bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioactive Composition and Nutritional Profile of Microgreens Cultivated in Thailand
Authors: Kowitcharoen Laddawan , Phornvillay Surisa , Lekkham Pornpan , Pongprasert Nutthachai , Srilaong Varit
Published: August 2021

Microgreens are young and tender leafy vegetables that have gained wider consumer acceptance. This is attributed to their low caloric composition and rich micronutrient and antioxidant composition. The present study investigated the bioactive composition and proximate analysis of fourteen microgreens belonging to Brassicaceae, Fabaceae, Pedaliaceae, Polygonaceae, Convolvulaceae, and Malvaceae. All the microgreens showed low calories (20.22 to 53.43 kcal 100 g−1) and fat (0.15 to 0.66 g 100 g−1), whilst mung bean and lentil microgreens showed considerable amounts of carbohydrate (7.16 g 100 g−1) and protein (6.47 g 100 g−1), respectively. Lentil microgreens had the highest total chlorophyll (112.62 mg 100 g−1) and carotenoid (28.37 mg 100 g−1) contents, whilst buckwheat microgreens showed the highest total phenolic content (268.99 mg GAE 100 g−1) and DPPH• scavenging activity (90.83 mM TEAC g−1). The lentil microgreens also presented high ascorbic acid content (128.70 mg 100 g−1) along with broccoli, Chinese kale, purple radish, and red cabbage microgreens (79.11, 81.33, 82.58, and 89.49 mg 100 g−1, respectively). Anthocyanin content was only detected in purple radish (0.148 mg CGE 100 g−1) and red cabbage (0.246 mg CGE 100 g−1). The results provide basic information and highlight the benefits of utilizing genetic biodiversity to obtain microgreens with the desired nutrients and antioxidants.
Multi-Classifier Feature Fusion-Based Road Detection for Connected Autonomous Vehicles
Authors: Subramani Prabu , Sattar Khalid , de Prado Rocío , Girirajan Balasubramanian , Wozniak Marcin
Published: August 2021

Connected autonomous vehicles (CAVs) currently promise cooperation between vehicles, providing abundant and real-time information through wireless communication technologies. In this paper, a two-level fusion of classifiers (TLFC) approach is proposed by using deep learning classifiers to perform accurate road detection (RD). The proposed TLFC-RD approach improves the classification by considering four key strategies such as cross fold operation at input and pre-processing using superpixel generation, adequate features, multi-classifier feature fusion and a deep learning classifier. Specifically, the road is classified as drivable and non-drivable areas by designing the TLFC using the deep learning classifiers, and the detected information using the TLFC-RD is exchanged between the autonomous vehicles for the ease of driving on the road. The TLFC-RD is analyzed in terms of its accuracy, sensitivity or recall, specificity, precision, F1-measure and max F measure. The TLFC- RD method is also evaluated compared to three existing methods: U-Net with the Domain Adaptation Model (DAM), Two-Scale Fully Convolutional Network (TFCN) and a cooperative machine learning approach (i.e., TAAUWN). Experimental results show that the accuracy of the TLFC-RD method for the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) dataset is 99.12% higher than its competitors.
DOA Estimation in Low SNR Environment through Coprime Antenna Arrays: An Innovative Approach by Applying Flower Pollination Algorithm
Authors: Hameed Khurram , Tu Shanshan , Ahmed Nauman , Khan Wasim , Armghan Ammar , Alenezi Fayadh , Alnaim Norah , Qamar Muhammad Salman , Basit Abdul , Ali Farman
Published: August 2021

The design of the modern computing paradigm of heuristics is an innovative development for parameter estimation of direction of arrival (DOA) using sparse antenna arrays. In this study, the optimization strength of the flower pollination algorithm (FPA) is exploited for the DOA estimation in a low signal to noise ratio (SNR) regime by applying coprime sensor arrays (CSA). The enhanced degree of freedom (DOF) is achieved with FPA by investigating the global minima of highly nonlinear cost function with multiple local minimas. The sparse structure of CSA demonstrates that the DOF up to O(MN) is achieved by employing M+N CSA elements, where M and N are the numbers of antenna elements used to construct the CSA. Performance analysis is conducted for estimation accuracy, robustness against noise, robustness against snapshots, frequency distribution of root mean square error (RMSE), variability analysis of RMSE, cumulative distribution function (CDF) of RMSE over Monte Carlo runs and the comparative studies of particle swarm optimization (PSO). These reveal the worth of the proposed methodology for estimating DOA.
Cyclostationary Crosstalk Cancelation in High-Speed Transmission Lines
Authors: Kuznetsov Yury V. , Baev Andrey B. , Konovalyuk Maxim A. , Gorbunova Anastasia A.
Published: August 2021

