bluuebunny/crossref_metadata_2025 huggingface dataset:
Protective Effects of Black Raspberry (Rubus occidentalis) Extract against Hypercholesterolemia and Hepatic Inflammation in Rats Fed High-Fat and High-Choline Diets
Authors: Lim Taehwan , Ryu Juhee , Lee Kiuk , Park Sun Young , Hwang Keum Taek
Published: August 2020

Choline is converted to trimethylamine by gut microbiota and further oxidized to trimethylamine-N-oxide (TMAO) by hepatic flavin monooxygenases. Positive correlation between TMAO and chronic diseases has been reported. Polyphenols in black raspberry (BR), especially anthocyanins, possess various biological activities. The objective of this study was to determine the effects of BR extract on the level of choline-derived metabolites, serum lipid profile, and inflammation markers in rats fed high-fat and high-choline diets. Forty female Sprague-Dawley (SD) rats were randomly divided into four groups and fed for 8 weeks as follows: CON (AIN-93G diet), HF (high-fat diet), HFC (HF + 1.5% choline water), and HFCB (HFC + 0.6% BR extract). Serum levels of TMAO, total cholesterol, and low-density lipoprotein (LDL)-cholesterol and cecal trimethylamine (TMA) level were significantly higher in the HFC than in the HFCB. BR extract decreased mRNA expression of pro-inflammatory genes including nuclear factor-κB (NF-κB), interleukin (IL)-1β, IL-6, and cyclooxygenase-2 (COX-2), and protein expression of NF-κB and COX-2 in liver tissue. These results suggest that consistent intake of BR extract might alleviate hypercholesterolemia and hepatic inflammation induced by excessive choline with a high-fat diet via lowering elevated levels of cecal TMA and serum TMAO in rats.
Rehabilitation Nutrition for Injury Recovery of Athletes: The Role of Macronutrient Intake
Authors: Papadopoulou Sousana K.
Published: August 2020

An adequate and balanced diet is of utmost importance in recovery and rehabilitation. “Rehabilitation nutrition” for injury recovery of athletes is similar to sports nutrition, except for the differences that concern the prevention of the risk or presence of sarcopenia, malnutrition, or dysphagia. Rehabilitation nutrition also aims, combined with training, to an adequate long-term nutritional status of the athlete and also in physical condition improvement, in terms of endurance and resistance. The aim of this paper is to define the proper nutrition for athletes in order to hasten their return to the sports after surgery or injury. Energy intake should be higher than the energy target in order to fight sarcopenia—that is 25–30 kcal/kg of body weight. Macro- and micro-nutrients play an important role in metabolism, energy production, hemoglobin synthesis, lean mass and bone mass maintenance, immunity, health, and protection against oxidative damage. Nutritional strategies, such as supplementation of suboptimal protein intake with leucine are feasible and effective in offsetting anabolic resistance. Thus, maintaining muscle mass, without gaining fat, becomes challenging for the injured athlete. A dietary strategy should be tailored to the athlete’s needs, considering amounts, frequency, type and, most of all, protein quality. During rehabilitation, simultaneous carbohydrates and protein intake can inhibit muscle breakdown and muscle atrophy. The long-term intake of omega-3 fatty acids enhances anabolic sensitivity to amino acids; thus, it may be beneficial to the injured athlete. Adequate intakes of macronutrients can play a major role supporting athletes’ anabolism.
Hybrid Pectin-Liposome Formulation against Multi-Resistant Bacterial Strains
Authors: Ribeiro Lígia Nunes de Morais , de Paula Eneida , Rossi Daise Aparecida , Monteiro Guilherme Paz , Júnior Edson Campos Valadares , Silva Rogério Reis , Franco Rodrigo Rodrigues , Espíndola Foued Salmen , Goulart Luiz Ricardo , Fonseca Belchiolina Beatriz
Published: August 2020

This work describes the development of a gastroresistant antimicrobial formulation composed of two carriers, pectin and liposomes, intended to improve the efficiency of norfloxacin (NOR) against multi-resistant bacterial strains. The formulations showed physicochemical stability for 180 days (4 °C) in terms of size, polydispersity, and zeta potential of the vesicles, prolonging the in vitro release of NOR for 11 h. The hybrid nanocarriers improved the in vitro antimicrobial activity against different multidrug-resistant bacterial strains, such as Salmonella sp., Pseudomonasaeruginosa, E. coli and Campylobacterjejuni, in comparison to commercial NOR and liposomal suspensions. The in vivo toxicity assay in chicken embryos revealed that the hybrid systems were not toxic in any of the different parameters analyzed, a result also corroborated by the analyses of biochemical biomarkers of the chicken-embryos liver function.
Use of Supplemented or Human Material to Simulate PD Behavior of Antibiotics at the Target Site In Vitro
Authors: Nussbaumer-Pröll Alina , Zeitlinger Markus
Published: August 2020

