bluuebunny/crossref_metadata_2025 huggingface dataset:
SARS-CoV-2 IgG Antibodies Seroprevalence and Sera Neutralizing Activity in MEXICO: A National Cross-Sectional Study during 2020
Authors: Muñoz-Medina José Esteban , Grajales-Muñiz Concepción , Salas-Lais Angel Gustavo , Fernandes-Matano Larissa , López-Macías Constantino , Monroy-Muñoz Irma Eloísa , Santos Coy-Arechavaleta Andrea , Palomec-Nava Iliana Donají , Duque-Molina Célida , Madera-Sandoval Ruth Lizzeth , Rivero-Arredondo Vanessa , González-Ibarra Joaquín , Alvarado-Yaah Julio Elías , Rojas-Mendoza Teresita , Santacruz-Tinoco Clara Esperanza , González-Bonilla Cesar Raúl , Borja-Aburto Víctor Hugo
Published: April 2021

Until recently, the incidence of COVID-19 was primarily estimated using molecular diagnostic methods. However, the number of cases is vastly underreported using these methods. Seroprevalence studies estimate cumulative infection incidences and allow monitoring of transmission dynamics, and the presence of neutralizing antibodies in the population. In February 2020, the Mexican Social Security Institute began conducting anonymous unrelated sampling of residual sera from specimens across the country, excluding patients with fever within the previous two weeks and/or patients with an acute respiratory infection. Sampling was carried out weekly and began 17 days before Mexico’s first officially confirmed case. The 24,273 sera obtained were analyzed by chemiluminescent-linked immunosorbent assay (CLIA) IgG S1/S2 and, later, positive cases using this technique were also analyzed to determine the rate of neutralization using the enzyme-linked immunosorbent assay (ELISA). We identified 40 CLIA IgG positive cases before the first official report of SARS-CoV-2 infection in Mexico. The national seroprevalence was 3.5% in February and 33.5% in December. Neutralizing activity among IgG positives patients during overall study period was 86.1%. The extent of the SARS-CoV-2 infection in Mexico is 21 times higher than that reported by molecular techniques. Although the general population is still far from achieving herd immunity, epidemiological indicators should be re-estimated based on serological studies of this type.
Growth of Staphylococcus epidermidis on the Surface of Teatcups from Milking Parlours
Authors: Katsarou Eleni I. , Katsafadou Angeliki I. , Karakasidis Theodoros , Chatzopoulos Dimitris C. , Vasileiou Natalia G. C. , Lianou Daphne T. , Mavrogianni Vasia S. , Petinaki Efthymia , Fthenakis George C.
Published: April 2021

The growth of two Staphylococcus epidermidis isolates (one biofilm-forming and one not) on teatcups for cattle (made of rubber) or sheep (made of silicone) were assessed in nine multiplicates for 24 h post-smearing on the teatcup surface. Staphylococci were smeared on an area of 0.0003142 m2 on the material and their growth and expansion further on were monitored for 24 h. There were no differences in the frequency of recoveries between the two isolates (p > 0.82 for all comparisons). There were more recoveries from sheep teatcups than from cattle teatcups: 1280/1728 (74.1%) versus 942/1728 (54.5%), for both isolates (p < 0.0001). Significance was observed only 6 h to 15 h after smearing (p < 0.0001 for all comparisons). The median speed of linear dissemination of the isolates was 0.00000021 m s−1 on cattle teatcups and 0.00000033 m s−1 on sheep teatcups (p < 0.0001). The increased growth and faster expansion of staphylococci on silicone teatcups raise important points from a clinical viewpoint. The model could be used in the testing of staphylococcal growth in the material of milking parlours in various conditions.
Classification of Salmonella enterica of the (Para-)Typhoid Fever Group by Fourier-Transform Infrared (FTIR) Spectroscopy
Authors: Cordovana Miriam , Mauder Norman , Kostrzewa Markus , Wille Andreas , Rojak Sandra , Hagen Ralf Matthias , Ambretti Simone , Pongolini Stefano , Soliani Laura , Justesen Ulrik S. , Holt Hanne M. , Join-Lambert Olivier , Hello Simon Le , Auzou Michel , Veloo Alida C. , May Jürgen , Frickmann Hagen , Dekker Denise
Published: April 2021

