Hence, opportunities for improvement especially towards achieving the zero plastic waste are also presented.
Triggers and Obstacles to the Development of the FinTech Sector in Poland
Authors: Kliber Agata , Będowska-Sójka Barbara , Rutkowska Aleksandra , Świerczyńska Katarzyna
Published: February 2021

The article aims to show the opportunities for the formation of new FinTech startups in Poland and further development of the sector, as well as to identify the most critical threats. The study offers the descriptive and deductive analysis based on the literature review. The empirical part relies on the data from external databases as well as the dataset collected in a survey run among the FinTechs in Poland in January 2020. The paper reveals that Poland is a fast-growing FinTech market which satisfies various requirements such as the number of secure Internet servers, mobile telephone subscriptions, the available labor force, as well as growing tertiary education enrolment. The crucial obstacles to the development of the sector is the uncertainty about the availability of skilled workers in the future and the lack of proper legal regulations.
Efficiency Testing of Prediction Markets: Martingale Approach, Likelihood Ratio and Bayes Factor Analysis
Authors: Richard Mark , Vecer Jan
Published: February 2021

This paper studies efficient market hypothesis in prediction markets and the results are illustrated for the in-play football betting market using the quoted odds for the English Premier League. Our analysis is based on the martingale property, where the last quoted probability should be the best predictor of the outcome and all previous quotes should be statistically insignificant. We use regression analysis to test for the significance of the previous quotes in both the time setup and the spatial setup based on stopping times, when the quoted probabilities reach certain bounds. The main contribution of this paper is to show how a potentially different distributional opinion based on the violation of the market efficiency can be monetized by optimal trading, where the agent maximizes logarithmic utility function. In particular, the trader can realize a trading profit that corresponds to the likelihood ratio in the situation of one market maker and one market taker, or the Bayes factor in the situation of two or more market takers.
Estimating the BIS Capital Adequacy Ratio for Korean Banks Using Machine Learning: Predicting by Variable Selection Using Random Forest Algorithms
Authors: Park Jaewon , Shin Minsoo , Heo Wookjae
Published: February 2021

The purpose of this study is to find the most important variables that represent the future projections of the Bank of International Settlements’ (BIS) capital adequacy ratio, which is the index of financial soundness in a bank as a comprehensive and important measure of capital adequacy. This study analyzed the past 12 years of data from all domestic banks in South Korea. The research data include all financial information, such as key operating indicators, major business activities, and general information of the financial supervisory service of South Korea from 2008 to 2019. In this study, machine learning techniques, Random Forest Boruta algorithms, Random Forest Recursive Feature Elimination, and Bayesian Regularization Neural Networks (BRNN) were utilized. Among 1929 variables, this study found 38 most important variables for representing the BIS capital adequacy ratio. An additional comparison was executed to confirm the statistical validity of future prediction performance between BRNN and ordinary least squares (OLS) models. BRNN predicted the BIS capital adequacy ratio more robustly and accurately than the OLS models. We believe our findings would appeal to the readership of your journal such as the policymakers, managers and practitioners in the bank-related fields because this study highlights the key findings from the data-driven approaches using machine learning techniques.
Unmanned Aerial Drones for Inspection of Offshore Wind Turbines: A Mission-Critical Failure Analysis
Authors: Shafiee Mahmood , Zhou Zeyu , Mei Luyao , Dinmohammadi Fateme , Karama Jackson , Flynn David
Published: February 2021

With increasing global investment in offshore wind energy and rapid deployment of wind power technologies in deep water hazardous environments, the in-service inspection of wind turbines and their related infrastructure plays an important role in the safe and efficient operation of wind farm fleets. The use of unmanned aerial vehicle (UAV) and remotely piloted aircraft (RPA)—commonly known as “drones”—for remote inspection of wind energy infrastructure has received a great deal of attention in recent years. Drones have significant potential to reduce not only the number of times that personnel will need to travel to and climb up the wind turbines, but also the amount of heavy lifting equipment required to carry out the dangerous inspection works. Drones can also shorten the duration of downtime needed to detect defects and collect diagnostic information from the entire wind farm. Despite all these potential benefits, the drone-based inspection technology in the offshore wind industry is still at an early stage of development and its reliability has yet to be proven. Any unforeseen failure of the drone system during its mission may cause an interruption in inspection operations, and thereby, significant reduction in the electricity generated by wind turbines. In this paper, we propose a semiquantitative reliability analysis framework to identify and evaluate the criticality of mission failures—at both system and component levels—in inspection drones, with the goal of lowering the operation and maintenance (O&M) costs as well as improving personnel safety in offshore wind farms. Our framework is built based upon two well-established failure analysis methodologies, namely, fault tree analysis (FTA) and failure mode and effects analysis (FMEA). It is then tested and verified on a drone prototype, which was developed in the laboratory for taking aerial photography and video of both onshore and offshore wind turbines. The most significant failure modes and underlying root causes within the drone system are identified, and the effects of the failures on the system’s operation are analysed. Finally, some innovative solutions are proposed on how to minimize the risks associated with mission failures in inspection drones.
Transferability of Convolutional Neural Network Models for Identifying Damaged Buildings Due to Earthquake
Authors: Yang Wanting , Zhang Xianfeng , Luo Peng
Published: February 2021

