bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Investigation and Numerical Modeling of Elastic Modulus Variation with Stress during Hydration and Expansion Process of Static Cracking Agent
Authors: Qiu Zhaoguo , Ji You , Zhang Fengpeng , Yan Guangliang
Published: April 2021

Based on the “axial-output method”, the time histories of radial and axial expansive pressures during the hydration process of static cracking agent (SCA) in a cylinder with various diameters were obtained by experiments. With the load input taken as the product of the normalized axial expansive pressure and the amplitude coefficient, a finite element model was established to simulate the experimental chemical expansion process of SCA. The relationships between elastic modulus, radial and axial expansive pressures were then obtained. The results indicate that the elastic modulus increases with increasing radial and axial expansive pressures, and then tends to be constant. The effect of Poisson’s ratio was discussed with the elastic modulus unchanged. It is shown that the Poisson’s ratio is inversely proportional to the amplitude coefficient, and has no effect on the ratio between the axial and radial expansive pressures. Finally, a mechanical model for the variation of elastic modulus with stress during the hydration process of static cracking agent was established in terms of the major principal stress. The model was verified by the experimental results, which can be extended for numerical simulation of SCA expansion under other compressive loading conditions, and then provide practical mechanical parameters for engineering application of SCA.
Microencapsulation of Peppermint Oil by Complex Coacervation and Subsequent Spray Drying Using Bovine Serum Albumin/Gum Acacia and an Oxidized Starch Crosslinker
Authors: Glomm Wilhelm Robert , Molesworth Peter Patrick , Sandru Eugenia Mariana , Truong Le Thuy , Brunsvik Anders , Johnsen Heidi
Published: April 2021

Most liquid food flavours such as essential oils are volatile and prone to degradation in the presence of oxygen, light, moisture and high temperatures. Microencapsulation of volatile ingredients prior to use in food or beverages is a commonly used process to limit loss and degradation of flavours and aromas during processing and storage. Here, peppermint essential oil was microencapsulated via complex coacervation using a combination of bovine serum albumin and gum Acacia as wall materials. The resulting core-shell microcapsules were chemically crosslinked with a modified food-grade starch, and subsequently spray dried, resulting in dry microcapsules which could be easily redispersed in aqueous solutions. Microcapsule formation and stability, as well as microencapsulation yield of peppermint oil, were investigated as a function of polymer concentration, core material load/wall thickness and crosslinker concentration. The crosslinked peppermint oil microcapsules were spherical and mononuclear both before and after spray drying and redispersion, whereas control coacervate samples without crosslinker did not withstand the spray drying process. Microencapsulation yield as analysed by GC-MS showed no loss of peppermint oil during or after complex coacervation, and 54% loss after spray drying for the best combination of Polymer:Oil ratio and crosslinker concentration used here, indicating good overall protection of the core material.
Simultaneous Measurement Method and Error Analysis of Six Degrees of Freedom Motion Errors of a Rotary Axis Based on Polyhedral Prism
Authors: Ma Dong , Li Jiakun , Feng Qibo , He Qixin , Ding Yaowen , Cui Jianying
Published: April 2021

A novel method is proposed for measuring the six degrees-of-freedom (DOF) geometric motion errors of a rotary axis based on a polyhedral prism. An error-sensitive unit which consists of a polyhedral prism and a planar reflector, is designed to carry out measurement of all six DOF errors, including the angular positioning error, the tilt motion error around the Y axis, the tilt motion error around the X axis, the radial motion error along the X and Y axes, and the axial motion error along the Z axis. The mathematical error model, including the six DOF geometric motion errors of the rotary axis, the installation errors between the polyhedral prism and the rotary axis, the manufacturing errors of the polyhedral prism, and the position errors of the sensors, are established. The effectiveness of the proposed method and the compensation model was simulated and experimentally verified.
Functional and Bioactive Properties of Protein Extracts Generated from Spirulina platensis and Isochrysis galbana T-Iso
Authors: Bleakley Stephen , Hayes Maria
Published: April 2021

There is growing consumer demand for food products derived from microalgae, driven largely by the perceived health benefits associated with them. The functional and bioactive potential of proteins isolated from two microalgae—Spirulina sp. and Isochrysis galbana T-Iso—were determined. The results obtained show the potential of microalgal protein extracts for use in the beverage industry, based on solubility values and other functional characteristics, including water and oil holding capacities, foaming, emulsifying activities and stabilities, water activities, solubility and pH. The solubility of algal proteins was pH-dependent, and they were largely insoluble at pH values between 2 and 11. However, the proteins were increasingly soluble at a pH of 12, and they have potential use in formulating foods with higher viscosities or gels, where they could act as fillers to strengthen networks. Compared with whey and flaxseed proteins, the Spirulina sp. protein extract had a superior oil-holding capacity (OHC). The OHC is important in developing texture in food products such as meats. Overall, better foam stability was observed for both Spirulina sp. and Isochrysis sp. soluble protein extracts, compared with flaxseed protein at pH values from 2 to 10 over a period of 120 min. The foam capacity and stability increase the physical properties of foods. However, the emulsion activity and stability values for soluble algal protein extracts were less than the values observed for flaxseed and whey proteins. Algal proteins would not be suitable for use in creaming and food processing involving flocculation. In addition, algal protein extracts inhibited Angiotensin-converting enzyme-I (ACE-I) and renin, and they have potential for use in functional food ingredient applications to maintain heart health and also to act as meat substitutes.
Cognitive Modeling of Task Switching in Discretionary Multitasking Based on the ACT-R Cognitive Architecture
Authors: Oh Hyungseok , Yun Yongdeok , Myung Rohae
Published: April 2021