Typhoidal and para-typhoidal Salmonella are major causes of bacteraemia in resource-limited countries. Diagnostic alternatives to laborious and resource-demanding serotyping are essential. Fourier transform infrared spectroscopy (FTIRS) is a rapidly developing and simple bacterial typing technology. In this study, we assessed the discriminatory power of the FTIRS-based IR Biotyper (Bruker Daltonik GmbH, Bremen, Germany), for the rapid and reliable identification of biochemically confirmed typhoid and paratyphoid fever-associated Salmonella isolates. In total, 359 isolates, comprising 30 S. Typhi, 23 S. Paratyphi A, 23 S. Paratyphi B, and 7 S. Paratyphi C, respectively and other phylogenetically closely related Salmonella serovars belonging to the serogroups O:2, O:4, O:7 and O:9 were tested. The strains were derived from clinical, environmental and food samples collected at different European sites. Applying artificial neural networks, specific automated classifiers were built to discriminate typhoidal serovars from non-typhoidal serovars within each of the four serogroups. The accuracy of the classifiers was 99.9%, 87.0%, 99.5% and 99.0% for Salmonella Typhi, Salmonella Paratyphi A, B and Salmonella Paratyphi C, respectively. The IR Biotyper is a promising tool for fast and reliable detection of typhoidal Salmonella. Hence, IR biotyping may serve as a suitable alternative to conventional approaches for surveillance and diagnostic purposes.
Deconstruction of Lignin: From Enzymes to Microorganisms
Authors: Silva Jéssica P. , Ticona Alonso R. P. , Hamann Pedro R. V. , Quirino Betania F. , Noronha Eliane F.
Published: April 2021

Lignocellulosic residues are low-cost abundant feedstocks that can be used for industrial applications. However, their recalcitrance currently makes lignocellulose use limited. In natural environments, microbial communities can completely deconstruct lignocellulose by synergistic action of a set of enzymes and proteins. Microbial degradation of lignin by fungi, important lignin degraders in nature, has been intensively studied. More recently, bacteria have also been described as able to break down lignin, and to have a central role in recycling this plant polymer. Nevertheless, bacterial deconstruction of lignin has not been fully elucidated yet. Direct analysis of environmental samples using metagenomics, metatranscriptomics, and metaproteomics approaches is a powerful strategy to describe/discover enzymes, metabolic pathways, and microorganisms involved in lignin breakdown. Indeed, the use of these complementary techniques leads to a better understanding of the composition, function, and dynamics of microbial communities involved in lignin deconstruction. We focus on omics approaches and their contribution to the discovery of new enzymes and reactions that impact the development of lignin-based bioprocesses.
Discovery of Potential, Dual-Active Histamine H3 Receptor Ligands with Combined Antioxidant Properties
Authors: Kuder Kamil J. , Kotańska Magdalena , Szczepańska Katarzyna , Mika Kamil , Reiner-Link David , Stark Holger , Kieć-Kononowicz Katarzyna
Published: April 2021

In an attempt to find new dual acting histamine H3 receptor (H3R) ligands, we designed a series of compounds, structurally based on previously described in our group, a highly active and selective human histamine H3 receptor (hH3R) ligand KSK63. As a result, 15 obtained compounds show moderate hH3R affinity, the best being the compound 17 (hH3R Ki = 518 nM). Docking to the histamine H3R homology model revealed two possible binding modes, with key interactions retained in both cases. In an attempt to find possible dual acting ligands, selected compounds were tested for antioxidant properties. Compound 16 (hH3R Ki = 592 nM) showed the strongest antioxidant properties at the concentration of 10−4 mol/L. It significantly reduced the amount of free radicals presenting 50–60% of ascorbic acid activity in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, as well as showed antioxidative properties in the ferric reducing antioxidant power (FRAP) assay. Despite the yet unknown antioxidation mechanism and moderate hH3R affinity, 16 (QD13) constitutes a starting point for the search of potential dual acting H3R ligands-promising tools for the treatment of neurological disorders associated with increased neuronal oxidative stress.
GC-MS Discrimination of Citrulline from Ornithine and Homocitrulline from Lysine by Chemical Derivatization: Evidence of Formation of N5-Carboxy-ornithine and N6-Carboxy-lysine
Authors: Baskal Svetlana , Bollenbach Alexander , Tsikas Dimitrios
Published: April 2021

Derivatization of amino acids by 2 M HCl/CH3OH (60 min, 80 °C) followed by derivatization of the intermediate methyl esters with pentafluoropropionic anhydride (PFPA) in ethyl acetate (30 min, 65 °C) is a useful two-step derivatization procedure (procedure A) for their quantitative measurement in biological samples by gas chromatography-mass spectrometry (GC-MS) as methyl ester pentafluoropropionic (PFP) derivatives, (Me)m-(PFP)n. This procedure allows in situ preparation of trideutero-methyl esters PFP derivatives, (d3Me)m-(PFP)n, from synthetic amino acids and 2 M HCl/CD3OD for use as internal standards. However, procedure A converts citrulline (Cit) to ornithine (Orn) and homocitrulline (hCit) to lysine (Lys) due to the instability of their carbamide groups under the acidic conditions of the esterification step. In the present study, we investigated whether reversing the order of the two-step derivatization may allow discrimination and simultaneous analysis of these amino acids. Pentafluoropropionylation (30 min, 65 °C) and subsequent methyl esterification (30 min, 80 °C), i.e., procedure B, of Cit resulted in the formation of six open and cyclic reaction products. The most abundant product is likely to be N5-Carboxy-Orn. The second most abundant product was confirmed to be Orn. The most abundant reaction product of hCit was confirmed to be Lys, with the minor reaction product likely being N6-Carboxy-Lys. Mechanisms are proposed for the formation of the reaction products of Cit and hCit via procedure B. It is assumed that at the first derivatization step, amino acids form (N,O)-PFP derivatives including mixed anhydrides. At the second derivatization step, the Cit-(PFP)4 and hCit-(PFP)4 are esterified on their C1-Carboxylic groups and on their activated Nureido groups. Procedure B also allows in situ preparation of (d3Me)m-(PFP)n from synthetic amino acids for use as internal standards. It is demonstrated that the derivatization procedure B enables discrimination between Cit and Orn, and between hCit and Lys. The utility of procedure B to measure simultaneously these amino acids in biological samples such as plasma and urine remains to be demonstrated. Further work is required to optimize the derivatization conditions of procedure B for biological amino acids.
Diet in the Management of Weight Loss
Authors: Martínez-Vizcaíno Vicente , Álvarez-Bueno Celia , Cavero-Redondo Iván
Published: April 2021

