bluuebunny/crossref_metadata_2025 huggingface dataset:
Moisture Adsorption and Desorption Behavior of Raw Materials for the T-RTM Process
Authors: Herzog Janek , Wendel Rainer , Weidler Peter , Wilhelm Michael , Rosenberg Philipp , Henning Frank
Published: January 2021

The use of fiber reinforced plastics (FRPs) has significant potential to reduce the weight of components. As regards the sustainability of these components, thermoplastic matrices offer more potential for recycling than thermoset ones. A possible manufacturing process for the production of thermoplastic FRPs is thermoplastic resin transfer molding (T-RTM). In this very moisture-sensitive process, ε-caprolactam in addition to an activator and catalyst polymerizes anionically to polyamide 6 (aPA6). The anionic polymerization of aPA6 is slowed down or even completely blocked by the presence of water. This study analyses the sorption behavior of the matrix, fiber, binder and core materials for the production of anionic polyamide 6 composites, which are processed in the thermoplastic RTM process. Water vapor sorption measurements are used to determine the adsorption and desorption behavior of the materials. The maximum moisture loading of the materials provides information about the water adsorption capacity of the material. This knowledge is crucial for correct handling of the materials to achieve a fast process and good properties of the final product.
Ex Vivo Systems to Study Chondrogenic Differentiation and Cartilage Integration
Authors: Monaco Graziana , El Haj Alicia J. , Alini Mauro , Stoddart Martin J.
Published: January 2021

Articular cartilage injury and repair is an issue of growing importance. Although common, defects of articular cartilage present a unique clinical challenge due to its poor self-healing capacity, which is largely due to its avascular nature. There is a critical need to better study and understand cellular healing mechanisms to achieve more effective therapies for cartilage regeneration. This article aims to describe the key features of cartilage which is being modelled using tissue engineered cartilage constructs and ex vivo systems. These models have been used to investigate chondrogenic differentiation and to study the mechanisms of cartilage integration into the surrounding tissue. The review highlights the key regeneration principles of articular cartilage repair in healthy and diseased joints. Using co-culture models and novel bioreactor designs, the basis of regeneration is aligned with recent efforts for optimal therapeutic interventions.
Boat Noise and Black Drum Vocalizations in Mar Chiquita Coastal Lagoon (Argentina)
Authors: Ceraulo Maria , Sal Moyano María Paz , Hidalgo Fernando Jose , Bazterrica María Cielo , Mazzola Salvatore , Gavio María Andrea , Buscaino Giuseppa
Published: January 2021

Human-generated underwater noise and its effect on marine biota is recognized as an important issue. Boat noise can affect the communication success of fish species that use sounds for spawning purposes. During the reproductive period, males of the black drum Pogonias spp. produce calls ranging from 90 Hz to 300 Hz. In the Mar Chiquita coastal lagoon (Buenos Aires, Argentina), Pogonias courbina is one of the primary fishing species. Although no regulation is directly applied to protect it, a ban protects the reproductive period of other fish species during weekdays. Here, we investigated the potential effect of boat noise on P. courbina vocalizations through a passive acoustic method. Acoustic data were collected, and P. courbina calls were identified and counted. The files with boat noise passages were categorized into classes according to their noise frequency range (A = below 700 Hz, B = over 700 Hz, and C = below and above 700 Hz). The fish call rate was lower in files where boat noise overlapped the fish call frequency (Classes A and C). Only boat noise from Class C was significantly reduced during days with the active fishing ban. These results suggest that anthropogenic noise may affect the P. courbina call rate and underline the importance of including the evaluation of anthropogenic noise in the current management of the area.
Fabrication and Evaluation of Nano-TiO2 Superhydrophobic Coating on Asphalt Pavement
Authors: Li Hongfeng , Lin Xiangwen , Wang Hongguang
Published: January 2021

In order to address water damage of asphalt pavement, reduce the occurrence of water-related potholes, deformation, and other diseases, and improve the performance and service life of the pavement, a nano-TiO2 superhydrophobic coating (PSC) on asphalt pavement was prepared from waterborne polyurethane and nano-TiO2 modified by stearic acid. FT-IR measured stearic acid successfully modified low surface energy substance on the surface of nano-TiO2. The SEM image shows that the PSC has a rough surface structure. The contact angle and rolling angle of the PSC in the contact angle test are 153.5° and 4.7°, respectively. PSC has a super-hydrophobic ability, which can improve the water stability of the asphalt mixture. Although the texture depth and pendulum value have been reduced by 2.5% and 4.4%, respectively, they all comply with the standard requirements. After the abrasion resistance test, the PSC coating still has a certain hydrophobic ability. These results surface PSC coating can effectively reduce water damage on asphalt pavement, and has considerable application value.
Effects of Curing Conditions on the MECHANICAL and Microstructural Properties of Ultra-High-Performance Concrete (UHPC) Incorporating Iron Tailing Powder
Authors: Lu Dong , Zhong Jing , Yan Baobao , Gong Jing , He Ziye , Zhang Guanhua , Song Chengzhe
Published: January 2021