In antimicrobial drug development, in vitro antibiotic susceptibility testing is conducted in standard growth media, such as Mueller–Hinton broth (MHB). These growth media provide optimal bacterial growth, but do not consider certain host factors that would be necessary to mimic the in vivo bacterial environment in the human body. The present review aimed to include relevant data published between 1986 and 2019. A database search (PubMed) was done with text keywords, such as “MIC” (minimal inhibitory concentration), “TKC” (time kill curve), “blood”, “body fluid”, “PD” (pharmacodynamic), and “in vitro”, and 53 papers were ultimately selected. Additionally, a literature search for physiologic characteristics of body fluids was conducted. This review gives an excerpt of the complexity of human compartments with their physiologic composition. Furthermore, we present an update of currently available in vitro models operated either with adapted growth media or body fluids themselves. Moreover, the feasibility of testing the activity of antimicrobials in such settings is discussed, and pro and cons for standard practice methods are given. The impact on bacterial killing varies between individual adapted microbiological media, as well as direct pharmacodynamic simulations in body fluids, between bacterial strains, antimicrobial agents, and the compositions of the adjuvants or the biological fluid itself.
The Limits of Classical Extensional Mereology for the Formalization of Whole–Parts Relations in Quantum Chemical Systems
Authors: Banchetti-Robino Marina Paola
Published: August 2020

This paper examines whether classical extensional mereology is adequate for formalizing the whole–parts relation in quantum chemical systems. Although other philosophers have argued that classical extensional and summative mereology does not adequately formalize whole–parts relation within organic wholes and social wholes, such critiques often assume that summative mereology is appropriate for formalizing the whole–parts relation in inorganic wholes such as atoms and molecules. However, my discussion of atoms and molecules as they are conceptualized in quantum chemistry will establish that standard mereology cannot adequately fulfill this task, since the properties and behavior of such wholes are context-dependent and cannot simply be reduced to the summative properties of their parts. To the extent that philosophers of chemistry have called for the development of an alternative mereology for quantum chemical systems, this paper ends by proposing behavioral mereology as a promising step in that direction. According to behavioral mereology, considerations of what constitutes a part of a whole is dependent upon the observable behavior displayed by these entities. Thus, relationality and context-dependence are stipulated from the outset and this makes behavioral mereology particularly well-suited as a mereology of quantum chemical wholes. The question of which mereology is appropriate for formalizing the whole–parts relation in quantum chemical systems is relevant to contemporary philosophy of chemistry, since this issue is related to the more general questions of the reducibility of chemical wholes to their parts and of the reducibility of chemistry to physics, which have been of central importance within the philosophy of chemistry for several decades. More generally, this paper puts contemporary discussions of mereology within the philosophy of chemistry into a broader historical and philosophical context. In doing so, this paper also bridges the gap between formal mereology, conceived as a branch of formal ontology, and “applied” mereology, conceived as a branch of philosophy of science.
The Significance of Carrier Leakage for Stable Lasing in Split-Well Direct Phonon Terahertz Quantum Cascade Lasers
Authors: Lander Gower Nathalie , Piperno Silvia , Albo Asaf
Published: August 2020

We studied the temperature performance of split-well direct phonon terahertz quantum cascade lasers and found that it is limited by a lasing instability that becomes significant as the temperature increases. When the hot electrons of the upper laser level cannot scatter effectively to excited states due to the high radiative barriers of the structures, a lasing instability occurs, which limits the temperature performance.
Tetracycline Induces the Formation of Biofilm of Bacteria from Different Phases of Wastewater Treatment
Authors: Stachurová Tereza , Malachová Kateřina , Semerád Jaroslav , Sterniša Meta , Rybková Zuzana , Smole Možina Sonja
Published: August 2020

The study monitored the effect of tetracycline on bacterial biofilm formation and compared biofilm formation by resistant bacterial strains in different phases of the wastewater treatment process in wastewater treatment plant (WWTP). The crystal violet staining method was used to evaluate the biofilm formation. Biofilm-related bacterial properties were characterized by hydrophobicity, autoaggregation and motility tests. The relative abundance of tetracycline resistance genes (tetW, tetM, tetO, tetA and tetB) in wastewaters were subsequently quantified using qPCR. The results show that the isolates from the nitrification tank produce biofilm with up to 10 times greater intensity relative to the isolates from the sedimentation tank. In isolates of Aeromonas sp. from the nitrification tank, increased biofilm production in the occurrence of tetracycline from a concentration of 0.03125 µg/mL was observed. The tetW gene showed the highest relative abundance out of all the tested genes. From the sampling points, its abundance was the highest in the sedimentation tank of the WWTP. Based on these results, it can be assumed that resistant bacteria are able to form a biofilm and sub-inhibitory tetracycline concentrations induce biofilm formation. WWTPs thus represent a reservoir of antibiotic resistance genes and contribute to the spread of resistance in the natural environment.
Assessment of Eco-Friendly Pavement Construction and Maintenance Using Multi-Recycled RAP Mixtures
Authors: Vandewalle David , Antunes Vítor , Neves José , Freire Ana Cristina
Published: August 2020