The prevalence of obesity and related disorders has been growing at an alarming rate in both wealthy and middle–low-income countries [...]
Experiential Learning in a Gamified Pharmacy Simulation: A Qualitative Exploration Guided by Semantic Analysis
Authors: Hope Denise L. , Rogers Gary D. , Grant Gary D. , King Michelle A.
Published: April 2021

Experiential learning is an important component of pharmacist education and is primarily achieved through supervised placement or simulation. This study explored senior pharmacy students’ experiential learning in an extended, immersive, gamified simulation, conducted as a capstone learning activity toward the end of their final year of study, consolidating all prior learning and preparing students for intern practice. The simulation aimed to enhance student confidence, competence and collaboration. The three-week activity involved student teams competitively managing simulated pharmacies, assuming the role of pharmacists to complete all scaffolded assessments, including dispensing prescriptions, clinical cases, verbal counselling, simulated patient cases, interprofessional collaboration, and assignments. Assessments were marked continuously, with consequences of practice acknowledged through gain or loss of ‘patients’ for the pharmacy. From 2016 to 2018, 123 students completed multiple individual reflective journals (n = 733). Reflective journals were analyzed to explore the student experience, using a mixed methods approach. Initial Leximancer® 4.51 semantic analysis guided thematic analysis, conducted in NVivo® 12. The major themes that emerged were teamwork, patient-centeredness, medicines provision, future practice, and the learning experience. Student participants reported an intense and emotional experience in the gamified simulation, with many students revealing transformation in their skills, behaviors and attitudes over its duration.
Gluten-Free Rice Instant Pasta: Effect of Extrusion-Cooking Parameters on Selected Quality Attributes and Microstructure
Authors: Bouasla Abdallah , Wójtowicz Agnieszka
Published: April 2021

In the present study, we applied extrusion-cooking to polished rice flour so as to prepare gluten-free pasta. The aim of the work was to investigate the effect of feed moisture (28, 30 and 32%) and screw speed (60, 80 and 100 rpm) on selected rice pasta quality attributes (water absorption, cooking loss, firmness, stickiness and microstructure) and extrusion response (specific mechanical energy). Our results showed that feed moisture significantly affected all tested quality attributes of the rice pasta, while screw speed exhibited a significant effect on all quality attributes except cooking time and stickiness. Moreover, raising the feed moisture increased the cooking time, water absorption, cooking loss, hardness and stickiness, but decreased the firmness at high screw speed. In addition, increasing the screw speed enhanced the cooking loss and hardness, but diminished the water absorption and firmness of pasta with low feed moisture. Rice pasta prepared with 30% moisture content and at 80 rpm showed adequate quality, as confirmed by a firm texture and low cooking loss and stickiness. Microstructure analysis showed a compact and dense internal structure of the dry pasta, and the surface was smooth and even when at least 30% moisture was applied at 80 rpm screw speed during processing.
Fuzzy Static Output Control of T–S Fuzzy Stochastic Systems via Line Integral Lyapunov Function
Authors: Ku Cheung-Chieh , Yeh Yun-Chen , Lin Yann-Hong , Hsieh Yu-Yen
Published: April 2021

Considering some unmeasurable states, a fuzzy static output control problem of nonlinear stochastic systems is discussed in this paper. Based on a modelling approach, a Takagi–Sugeno (T–S) fuzzy system, constructed by a family of stochastic differential equations and membership functions, is applied to represent nonlinear stochastic systems. Parallel distributed compensation (PDC) technology is used to construct the static output controller. A line-integral Lyapunov function (LILF) is used to derive some sufficient conditions for guaranteeing the asymptotical stability in the mean square. From the LILF, a potential conservatism produced by the derivative of the membership function is eliminated to increase the relaxation of sufficient conditions. Furthermore, those conditions are transferred into linear matrix inequality (LMI) form via projection lemma. According to the convex optimization algorithm, the feasible solutions are directly obtained to establish the static output fuzzy controller. Finally, a numerical example is applied to demonstrate the effectiveness and usefulness of the proposed design method.
Simulation of Diffusion Processes in Chemical and Thermal Processing of Machine Parts
Authors: Kostyk Kateryna , Hatala Michal , Kostyk Viktoriia , Ivanov Vitalii , Pavlenko Ivan , Duplakova Darina
Published: April 2021