It has been reported that iron tailing powder (ITP) has the potential to partially replace cement to prepare ultra-high-performance concrete (UHPC). However, the reactivity of ITP particles in concrete largely depends on the curing method. This study investigates the effects of curing conditions on the mechanical and microstructural properties of UHPC containing ITP. To achieve this objective, three research tasks are conducted, including (1) preparing seven concrete formulations by introducing ITP; (2) characterizing their mechanical performance under different curing regimes; and (3) analyzing their microstructure by XRD patterns, FTIR analysis, and SEM observation. The experimental results show that there is an optimum ITP dosage (15%) for their application. The concrete with 15% ITP under standard curing obtains 94.3 MPa at 7 days, their early-age strength could be even further increased by ~30% (warm-water curing) and ~35% (steamed curing). The steam curing regime stimulates the activity of ITP and refines the microstructure. This study demonstrates the potential of replacing Portland cement with ITP in UHPC production.
Intrinsic Dielectric Loss in Zr0.8Sn0.2TiO4 Ceramics Investigated by Terahertz Time Domain Spectroscopy
Authors: Nedelcu Liviu , Geambasu Cezar Dragos , Enculescu Monica , Banciu Marian Gabriel
Published: January 2021

Terahertz time-domain spectroscopy (THz-TDS) was employed for estimation of intrinsic dielectric loss of Zr0.8Sn0.2TiO4 (ZST) ceramics. Single-phase ZST dielectric resonators (DRs) with various synthesis parameters and, consequently, different extrinsic losses, were prepared by conventional ceramic technology. Even though the DRs exhibit a similar microstructure, their quality factor (Q is the inverse of dielectric loss tangent) measured in microwave (MW) domain at 6 GHz varies between 2500 and 8400. On the other hand, it was found that the THz dielectric loss is less sensitive to the sample preparation. The intrinsic losses (Q × f ~60 THz) of the ZST ceramics have been derived from THz data.
Lyophilized Polyvinylpyrrolidone Hydrogel for Culture of Human Oral Mucosa Stem Cells
Authors: Oliver-Urrutia Carolina , Rosales Ibañez Raúl , Flores-Merino Miriam V. , Vojtova Lucy , Salplachta Jakub , Čelko Ladislav , Kaiser Jozef , Montufar Edgar B.
Published: January 2021

This work shows the synthesis of a polyvinylpyrrolidone (PVP) hydrogel by heat-activated polymerization and explores the production of hydrogels with an open porous network by lyophilisation to allow the three-dimensional culture of human oral mucosa stem cells (hOMSCs). The swollen hydrogel showed a storage modulus similar to oral mucosa and elastic solid rheological behaviour without sol transition. A comprehensive characterization of porosity by scanning electron microscopy, mercury intrusion porosimetry and nano-computed tomography (with spatial resolution below 1 μm) showed that lyophilisation resulted in the heterogeneous incorporation of closed oval-like pores in the hydrogel with broad size distribution (5 to 180 μm, d50 = 65 μm). Human oral mucosa biopsies were used to isolate hOMSCs, expressing typical markers of mesenchymal stem cells in more than 95% of the cell population. Direct contact cytotoxicity assay demonstrated that PVP hydrogel have no negative effect on cell metabolic activity, allowing the culture of hOMSCs with normal fusiform morphology. Pore connectivity should be improved in future to allow cell growth in the bulk of the PVP hydrogel.
Four-Fold Multi-Modal X-ray Microscopy Measurements of a Cu(In,Ga)Se2 Solar Cell
Authors: Ossig Christina , Strelow Christian , Flügge Jan , Kolditz Andreas , Siebels Jan , Garrevoet Jan , Spiers Kathryn , Seyrich Martin , Brückner Dennis , Pyrlik Niklas , Hagemann Johannes , Seiboth Frank , Schropp Andreas , Carron Romain , Falkenberg Gerald , Mews Alf , Schroer Christian , Kipp Tobias , Stuckelberger Michael
Published: January 2021

Inhomogeneities and defects often limit the overall performance of thin-film solar cells. Therefore, sophisticated microscopy approaches are sought to characterize performance and defects at the nanoscale. Here, we demonstrate, for the first time, the simultaneous assessment of composition, structure, and performance in four-fold multi-modality. Using scanning X-ray microscopy of a Cu(In,Ga)Se2 (CIGS) solar cell, we measured the elemental distribution of the key absorber elements, the electrical and optical response, and the phase shift of the coherent X-rays with nanoscale resolution. We found structural features in the absorber layer—interpreted as voids—that correlate with poor electrical performance and point towards defects that limit the overall solar cell efficiency.
Mycosporine-Like Amino Acids from Marine Resource
Authors: Figueroa Félix L.
Published: January 2021

In the last 10 years, a great number of publications (both regular papers and reviews) have been published on the interesting molecules—mycosporine-like amino acids (MAAs). Despite significant advances in the research of MAAs, current overviews in the recent publications involving MAA research still need reporting. The aim of this Special Issue is to join, as an interdisciplinary approach, the photochemical and photobiological aspects, with emphasis on new natural resources to obtain both algae and zooplankton MAAs, advances in methodology of extraction and chemical identification of new MAAs. Finally, this Special Issue reviews the bioactivities of MAAs including UVR screen, antioxidant, immunostimulant, growth factor, DNA protection, inhibition of collagenase, elastase and hyaluronidase, and anti-photoaging, among others, and their potential use as nutracosmeceutic molecules (i.e., oral and topic photoprotector).
The Proinflammatory Soluble CD40 Ligand Is Associated with the Systemic Extent of Stable Atherosclerosis
Authors: Pereira-da-Silva Tiago , Napoleão Patrícia , Pinheiro Teresa , Selas Mafalda , Silva Filipa , Ferreira Rui Cruz , Carmo Miguel Mota
Published: January 2021