Discretionary multitasking has emerged as a prevalent and important domain in research on human–computer interaction. Studies on modeling based on cognitive architectures such as ACT-R to gain insight into and predict human behavior in multitasking are critically important. However, studies on ACT-R modeling have mainly focused on concurrent and sequential multitasking, including scheduled task switching. Therefore, in this study, an ACT-R cognitive model of task switching in discretionary multitasking was developed to provide an integrated account of when and how humans decide on switching tasks. Our model contains a symbolic structure and subsymbolic equations that represent the cognitive process of task switching as self-interruption by the imposed demands and a decision to switch. To validate our model, it was applied to an illustrative dual task, including a memory game and a subitizing task, and the results were compared with human data. The results demonstrate that our model can provide a relatively accurate representation, in terms of task-switching percent just after the subtask, the number of task-switching during the subtask, and performance time depending on the task difficulty level; it exhibits enhanced performance in predicting human behavior in multitasking and demonstrates how ACT-R facilitates accounts of voluntary task switching.
A Novel Bacterial-Mediated Method for the Differentiation of Aedes spp. Larvae in Mixed-Nursery Assays and Its Application in the Determination of Vegetative Lysinibacillus sphaericus Biocontrol Efficiency in Invasive Vector Eradication
Authors: Dániel-Gómez Mario , Dussán Jenny
Published: April 2021

The establishment of Aedes aegypti and the recent invasion of Aedes albopictus has put Colombia at risk, as it now harbours two arboviral vector species. Studies have shown the susceptibility of Aedes aegypti to the vegetative toxins produced by Lysinibacillus sphaericus. This study aims to determine the potential of two L. sphaericus strains in the control of both Aedes species present in Colombia, in both single and mixed species nurseries. Given the similarities between both species, there exists a need to differentiate them for the development of precise control strategies. Accordingly, mixed nurseries employed a red fluorescent protein (mRFP)-expressing Escherichia coli strain as a differentiator. Coloration-aided differentiation facilitated the analysis of mixed nursery treatments and provided deeper scrutiny into the variables at play. This showed an increase in the biocontrol efficiency, pointing to probable ecological variables. Bioassays involving Ae. albopictus showed a lower resistance to the one reported for Ae. aegypti in single-species nurseries. The study concludes that the use of E. coli strains expressing fluorescent proteins are useful tools to be employed in areas like public health entomology. Moreover, it was found that the use of L. sphaericus strains for biocontrol of vector mosquitoes is a viable alternative to chemical insecticides.
Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate
Authors: Velashjerdi Farahani Azin , Jokisalo Juha , Korhonen Natalia , Jylhä Kirsti , Ruosteenoja Kimmo , Kosonen Risto
Published: April 2021

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.
Thymoquinone, but Not Metformin, Protects against Gentamicin-Induced Nephrotoxicity and Renal Dysfunction in Rats
Authors: Alsharidah Mansour , Abdel-Moneim Abdel-Moneim Hafez , Alsharidah Ashwag Saleh , Mobark Mugahid A. , Rahmani Arshad Husain , Shata Ahmed , Abdellatif Ahmed A. H. , El-Readi Mahmoud Zaki , Mohany Khalid M. , Al Rugaie Osamah
Published: April 2021

