bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Nile Blue Analogue Stains Yeast Vacuolar Membrane, Endoplasmic Reticulum, and Lipid Droplets, Inducing Cell Death through Vacuole Membrane Permeabilization
Authors: Ferreira João Carlos Canossa , Lopes Carla , Preto Ana , Gonçalves Maria Sameiro Torres , Sousa Maria João
Published: November 2021

Phenoxazine derivatives such as Nile Blue analogues are assumed to be increasingly relevant in cell biology due to their fluorescence staining capabilities and antifungal and anticancer activities. However, the mechanisms underlying their effects remain poorly elucidated. Using S. cerevisiae as a eukaryotic model, we found that BaP1, a novel 5- and 9-N-substituted benzo[a]phenoxazine synthesized in our laboratory, when used in low concentrations, accumulates and stains the vacuolar membrane and the endoplasmic reticulum. In contrast, at higher concentrations, BaP1 stains lipid droplets and induces a regulated cell death process mediated by vacuolar membrane permeabilization. BaP1 also induced mitochondrial fragmentation and depolarization but did not lead to ROS accumulation, changes in intracellular Ca2+, or loss of plasma membrane integrity. Additionally, our results show that the cell death process is dependent on the vacuolar protease Pep4p and that the vacuole permeabilization results in its translocation from the vacuole to the cytosol. In addition, although nucleic acids are commonly described as targets of benzo[a]phenoxazines, we did not find any alterations at the DNA level. Our observations highlight BaP1 as a promising molecule for pharmacological application, using vacuole membrane permeabilization as a targeted approach.
Numerical Modeling of the Leak through Semipermeable Walls for 2D/3D Stokes Flow: Experimental Scalability of Dual Algorithms
Authors: Haslinger Jaroslav , Kučera Radek , Motyčková Kristina , Šátek Václav
Published: November 2021

The paper deals with the Stokes flow subject to the threshold leak boundary conditions in two and three space dimensions. The velocity–pressure formulation leads to the inequality type problem that is approximated by the P1-bubble/P1 mixed finite elements. The resulting algebraic system is nonsmooth. It is solved by the path-following variant of the interior point method, and by the active-set implementation of the semi-smooth Newton method. Inner linear systems are solved by the preconditioned conjugate gradient method. Numerical experiments illustrate scalability of the algorithms. The novelty of this work consists in applying dual strategies for solving the problem.
The Rescaled Pólya Urn and the Wright—Fisher Process with Mutation
Authors: Aletti Giacomo , Crimaldi Irene
Published: November 2021

In recent papers the authors introduce, study and apply a variant of the Eggenberger—Pólya urn, called the “rescaled” Pólya urn, which, for a suitable choice of the model parameters, exhibits a reinforcement mechanism mainly based on the last observations, a random persistent fluctuation of the predictive mean and the almost sure convergence of the empirical mean to a deterministic limit. In this work, motivated by some empirical evidence, we show that the multidimensional Wright—Fisher diffusion with mutation can be obtained as a suitable limit of the predictive means associated to a family of rescaled Pólya urns.
Approximate Mei Symmetries and Invariants of the Hamiltonian
Authors: Kausar Umara , Feroze Tooba
Published: November 2021

It is known that corresponding to each Noether symmetry there is a conserved quantity. Another class of symmetries that corresponds to conserved quantities is the class of Mei symmetries. However, the two sets of symmetries may give different conserved quantities. In this paper, a procedure of finding approximate Mei symmetries and invariants of the perturbed/approximate Hamiltonian is presented that can be used in different fields of study where approximate Hamiltonians are under consideration. The results are presented in the form of theorems along with their proofs. A simple example of mechanics is considered to elaborate the method of finding these symmetries and the related Mei invariants. At the end, a comparison of approximate Mei symmetries and approximate Noether symmetries is also given. The comparison shows that there is only one common symmetry in both sets of symmetries. Hence, rest of the symmetries in the two sets correspond to two different sets of conserved quantities.
Parotid Space, a Different Space from Other Deep Neck Infection Spaces
Authors: Chen Shih-Lung , Young Chi-Kuang , Liao Chun-Ta , Tsai Tsung-You , Kang Chung-Jan , Huang Shiang-Fu
Published: November 2021