The collapse of buildings caused by earthquakes can lead to a large loss of life and property. Rapid assessment of building damage with remote sensing image data can support emergency rescues. However, current studies indicate that only a limited sample set can usually be obtained from remote sensing images immediately following an earthquake. Consequently, the difficulty in preparing sufficient training samples constrains the generalization of the model in the identification of earthquake-damaged buildings. To produce a deep learning network model with strong generalization, this study adjusted four Convolutional Neural Network (CNN) models for extracting damaged building information and compared their performance. A sample dataset of damaged buildings was constructed by using multiple disaster images retrieved from the xBD dataset. Using satellite and aerial remote sensing data obtained after the 2008 Wenchuan earthquake, we examined the geographic and data transferability of the deep network model pre-trained on the xBD dataset. The result shows that the network model pre-trained with samples generated from multiple disaster remote sensing images can extract accurately collapsed building information from satellite remote sensing data. Among the adjusted CNN models tested in the study, the adjusted DenseNet121 was the most robust. Transfer learning solved the problem of poor adaptability of the network model to remote sensing images acquired by different platforms and could identify disaster-damaged buildings properly. These results provide a solution to the rapid extraction of earthquake-damaged building information based on a deep learning network model.
Autonomous Vehicle Localization with Prior Visual Point Cloud Map Constraints in GNSS-Challenged Environments
Authors: Lin Xiaohu , Wang Fuhong , Yang Bisheng , Zhang Wanwei
Published: February 2021

Accurate vehicle ego-localization is key for autonomous vehicles to complete high-level navigation tasks. The state-of-the-art localization methods adopt visual and light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) to estimate the position of the vehicle. However, both of them may suffer from error accumulation due to long-term running without loop optimization or prior constraints. Actually, the vehicle cannot always return to the revisited location, which will cause errors to accumulate in Global Navigation Satellite System (GNSS)-challenged environments. To solve this problem, we proposed a novel localization method with prior dense visual point cloud map constraints generated by a stereo camera. Firstly, the semi-global-block-matching (SGBM) algorithm is adopted to estimate the visual point cloud of each frame and stereo visual odometry is used to provide the initial position for the current visual point cloud. Secondly, multiple filtering and adaptive prior map segmentation are performed on the prior dense visual point cloud map for fast matching and localization. Then, the current visual point cloud is matched with the candidate sub-map by normal distribution transformation (NDT). Finally, the matching result is used to update pose prediction based on the last frame for accurate localization. Comprehensive experiments were undertaken to validate the proposed method, showing that the root mean square errors (RMSEs) of translation and rotation are less than 5.59 m and 0.08°, respectively.
Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas
Authors: Muumbe Tasiyiwa Priscilla , Baade Jussi , Singh Jenia , Schmullius Christiane , Thau Christian
Published: February 2021

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.
Hyperspectral Reflectance and Indices for Characterizing the Dynamics of Crop–Weed Competition for Water
Authors: Ronay Inbal , Ephrath Jhonathan E. , Eizenberg Hanan , Blumberg Dan G. , Maman Shimrit
Published: February 2021

Understanding the spectral characteristics of crops in response to stress caused by weeds is a basic step in improving the precision of agricultural technologies that manage weeds in the field. This research focused on the competition between corn (Zea mays) and redroot pigweed (Amaranthus retroflexus), a common weed that strongly reduces corn yield. The aim of this research was to characterize the physiological changes that occur in corn during early growth because of crop–weed competition and to examine the ability to detect the effect of competition through hyperspectral measurements. A greenhouse experiment was conducted, and corn plants were examined during early growth, with and without weed competition. Hyperspectral measurements were combined with physiological measurements to examine the reflectance and photosynthetic activity of corn. Changes were expected to appear mainly in the short-wave infrared region (SWIR) due to competition for water. Relative water content (RWC), chlorophyll content, photosynthetic rate, and stomatal conductance were reduced in the presence of weeds, and intercellular CO2 levels increased. Deeper SWIR light absorption occurred in the weed treatment as expected, accompanied by spectral changes in the visible (VIS) and near infrared (NIR) ranges. The results highlight the potential of using spectral measurements as an indicator of competition for water.
Decreased Anthropogenic CO2 Emissions during the COVID-19 Pandemic Estimated from FTS and MAX-DOAS Measurements at Urban Beijing
Authors: Cai Zhaonan , Che Ke , Liu Yi , Yang Dongxu , Liu Cheng , Yue Xu
Published: February 2021

The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.
Shore Evidences of a High Antarctic Ocean Wave Event: Geomorphology, Event Reconstruction and Coast Dynamics through a Remote Sensing Approach
Authors: Ponti Stefano , Guglielmin Mauro
Published: February 2021

