bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature and Pressure Dependence of the Infrared Spectrum of 1-Ethyl-3-Methylimidazolium Trifluoromethanesulfonate Ionic Liquid
Authors: Trequattrini Francesco , Celeste Anna , Capitani Francesco , Palumbo Oriele , Cimini Adriano , Paolone Annalisa
Published: June 2020

The infrared absorption spectrum of 1-ethyl-3-methylimidazolium trifluoromethanesulfonate (EMI–TfO) was investigated at ambient pressure and variable temperatures between 120 and 330 K, or at room temperature and variable pressures up to 10 GPa. Upon cooling, the ionic liquid crystallizes; on the contrary, upon compression no evidence of crystallization can be obtained from the infrared spectra. Moreover, Density Functional Theory (DFT) calculations were applied to gain a better description of the ionic couple. The ωB97X-D functional, including not only the empirical dispersion corrections but also the presence of a polar solvent, gives a good agreement with the infrared spectrum and suggests that TfO resides above the plane of the imidazolium, with the shorter distance between the O atom of the anion and the C2 atom of the imidazolium ring equal to 2.23 Å.
Sustainable Energy Systems: Optimization and Efficiency
Authors: Carlos de Oliveira Matias João , Godina Radu , Pouresmaeil Edris
Published: June 2020

The world population is growing at a very high rate, which also entails a massive increase in energy consumption, and also, therefore, in its production, which is gradually and steadily increasing. Energy and the environment are essential to achieving sustainable development, and constitute a fundamental part of human activity. If we consider energy efficiency as the use of an appliance, process or installation for which we try to produce more energy, but with less energy consumption than the average for these appliances, processes or installations, then achieving a higher energy efficiency is imperative. Energy efficiency is a cornerstone policy on the road to stopping climate change and to achieving sustainable societies, along with the development of renewable energy and an environmentally friendly transport policy. In this Special Issue, 11 selected and peer-reviewed articles have been contributed, on a wide range of topics under the umbrella of sustainable energy systems. The published articles encompass distinct areas of interest. One area addresses distributed generation, which addresses such topics as the optimal planning of distributed generation, protection of blind areas in distribution networks, multi-objective optimization in distributed generation, energy management of virtual power plants in distributed generation, and the impact of demand-response programs on a home microgrid, as well as concentrating solar power into a highly renewable, penetrated power system. The second section of the Special Issue addresses a wide range of topics, from parametric studies of 2 MW gas engines or data centers, to combustion characteristics of a non-premixed oxy-flame, to new techniques of PV Tracking, to applications of nanofluids in the thermal performance enhancement of parabolic trough solar collectors.
Handover Management for D2D Communication in 5G Networks
Authors: Lai Wei Kuang , Shieh Chin-Shiuh , Chou Fu-Sheng , Hsu Chia-Yu , Shen Meng-Han
Published: June 2020

This study addresses the handover management issue for Device-to-Device communication in fifth-generation (5G) networks. The Third Generation Partnership Project (3GPP) drafted a standard for proximity services (ProSe), also named device-to-device (D2D) communication, which is a promising technology in offering higher throughput and lower latency services to end users. Handover is an essential issue in wireless mobile networks due to the mobility of user equipment (UE). Specifically, we need to transfer an ongoing connection from an old E-UTRAN Node B (eNB) to a new one, so that the UE can retain its connectivity. In the data plane, both parties of a D2D pair can communicate directly with each other without the involvement of the base station. However, in the control plane, devices must be connected to the eNB for tasks such as power control and resource allocation. In the current standard of handover scheme, the number of unnecessary handovers would be increased by the effect of shadowing fading on two devices. More important, the handover mechanism for D2D pairs is not standardized yet. LTE-A only considers the handover procedure of a single user. Therefore, when a D2D pair moves across cell boundaries, the control channels of the two UEs may connect to different base stations and result in increased latency due to the exchange of D2D related control messages. Hence, we propose a handover management scheme for D2D communication to let both parties of a D2D pair handover to the same destination eNB at the same time. By doing so, the number of unnecessary handovers, as well as the handover latency, can be reduced. In the proposed method, we predict the destination eNB of D2D users based on their movements and the received signal characteristics. Subsequently, we make a handover decision for each D2D pair by jointly factoring in the signal quality and connection stability. Expected improvement can be attained, as revealed in the simulation. Unnecessary handover can be avoided. Consequently, both UEs of a D2D pair reside in the same cell and, therefore, result in increased throughput and decreased delay.
Harmony Search Optimization of Nozzle Movement for Additive Manufacturing of Concrete Structures and Concrete Elements
Authors: Toklu Yusuf , Bekdaş Gebrail , Geem Zong
Published: June 2020