Deep neck infections (DNIs) such as parotid abscesses are medical emergencies with a seemingly different etiology and treatment course from other DNIs. We sought to confirm this in the present retrospective population-based cohort study. Between August 2016 and January 2020, 412 patients with DNIs seen at a tertiary medical center were enrolled in this study. Infections of the parotid space were compared with those of other deep neck spaces, according to patient characteristics. All patients were divided into parotid space (PS; n = 91, 22.08%) and non-parotid space (NPS; n = 321, 77.92%) subgroups. We further divided the patients into single parotid space (PS-single; n = 50, 12.13%), single non-parotid space (NPS-single; n = 149, 36.16%), multiple parotid space (PS-multiple; n = 41, 9.95%), and multiple non-parotid space (NPS-multiple; n = 172, 41.76%) DNI subgroups. In the PS-single and PS-multiple subgroups, a longer duration of symptoms (p = 0.001), lower white blood cell count (p = 0.001), lower C-reactive protein level (p = 0.010), higher rate of ultrasonography-guided drainage (p < 0.001), and lower rates of surgical incision and drainage (p < 0.001) were observed compared with the NPS-single and NPS-multiple subgroups. The PS group had a higher positive Klebsiella pneumoniae culture rate (p < 0.001), and lower positive Streptococcus constellatus (p = 0.002), and Streptococcus anginosus (p = 0.025) culture rates than the NPS group. In a multivariate analysis, K. pneumoniae was independently associated with parotoid space involvement in comparisons of the PS and NPS groups, PS-single and NPS-single subgroups, and PS-multiple and NPS-multiple subgroups. The clinical presentation of a parotid space infection differs from that of other deep neck space infections.
Microbial Communities Involved in Methane, Sulfur, and Nitrogen Cycling in the Sediments of the Barents Sea
Authors: Begmatov Shahjahon , Savvichev Alexander S. , Kadnikov Vitaly V. , Beletsky Alexey V. , Rusanov Igor I. , Klyuvitkin Alexey A. , Novichkova Ekaterina A. , Mardanov Andrey V. , Pimenov Nikolai V. , Ravin Nikolai V.
Published: November 2021

A combination of physicochemical and radiotracer analysis, high-throughput sequencing of the 16S rRNA, and particulate methane monooxygenase subunit A (pmoA) genes was used to link a microbial community profile with methane, sulfur, and nitrogen cycling processes. The objects of study were surface sediments sampled at five stations in the northern part of the Barents Sea. The methane content in the upper layers (0–5 cm) ranged from 0.2 to 2.4 µM and increased with depth (16–19 cm) to 9.5 µM. The rate of methane oxidation in the oxic upper layers varied from 2 to 23 nmol CH4 L−1 day−1 and decreased to 0.3 nmol L−1 day−1 in the anoxic zone at a depth of 16–19 cm. Sulfate reduction rates were much higher, from 0.3 to 2.8 µmol L−1 day−1. In the surface sediments, ammonia-oxidizing Nitrosopumilaceae were abundant; the subsequent oxidation of nitrite to nitrate can be carried out by Nitrospira sp. Aerobic methane oxidation could be performed by uncultured deep-sea cluster 3 of gamma-proteobacterial methanotrophs. Undetectable low levels of methanogenesis were consistent with a near complete absence of methanogens. Anaerobic methane oxidation in the deeper sediments was likely performed by ANME-2a-2b and ANME-2c archaea in consortium with sulfate-reducing Desulfobacterota. Sulfide can be oxidized by nitrate-reducing Sulfurovum sp. Thus, the sulfur cycle was linked with the anaerobic oxidation of methane and the nitrogen cycle, which included the oxidation of ammonium to nitrate in the oxic zone and denitrification coupled to the oxidation of sulfide in the deeper sediments. Methane concentrations and rates of microbial biogeochemical processes in sediments in the northern part of the Barents Sea were noticeably higher than in oligotrophic areas of the Arctic Ocean, indicating that an increase in methane concentration significantly activates microbial processes.
Model Based Design and Validation of a Batch Ohmic Heating System
Authors: Oluwole-ojo Oluwaloba , Zhang Hongwei , Howarth Martin , Xu Xu
Published: November 2021

Using moderate electric field (MEF) techniques, Ohmic heating (OH) provides the rapid and uniform heating of food products by applying electric fields to them. A range of theoretical Ohmic heating models have been studied by researchers, but model validation and comparisons using experimental data and model development using system identification techniques from experimental data have not been evaluated. In this work, numerical models, mathematical models, and system identification models for an MEF process were developed. The MEF models were developed and simulated using COMSOL and MATLAB/Simulink software. When simulated, the developed models showed a volumetric rise in the overall food temperature. It was found that upon the application of an electric field, the resultant temperature depends on the electrical conductivity, product temperature, and magnitude of the electric field. For this reason, a systematic approach was used to validate the developed models. Experimental data derived from a commercially available batch Ohmic heater from C-Tech Innovation were used to validate the simulated models. Validation, analysis, and model comparison were conducted to compare developed models with experimental data. The validated simulated model helped improve the understanding of the effect of different critical process parameters of foods with a range of initial conditions. The validated model could accurately predict the temperature of heating under varying electric fields and food products with different thermo–physical properties.
Efficient Removal of Pb(II) from Aqueous Medium Using Chemically Modified Silica Monolith
Authors: Ali Ashraf , Alharthi Sarah , Ahmad Bashir , Naz Alia , Khan Idrees , Mabood Fazal
Published: November 2021