The theoretical and experimental evaluation of the cyclostationary random data transferring process corrupted by the individually and jointly cyclostationary crosstalk interference is presented. The interference and the message signals were measured by the real time digital oscilloscope. Autocorrelation functions were evaluated by synchronous cyclic averaging procedure. The analyzed periodic two-dimensional impulse response of the time-varying filter allows to obtain the output random process with the same cyclic frequency at the output of the filter by separation of orthogonal stationary waveforms constituting the input cyclostationary random process (CSRP). The filtering of the measured random process was implemented by the cyclic Wiener filter. The evaluation of the two-dimensional autocorrelation function and eye diagrams at the output of the cyclic Wiener filter showed significant reduction of the independent interference components in the estimated message signal.
Virtual Machine Migration Strategy Based on Multi-Agent Deep Reinforcement Learning
Authors: Dai Yu , Zhang Qiuhong , Yang Lei
Published: August 2021

Mobile edge computing is a new computing model, which pushes cloud computing power from centralized cloud to network edge. However, with the sinking of computing power, user mobility brings new challenges: since it is usually unstable, services should be dynamically migrated between multiple edge servers to maintain service performance, that is, user-perceived latency. Considering that Mobile Edge Computing is a highly distributed computing environment and it is difficult to synchronize information between servers, in order to ensure the real-time performance of the migration strategy, a virtual machine migration strategy based on Multi-Agent Deep Reinforcement Learning is proposed in this paper. The method of centralized training and distributed execution is adopted, that is, the transfer action is guided by the global information during training, and only the local observation information is needed to obtain the transfer action. Compared with the centralized control method, the proposed method alleviates communication bottleneck. Compared with other distributed control methods, this method only needs local information, does not need communication between servers, and speeds up the perception of the current environment. Migration strategies can be generated faster. Simulation results show that the proposed strategy is better than the contrast strategy in terms of convergence and energy consumption.
Protective Effects of Tocotrienols in Cerebral and Myocardial Ischemia-Reperfusion Injury: A Systematic Review
Authors: Ramli Fitri Fareez , Ali Adli , Ibrahim Nurul ’Izzah
Published: August 2021

Although the current treatments for stroke and myocardial infarction contribute to an improvement in mortality rates, the consequences of reperfusion therapy have remained a challenge. Tocotrienols have been shown to exert beneficial effects on the brain and heart. This review aimed to determine the effects of tocotrienols in cerebral and myocardial ischemia-reperfusion (I/R) injury. We retrieved articles from Scopus, MEDLINE and PubMed from inception to June 2021, and included any studies using tocotrienols as a treatment for cerebral or myocardial I/R injury therapy. Observational studies and review articles were excluded, and the risk of bias was conducted using a specific tool for animal study (SYRCLE). The data were analyzed qualitatively. Twelve articles met the eligibility criteria. Tocotrienols significantly improved the structural, functional, and biochemical parameters in both cerebral and myocardial I/R injury models. In contrast, oxidative stress, inflammation, and apoptosis were markedly attenuated by tocotrienol treatment. Limitations to the analysis included marked differences in animal models, disease inductions, forms of tocotrienols, and an unclear risk of bias in certain types of bias. However, tocotrienols have the potential to serve as a supplement for reducing the impact of reperfusion injury.
Adaptative Cover to Achieve Thermal Comfort in Open Spaces of Buildings: Experimental Assessment and Modelling
Authors: Guerrero Delgado MCarmen , Castro Medina Daniel , Sánchez Ramos Jose , Palomo Amores Teresa Rocío , Álvarez Domínguez Servando , Tenorio Ríos José Antonio
Published: August 2021

The global need for healthy and safe open spaces faces continuous temperature rise due to the heat island phenomenon and climate change. This problem requires new strategies for improving the habitability of open spaces (indoor and outdoor conditions in buildings). These techniques include reducing solar radiation, reducing the temperature of surrounding surfaces, and reducing the air temperature. The radiant solutions are essential for outdoor comfort, both in summer and in winter. They are easy to integrate into open spaces. This study explores a new concept of radiant solutions adapted for outdoor spaces. The solution was evaluated in a test cell to obtain its thermal behaviour in different operation conditions. Solutions were optimised for operating in a cooling regimen since it has been identified that the demands for comfort in open spaces in hot climates during the most severe summer months are more pronounced. Experimental results have allowed getting an inverse model to analyse the thermal behaviour of the solution. The inverse model achieved high precision in its estimations. Also, it facilitated knowing the radiant and convective effects. Only the radiant heat flux is relevant in open spaces with a low level of air confinement. Finally, the discussion describes the application of the proposed model. The model allows the replicability of the solution—creating new designs (integration) or evaluating into different operating conditions of the system. This discussion demonstrates the high level of knowledge acquired in the characterisation of the solution studied.
pH Measurement of Cement-Based Materials: The Effect of Particle Size
Authors: Loh Poh Yee , Shafigh Payam , Katman Herda Yati Binti , Ibrahim Zainah , Yousuf Sumra
Published: August 2021