To solve a number of technological issues, it is advisable to use mathematical modeling, which will allow us to obtain the dependences of the influence of the technological parameters of chemical and thermal treatment processes on forming the depth of the diffusion layers of steels and alloys. The paper presents mathematical modeling of diffusion processes based on the existing chemical and thermal treatment of steel parts. Mathematical modeling is considered on the example of 38Cr2MoAl steel after gas nitriding. The gas nitriding technology was carried out at different temperatures for a duration of 20, 50, and 80 h in the SSHAM-12.12/7 electric furnace. When modeling the diffusion processes of surface hardening of parts in general, providing a specifically given distribution of nitrogen concentration over the diffusion layer’s depth from the product’s surface was solved. The model of the diffusion stage is used under the following assumptions: The diffusion coefficient of the saturating element primarily depends on temperature changes; the metal surface is instantly saturated to equilibrium concentrations with the saturating atmosphere; the surface layer and the entire product are heated unevenly, that is, the product temperature is a function of time and coordinates. Having satisfied the limit, initial, and boundary conditions, the temperature distribution equations over the diffusion layer’s depth were obtained. The final determination of the temperature was solved by an iterative method. Mathematical modeling allowed us to get functional dependencies for calculating the temperature distribution over the depth of the layer and studying the influence of various factors on the body’s temperature state of the body.
Noise-Assisted Discord-Like Correlations in Light-Harvesting Photosynthetic Complexes
Authors: Reséndiz-Vázquez Pablo , Román-Ancheyta Ricardo , de J. León-Montiel Roberto
Published: April 2021

Transport phenomena in photosynthetic systems have attracted a great deal of attention due to their potential role in devising novel photovoltaic materials. In particular, energy transport in light-harvesting complexes is considered quite efficient due to the balance between coherent quantum evolution and decoherence, a phenomenon coined Environment-Assisted Quantum Transport (ENAQT). Although this effect has been extensively studied, its behavior is typically described in terms of the decoherence’s strength, namely weak, moderate or strong. Here, we study the ENAQT in terms of quantum correlations that go beyond entanglement. Using a subsystem of the Fenna–Matthews–Olson complex, we find that discord-like correlations maximize when the subsystem’s transport efficiency increases, while the entanglement between sites vanishes. Our results suggest that quantum discord is a manifestation of the ENAQT and highlight the importance of beyond-entanglement correlations in photosynthetic energy transport processes.
Neutron Beam Characterization at Neutron Radiography (NRAD) Reactor East Beam Following Reactor Modifications
Authors: Giegel Sam H. , Craft Aaron E. , Papaioannou Glen C. , Smolinski Andrew T. , Pope Chad L.
Published: April 2021

The Neutron Radiography Reactor at Idaho National Laboratory (INL) has two beamlines extending radially outward from the east and north faces of the reactor core. The control rod withdrawal procedure has recently been altered, potentially changing power distribution of the reactor and thus the properties of the neutron beams, calling for characterization of the neutron beams. The characterization of the East Radiography Station involved experiments used to measure the following characteristics: Neutron flux, neutron beam uniformity, cadmium ratio, image quality, and the neutron energy spectrum. The ERS is a Category-I neutron radiography facility signifying it has the highest possible rank a radiography station can achieve. The thermal equivalent neutron flux was measured using gold foil activation and determined to be 9.61 × 106 ± 2.47 × 105 n/cm2-s with a relatively uniform profile across the image plane. The cadmium ratio measurement was performed using bare and cadmium-covered gold foils and measured to be 2.05 ± 2.9%, indicating large epithermal and fast neutron content in the beam. The neutron energy spectrum was measured using foil activation coupled with unfolding algorithms provided by the software package Unfolding with MAXED and GRAVEL (UMG). The Monte-Carlo N-Particle (MCNP6) transport code was used to assist with the unfolding process. UMG, MCNP6, and measured foil activities were used to determine a neutron energy spectrum which was implemented into the MCNP6 model of the east neutron beam to contribute to future studies.
The Recycling of Waste Laminated Glass through Decomposition Technologies
Authors: Šooš Ľubomír , Matúš Miloš , Pokusová Marcela , Čačko Viliam , Bábics Jozef
Published: April 2021