The adsorptive removal of lead (II) from aqueous medium was carried out by chemically modified silica monolith particles. Porous silica monolith particles were prepared by the sol-gel method and their surface modification was carried out using trimethoxy silyl propyl urea (TSPU) to prepare inorganic–organic hybrid adsorbent. The resultant adsorbent was evaluated for the removal of lead (Pb) from aqueous medium. The effect of pH, adsorbent dose, metal ion concentration and adsorption time was determined. It was found that the optimum conditions for adsorption of lead (Pb) were pH 5, adsorbent dose of 0.4 g/L, Pb(II) ions concentration of 500 mg/L and adsorption time of 1 h. The adsorbent chemically modified SM was characterized by scanning electron microscopy (SEM), BET/BJH and thermo gravimetric analysis (TGA). The percent adsorption of Pb(II) onto chemically modified silica monolith particles was 98%. An isotherm study showed that the adsorption data of Pb(II) onto chemically modified SM was fully fitted with the Freundlich and Langmuir isotherm models. It was found from kinetic study that the adsorption of Pb(II) followed a pseudo second-order model. Moreover, thermodynamic study suggests that the adsorption of Pb(II) is spontaneous and exothermic. The adsorption capacity of chemically modified SM for Pb(II) ions was 792 mg/g which is quite high as compared to the traditional adsorbents. The adsorbent chemically modified SM was regenerated, used again three times for the adsorption of Pb(II) ions and it was found that the adsorption capacity of the regenerated adsorbent was only dropped by 7%. Due to high adsorption capacity chemically modified silica monolith particles could be used as an effective adsorbent for the removal of heavy metals from wastewater.
Targeted Multiresidue Method for the Analysis of Different Classes of Pesticides in Agro-Food Industrial Sludge by Liquid Chromatography Tandem Mass Spectrometry
Authors: Maragou Niki C. , Balayiannis George , Karanasios Evangelos , Markellou Emilia , Liapis Konstantinos
Published: November 2021

Sludge generated after washing of fruits and vegetables during agro-food processes is a complex matrix and selective methods for the identification and quantification of pesticides’ residues are necessary in order to achieve a sustainable and effective management of the total sewage. The present work describes the development and validation of a reliable, simple and fast analytical method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the determination of 47 pesticides of different chemical classes, including organosphosphates, pyrethroids, neonicotinoids, triazoles and others, in sludge samples after QuEChERS sample preparation. The necessity of the individual steps of QuEChERS was investigated and the LC-ESI-MS/MS conditions were optimized to achieve maximum sensitivity of the target analytes. The method limits of detection (LODs) ranged between 0.0005 mg/kg (imidacloprid) and 0.05 mg/kg (beta cyfluthrin). The recoveries ranged between 71–120% and the repeatability of the method was ≤25% expressed as relative standard deviation. The method was applied to sludge samples generated after washing of fruits in an agro-fruit-packaging unit in Greece. The results showed the presence of 37 pesticides’ active substances with concentrations ranging from low ppbs, such as fludioxinil (5 μg/kg) up to low ppms such as beta cyfluthrin (3.5 mg/kg) and with their sum concentration reaching up to 19 mg/kg.
Polyhydroxybutyrate-Based Nanocomposites for Bone Tissue Engineering
Authors: Mohan Anand , Girdhar Madhuri , Kumar Raj , Chaturvedi Harshil S. , Vadhel Agrataben , Solanki Pratima R. , Kumar Anil , Kumar Deepak , Mamidi Narsimha
Published: November 2021

Bone-related diseases have been increasing worldwide, and several nanocomposites have been used to treat them. Among several nanocomposites, polyhydroxybutyrate (PHB)-based nanocomposites are widely used in drug delivery and tissue engineering due to their excellent biocompatibility and biodegradability. However, PHB use in bone tissue engineering is limited due to its inadequate physicochemical and mechanical properties. In the present work, we synthesized PHB-based nanocomposites using a nanoblend and nano-clay with modified montmorillonite (MMT) as a filler. MMT was modified using trimethyl stearyl ammonium (TMSA). Nanoblend and nano-clay were fabricated using the solvent-casting technique. Inspection of the composite structure revealed that the basal spacing of the polymeric matrix material was significantly altered depending on the loading percentage of organically modified montmorillonite (OMMT) nano-clay. The PHB/OMMT nanocomposite displayed enhanced thermal stability and upper working temperature upon heating as compared to the pristine polymer. The dispersed (OMMT) nano-clay assisted in the formation of pores on the surface of the polymer. The pore size was proportional to the weight percentage of OMMT. Further morphological analysis of these blends was carried out through FESEM. The obtained nanocomposites exhibited augmented properties over neat PHB and could have an abundance of applications in the industry and medicinal sectors. In particular, improved porosity, non-immunogenic nature, and strong biocompatibility suggest their effective application in bone tissue engineering. Thus, PHB/OMMT nanocomposites are a promising candidate for 3D organ printing, lab-on-a-chip scaffold engineering, and bone tissue engineering.
Super-Resolution Imaging with Patchy Microspheres
Authors: Shang Qingqing , Tang Fen , Yu Lingya , Oubaha Hamid , Caina Darwin , Yang Songlin , Melinte Sorin , Zuo Chao , Wang Zengbo , Ye Ran
Published: November 2021