There are several ways of using three-dimensional printing techniques in the construction industry. One method that seems quite feasible is the concreting of walls and structural components starting at the bottom and progressing up in layers according to the principles of additive manufacturing. The goal of this study is to optimize the movements of a nozzle at one level that will result in this operation. This study considers that the movements of the nozzle can be of two types: rectangular only (i.e., only in x and y directions) or more freely, including moving in diagonal directions. Applications are performed on four hypothetical flats (with 7, 8, 14, and 31 walls, respectively) and a structural component with 17 members. It is shown that as the number of walls and members increase, the problem of optimizing the movements of the nozzle becomes increasingly difficult due to exponentially increasing path combinations. A comparison is presented in terms of the ratio of movements of the nozzle without concreting to total distances traveled. The optimization process is conducted using the Harmony Search algorithm with a special coding and encoding system.
Investigation of the Blast-Induced Crack Propagation Behavior in a Material Containing an Unfilled Joint
Authors: Xu Peng , Yang Renshu , Guo Yang , Guo Zhicheng
Published: June 2020

This study uses a dynamic caustic technique to study the crack propagation in a medium containing an unfilled joint under blasting. The results show that for the medium containing a vertical unfilled joint, the reflected dilatational wave from the joint tends to suppress both the K I d and the velocity of the opposite propagating crack. However, for the medium containing an oblique joint, the reflected wave from the joint increases K II d , and induces the opposite propagating crack deflect from its original path. Compared with the medium with a vertical joint, the wing cracks are more easy to initiate at the oblique joint where a significant stress concentration is formed under the diffraction of the blast wave. Combined with numerical results, it is found that the wing crack deflects in the clockwise direction when the shear stress was negative, and it turns to counterclockwise when the shear stress was positive.
A Room Monitoring System Using Deep Learning and Perspective Correction Techniques
Authors: Ngo Huu-Huy , Lin Feng-Cheng , Sehn Yang-Ting , Tu Mengru , Dow Chyi-Ren
Published: June 2020

Studies on room monitoring have only focused on objects in a singular and uniform posture or low-density groups. Considering the wide use of convolutional neural networks for object detection, especially person detection, we use deep learning and perspective correction techniques to propose a room monitoring system that can detect persons with different motion states, high-density groups, and small-sized persons owing to the distance from the camera. This system uses consecutive frames from the monitoring camera as input images. Two approaches are used: perspective correction and person detection. First, perspective correction is used to transform an input image into a 2D top-view image. This allows users to observe the system more easily with different views (2D and 3D views). Second, the proposed person detection scheme combines the Mask region-based convolutional neural network (R-CNN) scheme and the tile technique for person detection, especially for detecting small-sized persons. All results are stored in a cloud database. Moreover, new person coordinates in 2D images are generated from the final bounding boxes and heat maps are created according to the 2D images; these enable users to examine the system quickly in different views. Additionally, a system prototype is developed to demonstrate the feasibility of the proposed system. Experimental results prove that our proposed system outperforms existing schemes in terms of accuracy, mean absolute error (MAE), and root mean squared error (RMSE).
Can We Rely on Flight Time to Measure Jumping Performance or Neuromuscular Fatigue-Overload in Professional Female Soccer Players?
Authors: Armada-Cortés Estrella , Peláez Barrajón Javier , Benítez-Muñoz José Antonio , Navarro Enrique , San Juan Alejandro F.
Published: June 2020