Background and objectives: Polyvascular atherosclerosis is frequent and associated with a high cardiovascular risk, although the mechanisms regulating the atherosclerosis extent to single or multiple arterial territories are still poorly understood. Inflammation regulates atherogenesis and soluble CD40 ligand (sCD40L) is an inflammatory mediator associated with the presence of single-territorial atherosclerosis. We assessed whether the sCD40L expression is associated with the atherosclerosis extent to single or multiple arterial territories and with the atherosclerosis severity in different territories. Materials and Methods: We prospectively enrolled 94 participants with no atherosclerosis (controls, n = 26); isolated coronary atherosclerosis (group 1, n = 20); coronary and lower extremity (LE) atherosclerosis (group 2, n = 18); coronary and carotid atherosclerosis (group 3, n = 12); and coronary, LE, and carotid atherosclerosis (group 4, n = 18). Serum sCD40L levels were quantified. Results: The sCD40L levels (ng/mL, mean (standard deviation)) were 4.0 (1.5), 5.6 (2.6), 7.2 (4.2), 5.9 (3.7), and 5.1 (2.4) in controls and groups 1 to 4, respectively (ANOVA p = 0.012). In nonrevascularized patients, the sCD40L levels were significantly higher in group 2 than in group 1 and were correlated with the number of LE diseased segments. Prior LE bypass surgery was associated with lower sCD40L levels. Coexistence of coronary and LE atherosclerosis was independently associated with the sCD40L levels. Conclusions: The sCD40L levels were increased in stable atherosclerosis, particularly in polyvascular coronary and LE atherosclerosis. The number of LE diseased segments and prior LE revascularization were associated with sCD40L expression. To our knowledge, these are novel data, which provide insights into the mechanisms underlying multi-territorial atherosclerosis expression. sCD40L may be a promising noninvasive tool for refining the stratification of the systemic atherosclerotic burden.
Helicobacter Infection and Gastric Adenoma
Authors: Bertz Simone , Angeloni Miriam , Drgac Jan , Falkeis Christina , Lang-Schwarz Corinna , Sterlacci William , Veits Lothar , Hartmann Arndt , Vieth Michael
Published: January 2021

Background: We aimed to provide insight into the actual frequencies of gastric adenoma types and their association with gastritis status and associated mucosal changes with a focus on Helicobacter infection and the operative link on gastritis assessment (OLGA)/operative link on gastric intestinal metaplasia assessment (OLGIM) staging. Methods: From the archive of the Institute of Pathology in Bayreuth, we collected a consecutive series of 1058 gastric adenomas diagnosed between 1987 and 2017. Clinicopathological parameters retrieved from diagnostic reports included adenoma type and localization, associated mucosal changes in antrum and corpus (i.e., type of gastritis, the extent of intestinal metaplasia and atrophy), gender, date of birth, and date of diagnosis. Results: Intestinal-type adenoma was the most frequent adenoma (89.1%), followed by foveolar-type adenoma (4.3%), pyloric gland adenoma (3.4%), adenomas associated with hereditary tumor syndromes (2.8%), and oxyntic gland adenoma (0.4%). Adenomas were found in the background of Helicobacter pylori (H. pylori) gastritis in 23.9%, Ex-H. pylori gastritis in 36.0%, autoimmune gastritis in 24.8%, chemical reactive gastritis in 7.4%, and others in 0.1%. More than 70% of patients with gastric adenomas had low-risk stages in OLGA and OLGIM. Conclusions: We found a higher frequency of foveolar-type adenoma than anticipated from the literature. It needs to be questioned whether OLGA/OLGIM staging can be applied to all patients.
Therapeutic Potential of Natural Products in Treatment of Cervical Cancer: A Review
Authors: Park Seung-Hyeok , Kim Minsun , Lee Somi , Jung Woojin , Kim Bonglee
Published: January 2021

Cervical cancer is the fourth most common cancer among women worldwide. Though several natural products have been reported regarding their efficacies against cervical cancer, there has been no review article that categorized them according to their anti-cancer mechanisms. In this study, anti-cancerous natural products against cervical cancer were collected using Pubmed (including Medline) and google scholar, published within three years. Their mechanisms were categorized as induction of apoptosis, inhibition of angiogenesis, inhibition of metastasis, reduction of resistance, and regulation of miRNAs. A total of 64 natural products suppressed cervical cancer. Among them, Penicillium sclerotiorum extracts from Cassia fistula L., ethanol extracts from Bauhinia variegate candida, thymoquinone obtained from Nigella sativa, lipid-soluble extracts of Pinellia pedatisecta Schott., and 1′S-1′-acetoxychavicol extracted from Alpinia conchigera have been shown to have multi-effects against cervical cancer. In conclusion, natural products could be attractive candidates for novel anti-cancer drugs.
Mechanical Properties of Poly(ethylene-co-methacrylic acid) Reinforced with Carbon Fibers
Authors: Haramina Tatjana , Pugar Daniel , Ivančević Darko , Smojver Ivica
Published: January 2021