Laminated glass is ever more frequently used nowadays. This applies to the automobile industry and the construction industry. In cars, this refers mostly to the front and rear windows, whereas in construction, technical safety glass is used for railings and window glass. The task of this type of glass is to provide sufficient resistance against mechanical impact and unpleasant weather conditions. At the same time, if it is damaged, it has to break into the smallest possible pieces, or, wherever possible, the glass should remain intact on the interlayer film to prevent shards from injuring people and animals in the immediate vicinity. The paper deals with the recycling of laminated glass, especially with the effective separation of glass (in the form of cullet) from the polyvinyl butyral (PVB) interlayer film. The experimental research is focused on the mechanical separation of glass from the interlayer film by vibration, and also on the chemical cleaning of PVB film in order to allow subsequent recycling of both materials. The results quantify the efficiency of mechanical separation in the form of weight loss of the sample of laminated glass and define the particle size distribution of glass cullet, which is an important parameter in the possibility of glass recycling. The research leads to a methodology proposal for the separation of glass and PVB film and the design of equipment for this method.
Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing
Authors: Zheng Yaoyao , Li Yao , Hou Hao , Murayama Yuji , Wang Ruci , Hu Tangao
Published: April 2021

The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands.
High-Resolution Mangrove Forests Classification with Machine Learning Using Worldview and UAV Hyperspectral Data
Authors: Jiang Yufeng , Zhang Li , Yan Min , Qi Jianguo , Fu Tianmeng , Fan Shunxiang , Chen Bowei
Published: April 2021

Mangrove forests, as important ecological and economic resources, have suffered a loss in the area due to natural and human activities. Monitoring the distribution of and obtaining accurate information on mangrove species is necessary for ameliorating the damage and protecting and restoring mangrove forests. In this study, we compared the performance of UAV Rikola hyperspectral images, WorldView-2 (WV-2) satellite-based multispectral images, and a fusion of data from both in the classification of mangrove species. We first used recursive feature elimination‒random forest (RFE-RF) to select the vegetation’s spectral and texture feature variables, and then implemented random forest (RF) and support vector machine (SVM) algorithms as classifiers. The results showed that the accuracy of the combined data was higher than that of UAV and WV-2 data; the vegetation index features of UAV hyperspectral data and texture index of WV-2 data played dominant roles; the overall accuracy of the RF algorithm was 95.89% with a Kappa coefficient of 0.95, which is more accurate and efficient than SVM. The use of combined data and RF methods for the classification of mangrove species could be useful in biomass estimation and breeding cultivation.
Managing Agricultural Water Considering Water Allocation Priority Based on Remote Sensing Data
Authors: Luo Biao , Zhang Fan , Liu Xiao , Pan Qi , Guo Ping
Published: April 2021

To fairly distribute limited irrigation water resources in arid regions, a water allocation priority evaluation method based on remote sensing data was proposed and integrated with an optimization model. First, the water supply response unit was divided according to canal system conditions. Then, a spatialization method was used for generating spatial agricultural output value (income from planting industry) and grain yield (yield of food crops) with the help of NDVI and the potential yield of farmland. Third, the AHP-TOPSIS method was employed to calculate the water allocation priority based on the above information. Finally, the evaluation results were integrated with a nonlinear multiobjective model to optimally allocate agricultural land and water resources, considering the combined objective of minimum envy and proportional fairness. The method was applied to Hetao irrigation area, an arid agriculture-dominant region in Northwest China. After solving the model, optimization alternatives were obtained, which indicate that: (1) the spatial method of agricultural output value can improve the accuracy by around 16% compared with the traditional method, and the spatial method of grain yield also have good accuracy (MAPE = 14.66%); (2) the rank of water allocation priority can reflect more spatial information, and provide practical decision support for the distribution of water resources; (3) the envy index can better improve the efficiency of an allocation system compared to the Gini coefficient method.
Efficient Rock Mass Point Cloud Registration Based on Local Invariants
Authors: Wang Yunbiao , Xiao Jun , Liu Lupeng , Wang Ying
Published: April 2021

Point cloud registration is one of the basic research hotspots in the field of 3D reconstruction. Although many previous studies have made great progress, the registration of rock point clouds remains an ongoing challenge, due to the complex surface, arbitrary shape, and high resolution of rock masses. To overcome these challenges, a novel registration method for rock point clouds, based on local invariants, is proposed in this paper. First, to handle the massive point clouds, a point of interest filtering method based on a sum vector is adopted to reduce the number of points. Second, the remaining points of interest are divided into several cluster point sets and the centroid of each cluster is calculated. Then, we determine the correspondence between the original point cloud and the target point cloud by proving the inherent similarity (using the trace of the covariance matrix) of the remaining point sets. Finally, the rotation matrix and translation vector are calculated, according to the corresponding centroids, and a correction method is used to adjust the positions of the centroids. To illustrate the superiority of our method, in terms of accuracy and efficiency, we conducted experiments on multiple datasets. The experimental results show that the method has higher accuracy (about ten times) and efficiency than similar existing methods.
Analysis of Embedded Optical Interferometry in Transparent Elastic Grating for Optical Detection of Ultrasonic Waves
Authors: Sukkasem Chayanisa , Sasivimolkul Suvicha , Suvarnaphaet Phitsini , Pechprasarn Suejit
Published: April 2021