The demand for more sustainable solutions has led an ever-growing number of stakeholders to being committed to pursue the principles of sustainability in pavement management. Different stakeholders have been looking for tools and methodologies to evaluate the environmental impacts of the solutions, for which the life cycle assessment (LCA) proved to be an appropriate methodology. This paper is focused on the LCA of road pavement multi-recycling based on the use of bituminous mixtures with high rates of reclaimed asphalt pavement (RAP). In order to promote the circular economy, a comparative analysis was performed on a road pavement section by taking into account different scenarios, which stem from the combination of production, construction and rehabilitation activities incorporating different RAP rates in new bituminous mixtures: 0% (as reference), 25%, 50%, 75% and 100%, respectively. LCA results have been expressed in terms of four damage categories: human health, ecosystem quality, climate change and resources. Results have shown that both recycled and multi-recycled bituminous mixtures lead to substantial benefits in comparison with the solution employing virgin materials, hence embodying a sustainable approach. The benefits grow with the increase in the RAP rate with an average decrease of 19%, 23%, 31% and 33% in all the impact categories for a 25%, 50%, 75% and 100% of RAP rate.
Detection of Tailings Dams Using High-Resolution Satellite Imagery and a Single Shot Multibox Detector in the Jing–Jin–Ji Region, China
Authors: Li Qingting , Chen Zhengchao , Zhang Bing , Li Baipeng , Lu Kaixuan , Lu Linlin , Guo Huadong
Published: August 2020

The timely and accurate mapping and monitoring of mine tailings dams is crucial to the improvement of management practices by decision makers and to the prevention of disasters caused by failures of these dams. Due to the complex topography, varying geomorphological characteristics, and the diversity of ore types and mining activities, as well as the range of scales and production processes involved, as they appear in remote sensing imagery, tailings dams vary in terms of their scale, color, shape, and surrounding background. The application of high-resolution satellite imagery for automatic detection of tailings dams at large spatial scales has been barely reported. In this study, a target detection method based on deep learning was developed for identifying the locations of tailings ponds and obtaining their geographical distribution from high-resolution satellite imagery automatically. Training samples were produced based on the characteristics of tailings ponds in satellite images. According to the sample characteristics, the Single Shot Multibox Detector (SSD) model was fine-tuned during model training. The results showed that a detection accuracy of 90.2% and a recall rate of 88.7% could be obtained. Based on the optimized SSD model, 2221 tailing ponds were extracted from Gaofen-1 high resolution imagery in the Jing–Jin–Ji region in northern China. In this region, the majority of tailings ponds are located at high altitudes in remote mountainous areas. At the city level, the tailings ponds were found to be located mainly in Chengde, Tangshan, and Zhangjiakou. The results prove that the deep learning method is very effective at detecting complex land-cover features from remote sensing images.
Climatology Characteristics of Ionospheric Irregularities Described with GNSS ROTI
Authors: Kotulak Kacper , Zakharenkova Irina , Krankowski Andrzej , Cherniak Iurii , Wang Ningbo , Fron Adam
Published: August 2020

At equatorial and high latitudes, the intense ionospheric irregularities and plasma density gradients can seriously affect the performances of radio communication and satellite-based navigation systems; that represents a challenging topic for the scientific and engineering communities and operational use of communication and navigation services. The GNSS-based ROTI (rate of TEC index) is one of the most widely used indices to monitor the occurrence and intensity of ionospheric irregularities. In this paper, we examined the long-term performance of the ROTI in terms of finding the climatological characteristics of TEC fluctuations. We considered the different scale temporal signatures and checked the general sensitivity to the solar and geomagnetic activity. We retrieved and analyzed long-term time-series of ROTI values for two chains of GNSS stations located in European and North-American regions. This analysis covers three full years of the 24th solar cycle, which represent different levels of solar activity and include periods of intense geomagnetic storms. The ionospheric irregularities’ geographical distribution, as derived from ROTI, shows a reasonable consistency to be found within the poleward/equatorward boundaries of the auroral oval specified by empirical models. During magnetic midnight and quiet-time conditions, the equatorward boundary of the ROTI-derived ionospheric irregularity zone was observed at 65–70° of north magnetic latitude, while for local noon conditions this boundary was more poleward at 75–85 magnetic latitude. The ionospheric irregularities of low-to-moderate intensity were found to occur within the auroral oval at all levels of geomagnetic activity and seasons. At moderate and high levels of solar activity, the intensities of ionospheric irregularities are larger during local winter conditions than for the local summer and polar day conditions. We found that ROTI displays a selective latitudinal sensitivity to the auroral electrojet activity—the strongest dependence (correlation R > 0.6–0.8) was observed within a narrow latitudinal range of 55–70°N magnetic latitude, which corresponded to a band of the largest ROTI values within the auroral oval zone expanded equatorward during geomagnetic disturbances.
A Robust Laser Stripe Extraction Method for Structured-Light Vision Sensing
Authors: Zhao Congyang , Yang Jianing , Zhou Fuqiang , Sun Junhua , Li Xiaosong , Xie Wentao
Published: August 2020