Background: Gentamicin (GM) is an antibiotic that is widely used to treat many Gram-negative bacteria, such as those involved in urinary tract infections. However, being nephrotoxic, GM dose adjustment and reno-protective elements must be concurrently administered with GM to minimize kidney damage. Oxidative stress plays a pivotal role in the pathogenesis of GM-induced nephrotoxicity. Thymoquinone (TQ) is a promising therapeutic substance, that is being extensively studied in many diseases, such as diabetes mellitus, cancer, hypertension, and others. The powerful antioxidant properties of TQ may greatly help in minimizing GM nephrotoxicity. Metformin (MF) is a well-known, clinically approved oral hypoglycaemic drug that has many other actions, including antioxidant properties. The aim of this work was to evaluate the possible antioxidant and reno-protective effects of TQ and metformin in GM-induced nephrotoxicity in the same model (rats) at the same time. In addition, we aimed to further understand the effects underlying GM-induced nephrotoxicity. Methods: Twenty male rats were randomly divided into four equal groups: the first group (control) received distilled water; the second group received GM only; the third group received concurrent oral TQ and GM; and the fourth group received concurrent oral MF and GM. After 4 weeks, renal function and histopathology, as well as levels of the oxidative markers glutathione peroxidase-1 (GLPX1), superoxide dismutase (SOD), and malondialdehyde (MDA) in the kidney tissues, were assessed. Results: Compared with the control group, and as expected, the GM-injected rats showed significant biochemical and histological changes denoting renal damage. Compared with GM-injected rats, the concurrent administration of TQ with GM significantly reduced the levels of serum creatinine, serum urea, and tissue MDA and significantly increased the levels of GLPX1 and SOD. Concurrent metformin administration with GM significantly increased the levels of both GLPX1 and SOD and significantly decreased the levels of tissue MDA but had no significant effect on serum creatinine and urea levels. Compared with GM-injected rats, the addition of either TQ or MF resulted in a reduction in endothelial proliferation and mesangial hypercellularity. Conclusions: Both TQ and MF effectively alleviated the oxidative stress in GM-induced nephrotoxicity in rats, with TQ but not MF producing a complete reno-protective effect. Further studies for evaluation of different reno-protective mechanisms of TQ should be conducted.
Enabling Flexibility in Manufacturing by Integrating Shopfloor and Process Perception for Mobile Robot Workers
Authors: Bavelos Angelos Christos , Kousi Niki , Gkournelos Christos , Lotsaris Konstantinos , Aivaliotis Sotiris , Michalos George , Makris Sotiris
Published: April 2021

Robotic flexibility in industry is becoming more and more relevant nowadays, especially with the rise of the Industry 4.0 concept. This paper presents a smart execution control framework for enabling the autonomous operation of flexible mobile robot workers. These robot resources are able to autonomously navigate the shopfloor, undertaking multiple operations while acting as assistants to human operators. To enable this autonomous behavior, the proposed framework integrates robot perception functions for the real-time shopfloor and process understanding while orchestrating the process execution. A Digital World Model is deployed synthesizing the sensor data coming from multiple 2D and 3D sensors from the shopfloor. This model is consumed for the perception functions enabling the real-time shopfloor and process perception by the robot workers. This smart control system has been applied and validated in a case study from the automotive sector.
A New Affinely Adjustable Robust Model for Security Constrained Unit Commitment under Uncertainty
Authors: Sierra-Aguilar Juan Esteban , Marín-Cano Cristian Camilo , López-Lezama Jesús M. , Jaramillo-Duque Álvaro , Villegas Juan G.
Published: April 2021

Currently, optimization models for the safe and reliable operation of power systems deal with two major challenges: the first one is the reduction of the computational load when considering N−1 contingencies; the second one is the adequate modeling of the uncertainty of intermittent generation and demand. This paper proposes a new affinely adjustable robust model to solve the security constrained unit commitment problem considering these sources of uncertainty. Linear decision rules, which take into account the forecasts and forecast errors of the different sources of uncertainty, are used for the affine formulation of the dispatch variables, thus allowing the tractability of the model. Another major novelty is that the evaluation of the N−1 security constraints is performed by incorporating a novel method, proposed in the literature, based on the user-cuts concept. This method efficiently and dynamically adds only the binding N−1 security constraints, increasing the computational efficiency of the model when transmission line contingencies are considered. Finally, Monte Carlo simulations on the post-optimization results were run to demonstrate the effectiveness, feasibility and robustness of the solutions provided by the proposed model.
Study of Atomic Hydrogen Concentration in Grain Boundaries of Polycrystalline Diamond Thin Films
Authors: de Obaldía Elida I. , Alcantar-Peña Jesus J. , Wittel Frederick P. , Veyan Jean François , Gallardo-Hernadez Salvador , Koudriavtsev Yury , Berman-Mendoza Dainet , Auciello Orlando
Published: April 2021

This paper describes research focused on investigating the effect of hydrogen (H) atom insertion into the grain boundaries of polycrystalline diamond (PCD) films. This is required in order to understand the key morphological, chemical, physical, and electronic properties of the films. The PCD films were grown using the hot filament chemical vapor deposition (HFCVD) process, with flowing Ar gas mixed with CH4 and H2 gases to control film growth into microcrystalline diamond (MCD, 0.5–3 µm grain sizes), nanocrystalline diamond (NCD, 10–500 nm grain sizes), and ultrananocrystalline diamond (UNCD, 2–5 nm grain sizes) films depending on the Ar/CH4/H2 flow ratios. This study focused on measuring the H atom concentration of the PCD films to determine the effect on the properties indicated above. A simple model is presented, including a hypothesis that the two dangling bonds per unit cell of C atoms serve as the site of hydrogen incorporation. This correlates well with the observed concentration of H atoms in the films. Dangling bonds which are not passivated by hydrogen are postulated to form surface structures which include C double bonds. The Raman peak from these surface structures are the same as observed for transpolyacetyline (TPA). The data reveal that the concentration of H atoms at the grain boundaries is around 1.5 × 1015 atoms/cm2 regardless of grain size. Electrical current measurements, using a conductive atomic force microscopy (CAFM) technique, were performed using an MCD film, showing that the current is concentrated at the grain boundaries. Ultraviolet photo electron spectroscopy (UPS) confirmed that all the PCD films exhibited a metallic behavior. This is to be expected if the nature of grain boundaries is the same regardless of grain size.
Life Cycle Assessment of CO2 Emissions of Online Music and Videos Streaming in Japan
Authors: Tabata Tomohiro , Wang Tse Yu
Published: April 2021