In this paper, we propose a theoretical framework to explain how the transparent elastic grating structure can be employed to enhance the mechanical and optical properties for ultrasonic detection. Incident ultrasonic waves can compress the flexible material, where the change in thickness of the elastic film can be measured through an optical interferometer. Herein, the polydimethylsiloxane (PDMS) was employed in the design of a thin film grating pattern. The PDMS grating with the grating period shorter than the ultrasound wavelength allowed the ultrasound to be coupled into surface acoustic wave (SAW) mode. The grating gaps provided spaces for the PDMS grating to be compressed when the ultrasound illuminated on it. This grating pattern can provide an embedded thin film based optical interferometer through Fabry–Perot resonant modes. Several optical thin film-based technologies for ultrasonic detection were compared. The proposed elastic grating gave rise to higher sensitivity to ultrasonic detection than a surface plasmon resonance-based sensor, a uniform PDMS thin film, a PDMS sensor with shearing interference, and a conventional Fabry–Perot-based sensor. The PDMS grating achieved the enhancement of sensitivity up to 1.3 × 10−5 Pa−1 and figure of merit of 1.4 × 10−5 Pa−1 which were higher than those of conventional Fabry–Perot structure by 7 times and 4 times, respectively.
A Security Scheme Based on Intranal-Adding Links for Integrated Industrial Cyber-Physical Systems
Authors: Zhao Dandan , Liu Can , Peng Hao , Yu Juan , Han Jianmin
Published: April 2021

With the advent of the Internet of Everything era, the Industrial Internet is increasingly showing mutual integration and development. Its core framework, the industrial CPS (Cyber-Physical Systems), has received more and more attention and in-depth research in recent years. These complex industrial CPS systems are usually composed of multiple interdependent sub-networks (such as physical networks and control networks, etc.). Minor faults or failure behaviors between sub-networks may cause serious cascading failure effects of the entire system. In this paper, we will propose a security scheme based on intranal-adding links in the face of the integrated and converged industrial CPS system environment. Firstly, by calculating the size of the largest connected component in the entire system, we can compare and analyze industrial CPS systems’ security performance under random attacks. Secondly, we compare and analyze the risk of cascading failure between integrated industrial CPS systems under different intranal-adding link strategies. Finally, the simulation results verify the system security strategy’s effectiveness under different strategies and show a relatively better exchange strategy to enhance the system’s security. In addition, this paper’s research work can help us design how to further optimize the interdependent industrial CPS system’s topology to cope with the integrated and converged industrial CPS system environment.
Bi-FPNFAS: Bi-Directional Feature Pyramid Network for Pixel-Wise Face Anti-Spoofing by Leveraging Fourier Spectra
Authors: Roy Koushik , Hasan Md. , Rupty Labiba , Hossain Md. Sourave , Sengupta Shirshajit , Taus Shehzad Noor , Mohammed Nabeel
Published: April 2021

The emergence of biometric-based authentication using modern sensors on electronic devices has led to an escalated use of face recognition technologies. While these technologies may seem intriguing, they are accompanied by numerous implicit drawbacks. In this paper, we look into the problem of face anti-spoofing (FAS) on a frame level in an attempt to ameliorate the risks of face-spoofed attacks in biometric authentication processes. We employed a bi-directional feature pyramid network (BiFPN) that is used for convolutional multi-scaled feature extraction on the EfficientDet detection architecture, which is novel to the task of FAS. We further use these convolutional multi-scaled features in order to perform deep pixel-wise supervision. For all of our experiments, we performed evaluations across all major datasets and attained competitive results for the majority of the cases. Additionally, we showed that introducing an auxiliary self-supervision branch tasked with reconstructing the inputs in the frequency domain demonstrates an average classification error rate (ACER) of 2.92% on Protocol IV of the OULU-NPU dataset, which is significantly better than the currently available published works on pixel-wise face anti-spoofing. Moreover, following the procedures of prior works, we performed inter-dataset testing, which further consolidated the generalizability of the proposed models, as they showed optimum results across various sensors without any fine-tuning procedures.
Mapping of Agricultural Subsurface Drainage Systems Using Unmanned Aerial Vehicle Imagery and Ground Penetrating Radar
Authors: Koganti Triven , Ghane Ehsan , Martinez Luis Rene , Iversen Bo V. , Allred Barry J.
Published: April 2021