Environmental sensing is a key technology for the development of unmanned cars, drones and robots. Many vision sensors cannot work normally in an environment with insufficient light, and the cost of using multiline LiDAR is relatively high. In this paper, a novel and inexpensive visual navigation sensor based on structured-light vision is proposed for environment sensing. The main research contents of this project include: First, we propose a laser-stripe-detection neural network (LSDNN) that can eliminate the interference of reflective noise and haze noise and realize the highly robust extraction of laser stripes region. Then we use a gray-gravity approach to extract the center of laser stripe and used structured-light model to reconstruct the point clouds of laser center. Then, we design a single-line structured-light sensor, select the optimal parameters for it and build a car–platform for experimental evaluation. This approach was shown to be effective in our experiments and the experimental results show that this method is more accurate and robust in complex environment.
Application of Linear Gradient Magnetic Field in Arterial Profile Scanning Imaging
Authors: Liu Yanjun , Liu Guoqiang , Yang Dan , Xu Bin
Published: August 2020

Background and Objectives: Cardiovascular and cerebrovascular diseases caused by arterial stenosis and sclerosis are the main causes of human death. Although there are mature diagnostic techniques in clinical practice, they are not suitable for early disease prediction and monitoring due to their high cost and complex operation. The purpose of this paper is to study the coupling effect of arterial blood flow and linear gradient magnetic field, and to propose a method for the reconstruction of the arterial profile, which will lay a theoretical foundation for new electromagnetic artery scanning imaging technology. Methods and Models: A combination coil composed of gradient coils and drive coils is applied as a magnetic field excitation source. By controlling the excitation current, a linearly gradient magnetic field with a line-shaped zero magnetic field is generated, and the zero magnetic field is driven to scan in a specific direction. According to the magnetoelectric effect of blood flow, under the action of the external magnetic field, the voltage signals on the body surface can be detected by measuring electrodes. The location of the artery center line can be determined by the time–space relationship between voltage signals and zero magnetic field scanning. In addition, based on the reciprocity theorem integral equation, a numerical model between the amplitude of the voltage signal and the arterial radius is derived to reconstruct the arterial radius. The above physical process was simulated in the finite element analysis software COMSOL, and the voltage signals obtained from the simulation verified the arterial profile reconstruction. Results: Through finite element simulation verification, the imaging method based on a linear gradient magnetic field has a numerical accuracy of 90% and a spatial resolution of 1 mm. Moreover, under 100 Hz low-frequency alternating current excitation, the single scanning time is 0.005 s, which is far shorter than the arterial blood flow change cycle, meeting the requirements of real-time imaging. The results demonstrate the effectiveness and high theoretical feasibility of the proposed method in real-time arterial imaging. Conclusions: This study indicates the potential application of linear gradient magnetic fields in arterial profile imaging. Compared with traditional electromagnetic imaging methods, the proposed method has the advantages of fast imaging speed and high resolution, showing the certain application value in early real-time imaging of arterial disease. However, further studies are necessary to confirm its effectiveness in clinical practice by more medical data and real cases.
Development of a Diagnosis and Evaluation System for Hemiplegic Patients Post-Stroke Based on Motion Recognition Tracking and Analysis of Wrist Joint Kinematics
Authors: Kim Subok , Park Seoho , Lee Onseok
Published: August 2020

An inexperienced therapist lacks the analysis of a patient’s movement. In addition, the patient does not receive objective feedback from the therapist due to the visual subjective judgment. The aim is to provide a guide for in-depth rehabilitation therapy in virtual space by continuously tracking the user’s wrist joint during Leap Motion Controller (LMC) activities and present the basic data to confirm steady therapy results in real-time. The conventional Box and Block Test (BBT) is commonly used in upper extremity rehabilitation therapy. It was modeled in proportion to the actual size and Auto Desk Inventor was used to perform the 3D modeling work. The created 3D object was then implemented in C # through Unity5.6.2p4 based on LMC. After obtaining a wrist joint motion value, the motion was analyzed by 3D graph. Healthy subjects (23 males and 25 females, n = 48) were enrolled in this study. There was no statistically significant counting difference between conventional BBT and system BBT. This indicates the possibility of effective diagnosis and evaluation of hemiplegic patients post-stroke. We can keep track of wrist joints, check real-time continuous feedback in the implemented virtual space, and provide the basic data for an LMC-based quantitative rehabilitation therapy guide.
The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat
Authors: Liu Huajian , Bruning Brooke , Garnett Trevor , Berger Bettina
Published: August 2020