In this study, we analyzed the CO2 emissions of online music and video streaming services, as one of the digital contents, in Japan using life cycle assessment. As a system boundary of online music and video streaming, processes such as data center construction and server manufacturing, usage of communication networks and internet communication technology devices (personal computers (PCs) and smartphones), and disposal of data centers and servers were considered. Data were collected using statistical and online surveys, and CO2 emissions per 1 MB of communication volume were calculated. One of the results revealed that the lifecycle CO2 emissions of listening to online music using PCs and smartphones were 5.88 × 10−4 and 1.43 × 10−4 kg-CO2/MB, respectively. The overall CO2 emissions for domestic music and video streaming services in 2019 was 921 thousand t-CO2. Online video streaming accounted for 87.7% of the total emissions, which corresponded to approximately 0.23% of domestic CO2 emissions derived from electric power generation.
Effects of Treatment Combining 9300 nm Carbon Dioxide Lasers and Fluoride on Prevention of Enamel Caries: A Systematic Review and Meta-Analysis
Authors: Xue Vicky Wenqing , Zhao Irene Shuping , Yin Iris Xiaoxue , Niu John Yun , Lo Edward Chin Man , Chu Chun Hung
Published: April 2021

The objective of this study is to conduct a systematic review of the literatures on the effect of treatment combining 9300 nm carbon dioxide (CO2) lasers and fluoride on prevention of enamel caries. A literature search was performed using PubMed, Scopus, and Web of Science. The keywords were ((9300 nm) OR (9.3 µm) OR (carbon dioxide laser) OR (carbon dioxide lasers) OR (CO2 laser) OR (CO2 lasers)) AND ((fluoride) OR (fluorides)) AND ((dental caries) OR (caries) OR (remineralization) OR (remineralization) OR (demineralization) OR (demineralization)). Meta-analysis was performed to compare the change in mineral content by laser irradiation and fluoride treatment (F + L) with that of fluoride treatment (F) and laser treatment (L). The search identified 946 potential publications and five laboratory studies using a chemical model for cariogenic challenge and determining mineral loss of the enamel were included in this review. Meta-analysis comparing F + L with L on enamel showed a standard mean difference of −1.58 (CI: −2.13, −1.03). Meta-analysis comparing F + L with F on enamel showed a standard mean difference of −1.84 (CI: −2.30, −1.39), with low heterogeneity (I2 = 49%, p = 0.04). In conclusion, F + L was better than L and F in preventing enamel demineralization.
A Convex Combination Approach for Artificial Neural Network of Interval Data
Authors: Yamaka Woraphon , Phadkantha Rungrapee , Maneejuk Paravee
Published: April 2021

As the conventional models for time series forecasting often use single-valued data (e.g., closing daily price data or the end of the day data), a large amount of information during the day is neglected. Traditionally, the fixed reference points from intervals, such as midpoints, ranges, and lower and upper bounds, are generally considered to build the models. However, as different datasets provide different information in intervals and may exhibit nonlinear behavior, conventional models cannot be effectively implemented and may not be guaranteed to provide accurate results. To address these problems, we propose the artificial neural network with convex combination (ANN-CC) model for interval-valued data. The convex combination method provides a flexible way to explore the best reference points from both input and output variables. These reference points were then used to build the nonlinear ANN model. Both simulation and real application studies are conducted to evaluate the accuracy of the proposed forecasting ANN-CC model. Our model was also compared with traditional linear regression forecasting (information-theoretic method, parametrized approach center and range) and conventional ANN models for interval-valued data prediction (regularized ANN-LU and ANN-Center). The simulation results show that the proposed ANN-CC model is a suitable alternative to interval-valued data forecasting because it provides the lowest forecasting error in both linear and nonlinear relationships between the input and output data. Furthermore, empirical results on two datasets also confirmed that the proposed ANN-CC model outperformed the conventional models.
Glycemic Control Potential of Chemically Characterized Extract from Withania frutescens L. Roots in Severe Diabetes-Induced Mice
Authors: El Moussaoui Abdelfattah , Mechchate Hamza , Bourhia Mohammed , Es-safi Imane , Salamatullah Ahmad Mohammad , Alkaltham Mohammed Saeed , Alyahya Heba Khalil , Bousta Dalila , Bari Amina
Published: April 2021