Healthy reinforced concrete should be highly alkaline to safeguard the passive protective film for reinforcement of steel bars against corrosion. pH measurement is gaining importance in research of cement-based materials (CBMs), such as paste, mortar and concrete, as well as in structural health monitoring and forensic engineering applications. However, insufficient information is available regarding the most practical, economical and applicable quantitative pH measurement method for CBMs from the sampling to measurement stage. Existing recommended methods for measuring pH have many variables that need to be investigated to determine how they influence the pH value. Samples were recommended to be ground into very fine particles for pH measurement. Preparing very fine particles of CBMs is costly and time consuming, while larger particles, with sizes similar to sand particles, are easier to obtain, without needing special equipment. This study aims to investigate the effect of different particle sizes on the pH of cement mortar. Mortar specimens were crushed and sieved to obtain different ranges of particle sizes to measure the pH values. Results showed that specimens with large particle sizes (between 600 µm and 4.75 mm) can produce similar results to specimens with very fine particle sizes (<600 µm) by increasing the solid-to-solvent ratio or the leaching time.
Optimization of Neural Network-Based Self-Tuning PID Controllers for Second Order Mechanical Systems
Authors: Lee Yong-Seok , Jang Dong-Won
Published: August 2021

The feasibility of a neural network method was discussed in terms of a self-tuning proportional–integral–derivative (PID) controller. The proposed method was configured with two neural networks to dramatically reduce the number of tuning attempts with a practically achievable small amount of data acquisition. The first network identified the target system from response data, previous PID parameters, and response characteristics. The second network recommended PID parameters based on the results of the first network. The results showed that it could recommend PID parameters within 2 s of observing responses. When the number of trained data was as low as 1000, the performance efficiency of these methods was 92.9%, and the tuning was completed in an average of 2.94 attempts. Additionally, the robustness of these methods was determined by considering a system with noise or a situation when the target position was modified. These methods are also applicable for traditional PID controllers, thus enabling conservative industries to continue using PID controllers.
High Strain Rate Properties of Various Forms of Ti6Al4V(ELI) Produced by Direct Metal Laser Sintering
Authors: Muiruri Amos , Maringa Maina , du Preez Willie
Published: August 2021

For analysis of engineering structural materials to withstand harsh environmental conditions, accurate knowledge of properties such as flow stress and failure over conditions of high strain rate and temperature plays an essential role. Such properties of additively manufactured Ti6Al4V(ELI) are not adequately studied. This paper documents an investigation of the high strain rate and temperature properties of different forms of heat-treated Ti6Al4V(ELI) samples produced by the direct metal laser sintering (DMLS). The microstructure and texture of the heat-treated samples were analysed using a scanning electron microscope (SEM) equipped with an electron backscatter diffraction detector for electron backscatter diffraction (EBSD) analysis. The split Hopkinson pressure bar (SHPB) equipment was used to carry out tests at strain rates of 750, 1500 and 2450 s−1, and temperatures of 25, 200 and 500 °C. The heat-treated samples of DMLS Ti6Al4V(ELI) alloys tested here were found to be sensitive to strain rate and temperature. At most strain rates and temperatures, the samples with finer microstructure exhibited higher dynamic strength and lower strain, while the dynamic strength and strain were lower and higher, respectively, for samples with coarse microstructure. The cut surfaces of the samples tested were characterised by a network of well-formed adiabatic shear bands (ASBs) with cracks propagating along them. The thickness of these ASBs varied with the strain rate, temperature, and various alloy forms.
Hybrid Structure of a ZnO Nanowire Array on a PVDF Nanofiber Membrane/Nylon Mesh for use in Smart Filters: Photoconductive PM Filters
Authors: Kang Dong Hee , Kim Na Kyong , Kang Hyun Wook
Published: August 2021

A nanofiber membrane with a high surface-to-volume ratio has advantages in applications such as those used for particulate matter filtration and gas detection. To maximize the potentials of the membrane structure, recent research has been attempted to control nanofiber geometries. In this paper, surface modification of a nanofiber membrane with a metal/ceramic nanostructure is performed to improve multi-functional filter performance, enhancing fine particle filtration and toxic gas absorption. Here, a smart filter is fabricated by electrospinning polyvinylidene difluoride (PVDF) nanofiber onto a nylon mesh and hydrothermal synthesis of ZnO nanoparticles onto a nanowire array on a PVDF nanofiber surface. On the ZnO nanowires–PVDF nanofiber layer filter, the pressure difference (ΔP = 4.13 kPa) is higher than the pure PVDF nanofiber layer. However, the filtration efficiency is 94.3% for a 0.3 μm particle size, which is higher than that of other sizes. Additionally, a ZnO nanowire array with high density on a PVDF nanofiber layer affects sensitivity (S = 39.37), with high resolution. The photocurrent characteristics of a smart filter have the potential for a photo-assisted redox reaction to detect toxic polar molecules in continuous airflow in real-time in indoor environments.
Analysis of Harassment Complaints to Detect Witness Intervention by Machine Learning and Soft Computing Techniques
Authors: Alonso-Parra Marina , Puente Cristina , Laguna Ana , Palacios Rafael
Published: August 2021