The diffraction limit is a fundamental barrier in optical microscopy, which restricts the smallest resolvable feature size of a microscopic system. Microsphere-based microscopy has proven to be a promising tool for challenging the diffraction limit. Nevertheless, the microspheres have a low imaging contrast in air, which hinders the application of this technique. In this work, we demonstrate that this challenge can be effectively overcome by using partially Ag-plated microspheres. The deposited Ag film acts as an aperture stop that blocks a portion of the incident beam, forming a photonic hook and an oblique near-field illumination. Such a photonic hook significantly enhanced the imaging contrast of the system, as experimentally verified by imaging the Blu-ray disc surface and colloidal particle arrays.
Experimental Demonstration of Fine-Grained Steering Inequality of Two-Qubit Mixed States
Authors: Bian Zhi-Hao , Yin Cong-Yue
Published: November 2021

Quantum steering, as a cornerstone of quantum information, is usually used to witness the quantum correlation of bipartite and multi-partite states. Here, we experimentally demonstrate the quantum steering inequality of two-qubit mixed states based on the fine-grained uncertainty relation. Our experimental results show that the steering inequality has potent sensitivity to Werner states and Bell diagonal states. The steering strategy exhibits a strong ability to identify that Werner states are steerable when the decoherence coefficient a>12. Compared to the steering inequality obtained by another stratagem, the steering witness criteria of mixed states based on the fine-grained uncertainty relation demonstrated in our experiment has better precision and accuracy. Moreover, the detection efficiency in our measurement setup is only required to be 50% to close the detection loophole, which means our approach needs less detector efficiency to certificate the steerability of mixed states.
Predictive Analysis of Municipal Solid Waste Generation Using an Optimized Neural Network Model
Authors: Elshaboury Nehal , Mohammed Abdelkader Eslam , Al-Sakkaf Abobakr , Alfalah Ghasan
Published: November 2021

Developing successful municipal waste management planning strategies is crucial for implementing sustainable development. The research proposed the application of an optimized artificial neural network (ANN) to forecast quantities of waste in Poland. The neural network coupled with particle swarm optimization (PSO) algorithm is compared to the conventional neural network using five assessment metrics. The metrics are coefficient of efficiency (CE), Pearson correlation coefficient (R), Willmott’s index of agreement (WI), root mean squared error (RMSE), and mean bias error (MBE). Selected explanatory factors are incorporated in the developed models to reflect the influence of economic, demographic, and social aspects on the rate of waste generation. These factors are population, employment to population ratio, revenue per capita, number of entities by type of business activity, and number of entities enlisted in REGON per 10,000 population. According to the findings, the ANN–PSO model (CE = 0.92, R = 0.96, WI = 0.98, RMSE = 11,342.74, and MBE = 6548.55) significantly outperforms the traditional ANN model (CE = 0.11, R = 0.68, WI = 0.78, RMSE = 38,571.68, and MBE = 30,652.04). The significant level of the reported outputs is evaluated using the Wilcoxon–Mann–Whitney U-test, with a significance level of 0.05. The p-values of the pairings (ANN, observed) and (ANN, ANN–PSO) are all less than 0.05, suggesting that the models are statistically different. On the other hand, the P-value of (ANN–PSO, observed) is more than 0.05, suggesting that the difference between the models is statistically insignificant. Therefore, the proposed ANN–PSO model proves its efficiency at estimating municipal solid waste quantities and may be regarded as a cost-efficient method of developing integrated waste management systems.
X-ray Imaging-Based Void Fraction Measurement in Saturated Flow Boiling Experiments with Seawater Coolant
Authors: Eckels Seth , Ahmed Zayed , Ross Molly , Franken Daniel , Eckels Steven , Bindra Hitesh
Published: November 2021

Recent studies have shown that the presence of dissolved salts in water can exhibit peculiar flow boiling and two-phase flow regimes. Two-phase flow and convective flow boiling are typically characterized with the help of void fraction measurements. To quantitatively improve our understanding of two-phase flow and boiling phenomenon with seawater coolant, void fraction data are needed, which can not be obtained from optical imaging. In this paper, we present experimental void fraction measurements of saturated flow boiling of tap water and seawater using X-ray radiography. X-rays with a maximum energy level of 40 KeV were used for imaging the exit region of the heated test section. At lower heat flux levels, the two phase flow in seawater was bubbly and homogeneous in nature, resulting in higher void fractions as compared to tap water. With an increase in heat flux, the flow regime was similar to slug flow, and void fraction measurements approached similarity with tap water. The predicted pressure drop using the measured void faction shows good agreement with the measured total pressure drop across the test section, demonstrating the validity of the measurement process.
A 3D Compensation Method for the Systematic Errors of Kinect V2
Authors: Li Chang , Li Bingrui , Zhao Sisi
Published: November 2021