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.
First Evaluation of PRISMA Level 1 Data for Water Applications
Authors: Giardino Claudia , Bresciani Mariano , Braga Federica , Fabbretto Alice , Ghirardi Nicola , Pepe Monica , Gianinetto Marco , Colombo Roberto , Cogliati Sergio , Ghebrehiwot Semhar , Laanen Marnix , Peters Steef , Schroeder Thomas , Concha Javier A. , Brando Vittorio E.
Published: August 2020

This study presents a first assessment of the Top-Of-Atmosphere (TOA) radiances measured in the visible and near-infrared (VNIR) wavelengths from PRISMA (PRecursore IperSpettrale della Missione Applicativa), the new hyperspectral satellite sensor of the Italian Space Agency in orbit since March 2019. In particular, the radiometrically calibrated PRISMA Level 1 TOA radiances were compared to the TOA radiances simulated with a radiative transfer code, starting from in situ measurements of water reflectance. In situ data were obtained from a set of fixed position autonomous radiometers covering a wide range of water types, encompassing coastal and inland waters. A total of nine match-ups between PRISMA and in situ measurements distributed from July 2019 to June 2020 were analysed. Recognising the role of Sentinel-2 for inland and coastal waters applications, the TOA radiances measured from concurrent Sentinel-2 observations were added to the comparison. The results overall demonstrated that PRISMA VNIR sensor is providing TOA radiances with the same magnitude and shape of those in situ simulated (spectral angle difference, SA, between 0.80 and 3.39; root mean square difference, RMSD, between 0.98 and 4.76 [mW m−2 sr−1 nm−1]), with slightly larger differences at shorter wavelengths. The PRISMA TOA radiances were also found very similar to Sentinel-2 data (RMSD < 3.78 [mW m−2 sr−1 nm−1]), and encourage a synergic use of both sensors for aquatic applications. Further analyses with a higher number of match-ups between PRISMA, in situ and Sentinel-2 data are however recommended to fully characterize the on-orbit calibration of PRISMA for its exploitation in aquatic ecosystem mapping.
Why Temporal Persistence of Biometric Features, as Assessed by the Intraclass Correlation Coefficient, Is So Valuable for Classification Performance
Authors: Friedman Lee , Stern Hal S. , Price Larry R. , Komogortsev Oleg V.
Published: August 2020

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer this question. In a recent report, we introduced the intraclass correlation coefficient (ICC) as an index of temporal persistence for such features. Here, we present a novel approach using synthetic features to study which aspects of a biometric identification study are influenced by the temporal persistence of features. What we show is that using more temporally persistent features produces effects on the similarity score distributions that explain why this quality is so key to biometric performance. The results identified with the synthetic data are largely reinforced by an analysis of two datasets, one based on eye-movements and one based on gait. There was one difference between the synthetic and real data, related to the intercorrelation of features in real data. Removing these intercorrelations for real datasets with a decorrelation step produced results which were very similar to that obtained with synthetic features.
Anonymous Real-Time Analytics Monitoring Solution for Decision Making Supported by Sentiment Analysis
Authors: de Oliveira Júnior Gildásio Antonio , de Oliveira Albuquerque Robson , Borges de Andrade César Augusto , de Sousa Rafael Timóteo , Sandoval Orozco Ana Lucila , García Villalba Luis Javier
Published: August 2020

Currently, social networks present information of great relevance to various government agencies and different types of companies, which need knowledge insights for their business strategies. From this point of view, an important technique for data analysis is to create and maintain an environment for collecting data and transforming them into intelligence information to enable analysts to observe the evolution of a given topic, elaborate the analysis hypothesis, identify botnets, and generate data to aid in the decision-making process. Focusing on collecting, analyzing, and supporting decision-making, this paper proposes an architecture designed to monitor and perform anonymous real-time searches in tweets to generate information allowing sentiment analysis on a given subject. Therefore, a technological structure and its implementation are defined, followed by processes for data collection and analysis. The results obtained indicate that the proposed solution provides a high capacity to collect, process, search, analyze, and view a large number of tweets in several languages, in real-time, with sentiment analysis capabilities, at a low cost of implementation and operation.
Parameter Estimation for Two-Dimensional Incoherently Distributed Source with Double Cross Arrays
Authors: Wu Tao , Li Yiwen , Deng Zhenghong , Feng Bo , Ma Xinping
Published: August 2020