Diabetes mellitus is a metabolic syndrome that causes impairment, mortality, and many other complications. Insulin and several synthetic medications are currently used in the treatment of diabetes. However, these pharmaceutical drugs are costly, and therefore medicines place priority on alternatives to fight this lethal disease. This modest study aims to investigate the chemical composition, antidiabetic and antihyperglycemic potentials along with subacute toxicity (bodyweight change and biochemical parameters) of hydroethanol extract from Withania frutescens L. roots (WFRE). The chemical analysis was carried out using GC–MS after extract silylation. The chemical analysis identified many potentially active compounds that may determine the antidiabetic results of WFRE. The antidiabetic effect of WFRE was evaluated in mice with severe diabetes using oral administration of doses up to 400 mg/kg for 28 days. The results of the antidiabetic and antihyperglycemic tests indicate that WFRE possesses promising glucose-lowering effects and, as a result, it may serve as an antidiabetic alternative for long-term use. The 4-week treatments with different doses of plant extract did not alter the bodyweight appearance of the diabetic mice nor their biochemical parameters (AST and ALT). The findings obtained indicate that the studied plant extract controlled severe diabetes in mice. Therefore, Withania frutescens L. can serve society as it provides natural agents to control diabetes.
An Improved Attention-Based Integrated Deep Neural Network for PM2.5 Concentration Prediction
Authors: Shi Pengfei , Fang Xiaolong , Ni Jianjun , Zhu Jinxiu
Published: April 2021

The air quality prediction is a very important and challenging task, especially PM2.5 (particles with diameter less than 2.5 μm) concentration prediction. To improve the accuracy of the PM2.5 concentration prediction, an improved integrated deep neural network method based on attention mechanism is proposed in this paper. Firstly, the influence of exogenous series of other sites on the central site is considered to determine the best relevant site. Secondly, the data of all relevant sites are input into the improved dual-stage two-phase (DSTP) model, then the PM2.5 prediction result of each site is obtained. Finally, with the PM2.5 prediction result of each site, the attention-based layer predicts the PM2.5 concentration at the central site. The experimental results show that the proposed model is superior to most of the latest models.
Geotechnical Property Modeling and Construction Safety Zoning Based on GIS and BIM Integration
Authors: Khan Muhammad Shoaib , Park Jaemin , Seo Jongwon
Published: April 2021

The increase in population and urbanization needs attention towards intense construction activities to meet the social and economic needs. Soil excavation is a primary step in every construction project that needs proper surface and subsurface information modeling since it is vulnerable to construction hazards. Geographic information system (GIS) provides significant information about the existing contextual surface information while building information modeling (BIM) gives information about the asset in a great detail that has been integrated into the construction industry for many applications. However, the integration of BIM and GIS for the subsurface geotechnical property modeling and classification into zones has been rarely explored. This paper presents the integration of BIM and GIS for modeling geotechnical properties and safe construction zones based on soil type. The use of open standard IFC classes such as IfcBorehole, IfcGeoslice, and IfcGeomodel enhances the collaboration and allows the exchange of geotechnical information among different stakeholders. The method has been applied to the in-situ and laboratory test dataset of the Peshawar, region, to validate the proof of concept. The results demonstrate that the proposed method successfully integrates BIM and GIS providing a three-dimensional surface and subsurface model. The 3D digital geotechnical model has excellent potential to provide information about soil type, properties, depth, and volume of each available soil layer that can be used by construction planners and managers to identify best construction practices and plan for safe construction.
Many-Objective Optimization for Anomaly Detection on Multi-Layer Complex Interaction Networks
Authors: Maulana Asep , Atzmueller Martin
Published: April 2021

Anomaly detection in complex networks is an important and challenging task in many application domains. Examples include analysis and sensemaking in human interactions, e.g., in (social) interaction networks, as well as the analysis of the behavior of complex technical and cyber-physical systems such as suspicious transactions/behavior in financial or routing networks; here, behavior and/or interactions typically also occur on different levels and layers. In this paper, we focus on detecting anomalies in such complex networks. In particular, we focus on multi-layer complex networks, where we consider the problem of finding sets of anomalous nodes for group anomaly detection. Our presented method is based on centrality-based many-objective optimization on multi-layer networks. Starting from the Pareto Front obtained via many-objective optimization, we rank anomaly candidates using the centrality information on all layers. This ranking is formalized via a scoring function, which estimates relative deviations of the node centralities, considering the density of the network and its respective layers. In a human-centered approach, anomalous sets of nodes can then be identified. A key feature of this approach is its interpretability and explainability, since we can directly assess anomalous nodes in the context of the network topology. We evaluate the proposed method using different datasets, including both synthetic as well as real-world network data. Our results demonstrate the efficacy of the presented approach.
Comparison of Amsler–Krumeich and Sandali Classifications for Staging Eyes with Keratoconus
Authors: Giannaccare Giuseppe , Murano Gianluca , Carnevali Adriano , Yu Angeli Christy , Vaccaro Sabrina , Scuteri Gianfranco , Maltese Laura , Scorcia Vincenzo
Published: April 2021