The capability of poly(ethylene-co-methacrylic acid) (E/MAA) to self-heal is well known, however, its mechanical properties are weak. In this study, composites with single and double layers of unidirectional (UD) carbon fibers were prepared by compression molding. Even a low mass fraction of fibers substantially improved the polymer. The flexural and tensile properties were tested at 0°, 45° and 90° fibers direction and compared to those of the matrix. The mechanical properties in the 0° direction proved superior. Flexural properties depended on the reinforcement distance from the stress neutral plane. The tensile modulus in the 0° direction was 13 times greater despite only a 2.5% mass fraction of fibers. However, both tensile modulus and strength were observed to degrade in the 90° direction. Dynamic mechanical analysis showed the dependence of both structure and properties on the thermal history of E/MAA. Tensile tests after ballistic impact showed that the modulus of the self-healed E/MAA was not affected, yet the strength, yield point, and particularly the elongation at break were reduced. A composite with higher fiber content could be prepared by mixing milled E/MAA particles in fibers prior to compression.
Polymeric Materials for Water and Wastewater Management
Authors: Kyzas George Z. , Mitropoulos Athanasios C.
Published: January 2021

Water is a crucial point of interest nowadays due to its special management [...]
Prediction of Maize Yield at the City Level in China Using Multi-Source Data
Authors: Chen Xinxin , Feng Lan , Yao Rui , Wu Xiaojun , Sun Jia , Gong Wei
Published: January 2021

Maize is a widely grown crop in China, and the relationships between agroclimatic parameters and maize yield are complicated, hence, accurate and timely yield prediction is challenging. Here, climate, satellite data, and meteorological indices were integrated to predict maize yield at the city-level in China from 2000 to 2015 using four machine learning approaches, e.g., cubist, random forest (RF), extreme gradient boosting (Xgboost), and support vector machine (SVM). The climate variables included the diffuse flux of photosynthetic active radiation (PDf), the diffuse flux of shortwave radiation (SDf), the direct flux of shortwave radiation (SDr), minimum temperature (Tmn), potential evapotranspiration (Pet), vapor pressure deficit (Vpd), vapor pressure (Vap), and wet day frequency (Wet). Satellite data, including the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and adjusted vegetation index (SAVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), were used. Meteorological indices, including growing degree day (GDD), extreme degree day (EDD), and the Standardized Precipitation Evapotranspiration Index (SPEI), were used. The results showed that integrating all climate, satellite data, and meteorological indices could achieve the highest accuracy. The highest estimated correlation coefficient (R) values for the cubist, RF, SVM, and Xgboost methods were 0.828, 0.806, 0.742, and 0.758, respectively. The climate, satellite data, or meteorological indices inputs from all growth stages were essential for maize yield prediction, especially in late growth stages. R improved by about 0.126, 0.117, and 0.143 by adding climate data from the early, peak, and late-period to satellite data and meteorological indices from all stages via the four machine learning algorithms, respectively. R increased by 0.016, 0.016, and 0.017 when adding satellite data from the early, peak, and late stages to climate data and meteorological indices from all stages, respectively. R increased by 0.003, 0.032, and 0.042 when adding meteorological indices from the early, peak, and late stages to climate and satellite data from all stages, respectively. The analysis found that the spatial divergences were large and the R value in Northwest region reached 0.942, 0.904, 0.934, and 0.850 for the Cubist, RF, SVM, and Xgboost, respectively. This study highlights the advantages of using climate, satellite data, and meteorological indices for large-scale maize yield estimation with machine learning algorithms.
SBAS-Aided GPS Positioning with an Extended Ionosphere Map at the Boundaries of WAAS Service Area
Authors: Kim Mingyu , Kim Jeongrae
Published: January 2021

Space-based augmentation system (SBAS) provides correction information for improving the global navigation satellite system (GNSS) positioning accuracy in real-time, which includes satellite orbit/clock and ionospheric delay corrections. At SBAS service area boundaries, the correction is not fully available to GNSS users and only a partial correction is available, mostly satellite orbit/clock information. By using the geospatial correlation property of the ionosphere delay information, the ionosphere correction coverage can be extended by a spatial extrapolation algorithm. This paper proposes extending SBAS ionosphere correction coverage by using a biharmonic spline extrapolation algorithm. The wide area augmentation system (WAAS) ionosphere map is extended and its ionospheric delay error is compared with the GPS Klobuchar model. The mean ionosphere error reduction at low latitude is 52.3%. The positioning accuracy of the extended ionosphere correction method is compared with the accuracy of the conventional SBAS positioning method when only a partial set of SBAS corrections are available. The mean positioning error reduction is 44.8%, and the positioning accuracy improvement is significant at low latitude.
Assessing the Potential of LPWAN Communication Technologies for Near Real-Time Leak Detection in Water Distribution Systems
Authors: Pointl Michael , Fuchs-Hanusch Daniela
Published: January 2021