A direction of arrival (DOA) estimator for two-dimensional (2D) incoherently distributed (ID) sources is presented under proposed double cross arrays, satisfying both the small interval of parallel linear arrays and the aperture equalization in the elevation and azimuth dimensions. First, by virtue of a first-order Taylor expansion for array manifold vectors of parallel linear arrays, the received signal of arrays can be reconstructed by the products of generalized manifold matrices and extended signal vectors. Then, the rotating invariant relations concerning the nominal elevation and azimuth are derived. According to the rotating invariant relationships, the rotating operators are obtained through the subspace of the covariance matrix of the received vectors. Last, the angle matching approach and angular spreads are explored based on the Capon principle. The proposed method for estimating the DOA of 2D ID sources does not require a spectral search and prior knowledge of the angular power density function. The proposed DOA estimation has a significant advantage in terms of computational cost. Investigating the influence of experimental conditions and angular spreads on estimation, numerical simulations are carried out to validate the effectiveness of the proposed method. The experimental results show that the algorithm proposed in this paper has advantages in terms of estimation accuracy, with a similar number of sensors and the same experimental conditions when compared with existing methods, and that it shows a robustness in cases of model mismatch.
Development of Real-Time Hand Gesture Recognition for Tabletop Holographic Display Interaction Using Azure Kinect
Authors: Lee Chanhwi , Kim Jaehan , Cho Seoungbae , Kim Jinwoong , Yoo Jisang , Kwon Soonchul
Published: August 2020

The use of human gesturing to interact with devices such as computers or smartphones has presented several problems. This form of interaction relies on gesture interaction technology such as Leap Motion from Leap Motion, Inc, which enables humans to use hand gestures to interact with a computer. The technology has excellent hand detection performance, and even allows simple games to be played using gestures. Another example is the contactless use of a smartphone to take a photograph by simply folding and opening the palm. Research on interaction with other devices via hand gestures is in progress. Similarly, studies on the creation of a hologram display from objects that actually exist are also underway. We propose a hand gesture recognition system that can control the Tabletop holographic display based on an actual object. The depth image obtained using the latest Time-of-Flight based depth camera Azure Kinect is used to obtain information about the hand and hand joints by using the deep-learning model CrossInfoNet. Using this information, we developed a real time system that defines and recognizes gestures indicating left, right, up, and down basic rotation, and zoom in, zoom out, and continuous rotation to the left and right.
Design of Wearable EEG Devices Specialized for Passive Brain–Computer Interface Applications
Authors: Park Seonghun , Han Chang-Hee , Im Chang-Hwan
Published: August 2020

Owing to the increased public interest in passive brain–computer interface (pBCI) applications, many wearable devices for capturing electroencephalogram (EEG) signals in daily life have recently been released on the market. However, there exists no well-established criterion to determine the electrode configuration for such devices. Herein, an overall procedure is proposed to determine the optimal electrode configurations of wearable EEG devices that yield the optimal performance for intended pBCI applications. We utilized two EEG datasets recorded in different experiments designed to modulate emotional or attentional states. Emotion-specialized EEG headsets were designed to maximize the accuracy of classification of different emotional states using the emotion-associated EEG dataset, and attention-specialized EEG headsets were designed to maximize the temporal correlation between the EEG index and the behavioral attention index. General purpose electrode configurations were designed to maximize the overall performance in both applications for different numbers of electrodes (2, 4, 6, and 8). The performance was then compared with that of existing wearable EEG devices. Simulations indicated that the proposed electrode configurations allowed for more accurate estimation of the users’ emotional and attentional states than the conventional electrode configurations, suggesting that wearable EEG devices should be designed according to the well-established EEG datasets associated with the target pBCI applications.
ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning
Authors: Jia Hongwei , Luo Haiyong , Wang Hao , Zhao Fang , Ke Qixue , Wu Mingyao , Zhao Yunyun
Published: August 2020

Passenger flow prediction has drawn increasing attention in the deep learning research field due to its great importance in traffic management and public safety. The major challenge of this essential task lies in multiple spatiotemporal correlations that exhibit complex non-linear correlations. Although both the spatial and temporal perspectives have been considered in modeling, most existing works have ignored complex temporal correlations or underlying spatial similarity. In this paper, we identify the unique spatiotemporal correlation of urban metro flow, and propose an attention-based deep spatiotemporal network with multi-task learning (ADST-Net) at a citywide level to predict the future flow from historical observations. ADST-Net uses three independent channels with the same structure to model the recent, daily-periodic and weekly-periodic complicated spatiotemporal correlations, respectively. Specifically, each channel uses the framework of residual networks, the rectified block and the multi-scale convolutions to mine spatiotemporal correlations. The residual networks can effectively overcome the gradient vanishing problem. The rectified block adopts an attentional mechanism to automatically reweigh measurements at different time intervals, and the multi-scale convolutions are used to extract explicit spatial relationships. ADST-Net also introduces an external embedding mechanism to extract the influence of external factors on flow prediction, such as weather conditions. Furthermore, we enforce multi-task learning to utilize transition passenger flow volume prediction as an auxiliary task during the training process for generalization. Through this model, we can not only capture the steady trend, but also the sudden changes of passenger flow. Extensive experimental results on two real-world traffic flow datasets demonstrate the obvious improvement and superior performance of our proposed algorithm compared with state-of-the-art baselines.
Enhancing an Analysis Method of Compound Flooding in Coastal Areas by Linking Flow Simulation Models of Coasts and Watershed
Authors: Lee Sangho , Kang Taeuk , Sun Dongkyun , Park Jong-Jip
Published: August 2020