Keratoconus (KC) is the most common corneal ectasia characterized by progressive corneal thinning, protrusion, and irregular astigmatism. The Amsler–Krumeich classification based on the analysis of corneal topography, corneal thickness, refraction and biomicroscopy is the most commonly used; recently, a new classification based on anterior segment Optical Coherence Tomography was introduced by Sandali and colleagues. Since there is no information about the possible agreement between these two classifications, the aim of this study is to compare the stratification of consecutive KC patients using the Amsler–Krumeich and Sandali classifications, and to further ascertain KC cases in which one classification is preferred over the other. Overall, 252 eyes of 137 patients (41.45 ± 16.93 years) were analyzed: in 156 eyes (61.9%), the Amsler and Sandali staging differed in one stage while in 75 cases (29.8%) it differed in two or more stages. In 222 eyes (88.1%), the Sandali staging was higher compared to the Amsler one. These results show that the two classifications are not fully interchangeable: the Amsler–Krumeich classification is more appropriate in identifying and longitudinally monitoring patients with early stages of KC, while the Sandali classification for the diagnosis and follow-up of patients with more advanced stages, particularly when a surgical planning has to be chosen.
Fast and High Precise Spatial Documentation of Traffic Accident Site Using Only Low-Cost RPAS
Authors: Stuchlík Radim , Kubíček Petr
Published: April 2021

Traffic accident documentation worldwide is generally done by conventional methods (e.g., surveying wheel and steel tapeline) followed by sketch and plan creation. These conventional methods are time-consuming and inaccurate; therefore, they can possibly be replaced by advanced modern methods, using the remotely piloted aircraft system (RPAS) for obtaining data, as well as the structure from motion (SfM) for processing. For the proof of concept, we designed and performed an experiment using low-cost multi-rotor RPAS on an arranged traffic accident involving three cars. The result of this experiment was an accurate 3D model with the possibility of precise measurement. The differences in distances and reference objects’ dimensions were in general below 1% compared to real values. The presented method is time-saving (requiring 85% less time), more precise, and more efficient compared to conventional methods. Moreover, it allows better data reusability, thus is very suitable and can be recommended for usage in routine situations in traffic accident documentation.
Investigations of the Absorption Front in High-Speed Laser Processing Up to 600 m/min
Authors: Hellwig Peter , Schricker Klaus , Bergmann Jean Pierre
Published: April 2021

High processing speeds enormously enlarge the number of possible fields of application for laser processes. For example, material removal for sheet cutting using multiple passes or precise mass corrections can be achieved by means of spatter formation. For a better understanding of spatter formation at processing speeds of several hundred meters per minute, characterizations of the processing zone are required. For this purpose, a 400 W single-mode fiber laser was used in this study to process stainless steel AISI 304 (1.4301/X5CrNi18-10) with speeds of up to 600 m/min. A setup was developed that enabled a lateral high-speed observation of the processing zone by means of a glass plate flanking. This approach allowed for the measurement of several dimensions, such as the penetration depth, spatter formation, and especially, the inclination angle of the absorption front. It was shown that the loss of mass started to significantly increase when the absorption front was inclined at about 60°. In combination with precise weighings, metallographic examinations, and further external process observations, these findings provided an illustration of four empirical process models for different processing speeds.
Supervised Machine Learning Approach for Detecting Missing Clamps in Rail Fastening System from Differential Eddy Current Measurements
Authors: Chandran Praneeth , Thierry Florian , Odelius Johan , Famurewa Stephen M. , Lind Håkan , Rantatalo Matti
Published: April 2021

The rail fastening system forms an integral part of rail tracks, as it maintains the rail in a fixed position, upholding the track stability and track gauge. Hence, it becomes necessary to monitor their conditions periodically to ensure safe and reliable operation of the railway. Inspection is normally carried out manually by trained operators or by employing 2-D visual inspection methods. However, these methods have drawbacks when visibility is minimal and are found to be expensive and time consuming. In the previous study, the authors proposed a train-based differential eddy current sensor system that uses the principle of electromagnetic induction for inspecting the railway fastening system that can overcome the above-mentioned challenges. The sensor system includes two individual differential eddy current sensors with a driving field frequency of 18 kHz and 27 kHz respectively. This study analyses the performance of a machine learning algorithm for detecting and analysing missing clamps within the fastening system, measured using a train-based differential eddy current sensor. The data required for the study was collected from field measurements carried out along a heavy haul railway line in the north of Sweden, using the train-based differential eddy current sensor system. Six classification algorithms are tested in this study and the best performing model achieved a precision and recall of 96.64% and 95.52% respectively. The results from the study shows that the performance of the machine learning algorithms improved when features from both the driving channels were used simultaneously to represent the fasteners. The best performing algorithm also maintained a good balance between the precision and recall scores during the test stage.
A Review of the Challenges in Deep Learning for Skeletal and Smooth Muscle Ultrasound Images
Authors: Ardhianto Peter , Tsai Jen-Yung , Lin Chih-Yang , Liau Ben-Yi , Jan Yih-Kuen , Akbari Veit Babak Hamun , Lung Chi-Wen
Published: April 2021