Remote sensing can be helpful in defining the dynamic of a high-latitude coastal environment where the role of cryogenic processes like sea-ice or permafrost are the main drivers together with storm surge and wind action. Here we examined the geomorphological dynamics of a beach located at Edmonson Point (74° S) not far from the Italian Antarctic Station “Mario Zucchelli” between 1993 and 2019 using different remote sensing techniques and field measurements. Our data demonstrate that the average rate of surficial increase of the beach (0.002 ± 0.032 m yr−1) was slightly higher than the uplift rate determined by previous authors (0–1 cm yr−1) in case of pure isostatic rebound. However, we suggest that the evolution of EPNB is likely due to the couple effect of vertical uplift and high wave-energy events. Indeed, the coastline accumulation could be related to the subsurface sea water infiltration and annually freezing at the permafrost table interface as aggradational ice as suggested by the ERT carried out in 1996. This ERT suggests the occurrence of saline frozen permafrost or hypersaline brines under the sea level while permafrost with ice occurred above the sea level. The beach also revealed areas that had quite high subsidence values (between 0.08 and 0.011 m yr−1) located in the area where ice content was higher in 1996 and where the active layer thickening and wind erosion could explain the measured erosion rates. Here, we also dated at the late morning of 15 February 2019 coastal flooding and defined a significant wave height of 1.95 m. During the high oceanic wave event the sea level increased advancing shoreward up to 360 m, three times higher than the previous reported storm surge (81 m) and with a sea level rise almost five times higher than has been previously recorded in the Ross Sea.
Editorial for the Special Issue: Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas
Authors: Pour Amin Beiranvand , Zoheir Basem , Pradhan Biswajeet , Hashim Mazlan
Published: February 2021

In recent decades, multispectral and hyperspectral remote sensing data provide unprecedented opportunities for the initial stages of mineral exploration and environmental hazard monitoring [...]
Experimental Evaluation of the Availability of LoRaWAN Frequency Channels in the Czech Republic
Authors: Novák Vojtěch , Stočes Michal , Čížková Tereza , Jarolímek Jan , Kánská Eva
Published: February 2021

LoRaWAN communication allows you to create IoT (Internet of Things) solutions across many disciplines. A specific field of application is precision agriculture, which demands this technology mainly due to the fact that it is possible to create low power sensor devices with it. However, in densely populated areas, a lower success rate of message delivery can be observed on some communication channels. For example, this can have an impact on urban agriculture projects. After performing an experiment and analytical–statistical data processing using the Geographic Information System (GIS) tool ArcGIS Insights, it was shown that the success of message delivery on the basic LoRaWAN channel (868.3 MHz) is lower than for the others. Therefore, to ensure higher reliability and thus energy savings, it is appropriate to optimize the use of frequency channels.
Real-Time Production of PGA, PGV, Intensity, and Sa Shakemaps Using Dense MEMS-Based Sensors in Taiwan
Authors: Yang Benjamin M. , Mittal Himanshu , Wu Yih-Min
Published: February 2021

Using low-cost sensors to build a seismic network for earthquake early warning (EEW) and to generate shakemaps is a cost-effective way in the field of seismology. National Taiwan University (NTU) network employing 748 P-Alert sensors based on micro-electro-mechanical systems (MEMS) technology is operational for almost the last 10 years. This instrumentation is capable of recording the strong ground motions of up to ± 2g and is dense enough to record the near-field ground motion. It has proven effective in generating EEW warnings and delivering real-time shakemaps to the concerned disaster relief agencies to mitigate the earthquake-affected regions. Before 2020, this instrumentation was used to plot peak ground acceleration (PGA) shakemaps only; however, recently it has been upgraded to generate the peak ground velocity (PGV), Central Weather Bureau (CWB) Intensity scale, and spectral acceleration (Sa) shakemaps at different periods as value-added products. After upgradation, the performance of the network was observed using the latest recorded earthquakes in the country. The experimental results in the present work demonstrate that the new parameters shakemaps added in the current work provide promising outputs, and are comparable with the shakemaps given by the official agency CWB. These shakemaps are helpful to delineate the earthquake-hit regions which in turn is required to assist the needy well in time to mitigate the seismic risk.
A Systematic Comparison of Depth Map Representations for Face Recognition
Authors: Pini Stefano , Borghi Guido , Vezzani Roberto , Maltoni Davide , Cucchiara Rita
Published: February 2021

Nowadays, we are witnessing the wide diffusion of active depth sensors. However, the generalization capabilities and performance of the deep face recognition approaches that are based on depth data are hindered by the different sensor technologies and the currently available depth-based datasets, which are limited in size and acquired through the same device. In this paper, we present an analysis on the use of depth maps, as obtained by active depth sensors and deep neural architectures for the face recognition task. We compare different depth data representations (depth and normal images, voxels, point clouds), deep models (two-dimensional and three-dimensional Convolutional Neural Networks, PointNet-based networks), and pre-processing and normalization techniques in order to determine the configuration that maximizes the recognition accuracy and is capable of generalizing better on unseen data and novel acquisition settings. Extensive intra- and cross-dataset experiments, which were performed on four public databases, suggest that representations and methods that are based on normal images and point clouds perform and generalize better than other 2D and 3D alternatives. Moreover, we propose a novel challenging dataset, namely MultiSFace, in order to specifically analyze the influence of the depth map quality and the acquisition distance on the face recognition accuracy.