Rainfall, tide, and wave overtopping can together cause inundation in some coastal areas. However, there have been few cases of inundation analysis considering compound flooding due to the difficulty of the interdisciplinary technique. The purpose of this study is to suggest an analysis technique of compound flooding in coastal areas that links flow simulation tools of coasts and watershed. XP-SWMM was used to analyze rainfall–runoff simulation and 2D surface inundation analysis. A coupled model of ADCIRC and SWAN (ADCSWAN) was used for analyzing expected flow, including wave spectrum, tide, and storm surge from the distant ocean, and the FLOW-3D model was used to estimate the flow and wave overtopping in the coastal area. The analysis technique was applied to Marine City located in Busan, the Republic of Korea, where rainfall and wave overtopping occurred simultaneously during typhoons, and the results were reasonable. The study results are meaningful as they can contribute to the improvement of reproducibility of real phenomena of compound flooding in coastal areas through linked application of flow simulation tools of coasts and watershed.
The Spillover Effect between Carbon Emission Trading (CET) Price and Power Company Stock Price in China
Authors: Li Yanbin , Nie Dan , Li Bingkang , Li Xiyu
Published: August 2020

The power sector is one of the major contributors to China’s carbon emissions, and its low-carbon transformation is of vital importance to China’s long-term sustainable development. This paper aims to investigate the spillover effect between the carbon emission trading (CET) market and power sector in China from a systematic perspective. We adopted the recently developed method of connectedness network and rolling window approach, and found that: (i) during our sample period, the total static spillover index and the average of total dynamic spillover indexes were 60.5735% and 57.9704%, respectively, and the spillover effect of this carbon-power system was relatively strong; (ii) there is weak bidirectional spillover effect between the CET market and the power sector, and the CET market is a net receiver of the information from the power sector; (iii) the CET market may exert a relatively high degree of impact on the power sector occasionally; (iv) for regulated power companies, their interactions with the carbon-power system may be related to its total holding installed capacity and the proportion of renewable energy installed. This study provides implications for policymakers, company managers, and market participants.
Does Gender Diversity Affect Performance in Agri-Food Cooperatives? A Moderated Model
Authors: Meliá-Martí Elena , Tormo-Carbó Guillermina , Juliá-Igual Juan Francisco
Published: August 2020

Existing research about the relationship between gender diversity and performance in cooperatives is not conclusive. In view of this reality, this paper aims firstly to analyse the effectiveness of gender diversity and equality management systems (GDMS) in promoting gender diversity in the decision-making bodies (GDDB) as well as in the performance of agri-food cooperatives. Secondly, the objective is to establish the relationship between GDDB and performance, and subsequently, to analyse the moderating effect of GDDB on three of the business strategies adopted by cooperatives in order to achieve competitive advantages: Integration strategies, internationalisation strategies, and environmental concern, based on a survey carried out in 2018 using a sample of 2489 Spanish agri-food cooperatives. A moderation analysis was conducted to test the proposed model and hypotheses. The results obtained confirm a positive relationship between the implementation by cooperatives of GDMS and GDDB. The relationship between GDMS, GDDB, and performance was not significant. The moderating effect of GDDB was only statistically significant in the case of export intensity (EI) and environmental concern (EC), although, contrary to expectations, this effect was negative, meaning that the impact of both strategies on performance becomes more apparent as GDDB is reduced.
Entrepreneurship, Competitiveness and Innovation
Authors: Franco Mário
Published: August 2020

This Special Issue, “Entrepreneurship, Competitiveness and Innovation”, comprises a selection of papers addressing approaches and tools to understand how entrepreneurship and innovation can be good vehicles for competitiveness. These studies address the multifaceted topics surrounding entrepreneurship, such as exploratory and exploitative innovation performance, inter-enterprise knowledge, clusters, entrepreneurial orientation, learning orientation, sustainable growth, etc. These topics include the definitions of the concepts of entrepreneurship, innovation, and competitiveness, as well as the identification of factors affecting these types of phenomena. Perspectives guiding the design of entrepreneurship and innovation are presented to be considered when implementing public policies for increasing economic growth and competitiveness. Papers use some support theories to explain the topics studied here, such as cluster theory, resources-based theory, social theory and institutional theory, among others. Thus, in general, this Special Issue is devoted to the study of the benefits of entrepreneurship, innovation practices, and competitiveness in various countries and regions worldwide, but mainly in China. Therefore, this Special Issue is of particular value for both academic research and the context of business.
Dynamic Behavior and Deposit Features of Debris Avalanche in Model Tests Using High Speed Photogrammetry
Authors: Wei Yong , Xu Qiang , Yang He , Li Huajin , Kou Pinglang
Published: August 2020