Deep learning has aided in the improvement of diagnosis identification, evaluation, and the interpretation of muscle ultrasound images, which may benefit clinical personnel. Muscle ultrasound images presents challenges such as low image quality due to noise, insufficient data, and different characteristics between skeletal and smooth muscles that can affect the effectiveness of deep learning results. From 2018 to 2020, deep learning has the improved solutions used to overcome these challenges; however, deep learning solutions for ultrasound images have not been compared to the conditions and strategies used to comprehend the current state of knowledge for handling skeletal and smooth muscle ultrasound images. This study aims to look at the challenges and trends of deep learning performance, especially in regard to overcoming muscle ultrasound image problems such as low image quality, muscle movement in skeletal muscles, and muscle thickness in smooth muscles. Skeletal muscle segmentation presents difficulties due to the regular movement of muscles and resulting noise, recording data through skipped connections, and modified layers required for upsampling. In skeletal muscle classification, the problems faced are area-specific, thus making a cropping strategy useful. Furthermore, there is no need to add additional layer modifications for smooth muscle segmentation as muscle thickness is the main problem in such cases.
Becoming Asia’s Art Market Hub: Comparing Singapore and Hong Kong
Authors: Molho Jeremie
Published: April 2021

The recent emergence of new regions in the global art market has been structured by hub cities that concentrate key actors, such as global auction houses, influential art fairs, and galleries. Both Singapore and Hong Kong have developed explicit strategies aimed at positioning themselves as Asia’s art market hub. This followed the steep rise of the Chinese art market, but also the general perception of Asia as the world’s most dynamic art market. While Hong Kong’s emergence derives from its status as gateway to the Chinese market, and has been driven by key global players, such as the auction houses Christies’ and Sotheby’s, the Art Basel fair, and mega-galleries, Singapore’s strategy has been driven by the state. At the end of the 2000s, the city identified the art market as a new growth sector, and proactively invested, by creating a cluster concentrating international galleries and supporting art fairs, art weeks, and new world-class cultural institutions. Based on comparative fieldwork, and interviews with actors of the Singapore and Hong Kong art markets, this article shows that the two cities’ distinct strategies have generated contrasted models of “cultural hubs”, and that they play complementary roles in the structuration of the region’s art market.
Street Photography Reframed
Authors: Schwartz Stephanie
Published: April 2021

Afraid of contagion [...]
Ubiquitin Conjugating Enzyme E2 H (UBE2H) Is Linked to Poor Outcomes and Metastasis in Lung Adenocarcinoma
Authors: Yen Meng-Chi , Wu Kuan-Li , Liu Yu-Wei , Chang Yung-Yun , Chang Chao-Yuan , Hung Jen-Yu , Tsai Ying-Ming , Hsu Ya-Ling
Published: April 2021

The prognosis of patients with metastatic lung adenocarcinoma (LUAD) is poor. Although novel lung cancer treatments have been developed for metastatic LUAD, not all patients are fit to receive these treatments. The present study aimed to identify the novel regulatory genes in metastatic LUAD. Because the pleural cavity is a frequent metastasis site of LUAD, the adjacent non-tumor tissue, primary tumor tissue, and metastatic lung tumor tissue in the pleura of a single patient with LUAD were collected. The gene expression profiles of the collected samples were further analyzed via RNA sequencing and bioinformatic analysis. A high expression level of ubiquitin conjugating enzyme E2 H (UBE2H), a hypoxia-mediated gene, was identified in the metastatic malignant pleural tumor. After accessing the survival data in patients with lung adenocarcinoma through online databases, a high UBE2H expression was associated with poor survival for LUAD. UBE2H knockdown in two lung adenocarcinoma cell lines suppressed the cell migration capacity and reversed the epithelial–mesenchymal transition (EMT) signaling pathway. A high expression of UBE2H-targeting microRNAs, including miR-101, miR-30a, miR-30b, miR-328, and miR-497, were associated with a favorable prognosis. Moreover, the UBE2H expression revealed a significant correlation with the copy number variation. Taken together, the presence of UBE2H regulated the EMT program and metastasis in LUAD.
Comparative Analysis of Periodontal Pain According to the Type of Precision Orthodontic Appliances: Vestibular, Lingual and Aligners. A Prospective Clinical Study
Authors: Antonio-Zancajo Laura , Montero Javier , Garcovich Daniele , Alvarado-Lorenzo Mario , Albaladejo Alberto , Alvarado-Lorenzo Alfonso
Published: April 2021

The objective of this prospective clinical study was to analyze the pain (intensity, location and type) that patients presented after the placement of different types of orthodontic appliances: conventional, low friction, lingual and aligners. The sample consisted of 120 patients divided into four groups: conventional (CON), low friction (LF), lingual (LO) and aligners (INV). The participants were given the Short-Form McGill Pain Questionnaire (Ortho-SF-MPQ), where they had to record the pain intensity (no pain, mild, moderate or intense) and the periodontal location at different time points, from the first 4 h to 7 days after the start of treatment. In all the study groups, the most frequent location was both anterior arches, with maximum values between 56.7% (CON group at 24 h) and 30% (LO group at 4 h). The “whole mouth” and “complete lower arch” locations were indicated only by the patients in the lingual group. Regarding pain intensity, the patients reported a higher percentage of mild–moderate pain during the first 3 days of treatment (96.7% in LO at 4 h, 86.7% in CON, 83.3% in LF and 90% in INV at 24 h); later, the reported pain decreased to no pain/mild pain, especially in the lingual group, until reaching values close to zero at 7 days post-treatment. The most frequent type of pain was acute in the low friction and lingual groups (with maxima of 60% and 46.7% at 24 h, respectively). On the contrary, in the conventional (36.7% at 4 h) and Invisalign (40% at 24 h) groups, the sensitive type was the most frequent. There are differences regarding periodontal pain in its intensity, location and type according to the use of different orthodontic techniques.
Targeting RIP Kinases in Chronic Inflammatory Disease
Authors: Speir Mary , Djajawi Tirta M. , Conos Stephanie A. , Tye Hazel , Lawlor Kate E.
Published: April 2021