This research is aimed to analyze textual descriptions of harassment situations collected anonymously by the Hollaback! project. Hollaback! is an international movement created to end harassment in all of its forms. Its goal is to collect stories of harassment through the web and a free app all around the world to elevate victims’ individual voices to find a societal solution. Hollaback! pretends to analyze the impact of a bystander during a harassment in order to launch a public awareness-raising campaign to equip everyday people with tools to undo harassment. Thus, the analysis presented in this paper is a first step in Hollaback!’s purpose: the automatic detection of a witness intervention inferred from the victim’s own report. In a first step, natural language processing techniques were used to analyze the victim’s free-text descriptions. For this part, we used the whole dataset with all its countries and locations. In addition, classification models, based on machine learning and soft computing techniques, were developed in the second part of this study to classify the descriptions into those that have bystander presence and those that do not. For this machine learning part, we selected the city of Madrid as an example, in order to establish a criterion of the witness behavior procedure.
Probabilistic and Semi-Probabilistic Analysis of Slender Columns Frequently Used in Structural Engineering
Authors: Strauss Alfred , Hauser Michael , Täubling Benjamin , Ivanković Ana Mandić , Skokandić Dominik , Matos José , Galvão Neryvaldo , Benko Vladimir , Dobrý Jakub , Wan-Wendner Roman , Ninčević Krešimir , Orcesi André
Published: August 2021

The stability of slender columns is a topic that has been dealt with in research and practice for many years. The importance of this topic also increases with the possibility of using non-linear modeling approaches to determine the stability and with the increasingly complex safety formats. In order to show the complexity and the variability associated with the non-linear models, two previous contributions discussed and compared (a) the results of the Round Robin Non-Linear Modeling, and (b) the existing international associated standard specifications and safety concepts with respect to experimental results. The aim herein is to determine the reliability level (safety index) on the basis of these investigations and findings and to examine the existing safety formats of classical and extended probabilistic analyses and to derive any necessary adjustments. In addition, the method of the safety format Estimation of Coefficient of Variance of resistance (ECOV) is used for the determination of the global safety resistance factors based on the non-linear analyses’ findings of the Round Robin modeling partners.
A Prediction Model for Additive Manufacturing of Inconel 718 Superalloy
Authors: Ravichander Bharath Bhushan , Rahimzadeh Atabak , Farhang Behzad , Shayesteh Moghaddam Narges , Amerinatanzi Amirhesam , Mehrpouya Mehrshad
Published: August 2021

Inconel 718 is a nickel-based superalloy and an excellent candidate for the aerospace, oil, and gas industries due to its high strength and corrosion resistance properties. The machining of IN718 is very challenging; therefore, the application of additive manufacturing (AM) technology is an effective approach to overcoming these difficulties and for the fabrication of complex geometries that cannot be manufactured by the traditional techniques. Selective laser melting (SLM), which is a laser powder bed fusion method, can be applied for the fabrication of IN718 samples with high accuracy. However, the process parameters have a high impact on the properties of the manufactured samples. In this study, a prediction model is developed for obtaining the optimal process parameters, including laser power, hatch spacing, and scanning speed, in the SLM process of the IN718 alloy. For this purpose, artificial neural network (ANN) modeling with various algorithms is employed to estimate the process outputs, namely, sample height and surface hardness. The modeling results fit perfectly with the experimental output, and this consequently proves the benefit of ANN modeling for predicting the optimal process parameters.
Synthesis and Formation Process of a Typical Doped Solid-Solution Ye’elimite (Ca3.8Na0.2Al5.6Fe0.2Si0.2SO16): Experiments and Kinetic Analysis
Authors: Zhao Jiuye , Huang Jiazhi , Yu Chunyang , Cui Chunyi
Published: August 2021

Ye’elimite is a dominant phase in calcium sulfoaluminate cement, which is a promising alternative type of cementitious binder. Ca3.8Na0.2Al5.6Fe0.2Si0.2SO16 (abbreviated as ss-C4A3$) is a kind of typical doped solid-solution ye’elimite. In this study, the formation process of ss-C4A3$ was investigated. Clinkers of ss-C4A3$ were sintered at various temperatures for different holding times. X-ray diffraction tests and Rietveld quantitative phase analysis were conducted to determine the phase compositions of the clinkers. Meanwhile, the formation process of ss-C4A3$ was analyzed by kinetic theory. The results show that solid reactions between intermediate phases (calcium aluminate phases) and anhydrite mainly resulted in the formation of ss-C4A3$. In the conditions of 1150–1250 °C, ss-C4A3$ tended to be formed and stable until 4 h. However, when the sintering temperature was 1300 °C, the ss-C4A3$ decreased to generate calcium aluminate phases after 2 h. Compared to other kinetic models, the three-dimensional diffusion model mostly conformed with the formation process of ss-C4A3$, and the fitting results obtained by the Jander model exhibited the highest correlation coefficients. The activation energy of ss-C4A3$ formation equaled 285.6 kJ/mol, which was smaller than that of stoichiometric ye’elimite.
Differences in Gait Cycle and Biomechanical Lower-Limb Joint Function between Elderly People with and without Cognitive Decline
Authors: Kwak Kiyoung , Kostic Emilija , Kim Dongwook
Published: August 2021