To reduce the 3D systematic error of the RGB-D camera and improve the measurement accuracy, this paper is the first to propose a new 3D compensation method for the systematic error of a Kinect V2 in a 3D calibration field. The processing of the method is as follows. First, the coordinate system between the RGB-D camera and 3D calibration field is transformed using 3D corresponding points. Second, the inliers are obtained using the Bayes SAmple Consensus (BaySAC) algorithm to eliminate gross errors (i.e., outliers). Third, the parameters of the 3D registration model are calculated by the iteration method with variable weights that can further control the error. Fourth, three systematic error compensation models are established and solved by the stepwise regression method. Finally, the optimal model is selected to calibrate the RGB-D camera. The experimental results show the following: (1) the BaySAC algorithm can effectively eliminate gross errors; (2) the iteration method with variable weights could better control slightly larger accidental errors; and (3) the 3D compensation method can compensate 91.19% and 61.58% of the systematic error of the RGB-D camera in the depth and 3D directions, respectively, in the 3D control field, which is superior to the 2D compensation method. The proposed method can control three types of errors (i.e., gross errors, accidental errors and systematic errors) and model errors and can effectively improve the accuracy of depth data.
Monitoring the Effects of Slope Hazard Mitigation and Weather on Rockfall along a Colorado Highway Using Terrestrial Laser Scanning
Authors: Weidner Luke , Walton Gabriel
Published: November 2021

Rockfall is a frequent hazard in mountainous areas, but risks can be mitigated by the construction of protection structures and slope modification. In this study, two rock slopes along a highway in western Colorado were monitored monthly using Terrestrial Laser Scanning (TLS) before, during, and after mitigation activities were performed to observe the influence of construction and weather variables on rockfall activity. Between September 2020 and February 2021, the slopes were mechanically scaled and reinforced using rock bolts, wire mesh, and polyurethane resin injection. We used a state-of-the-art TLS monitoring workflow to process the acquired point clouds, including semi-automated algorithms for alignment, change detection, clustering, and rockfall-volume calculation. Our initial hypotheses were that the slope-construction activities would have an immediate effect on the rockfall rate post-construction and would exhibit a decreased correlation with weather-related triggering factors, such as precipitation and freeze-thaw cycles. However, our observations did not confirm this, and instead an increase in post-construction rockfall was recorded, with strong correlation to weather-related triggering factors. While this does not suggest that the overall mitigation efforts were ineffective in reducing rockfall hazard and risk of large blocks, we did not find evidence that mitigation efforts influenced the rockfall hazard associated with the release of small- to medium-sized blocks (<1 m3). These results can be used to develop improved and tailored mitigation methods for rock slopes in the future.
Sea-Land Clutter Classification Based on Graph Spectrum Features
Authors: Zhang Le , Xue Anke , Zhao Xiaodong , Xu Shuwen , Mao Kecheng
Published: November 2021

In this paper, an approach for radar clutter, especially sea and land clutter classification, is considered under the following conditions: the average amplitude levels of the clutter are close to each other, and the distributions of the clutter are unknown. The proposed approach divides the dataset into two parts. The first data sequence from sea and land is used to train the model to compute the parameters of the classifier, and the second data sequence from sea and land under the same conditions is used to test the performance of the algorithm. In order to find the essential structure of the data, a new data representation method based on the graph spectrum is utilized. The method reveals the nondominant correlation implied in the data, and it is quite different from the traditional method. Furthermore, this representation is combined with the support vector machine (SVM) artificial intelligence algorithm to solve the problem of sea and land clutter classification. We compare the proposed graph feature set with nine exciting valid features that have been used to classify sea clutter from the radar in other works, especially when the average amplitude levels of the two types of clutter are very close. The experimental results prove that the proposed extraction can represent the characteristics of the raw data efficiently in this application.
Non-Contact Spirometry Using a Mobile Thermal Camera and AI Regression
Authors: Fraiwan Luay , Khasawneh Natheer , Lweesy Khaldon , Elbalki Mennatalla , Almarzooqi Amna , Abu Hamra Nada
Published: November 2021

Non-contact physiological measurements have been under investigation for many years, and among these measurements is non-contact spirometry, which could provide acute and chronic pulmonary disease monitoring and diagnosis. This work presents a feasibility study for non-contact spirometry measurements using a mobile thermal imaging system. Thermal images were acquired from 19 subjects for measuring the respiration rate and the volume of inhaled and exhaled air. A mobile application was built to measure the respiration rate and export the respiration signal to a personal computer. The mobile application acquired thermal video images at a rate of nine frames/second and the OpenCV library was used for localization of the area of interest (nose and mouth). Artificial intelligence regressors were used to predict the inhalation and exhalation air volume. Several regressors were tested and four of them showed excellent performance: random forest, adaptive boosting, gradient boosting, and decision trees. The latter showed the best regression results, with an R-square value of 0.9998 and a mean square error of 0.0023. The results of this study showed that non-contact spirometry based on a thermal imaging system is feasible and provides all the basic measurements that the conventional spirometers support.
Field Decorrelation and Isolation Improvement in an MIMO Antenna Using an All-Dielectric Device Based on Transformation Electromagnetics
Authors: Qureshi Usman , Khan Muhammad Umar , Sharawi Mohammad S. , Burokur Shah Nawaz , Mittra Raj
Published: November 2021