While low-power wide-area network (LPWAN) technologies have been studied extensively for a broad spectrum of smart city applications, their potential for water distribution system monitoring in high temporal resolution has not been studied in detail. However, due to their low power demand, these technologies offer new possibilities for operating pressure-monitoring devices for near real-time leak detection in water distribution systems (WDS). By combining long-distance wireless communication with low power consumption, LPWAN technologies promise long periods of maintenance-free device operation without having to rely on an external power source. This is of particular importance for pressure-based leak detection where optimal sensor positions are often located in the periphery of WDS without a suitable power source. To assess the potential of these technologies for replacing widely-used wireless communication technologies for leak detection, GPRS is compared with the LPWAN standards Narrowband IoT, long-range wide area network (LoRaWAN) and Sigfox. Based on sampling and transmission rates commonly applied in leak detection, the ability of these three technologies to replace GPRS is analyzed based on a self-developed low-power pressure-monitoring device and a simplified, linear energy-consumption model. The results indicate that even though some of the analyzed LPWAN technologies may suffer from contractual and technical limitations, all of them offer viable alternatives, meeting the requirements of leak detection in WDS. In accordance with existing research on data transmission with these technologies, the findings of this work show that even while retaining a compact design, which entails a limited battery capacity, pressure-monitoring devices can exceed runtimes of 5 years, as required for installation at water meters in Austria. Thus, LPWAN technologies have the potential to advance the wide application of near real-time, pressure-based leak detection in WDS, while simultaneously reducing the cost of device operation significantly.
SynPo-Net—Accurate and Fast CNN-Based 6DoF Object Pose Estimation Using Synthetic Training
Authors: Su Yongzhi , Rambach Jason , Pagani Alain , Stricker Didier
Published: January 2021

Estimation and tracking of 6DoF poses of objects in images is a challenging problem of great importance for robotic interaction and augmented reality. Recent approaches applying deep neural networks for pose estimation have shown encouraging results. However, most of them rely on training with real images of objects with severe limitations concerning ground truth pose acquisition, full coverage of possible poses, and training dataset scaling and generalization capability. This paper presents a novel approach using a Convolutional Neural Network (CNN) trained exclusively on single-channel Synthetic images of objects to regress 6DoF object Poses directly (SynPo-Net). The proposed SynPo-Net is a network architecture specifically designed for pose regression and a proposed domain adaptation scheme transforming real and synthetic images into an intermediate domain that is better fit for establishing correspondences. The extensive evaluation shows that our approach significantly outperforms the state-of-the-art using synthetic training in terms of both accuracy and speed. Our system can be used to estimate the 6DoF pose from a single frame, or be integrated into a tracking system to provide the initial pose.
Trajectory Identification for Moving Loads by Multicriterial Optimization
Authors: Gawlicki Michał , Jankowski Łukasz
Published: January 2021

Moving load is a fundamental loading pattern for many civil engineering structures and machines. This paper proposes and experimentally verifies an approach for indirect identification of 2D trajectories of moving loads. In line with the “structure as a sensor” paradigm, the identification is performed indirectly, based on the measured mechanical response of the structure. However, trivial solutions that directly fit the mechanical response tend to be erratic due to measurement and modeling errors. To achieve physically meaningful results, these solutions need to be numerically regularized with respect to expected geometric characteristics of trajectories. This paper proposes a respective multicriterial optimization framework based on two groups of criteria of a very different nature: mechanical (to fit the measured response of the structure) and geometric (to account for the geometric regularity of typical trajectories). The state-of-the-art multiobjective genetic algorithm NSGA-II is used to find the Pareto front. The proposed approach is verified experimentally using a lab setup consisting of a plate instrumented with strain gauges and a line-follower robot. Three trajectories are tested, and in each case the determined Pareto front is found to properly balance between the mechanical response fit and the geometric regularity of the trajectory.
A Hybrid Approach to Industrial Augmented Reality Using Deep Learning-Based Facility Segmentation and Depth Prediction
Authors: Kim Minseok , Choi Sung Ho , Park Kyeong-Beom , Lee Jae Yeol
Published: January 2021

Typical AR methods have generic problems such as visual mismatching, incorrect occlusions, and limited augmentation due to the inability to estimate depth from AR images and attaching the AR markers onto physical objects, which prevents the industrial worker from conducting manufacturing tasks effectively. This paper proposes a hybrid approach to industrial AR for complementing existing AR methods using deep learning-based facility segmentation and depth prediction without AR markers and a depth camera. First, the outlines of physical objects are extracted by applying a deep learning-based instance segmentation method to the RGB image acquired from the AR camera. Simultaneously, a depth prediction method is applied to the AR image to estimate the depth map as a 3D point cloud for the detected object. Based on the segmented 3D point cloud data, 3D spatial relationships among the physical objects are calculated, which can assist in solving the visual mismatch and occlusion problems properly. In addition, it can deal with a dynamically operating or a moving facility, such as a robot—the conventional AR cannot do so. For these reasons, the proposed approach can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. Quantitative and qualitative analyses verify the advantage of the proposed approach compared with existing AR methods. Some case studies also prove that the proposed method can be applied not only to manufacturing but also to other fields. These studies confirm the scalability, effectiveness, and originality of this proposed approach.
Influence of the Bearing Thermal Deformation on Nonlinear Dynamic Characteristics of an Electric Drive Helical Gear System
Authors: Liu Xianghuan , Liu Defu , Hu Xiaolan
Published: January 2021