Because dementia is difficult to treat, the best way is to detect the prodromal stage; this can identify those at high risk of dementia and help to delay its onset. It is a well-known fact that gait has a high correlation with cognitive function. Considering that dementia starts with cognitive decline, investigating the association between cognitive decline and gait may contribute to the detection of elderly individuals at high risk of dementia and even the prevention of dementia. The purpose of the present study was to investigate the gait cycle and biomechanics of elderly people with and without cognitive decline. A three-dimensional motion analysis system was used, and older adults over 65 participated in this study. K-MoCA was used to assess cognitive function and, according to the results of a cognition function assessment, they were classified into two groups. Spatiotemporal variables, subdivisions of the gait cycle, joint angle, joint moment, joint power, and support moment were investigated. Significant differences between both groups appeared in the subdivisions of the gait cycle, and parameters of gait biomechanics were established. These results provide insight into the mechanism dictating the gait of elderly individuals with cognitive decline.
Multi-Technique Characterization of Pictorial Organic Binders on XV Century Polychrome Sculptures by Combining Micro- and Non-Invasive Sampling Approaches
Authors: Rigante Elena C. L. , Calvano Cosima D. , Picca Rosaria A. , Armenise Simona , Cataldi Tommaso R. I. , Sabbatini Luigia
Published: August 2021

A stony sculptural composition of the Nativity Scene is preserved in Altamura’s Cathedral (Apulia, Italy). This commonly called Apulian “presepe”, attributed to an unknown stonemason, is composed of polychrome carbonate white stone sculptures. While earlier stratigraphic tests have unveiled a complex superimposition of painting layers—meaning that several editions of the sculptures succeeded from the 16th to 20th century—a chemical investigation intended to identify the organic binding media used in painting layers was undertaken. Drawing on current literature, two strategies were exploited: a non-invasive in situ digestion analysis and an approach based on micro-removal of painting film followed by the Bligh and Dyer extraction protocol. Both peptide and lipid mixtures were analyzed by matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) and reversed-phase liquid chromatography coupled to mass spectrometry by electrospray ionization (RPLC-ESI-MS). Attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR) examinations were also performed on micro-samples of painting films before lipids and proteins extraction. While human keratins were found to be common contaminants of the artwork’s surfaces, traces of animal collagen, siccative oils, and egg white proteins were evidenced in different sampling zones of the sculptures, thus suggesting the use of non-homogeneous painting techniques in the colored layers.
Systematically Investigating the Structural Variety of Crystalline and Kaleidoscopic Vortex Lattices by Using Laser Beam Arrays
Authors: Chen Chengshang , Fang Yuhan , Jang Chichen , Chen Wenchi , Lin Hui-Chi , Liang Hsingchih
Published: August 2021

We theoretically demonstrate that a family of vortex-lattice structures can be flexibly generated using a multi-beam interference approach. Numerical calculation presents a variety of crystalline and kaleidoscopic patterns. Based on the numerical analysis, we experimentally realized these structure beams by combining an amplitude mask with multiple apertures and a spiral phase plate. The excellent agreement between the experimental and theoretical results not only validates the presented method, but also manifests the structure of vortex lattices.
Acoustic and Dynamic Response of Unbaffled Plates of Arbitrary Shape
Authors: García-Fogeda Pablo , de la Iglesia Fernando , Salehi Keyvan
Published: August 2021

In this study, a method for determining the effects of fluids on the dynamic characteristics of an aerospace structure and the response of the structure when it is excited by the acoustical loads produced during a rocket launch, has been developed. Elevated acoustical loads are critical in the design of large lightweight structures, such as solar arrays and communication reflectors, because of the high acceleration levels. The acoustic field generated during rocket launch can be considered as a diffuse field composed of many uncorrelated incident plane waves traveling in different directions, which impinge on the structure. A boundary element method was used to calculate the pressure jump produced by an incoming plane wave on an unbaffled plate and the fluid–structure coupled loads generated through plate vibration. This method is based on Kirchhoff’s integral formulation of the Helmholtz equation for pressure fields. The generalized force matrix attributed to the fluid loads was then formulated, taking the modes of the plate in vacuum as base functions of the structural displacement. These modes are obtained using a finite-element model. An iteration procedure was developed to calculate the natural frequencies of the fully coupled fluid–plate system. Comparison of the results obtained using the proposed method with those of other theories and experimental data demonstrated its efficiency and accuracy. The proposed method is suitable for analyzing plates of arbitrary shape subjected to any boundary conditions in a diffuse field for low to medium values of the frequency excitation range.
Applying NMR T2 Spectral Parameters in Pore Structure Evaluation—An Example from an Eocene Low-Permeability Sandstone Reservoir
Authors: Lu Yan , Liu Keyu , Wang Ya
Published: August 2021