This work presents a new technique for enhancing the performance of a multiple-input multiple-output (MIMO) antenna by improving its correlation coefficient ρ. A broadband dielectric structure is designed using the transformation electromagnetics (TE) concept to decorrelate the fields of closely placed radiating elements of an MIMO antenna, thereby decreasing ρ and mutual coupling. The desired properties of the broadband dielectric wave tilting structure (DWTS) are determined by using quasi-conformal transformation electromagnetics (QCTE). Next, the permittivity profile of the DWTS is realized by employing air-hole technology, which is based on the effective medium theory, and the DWTS is fabricated using the additive manufacturing (3D printing) technique. The effectiveness of the proposed technique is verified by designing two-element patch-based MIMO antenna prototypes operating at 3 GHz, 5 GHz, and 7 GHz, respectively. The proposed technique helped to reduce the correlation coefficient ρ in the range of 37% to 99% in the respective operating bandwidth of each MIMO antenna, thereby, in each case, improving the isolation between antenna elements by better than 3 dB, which is an excellent performance.
Sentimental Analysis of COVID-19 Related Messages in Social Networks by Involving an N-Gram Stacked Autoencoder Integrated in an Ensemble Learning Scheme
Authors: Kandasamy Venkatachalam , Trojovský Pavel , Machot Fadi Al , Kyamakya Kyandoghere , Bacanin Nebojsa , Askar Sameh , Abouhawwash Mohamed
Published: November 2021

The current population worldwide extensively uses social media to share thoughts, societal issues, and personal concerns. Social media can be viewed as an intelligent platform that can be augmented with a capability to analyze and predict various issues such as business needs, environmental needs, election trends (polls), governmental needs, etc. This has motivated us to initiate a comprehensive search of the COVID-19 pandemic-related views and opinions amongst the population on Twitter. The basic training data have been collected from Twitter posts. On this basis, we have developed research involving ensemble deep learning techniques to reach a better prediction of the future evolutions of views in Twitter when compared to previous works that do the same. First, feature extraction is performed through an N-gram stacked autoencoder supervised learning algorithm. The extracted features are then involved in a classification and prediction involving an ensemble fusion scheme of selected machine learning techniques such as decision tree (DT), support vector machine (SVM), random forest (RF), and K-nearest neighbour (KNN). all individual results are combined/fused for a better prediction by using both mean and mode techniques. Our proposed scheme of an N-gram stacked encoder integrated in an ensemble machine learning scheme outperforms all the other existing competing techniques such unigram autoencoder, bigram autoencoder, etc. Our experimental results have been obtained from a comprehensive evaluation involving a dataset extracted from open-source data available from Twitter that were filtered by using the keywords “covid”, “covid19”, “coronavirus”, “covid-19”, “sarscov2”, and “covid_19”.
Development and Experimental Validation of an Intelligent Camera Model for Automated Driving
Authors: Genser Simon , Muckenhuber Stefan , Solmaz Selim , Reckenzaun Jakob
Published: November 2021

The virtual testing and validation of advanced driver assistance system and automated driving (ADAS/AD) functions require efficient and realistic perception sensor models. In particular, the limitations and measurement errors of real perception sensors need to be simulated realistically in order to generate useful sensor data for the ADAS/AD function under test. In this paper, a novel sensor modeling approach for automotive perception sensors is introduced. The novel approach combines kernel density estimation with regression modeling and puts the main focus on the position measurement errors. The modeling approach is designed for any automotive perception sensor that provides position estimations at the object level. To demonstrate and evaluate the new approach, a common state-of-the-art automotive camera (Mobileye 630) was considered. Both sensor measurements (Mobileye position estimations) and ground-truth data (DGPS positions of all attending vehicles) were collected during a large measurement campaign on a Hungarian highway to support the development and experimental validation of the new approach. The quality of the model was tested and compared to reference measurements, leading to a pointwise position error of 9.60% in the lateral and 1.57% in the longitudinal direction. Additionally, the modeling of the natural scattering of the sensor model output was satisfying. In particular, the deviations of the position measurements were well modeled with this approach.
An Expert System for Rotating Machine Fault Detection Using Vibration Signal Analysis
Authors: Kafeel Ayaz , Aziz Sumair , Awais Muhammad , Khan Muhammad Attique , Afaq Kamran , Idris Sahar Ahmed , Alshazly Hammam , Mostafa Samih M.
Published: November 2021