Based on the statics and quasi-statics analysis methods, the thermal deformation calculation model of a deep-groove ball bearing was constructed for the helical gear transmission system of a high speed electric drive, and the radial and axial bearing stiffness values of the bearing were calculated under the thermal deformation in this study. The obtained radial and axial stiffness values were introduced into the established dynamics model of helical gear system, and the influence of changed bearing stiffness, resulting from the thermal deformation, on the nonlinear dynamic characteristics of gear pair was analyzed using the Runge–Kutta method. The results show that the axial and radial deformations of bearing occur due to the increase of working speed and temperature, in which the axial stiffness of bearing is improved but the radial stiffness is reduced. The decreasing degree of axial stiffness and the increasing degree of radial stiffness decrease with the gradually increasing working rotational speed. When considering the influence of thermal deformation on the bearing stiffness, the helical gear system will have nonlinear behaviors, such as single periodic, double periodic, and chaotic motion with the change of working speed. Therefore, in order to improve the nonlinear dynamic characteristics of high speed electric drive gear systems, the influence of bearing stiffness change on the dynamic performance of a gear system should be considered in the industrial applications.
An Energy-Efficient and Secure Data Inference Framework for Internet of Health Things: A Pilot Study
Authors: Kang James Jin , Dibaei Mahdi , Luo Gang , Yang Wencheng , Haskell-Dowland Paul , Zheng Xi
Published: January 2021

Privacy protection in electronic healthcare applications is an important consideration, due to the sensitive nature of personal health data. Internet of Health Things (IoHT) networks that are used within a healthcare setting have unique challenges and security requirements (integrity, authentication, privacy, and availability) that must also be balanced with the need to maintain efficiency in order to conserve battery power, which can be a significant limitation in IoHT devices and networks. Data are usually transferred without undergoing filtering or optimization, and this traffic can overload sensors and cause rapid battery consumption when interacting with IoHT networks. This poses certain restrictions on the practical implementation of these devices. In order to address these issues, this paper proposes a privacy-preserving two-tier data inference framework solution that conserves battery consumption by inferring the sensed data and reducing data size for transmission, while also protecting sensitive data from leakage to adversaries. The results from experimental evaluations on efficiency and privacy show the validity of the proposed scheme, as well as significant data savings without compromising data transmission accuracy, which contributes to energy efficiency of IoHT sensor devices.
Lasers for Satellite Uplinks and Downlinks
Authors: Dmytryszyn Mark , Crook Matthew , Sands Timothy
Published: January 2021

The use of Light Amplification by Stimulated Emission of Radiation (i.e., LASERs or lasers) by the U.S. Department of Defense is not new and includes laser weapons guidance, laser-aided measurements, and even lasers as weapons (e.g., Airborne Laser). Lasers in the support of telecommunications is also not new. The use of laser light in fiber optics has shattered thoughts on communications bandwidth and throughput. Even the use of lasers in space is no longer new. Lasers are being used for satellite-to-satellite crosslinking. Laser communication can transmit orders-of-magnitude more data using orders-of-magnitude less power and can do so with minimal risk of exposure to the sending and receiving terminals. What is new is using lasers as the uplink and downlink between the terrestrial segment and the space segment of satellite systems. More so, the use of lasers to transmit and receive data between moving terrestrial segments (e.g., ships at sea, airplanes in flight) and geosynchronous satellites is burgeoning. This manuscript examines the technological maturation of employing lasers as the signal carrier for satellite communications linking terrestrial and space systems. The purpose of the manuscript is to develop key performance parameters (KPPs) to inform the U.S. Department of Defense initial capabilities documents (ICDs) for near-future satellite acquisition and development. By appreciating the history and technological challenges of employing lasers, rather than traditional radio frequency sources for satellite uplink and downlink signal carriers, this manuscript recommends ways for the U.S. Department of Defense to employ lasers to transmit and receive high bandwidth, and large-throughput data from moving platforms that need to retain low probabilities of detection, intercept, and exploit (e.g., carrier battle group transiting to a hostile area of operations, unmanned aerial vehicle collecting over adversary areas). The manuscript also intends to identify commercial sector early-adopter fields and those fields likely to adapt to laser employment for transmission and receipt.
Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service
Authors: Nam Sunghyun , Yoon Sejun , Raghavan Nagarajan , Park Hyunseok
Published: January 2021

This research proposes a data-driven systematic method to discover service opportunities in a specific service sector. Specifically, the method quantitatively identifies the important but unsatisfied customer needs by analyzing online review data. To represent customer needs in a structured form, the job-to-be-done-based customer outcomes are adopted from the outcome-driven innovation (ODI) framework. Therefore, job-to-be-done information is extracted from the review data and is transformed into customer outcomes. The outcomes having high service opportunities are selected by metrics for quantifying the importance and satisfaction score of the outcomes. This paper conducted an empirical study for hotel service using relevant review data. The results show that the method can identify customer needs in hotel service—e.g., maximizing safety to pay price/deposit, and maximizing possibility to avoid waiting at lobby—and objectively prioritize strategic directions for service innovation. Therefore, the proposed method can be used as an intelligent tool for the effective development of a business strategy.
A Holistic Approach to Integrate and Evaluate Sustainable Development in Higher Education. The Case Study of the University of the Basque Country
Authors: Sáez de Cámara Estibaliz , Fernández Idoia , Castillo-Eguskitza Nekane
Published: January 2021