The Eocene low-permeability sandstone reservoirs in the Dongying Depression, Bohai Bay Basin, China host a significant amount of oil reserves. The development of the reservoirs has been hampered by our inability to understand the complex and heterogeneous pore structures of the reservoirs. In this study, the pore systems, pore sizes, pore connectivity, and movable fluid distribution of the Eocene Shahejie Formation (Es4) sandstone reservoirs were investigated using an integrated analysis of optical and scanning electron microscopy (SEM), mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR). The full-range pore structures of the Es4 sandstone reservoirs were evaluated by using NMR experiments. Various NMR T2 spectral parameters suitable for describing the pore structures and movable fluid distribution were extracted through morphological and statistical analysis of NMR T2 spectra. In combination with corresponding MICP data and petrophysical properties, we have demonstrated the reliability and robustness of the T2 spectral parameters for pore structure characterization. Four types of pore structures (I, II, III, and IV) were distinguished from the NMR T2 spectral parameters in association with other petrophysical properties and macroscopic behaviors. We have demonstrated the effectiveness of using the NMR T2 spectral parameters to characterize and classify micropore structures, which may be applied to effectively evaluate and predict low-permeability reservoir quality.
In-Situ Evaluation of the Pitch of a Reflective-Type Scale Grating by Using a Mode-Locked Femtosecond Laser
Authors: Shin Dong Wook , Quan Lue , Shimizu Yuki , Matsukuma Hiraku , Cai Yindi , Manske Eberhard , Gao Wei
Published: August 2021

Major modifications are made to the setup and signal processing of the method of in-situ measurement of the pitch of a diffraction grating based on the angles of diffraction of the diffracted optical frequency comb laser emanated from the grating. In the method, the improvement of the uncertainty of in-situ pitch measurement can be expected since every mode in the diffracted optical frequency comb laser can be utilized. Instead of employing a Fabry-Pérot etalon for the separation of the neighboring modes in the group of the diffracted laser beams, the weight-of-mass method is introduced in the method to detect the light wavelength in the Littrow configuration. An attempt is also made to reduce the influence of the non-uniform spectrum of the optical comb laser employed in the setup through normalization operation. In addition, an optical alignment technique with the employment of a retroreflector is introduced for the precise alignment of optical components in the setup. Furthermore, a mathematical model of the pitch measurement by the proposed method is established, and theoretical analysis on the uncertainty of pitch measurement is carried out based on the guide to the expression of uncertainty in measurement (GUM).
Fault Detection for Pitch System of Wind Turbine-Driven Doubly Fed Based on IHHO-LightGBM
Authors: Tang Mingzhu , Peng Zhonghui , Wu Huawei
Published: August 2021

To address the issue of a large calculation and difficult optimization for the traditional fault detection of a wind turbine-based pitch control system, a fault detection model, based on LightGBM by the improved Harris Hawks optimization algorithm (light gradient boosting machine by the improved Harris Hawks optimization, IHHO-LightGBM) for the wind turbine-based pitch control system, is proposed in this article. Firstly, a trigonometric function model is introduced by IHHO to update the prey escape energy, to balance the global exploration ability and local development ability of the algorithm. In this model, the fault detection false alarm rate is used as the fitness function, and the two parameters are used as the optimization objects of the improved Harris Hawks optimization algorithm, to optimize the parameters, so as to achieve the global optimal parameters to improve the performance of the fault detection model. Three different fault data of the pitch control system in actual operations of domestic wind farms are used as the experimental data, the Pearson correlation analysis method is introduced, and the wind turbine power output is taken as the main state parameter, to analyze the correlation degree of all the characteristic variables of the data and screen the important characteristic variables out, so as to achieve the effective dimensionality reduction process of the data, by using the feature selection method. Three established fault detection models are selected and compared with the proposed method, to verify its feasibility. The experimental data indicate that compared with other algorithms, the fault detecting ability of the proposed model is improved in all aspects, and the false alarm rate and false negative rate are lower.
Digital Marketing Platforms and Customer Satisfaction: Identifying eWOM Using Big Data and Text Mining
Authors: Kitsios Fotis , Kamariotou Maria , Karanikolas Panagiotis , Grigoroudis Evangelos
Published: August 2021

Big data analytics provides many opportunities to develop new avenues for understanding hospitality management and to support decision making in this field. User-generated content (UGC) provides benefits for hotel managers to gain feedback from customers and enhance specific product attributes or service characteristics in order to increase business value and support marketing activities. Many scholars have provided significant findings about the determinants of customers’ satisfaction in hospitality. However, most researchers primarily used research methodologies such as customer surveys, interviews, or focus groups to examine the determinants of customers’ satisfaction. Thus, more studies must explore how to use UGC to bridge the gap between guest satisfaction and online reviews. This paper examines and compares the aspects of satisfaction and dissatisfaction of Greek hotels’ guests. Text analytics was implemented to deconstruct hotel guest reviews and then examine their relationship with hotel satisfaction. This paper helps hotel managers determine specific product attributes or service characteristics that impact guest satisfaction and dissatisfaction and how hotel guests’ attitudes to those characteristics are affected by hotels’ market positioning and strategies.
Laser Technology for the Formation of Bioelectronic Nanocomposites Based on Single-Walled Carbon Nanotubes and Proteins with Different Structures, Electrical Conductivity and Biocompatibility
Authors: Gerasimenko Alexander Yu. , Kurilova Uliana E. , Suetina Irina A. , Mezentseva Marina V. , Zubko Aleksandr V. , Sekacheva Marina I. , Glukhova Olga E.
Published: August 2021