Accurate and early detection of machine faults is an important step in the preventive maintenance of industrial enterprises. It is essential to avoid unexpected downtime as well as to ensure the reliability of equipment and safety of humans. In the case of rotating machines, significant information about machine’s health and condition is present in the spectrum of its vibration signal. This work proposes a fault detection system of rotating machines using vibration signal analysis. First, a dataset of 3-dimensional vibration signals is acquired from large induction motors representing healthy and faulty states. The signal conditioning is performed using empirical mode decomposition technique. Next, multi-domain feature extraction is done to obtain various combinations of most discriminant temporal and spectral features from the denoised signals. Finally, the classification step is performed with various kernel settings of multiple classifiers including support vector machines, K-nearest neighbors, decision tree and linear discriminant analysis. The classification results demonstrate that a hybrid combination of time and spectral features, classified using support vector machines with Gaussian kernel achieves the best performance with 98.2% accuracy, 96.6% sensitivity, 100% specificity and 1.8% error rate.
Backscatter Assisted NOMA-PLNC Based Wireless Networks
Authors: Rajkumar Samikkannu , Jayakody Dushantha Nalin K.
Published: November 2021

In this paper, sum capacity maximization of the non-orthogonal multiple access (NOMA)-based wireless network is studied in the presence of ambient backscattering (ABS). Assuming that ABS is located next to far nodes, it improves the signal strength of far node cluster. By applying suitable successive interference cancellation (SIC) operation, far node cluster act as an internet of things (IoT) reader. Moreover, to improve the uplink performance of the nodes, a physical layer network coding (PLNC) scheme is applied in the proposed network. Power optimization is employed at the access point (AP) to enhance the downlink performance with total transmit power constraint and minimum data rate requirement per user constraint using Lagrangian’s function. In addition, end-to-end outage performance of the proposed wireless network is analyzed to enhance each wireless link capacity. Numerical results evident that the outage performance of the proposed network is significantly improved while using the ABS. Furthermore, the average bit error rate (BER) performance of the proposed wireless network is studied to improve the reliability. Simulation results are presented to validate the analytical expressions.
A Framework to Strengthen Learning Culture and Safeguards
Authors: Suprapto Vendy Hendrawan , Pujawan Nyoman , Dewi Ratna Sari
Published: November 2021

Strengthening the learning culture and the safeguards in organizations can enhance safety and performance in preventing incidents. The effective implementation of human performance improvement and operational learning can support the organization in achieving these goals. However, there is no streamlined implementation framework that considers the alignment of strategic and tactical actions in the management system cycle to implement human performance improvement and operational learning. This paper presents an implementation framework that fills the above gaps. It consists of four steps: (1) establish/validate a strategic objective, (2) conduct an assessment, (3) develop a plan, and (4) execute the plan. The proposed framework also includes a site tour phase during operational learning as an alternative to storytelling, which has an inherent bias. This framework was tested in the land transportation system of one of Indonesia’s biggest oil producers.
The Impacts of Transportation Sustainability on Higher Education in China
Authors: Zu Daqing , Cao Kang , Xu Jian
Published: November 2021

Improving transportation sustainability serves as a means of reducing the perceived and real distance, thereby contributing to the city and higher education development. In this paper, the complexity of transport sustainability is measured via four different dimensions: economy, society, environment and politics. The variables are designed by the four dimensions. The higher education development is measured via the ratio of higher education degree holders, reflecting the skilled work mobility. Over the last 30 years, university students moving to cities for study and work purposes have become an important part of rural–urban transition mobility. However, few studies have explored the impacts of transportation sustainability on higher education development in China. The economic, environmental, social and political dimensions in transportation sustainability can boost China’s higher education attainment in different ways. Against this background, this study, drawing on the panel data and employing the spatial multilevel model, investigated the impacts of transportation sustainability on higher education in China, adding new empirical evidence for China’s higher education development. A panel analysis revealed that the increase in transportation sustainability induces the growth of higher education. Moreover, higher education attainment showed significant spatial dependence at the county level and had significant spatial clustering of county-level higher education attainment across provinces. Furthermore, modeled test results showed that the spatial multilevel model was more suitable for our study than traditional regression models. By identifying transport sustainability variables that have an effect on higher education, this study is the first to uncover the complexity of transportation sustainability and contributes to the latest policy implications for promoting higher education attainment through sustainable transportation.
A Strategy for Tourism Growth, Rebound, and Revival: Promoting Portugal as a Destination Post-COVID-19
Authors: McTeigue Catherine , Sanchez Claudia , Santos Edson , Walter Cicero Eduardo , Au-Yong-Oliveira Manuel
Published: November 2021