Since the United Nations (UN) approved the Agenda 2030 for Sustainable Development in 2015, higher education institutions have increasingly demonstrated their commitment by supporting several initiatives. Although a great deal of progress has been made, there is still a lack of integrative approaches to truly implement Sustainable Development Goals (SDGs) in higher education. This paper presents a practical case that illustrates how to design and articulate SDGs within an institutional setting adopting a holistic approach: EHUagenda 2030 plan of the University of the Basque Country (UPV/EHU). It is based on empirical inquiry into global and holistic sustainable transformation and a real experience to move towards a verifiable and pragmatic contribution to sustainability. This plan describes the contribution to 12 of the 17 SDGs, along with three sectorial plans (Equality Campus, Inclusion Campus and Planet Campus), as well as the refocus of the UPV/EHU’s Educational Model and the panel of sustainable development indicators, which addresses the technical aspects of monitoring the SDGs. The methodology (mapping; mainstreaming; diagnosis and definition and, finally, estimation) is systematic and replicable in other universities yet to embark upon this integration. This case study makes a contribution towards the understanding of the complexity of the changes in Higher Education and the ways to approach it.
Speed Limit Induced CO2 Reduction on Motorways: Enhancing Discussion Transparency through Data Enrichment of Road Networks
Authors: Kunkler Jan , Braun Maximilian , Kellner Florian
Published: January 2021

Considering climate change, recent political debates often focus on measures to reduce CO2 emissions. One key component is the reduction of emissions produced by motorized vehicles. Since the amount of emission directly correlates to the velocity of a vehicle via energy consumption factors, a general speed limit is often proposed. This article presents a methodology to combine openly available topology data of road networks from OpenStreetMap (OSM) with pay-per-use API traffic data from TomTom to evaluate such measures transparently by analyzing historical real-world circumstances. From our exemplary case study of the German motorway network, we derive that most parts of the motorway network on average do not reach their maximum allowed speed throughout the day due to traffic, construction sites and general road utilization by network participants. Nonetheless our findings prove that the introduction of a speed limit of 120 km per hour on the German autobahn would restrict 50.74% of network flow kilometers for a CO2 reduction of 7.43% compared to the unrestricted state.
Environmental Impact and Levelised Cost of Energy Analysis of Solar Photovoltaic Systems in Selected Asia Pacific Region: A Cradle-to-Grave Approach
Authors: Ahmad Ludin Norasikin , Ahmad Affandi Nurfarhana Alyssa , Purvis-Roberts Kathleen , Ahmad Azah , Ibrahim Mohd Adib , Sopian Kamaruzzaman , Jusoh Sufian
Published: January 2021

Sustainability has been greatly impacted by the reality of budgets and available resources as a targeted range of carbon emission reduction greatly increases due to climate change. This study analyses the technical and economic feasibility for three types of solar photovoltaic (PV) renewable energy (RE) systems; (i) solar stand-alone, a non-grid-connected building rooftop-mounted structure, (ii) solar rooftop, a grid-connected building rooftop-mounted structure, (iii) solar farm, a grid-connected land-mounted structure in three tropical climate regions. Technical scientific and economic tools, including life cycle assessment (LCA) and life cycle cost assessment (LCCA) with an integrated framework from a Malaysian case study were applied to similar climatic regions, Thailand, and Indonesia. The short-term, future scaled-up scenario was defined using a proxy technology and estimated data. Environmental locations for this scenario were identified, the environmental impacts were compared, and the techno-economic output were analysed. The scope of this study is cradle-to-grave. Levelised cost of energy (LCOE) was greatly affected due to PV performance degradation rate, especially the critical shading issues for large-scale installations. Despite the land use impact, increased CO2 emissions accumulate over time with regard to energy mix of the country, which requires the need for long-term procurement of both carbon and investment return. With regards to profitably, grid-connected roof-mounted systems achieve the lowest LCOE as compared to other types of installation, ranging from 0.0491 USD/kWh to 0.0605 USD/kWh under a 6% discounted rate. A simple payback (SPB) time between 7–10 years on average depends on annual power generated by the system with estimated energy payback of 0.40–0.55 years for common polycrystalline photovoltaic technology. Thus, maintaining the whole system by ensuring a low degradation rate of 0.2% over a long period of time is essential to generate benefits for both investors and the environment. Emerging technologies are progressing at an exponential rate in order to fill the gap of establishing renewable energy as an attractive business plan. Life cycle assessment is considered an excellent tool to assess the environmental impact of renewable energy.
Recovery of Zinc from Treatment of Spent Acid Solutions from the Pickling Stage of Galvanizing Plants
Authors: Zueva Svetlana B. , Ferella Francesco , Innocenzi Valentina , De Michelis Ida , Corradini Valentina , Ippolito Nicolò M. , Vegliò Francesco
Published: January 2021