Model tests of debris avalanche can not only illuminate formation mechanisms but also represent deformation and motion processes. At present, the static terrain data of model tests are measured before and after experiments using terrestrial laser scanning. To study the motion and deformation of research objects, it is necessary to explore new techniques to obtain dynamic terrain data in the course of experimentation. In this paper, taking specified experimental tests of debris avalanche as an example, the method of 4D reconstruction using high-speed close-range photogrammetry is described in detail. The dynamic terrain data of model tests were obtained after the data were processed. Then, the dynamic behavior and deposit features of debris avalanche were analyzed in detail. Results show that dynamic terrain data of model tests can be obtained rapidly and accurately with this method. The propagation and deposit processes of the debris avalanche have evident stage characteristics, which can be divided into the starting, acceleration, constant, and deceleration stages. The granular size, slope angle, and barrier effect have a great influence on the travel distance and duration of the debris avalanche. The depth of the intermediate and leading area of the debris avalanche increased gradually and the depth of the trailing area first increased then decreased. We believe that this approach can also be applied to other domains involving the acquisition of dynamic terrain data and, thus, deserves to be applied widely.
Change Factors and the Adaptability of Buildings
Authors: Kamara John M. , Heidrich Oliver , Tafaro Vincenza E. , Maltese Sebastiano , Dejaco Mario C. , Re Cecconi Fulvio
Published: August 2020

The adaptability of buildings addresses the responses of buildings to the changing needs of owners/users and the demands of external factors, over their lifecycle. An understanding of these changes is therefore key to the creation of adaptable buildings. This paper reports research which was aimed at modelling building changes to better understand the challenges for their adaptability. An in-depth study of the changes in selected case studies was conducted to understand the nature, characteristics, and implications of these changes for buildings and their ability to adapt. The findings from these case studies were analyzed against theoretical models reported in the literature on change and adaptability. As a result, a model was developed that identified and categorized a wide spectrum of changes to the building fabric within the broad remit of adaptability that are triggered by many factors, which are sometimes external to the building or organization. In the cases investigated, it was found that the factors that lead to actual changes to buildings were not necessarily due to the ease of making those changes, but rather the organizational will and means to make the changes. Similarly, changes were made not because the building systems were obsolete, but because of non-building factors. The timings of changes therefore did not correspond to the assumed lifespan models of different building layers, suggesting that a new way of predicting and/or categorizing building changes is needed. Furthermore, the interrelationships and nature of the triggers for change suggest that the adaptability of buildings is not just about building systems, but also about non-building factors. Thus, the further exploration of non-building triggers and enablers for change using the developed model presented here, will further enhance the creation of more adaptable buildings.
Analysis of CO2 Abatement Cost of Solar Energy Integration in a Solar-Aided Coal-Fired Power Generation System in China
Authors: Zhao Jun , Yang Kun
Published: August 2020

Utilization of renewable energy, improvement of power generation efficiency, and reduction of fossil fuel consumption are important strategies for the Chinese power industry in response to climate change and environment challenges. Solar thermal energy can be integrated into a conventional coal-fired power unit to build a solar-aided coal-fired power generation (SACPG) system. Because solar heat can be used more efficiently in a SACPG system, the solar-coal hybrid power system can reduce coal consumption and CO2 emissions. The performance and costs of a SACPG system are affected by the respective characteristics of its coal-fired system and solar thermal power system, their coupling effects, the solar energy resource, the costs of the solar power system, and other economic factors of coal price and carbon price. According to the characteristics of energy saving and CO2 emission reductions of a SACPG system, a general methodology of CO2 abatement cost for the hybrid system is proposed to assess the solar thermal energy integration reasonably and comprehensively. The critical factors for carbon abatement cost are also analyzed. Taking a SACPG system of 600 MW in Jinan, Shandong and in Hohhot, Inner Mongolia in China as an example, the methodology is further illustrated. The results show that the efficiency of solar heat-to-electricity should be high and it is 0.391 in the scheme of SIH1 in Hohhot, and that the designed direct normal irradiation (DNI) should be greater than 800 W/m2 in order to make full use of solar energy resources. It is indicated that the abatement cost of a SACPG system depends significantly both on the cost of solar power system and its relevant costs, and also on the fuel price or the carbon prices, and that the carbon abatement cost can be greatly reduced as the coal prices or CO2 price increase. The methodology of carbon abatement cost can provide support for the comprehensive assessment of a SACPG system for its design and optimal performance.