The COVID-19 pandemic has had a significant impact around the world on health, economies, businesses, equality and the movement of people in the form of tourism. In this context, this paper looks at the strategy chosen by Turismo de Portugal to adapt to the crisis in a country where tourism plays an important role in supporting the local economy, having grown significantly since 2010. The chosen strategy encouraged tourists not to visit Portugal during the pandemic, a turnaround from their previous digital marketing strategy, which invited tourists to discover the country. We undertook a survey that had 170 answers, predominantly from Ecuador, Mexico, the United Kingdom and Portugal but also from several other countries in Europe and Latin America. We aimed to understand whether their strategy was successful in encouraging people to consider Portugal as a holiday destination post-COVID-19. The Can’t Skip Hope campaign was created in a work-from-home environment, with the voiceover recorded on a smartphone. Previously recorded footage was re-edited. Our survey found that respondents said the video matched their views of Portugal and that 79.5% would consider Portugal as a holiday destination when they next booked a holiday. In terms of inferential statistics, we performed chi-square tests of significance on the survey data. Thus, this paper contributes to the body of work because it offers insight into marketing strategy adaptation by a local tourist board during a period of crisis.
Government Data Performance: The Roles of Technology, Government Capacity, and Globalization through the Effects of National Innovativeness
Authors: Myeong Seunghwan , Ahn Michael J. , Kim Younhee , Chu Shengli , Suh Woojong
Published: November 2021

The availability of open, relevant, and up-to-date public data is becoming an increasingly important dimension of national competitiveness and sustainable development. It serves as a foundation for novel technologies, such as big data analytics, machine learning, and artificial intelligence, to take root and flourish, and it can help improve the quality and efficiency of government decision making and render governments more transparent and accessible to the public. Often referred as Open Government Data, or OGD, governments around the world have committed resources to constructing various OGD platforms. However, building a robust and effective OGD system has proved difficult, as the promise of OGD has not been realized fully around the world. At this important juncture, this study aims to explore the relationship between national technological and organizational capacities and environmental factor and the quality of OGD systems. In addition, national innovativeness and the degree of “globalization” in a country and their moderating effects between the predictors and OGD performance are examined. Our findings indicate strong positive effects of national technological capacity, government organization capacity, and globalization on OGD quality and a positive moderating effect of national innovativeness.
Interpretation in Ásbyrgi: Communicating with National Park Visitors in Iceland
Authors: Burns Georgette Leah , Haraldsdóttir Laufey , Gunnarsdóttir Guðrún Þóra
Published: November 2021

Iceland has experienced rapid increases in tourism in recent years. This growth earns economic applause, but can come at considerable environmental cost. As Iceland’s unique environment is a drawcard for many tourists, careful management of destinations to ensure a sustainable environment is critical. The Icelandic Government is aware of the need for effective destination management and planning to ensure a sustainable future for tourism development, and the need to couple this with visitor compliance. It is a development that cannot be divorced from the need for environmental sustainability, and responsibility for this lies with all tourism stakeholders. One management tool to assist with such responsibility and compliance in tourism is interpretation: creating and delivering messages to visitors that enhance not only their satisfaction with an experience but also their understanding of it. This paper is based on an evaluation of visitors’ experiences and managers’ perceptions, as is necessary to ensure visitor satisfaction, while determining how best to maintain a sustainable environment. By observing and interviewing visitors, guides, rangers, and managers at Ásbyrgi in the northernmost part of Vatnajökull National Park, Iceland, we were able to discover what sort of information park visitors want to receive, what park managers want to convey, and the preferred way to deliver that information. Overall, most visitors and guides were satisfied with the interpretation in Ásbyrgi and preferred information provided verbally by guides or rangers over other types, such as on signs or in electronic format. Visitors want information about the unique geology and cultural history, as well as directional instructions for hiking trails. Managers want to create an accessible space in which visitors comply with instructions about safety and environmental sustainability. These findings can assist tourism management in Ásbyrgi, and other nature-based destinations, particularly in terms of sustainability of the natural environment.
Towards Explaining Knowledge Hiding through Relationship Conflict, Frustration, and Irritability: The Case of Public Sector Teaching Hospitals
Authors: Alam Tahira , Ullah Zia , AlDhaen Fatima Saleh , AlDhaen Esra , Ahmad Naveed , Scholz Miklas
Published: November 2021

Organizations grow and excel with knowledge sharing; on the other hand, knowledge hiding is a negative behavior that impedes innovation, growth, problem solving, and timely correct decision making in organizations. It becomes more critical in the case of teaching hospitals, where, besides patient care, medical students are taught and trained. We assume that negative emotions lead employees to hide explicit knowledge, and in the same vein, this study has attempted to explain the hiding of explicit knowledge in the presence of relational conflicts, frustration, and irritability. We collected data from 290 employees of a public sector healthcare organization on adopted scales to test conjectured relationships among selected variables. Statistical treatments were applied to determine the quality of the data and inferential statistics were used to test hypotheses. The findings reveal that relationship conflicts positively affect knowledge hiding, and frustration partially mediates the relationship between relationship conflicts and knowledge hiding. Irritability moderates the relationship between relationship conflicts and frustration. The findings have both theoretical and empirical implications. Theoretically, the study tests a novel combination of variables, and adds details regarding the intensity of their relationships to the existing body of literature. Practically, the study guides hospital administrators in managing knowledge hiding, and informs on how to maintain it at the lowest possible level.