Agricultural subsurface drainage systems are commonly installed on farmland to remove the excess water from poorly drained soils. Conventional methods for drainage mapping such as tile probes and trenching equipment are laborious, cause pipe damage, and are often inefficient to apply at large spatial scales. Knowledge of locations of an existing drainage network is crucial to understand the increased leaching and offsite release of drainage discharge and to retrofit the new drain lines within the existing drainage system. Recent technological developments in non-destructive techniques might provide a potential alternative solution. The objective of this study was to determine the suitability of unmanned aerial vehicle (UAV) imagery collected using three different cameras (visible-color, multispectral, and thermal infrared) and ground penetrating radar (GPR) for subsurface drainage mapping. Both the techniques are complementary in terms of their usage, applicability, and the properties they measure and were applied at four different sites in the Midwest USA. At Site-1, both the UAV imagery and GPR were equally successful across the entire field, while at Site-2, the UAV imagery was successful in one section of the field, and GPR proved to be useful in the other section where the UAV imagery failed to capture the drainage pipes’ location. At Site-3, less to no success was observed in finding the drain lines using UAV imagery captured on bare ground conditions, whereas good success was achieved using GPR. Conversely, at Site-4, the UAV imagery was successful and GPR failed to capture the drainage pipes’ location. Although UAV imagery seems to be an attractive solution for mapping agricultural subsurface drainage systems as it is cost-effective and can cover large field areas, the results suggest the usefulness of GPR to complement the former as both a mapping and validation technique. Hence, this case study compares and contrasts the suitability of both the methods, provides guidance on the optimal survey timing, and recommends their combined usage given both the technologies are available to deploy for drainage mapping purposes.
Rapid and Easy-to-Use Method for Accurate Characterization of Target Binding and Kinetics of Magnetic Particle Bioconjugates for Biosensing
Authors: Pushkarev Averyan V. , Orlov Alexey V. , Znoyko Sergey L. , Bragina Vera A. , Nikitin Petr I.
Published: April 2021

The ever-increasing use of magnetic particle bioconjugates (MPB) in biosensors calls for methods of comprehensive characterization of their interaction with targets. Label-free optical sensors commonly used for studying inter-molecular interactions have limited potential for MPB because of their large size and multi-component non-transparent structure. We present an easy-to-use method that requires only three 20-min express measurements to determine the key parameters for selection of optimal MPB for a biosensor: kinetic and equilibrium characteristics, and a fraction of biomolecules on the MPB surface that are capable of active targeting. The method also provides a prognostic dependence of MPB targeting efficiency upon interaction duration and sample volume. These features are possible due to joining a magnetic lateral flow assay, a highly sensitive sensor for MPB detection by the magnetic particle quantification technique, and a novel mathematical model that explicitly describes the MPB-target interactions and does not comprise parameters to be fitted additionally. The method was demonstrated by experiments on MPB targeting of cardiac troponin I and staphylococcal enterotoxin B. The validation by an independent label-free technique of spectral-correlation interferometry showed good correlation between the results obtained by both methods. The presented method can be applied to other targets for faster development and selection of MPB for affinity sensors, analytical technologies, and realization of novel concepts of MPB-based biosensing in vivo.
GC Analysis of Seven Seed Oils Containing Conjugated Fatty Acids
Authors: Goldschmidt Robert , Byrdwell William
Published: April 2021

The fatty acid compositions, including isomer compositions, of seven seed oils containing conjugated fatty acids (CFA) were determined. Seed oils were extracted using a modified Folch extraction, converted to fatty acid methyl esters, and analyzed by gas chromatography (GC) with mass spectrometry and flame ionization detection. The MS detector was operated in positive-ion chemical ionization mode using methane reagent gas. GC was performed using two columns providing different retention characteristics: a poly(ethylene glycol) column and a more polar biscyanopropyl column. The complimentary information provided by the two columns was crucial to peak identification in several cases. The major CFA species in the samples are well known but all contained lesser amounts of additional CFA that have not been widely reported. All samples contained multiple species of conjugated linolenic acid, and two samples also contained small amounts of conjugated linoleic acid. The seed oils of Jacaranda mimosifolia and Calendula officinalis were found to contain 8c,10t,12t-18:3, the natural occurrence of which has only been recently reported in some other samples. The seed oil of Impatiens balsamina has been reported to contain four conjugated 18:4 species, and we present evidence for a fifth conjugated 18:4 isomer.
An Enhanced Inverse Filtering Methodology for Drive-By Frequency Identification of Bridges Using Smartphones in Real-Life Conditions
Authors: Shirzad-Ghaleroudkhani Nima , Gül Mustafa
Published: April 2021

This paper develops an enhanced inverse filtering-based methodology for drive-by frequency identification of bridges using smartphones for real-life applications. As the vibration recorded on a vehicle is dominated by vehicle features including suspension system and speed as well as road roughness, inverse filtering aims at suppressing these effects through filtering out vehicle- and road-related features, thus mitigating a few of the significant challenges for the indirect identification of the bridge frequency. In the context of inverse filtering, a novel approach of constructing a database of vehicle vibrations for different speeds is presented to account for the vehicle speed effect on the performance of the method. In addition, an energy-based surface roughness criterion is proposed to consider surface roughness influence on the identification process. The successful performance of the methodology is investigated for different vehicle speeds and surface roughness levels. While most indirect bridge monitoring studies are investigated in numerical and laboratory conditions, this study proves the capability of the proposed methodology for two bridges in a real-life scale. Promising results collected using only a smartphone as the data acquisition device corroborate the fact that the proposed inverse filtering methodology could be employed in a crowdsourced framework for monitoring bridges at a global level in smart cities through a more cost-effective and efficient process.
A Flexible Multivariate Distribution for Correlated Count Data
Authors: Sellers Kimberly F. , Li Tong , Wu Yixuan , Balakrishnan Narayanaswamy
Published: April 2021