A laser technology for creating nanocomposites from alternating layers of albumin/collagen proteins with two types of single-walled carbon nanotubes (SWCNT) at concentrations of 0.001 and 0.01 wt.% was proposed. For this purpose, a setup with a diode laser (810 nm) and feedback system for controlling the temperature of the area affected by the radiation was developed. Raman spectroscopy was used to determine a decrease in the defectiveness of SWCNT with an increase in their concentration in the nanocomposite due to the formation of branched 3D networks with covalent bonds between nanotubes. It was revealed that adhesion of proteins to branched 3D networks from SWCNT occurred. The specific electrical conductivity of nanocomposites based on large SWCNT nanotubes was 3.2 and 4.3 S/m compared to that for nanocomposites based on small SWCNT with the same concentrations—1.1 and 1.8 S/m. An increase in the concentration and size of nanotubes provides higher porosity of nanocomposites. For small SWCNT-based nanocomposites, a significant number of mesopores up to 50 nm in size and the largest specific surface area and specific pore volume were found. Nanocomposites with small SWCNT (0.001 wt.%) provided the best cardiac fibroblast viability. Such technology can be potentially used to create bioelectronic components or scaffolds for heart tissue engineering.
Tracking Control of Autonomous Underwater Vehicles with Acoustic Localization and Extended Kalman Filter
Authors: Zhan Dongzhou , Zheng Huarong , Xu Wen
Published: August 2021

The absence of global positioning system (GPS) signals and the influence of ocean currents are two of the main challenges facing the autonomy of autonomous underwater vehicles (AUVs). This paper proposes an acoustic localization-based tracking control method for AUVs. Particularly, three buoys that emit acoustic signals periodically are deployed over the surface. Times of arrivals of these acoustic signals at the AUV are then obtained and used to calculate an estimated position of the AUV. Moreover, the uncertainties involved in the localization and ocean currents are handled together in the framework of the extended Kalman filter. To deal with system physical constraints, model predictive control relying on online repetitive optimizations is applied in the tracking controller design. Furthermore, due to the different sampling times between localization and control, the dead-reckoning technique is utilized considering detailed AUV dynamics. To avoid using the highly nonlinear and complicated AUV dynamics in the online optimizations, successive linearizations are employed to achieve a trade-off between computational complexity and control performance. Simulation results show that the proposed algorithms are effective and can achieve the AUV tracking control goals.
Optimal Techno-Economic Planning of a Smart Parking Lot—Combined Heat, Hydrogen, and Power (SPL-CHHP)-Based Microgrid in the Active Distribution Network
Authors: Hosseinnia Hamed , Mohammadi-Ivatloo Behnam , Mohammadpourfard Mousa
Published: August 2021

By installing distributed generation (DG) sources in a distribution system, there is a change from the inactive state, accompanied by one-way power flow, to the active state, with the possibility of bilateral power flow. Authorities involved in the electricity industry manage the consumption side by bringing in particular programs called demand response programs. To implement these programs, it is crucial to create infrastructure, including the installation of smart measuring units in the consumption sector. In this paper, we investigate the optimal design of smart meters and combined hydrogen, heat, and power in the active distribution system to provide two functions aimed at reducing voltage drop and minimizing the total planning costs by taking different scenarios into account. In the combined hydrogen, heat, and power (CHHP)-based DGs, due to the low efficiency of the electrolyzer, its power is supplied by a smart parking lot (including wind turbines, photovoltaic systems, and batteries). To model the unit’s uncertainties, a long short-time memory (LSTM) model is employed. Utilizing the technique for order preference by similarity to ideal solution (TOPSIS), a state that enhances both functions is acquired from different scenarios. All of the simulations are carried out in two 33-bus systems.
Health Risk and Environmental Assessment of Cement Production in Nigeria
Authors: Etim Mmemek-Abasi , Babaremu Kunle , Lazarus Justin , Omole David
Published: August 2021