Chronic inflammatory disorders are characterised by aberrant and exaggerated inflammatory immune cell responses. Modes of extrinsic cell death, apoptosis and necroptosis, have now been shown to be potent drivers of deleterious inflammation, and mutations in core repressors of these pathways underlie many autoinflammatory disorders. The receptor-interacting protein (RIP) kinases, RIPK1 and RIPK3, are integral players in extrinsic cell death signalling by regulating the production of pro-inflammatory cytokines, such as tumour necrosis factor (TNF), and coordinating the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome, which underpin pathological inflammation in numerous chronic inflammatory disorders. In this review, we firstly give an overview of the inflammatory cell death pathways regulated by RIPK1 and RIPK3. We then discuss how dysregulated signalling along these pathways can contribute to chronic inflammatory disorders of the joints, skin, and gastrointestinal tract, and discuss the emerging evidence for targeting these RIP kinases in the clinic.
Reflections on Cerebellar Neuropathology in Classical Scrapie
Authors: Toledano-Díaz Adolfo , Álvarez María Isabel , Rodríguez Jose-Julio , Badiola Juan Jose , Monzón Marta , Toledano Adolfo
Published: April 2021

In this review, the most important neuropathological changes found in the cerebella of sheep affected by classical natural scrapie are discussed. This disease is the oldest known of a group of unconventional “infections” caused by toxic prions of different origins. Scrapie is currently considered a “transmissible spongiform encephalopathy” (due to its neuropathological characteristics and its transmission), which is the paradigm of prion pathologies as well as many encephalopathies (prion-like) that present aberrant deposits of insoluble protein with neurotoxic effects due to errors in their catabolization (“misfolding protein diseases”). The study of this disease is, therefore, of great relevance. Our work data from the authors’ previous publications as well as other research in the field. The four most important types of neuropathological changes are neuron abnormalities and loss, neurogliosis, tissue vacuolization (spongiosis) and pathological or abnormal prion protein (PrP) deposits/deposition. These findings were analyzed and compared to other neuropathologies. Various aspects related to the presentation and progression of the disease, the involution of different neuronal types, the neuroglial responses and the appearance of abnormal PrP deposits are discussed. The most important points of controversy in scrapie neuropathology are presented.
Rapamycin Improves Spatial Learning Deficits, Vulnerability to Alcohol Addiction and Altered Expression of the GluN2B Subunit of the NMDA Receptor in Adult Rats Exposed to Ethanol during the Neonatal Period
Authors: Lopatynska-Mazurek Malgorzata , Antolak Anna , Grochecki Pawel , Gibula-Tarlowska Ewa , Bodzon-Kulakowska Anna , Listos Joanna , Kedzierska Ewa , Suder Piotr , Silberring Jerzy , Kotlinska Jolanta H.
Published: April 2021

Ethanol exposure during pregnancy alters the mammalian target of rapamycin (mTOR) signaling pathway in the fetal brain. Hence, in adult rats exposed to ethanol during the neonatal period, we investigated the influence of rapamycin, an mTOR Complex 1 (mTORC1) inhibitor, on deficits in spatial memory and reversal learning in the Barnes maze task, as well as the ethanol-induced rewarding effects (1.0 or 1.5 g/kg) using the conditioning place preference (CPP) paradigm. Rapamycin (3 and 10 mg/kg) was given before intragastric ethanol (5 g/kg/day) administration at postnatal day (PND)4–9 (an equivalent to the third trimester of human pregnancy). Spatial memory/reversal learning and rewarding ethanol effect were evaluated in adult (PND60–70) rats. Additionally, the impact of rapamycin pre-treatment on the expression of the GluN2B subunit of NMDA receptor in the brain was assessed in adult rats. Our results show that neonatal ethanol exposure induced deficits in spatial memory and reversal learning in adulthood, but the reversal learning outcome may have been due to spatial learning impairments rather than cognitive flexibility impairments. Furthermore, in adulthood the ethanol treated rats were also more sensitive to the rewarding effect of ethanol than the control group. Rapamycin prevented the neonatal effect of ethanol and normalized the GluN2B down-regulation in the hippocampus and the prefrontal cortex, as well as normalized this subunit’s up-regulation in the striatum of adult rats. Our results suggest that rapamycin and related drugs may hold promise as a preventive therapy for fetal alcohol spectrum disorders.