Typical methods for the treatment of waste pickling solutions include precipitation by alkaline reagents, most commonly calcium hydroxide. As a result, large volumes of galvanic sludge form, containing iron, calcium, sulphates, and a relatively small quantity of zinc (<20%), making Zn recovery not profitable. In summary, state-of-the-art Zn galvanization processes entail the loss of valuable metals and the irrational and expensive handling of spent pickling solutions (SPSs). The resulting conclusion is that there is room for a significant improvement in the way SPSs are treated, with the double goal of enhancing Zn galvanization methods’ economic viability and achieving a lesser impact on the environment’s processes. The experimental results show that it is possible to use SPS as a coagulant to treat the process wastewaters, kept separated, and added with sodium hydroxide. The results in obtaining precipitates with Zn contents higher than 40%, increasing the added advantage of making Zn recovery profitable. The results show the possibility of using SPS as a coagulant in the process of physical-chemical wastewater treatment and sodium hydroxide to obtain a precipitate with a zinc content of more than 40%.
Research on Competitiveness of China’s Social Commerce Enterprises Based on Macro- and Micro-Niche
Authors: Chen Xu , Wu Yingliang , Zhong Rujie
Published: January 2021

Imbalance of development and resources allocation can emerge during the rapid expansion of social commerce enterprises, which significantly reduces their competitiveness and sustainability. In this paper, we put forward the concept of social commerce ecosystem and propose a model composed of macro-niche and micro-niche to empirically analyze the performance of different social commerce enterprises in China. The results show that: (1) The social sharing e-commerce sub-industry is a monopoly market while the social retail e-commerce sub-industry tends to be a perfectly competitive market; (2) Compared with using only macro-niche or micro-niche, our model shows a more comprehensive insight of enterprise competitiveness, which provides a better niche evaluation for other industries.
Analytical Approach to Quantitative Country Risk Assessment for the Belt and Road Initiative
Authors: Li Jiaman , Dong Xiucheng , Jiang Qingzhe , Dong Kangyin
Published: January 2021

In recent years, the “Belt and Road Initiative” (BRI) promoted by the Chinese government has attracted a significant amount of international trade and transnational investment and other businesses. Accordingly, country risk assessment should be granted priority in the decision-making process for these projects. Based on a comprehensive consideration of important relevant countries and the availability of data of countries along the BRI, this paper uses data from 49 countries along the BRI between 2014–2019 and establishes a national risk-evaluation system for the BRI from four dimensions (i.e., political, economic, social, and investment). This paper adopts the Grey correlation analysis based on the Technique for Order Preference by Similarity to Ideal Solution (Grey-TOPSIS) method to identify and evaluate the risk of countries along the BRI. Geographic Information System (GIS) maps are drawn according to the criteria for classifying the five risk levels to show the rank of the four aspects of risk scores along the BRI in 2019 and the rank of overall country risk scores during the period 2014–2019. The proposed conclusion and policy implications can help the Chinese government and companies to make informed decisions and minimize potential risks.
Functional Lateralization of the Mirror Neuron System in Monkey and Humans
Authors: Errante Antonino , Fogassi Leonardo
Published: January 2021

To date, both in monkeys and humans, very few studies have addressed the issue of the lateralization of the cortical parietal and premotor areas involved in the organization of voluntary movements and in-action understanding. In this review, we will first analyze studies in the monkey, describing the functional properties of neurons of the parieto-frontal circuits, involved in the organization of reaching-grasping actions, in terms of unilateral or bilateral control. We will concentrate, in particular, on the properties of the mirror neuron system (MNS). Then, we will consider the evidence about the mirror neuron mechanism in humans, describing studies in which action perception, as well as action execution, produces unilateral or bilateral brain activation. Finally, we will report some investigations demonstrating plastic changes of the MNS following specific unilateral brain damage, discussing how this plasticity can be related to the rehabilitation outcome
Detection of False Synchronization of Stereo Image Transmission Using a Convolutional Neural Network
Authors: Kulawik Joanna , Kubanek Mariusz
Published: January 2021

The subject of the work described in this article is the detection of false synchronization in the transmission of digital stereo images. Until now, the synchronization problem was solved by using start triggers in the recording. Our proposal checks the discrepancy between the received pairs of images, which allows you to detect delays in transferring images between the left camera and the right camera. For this purpose, a deep network is used to classify the analyzed pairs of images into five classes: MuchFaster, Faster, Regular, Slower, and MuchSlower. As can be seen as a result of the conducted work, satisfactory research results were obtained as the correct classification. A high percentage of average probability in individual classes also indicates a high degree of certainty as to the correctness of the results. An author’s base of colorful stereo images in the number of 3070 pairs is used for the research.
Generalized Semi-Symmetric Non-Metric Connections of Non-Integrable Distributions
Authors: Wu Tong , Wang Yong
Published: January 2021

In this work, the cases of non-integrable distributions in a Riemannian manifold with the first generalized semi-symmetric non-metric connection and the second generalized semi-symmetric non-metric connection are discussed. We obtain the Gauss, Codazzi, and Ricci equations in both cases. Moreover, Chen’s inequalities are also obtained in both cases. Some new examples based on non-integrable distributions in a Riemannian manifold with generalized semi-symmetric non-metric connections are proposed.