The cement manufacturing industry has played a fundamental role in global economic development, but its production is a major facilitator to anthropogenic CO2 release and solid waste generation. Nigeria has the largest cement industry in West Africa, with an aggregate capacity of 58.9 million metric tonnes (MMT) per year. The Ministry for Mines and Steel Development asserts that the nation possesses total limestone deposits of around 2.3 trillion MT with 568 MMT standing as established reserves and 11 MMT used. Cement industries are largely responsible for releasing air pollutants and effluents into water bodies with apparent water quality deterioration over the years. Air pollution from lime and cement-producing plants is seen as a severe instigator of occupational health hazards and work-related life threats, negatively affecting crop yields, buildings, and persons residing in the vicinity of these industries. World Bank observed in 2015 that 94% of the Nigerian populace is susceptible to air pollutants that surpass WHO guidelines. In 2017, World Bank further reported that 49,100 premature deaths emanated from atmospheric PM2.5, with children beneath age 5 having the greatest vulnerability owing to lower respiratory infections, thereby representing approximately 60% of overall PM2.5-induced deaths. Cement manufacturing involves the significant production of SO2, NOx, and CO connected to adverse health effects on humans. Sensitive populations such as infants, the aged, and persons having underlying respiratory ailments like asthmatics, emphysema, or bronchitis are seen to be most affected. Consequently, in addressing this challenge, growing interests in enacting carbon capture, usage, and storage in the cement industry is expected to alleviate the negative environmental impact of cement production. Still, no carbon capture technology is yet to achieve commercialization in the cement industry. Nonetheless, huge advancement has been made in recent years with the advent of vital research in sorption-enhanced water gas shift, underground gasification combined cycle, ammonium hydroxide solution, and the microbial-induced synthesis of calcite for CO2 capture and storage, all considered sustainable and feasible in cement production.
Temporal and Spatial Trends in Particulate Matter and the Responses to Meteorological Conditions and Environmental Management in Xi’an, China
Authors: Tian Yulu , Zhang Lingnan , Wang Yang , Song Jinxi , Sun Haotian
Published: August 2021

Particulate matter contributes much to the haze pollution in China. Meteorological conditions and environmental management significantly influenced the accumulation, deposition, transportation, diffusion, and emission intensity of particulate matter. In this study, temporal and spatial variations of PM10 and PM2.5—and the responses to meteorological factors and environmental regulation intensity—were explored in Xi’an, China. The concentrations of PM10 were higher than those of PM2.5, especially in spring and winter. The mean annual concentrations of PM10 and PM2.5 markedly decreased from 2013 to 2017, but the decreasing trend has plateaued since 2015. The concentrations of PM10 and PM2.5 exhibited seasonal differences, with winter being the highest and summer the lowest. Air quality monitoring stations did not reveal significant spatial variability in PM10 and PM2.5 concentrations. The concentrations of PM10 and PM2.5 were significantly influenced by precipitation, relative humidity, and atmospheric temperature. The impact of wind speed was prominent in autumn and winter, while in spring and summer the impact of wind direction was obvious. Additionally, the emission intensity of SO2, smoke and dust could be effectively decreased with the increasing environmental regulation intensity, but not the concentrations of particulate matter. This study could provide a scientific framework for atmospheric pollution management.
Statistical Evidence for Managing Forest Density in Consideration of Natural Volatile Organic Compounds
Authors: Choi Yeji , Kim Geonwoo , Park Sujin , Lee Sangtae , Kim Soojin , Kim Eunsoo
Published: August 2021

Rapid deforestation, coupled with the growing population seeking forest therapy, urges the necessity for research on how to maximize forests’ therapeutic functions when cultivating damaged or unmanaged forests. This study was formulated to provide a basis for forest stand density management to maximize the therapeutic effects of forests with a focus on natural volatile organic compounds (NVOCs), a representative component of forest therapy through analysis of variance and regression analyses. The results of this study revealed all studied stand densities yield the highest total NVOC (TNVOC) emissions in summer, especially in the study site which has a forest density of 700/ha. In addition, treeless areas (0/ha) were found to have the most significant difference in average NVOC emissions when cultivated at a density of 700/ha. When managing forests with a density of 900/ha to 1000/ha, it has been shown that it is most desirable, in terms of therapeutic function efficiency, to control a density of 500/ha to 700/ha. Finally, regression equations for the five experimental sites with significant explanatory power were derived. Based on the results of the conducted analyses, 700/ha of forest density is recommended to maximize the therapeutic effects of forests, compared to other ranges of forest density.
Train Performance Analysis Using Heterogeneous Statistical Models
Authors: Wang Jianfeng , Yu Jun
Published: August 2021

This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance.
Genetic Determinants of Non-Syndromic Enlarged Vestibular Aqueduct: A Review
Authors: Roesch Sebastian , Rasp Gerd , Sarikas Antonio , Dossena Silvia
Published: August 2021

Hearing loss is the most common sensorial deficit in humans and one of the most common birth defects. In developed countries, at least 60% of cases of hearing loss are of genetic origin and may arise from pathogenic sequence alterations in one of more than 300 genes known to be involved in the hearing function. Hearing loss of genetic origin is frequently associated with inner ear malformations; of these, the most commonly detected is the enlarged vestibular aqueduct (EVA). EVA may be associated to other cochleovestibular malformations, such as cochlear incomplete partitions, and can be found in syndromic as well as non-syndromic forms of hearing loss. Genes that have been linked to non-syndromic EVA are SLC26A4, GJB2, FOXI1, KCNJ10, and POU3F4. SLC26A4 and FOXI1 are also involved in determining syndromic forms of hearing loss with EVA, which are Pendred syndrome and distal renal tubular acidosis with deafness, respectively. In Caucasian cohorts, approximately 50% of cases of non-syndromic EVA are linked to SLC26A4 and a large fraction of patients remain undiagnosed, thus providing a strong imperative to further explore the etiology of this condition.