Multivariate count data are often modeled via a multivariate Poisson distribution, but it contains an underlying, constraining assumption of data equi-dispersion (where its variance equals its mean). Real data are oftentimes over-dispersed and, as such, consider various advancements of a negative binomial structure. While data over-dispersion is more prevalent than under-dispersion in real data, however, examples containing under-dispersed data are surfacing with greater frequency. Thus, there is a demonstrated need for a flexible model that can accommodate both data types. We develop a multivariate Conway–Maxwell–Poisson (MCMP) distribution to serve as a flexible alternative for correlated count data that contain data dispersion. This structure contains the multivariate Poisson, multivariate geometric, and the multivariate Bernoulli distributions as special cases, and serves as a bridge distribution across these three classical models to address other levels of over- or under-dispersion. In this work, we not only derive the distributional form and statistical properties of this model, but we further address parameter estimation, establish informative hypothesis tests to detect statistically significant data dispersion and aid in model parsimony, and illustrate the distribution’s flexibility through several simulated and real-world data examples. These examples demonstrate that the MCMP distribution performs on par with the multivariate negative binomial distribution for over-dispersed data, and proves particularly beneficial in effectively representing under-dispersed data. Thus, the MCMP distribution offers an effective, unifying framework for modeling over- or under-dispersed multivariate correlated count data that do not necessarily adhere to Poisson assumptions.
Universal Mobility in Old Core Cities of India: People’s Perception
Authors: Mahapatra Gaurab Das , Mori Suguru , Nomura Rie
Published: April 2021

In this research, users’ perception towards Universal Mobility in old core cities of India has been critically analyzed. Despite Universal Design guidelines from the United Nations and Union Government of India, old cities in India seldom have Universal Mobility, in effect endangering the lifestyle of senior citizens and differently-abled people. The core of Kolkata Municipal Corporation in Kolkata, India, has been considered a case example for this research. This research has considered three types of datasets for analysis. First, the authors interviewed 310 respondents from the Indian design fraternity, with the objective of understanding their opinions on the concept of Universal Design. In the next investigative study of 125 respondents from different wards of Kolkata Municipal Corporation, the purpose was to comprehend people’s perception regarding walkability and mobility in an old Indian city. In the last visual survey of a stretch in Central Kolkata, the focus was on identifying hindrances in Universal Mobility in an old city core of Indian origin. Significant dissatisfaction was found regarding walkability amongst all user groups, which is linked to poor infrastructural conditions. Furthermore, accessing public transportation is difficult due to improper waiting facilities. However, the design fraternity in India suggests the need of separate accessibility guidelines for old and new cities in India. The design fraternity also recommends a customized rating system for accessing Universal Design. The result of this study indicates a need of recognizing the difficulty in imparting Universal Mobility in old core cities in India. This information can be used for preparing an access audit checklist through Architectural Planning, which is the first step in proposing a framework for Universal Mobility in old core cities in India.
How Far Away Are World Economies from Circularity: Assessing the Capacity of Circular Economy Policy Packages in the Operation of Raw Materials and Industrial Wastes
Authors: Ignatyeva Margarita , Yurak Vera , Dushin Alexey , Strovsky Vladimir , Zavyalov Sergey , Malyshev Alexander , Karimova Polina
Published: April 2021

Nowadays, circular economy (CE) is on the agenda, however, this concept of closed supply chains originated in the 1960s. The current growing quantity of studies in this area accounts for different discourses except the holistic one, which mixes both approaches—contextual and operating (contextual approach utilizes the thorough examination of the CE theory, stricture of the policy, etc.; the operating one uses any kind of statistical data)—to assess the capacity of circular economy regulatory policy packages (CERPP) in operating raw materials and industrial wastes. This article demonstrates new guidelines for assessing the degree level of capacity (DLC) of CERPPs in the operation of raw materials and industrial wastes by utilizing the apparatus of the fuzzy set theory. It scrupulously surveys current CERPPs in three regions: the EU overall, Finland and Russia; and assesses for eight regions—the EU overall, Finland, Russia, China, Greece, France, the Netherlands and South Korea—the DLC of CERPPs in operating raw materials and industrial wastes. The results show that EU is the best in CE policy and its CERPP is 3R. The following are South Korea and China with the same type of CERPP. Finland, France and the Netherlands have worse results than EU with the type of CERPP called “integrated waste management” because of the absence of a waste hierarchy (reduce, recover, recycle). Russia closes the list with the type of CERPP “basic waste management”.