The main purpose of this study was to compare the validity of the take-off velocity method (TOV) measured with a force platform (FP) (gold standard) versus the flight time method (FT) in a vertical jump to measure jumping performance or neuromuscular fatigue-overload in professional female football players. For this purpose, we used a FP and a validated smartphone application (APP). A total of eight healthy professional female football players (aged 27.25 ± 6.48 years) participated in this study. All performed three valid trials of a countermovement jump and squat jump and were measured at the same time with the APP and the FP. The results show that there is a lack of validity and reliability between jump height (JH) calculated through the TOV method with the FP and the FT method with the FP (r = 0.028, p > 0.84, intraclass correlation coefficient (ICC) = −0.026) and between the JH measured with the FP through the TOV method and the APP with the FT method (r = 0.116, p > 0.43, ICC = −0.094 (−0.314–0.157)). A significant difference between the JH measured through the TOV with the FP versus the APP (p < 0.05), and a trend between the JH obtained with the FP through the TOV and the FT (p = 0.052) is also shown. Finally, the JH with the FP through the FT and the APP did not differ (p > 0.05). The eta-squared of the one-way ANOVA was η2 = 0.085. It seems that only the TOV measured with a FP could guarantee the accuracy of the jump test in SJ+CMJ and SJ, so it is recommended that high-level sportswomen and men should be assessed with the FP through TOV as gold standard technology to ensure correct performance and/or fatigue-overload control during the sport season.
In Vitro Preliminary Evaluation of Bacterial Attachment on Grooved and Smooth Healing Abutments
Authors: Moses Ofer , Nemcovsky Carlos E. , Lewinstein Israel , Zoabi Hasan , Weinreb Miron , Levartovsky Shifra , Matalon Shlomo
Published: June 2020

This in vitro preliminary study investigated the attachment of Fusobacterium nucleatum and Porphyromonas gingivalis on titanium alloy healing abutments, which differed in their surface macro-morphology: one was groove-marked while the other was completely smooth. Altogether, twenty implant-healing abutments, ten of each macro-morphology, were evaluated with a single type of bacterial strain. Accordingly, four groups of five abutments each were created. The sterilized healing abutments with the cultured bacteria were placed under anaerobic conditions for 48 h at 37 °C. Afterwards, the abutments were examined with a scanning electron microscope, at a 2500x magnification. Attached bacteria were quantified in the four vertical quarters within the grooved abutments and in the two most coronal millimeters of the smooth abutments. The results were analyzed by applying two-way ANOVA, with square root transformation for a normal distribution. The bacterial attachment of both strains was statistically significantly larger in the grooved abutment areas than on the smooth surfaces (p ≤ 0.0001), twenty times so for Porphyromonas gingivalis and a hundred times so for Fusobacterium nucleatum.
Dynamic Behaviour of a Conveyor Belt Considering Non-Uniform Bulk Material Distribution for Speed Control
Authors: Zeng Fei , Yan Cheng , Wu Qing , Wang Tao
Published: June 2020

For the conveyor belt, variable material flow influences the energy efficiency of the speed control technology significantly. The fluctuation of material flow on the conveyor belt will lead to the detrimental vibrations on both the belt and the conveyor while the conveyor works at certain speeds. In order to improve the model inaccuracy caused by the uniform bulk material flow assumption in the current conveyor belt model, the paper establishes a high-precision dynamic model that can consider speed control of a conveyor belt under non-uniform bulk material transportation. In this dynamic model, a non-uniform bulk material distribution model is firstly proposed based on laser scanning technology. Then, a high-precision longitudinal dynamic model is proposed to investigate the dynamic behavior of a belt conveyor. Considering the micro-units of actual load on a conveyor belt, it can well describe the transient state of the conveyor belt. These models can be used to determine the optimal speed for safety and energy conservation in operation. Experimental results are used to validate the proposed dynamic model for analyzing belt mechanical behavior under non-uniform bulk material distribution on the belt. The results show that the proposed models can be used for optimizing the operating procedures of belt conveyor systems.
Interoperability Analyses of BIM Platforms for Construction Management
Authors: De Gaetani Carlo Iapige , Mert Mertkan , Migliaccio Federica
Published: June 2020

It is incontrovertible that an exchange of files is essentially required at several stages of the workflow in the architecture, engineering, and construction (AEC) industry. Therefore, investigating and detecting the capabilities/inabilities of building information modeling (BIM) software packages with respect to interoperability can be informative to stakeholders who exchange data between various BIM packages. The work presented in this paper includes a discussion on the interoperability of different software platforms commonly used in the AEC industry. Although, in theory, flawless interoperability of some types of files between different BIM platforms is ensured, in practical applications, this is not always the case. Hence, this research aims to identify faults in data exchange by assessing different possible scenarios where a sample Industry Foundation Classes (IFC) four-dimensions (4D) BIM model and related Gantt charts are exchanged. Throughout the interoperability analysis of both IFC file and Gantt charts, the following checks were carried out: geometrical and nongeometrical information exchange through IFC files, 4D information correct readability, and presence of missing schedule information in Gantt charts after their import/export procedure. The results show that interoperability between the analyzed platforms is not always ensured, providing useful insight into realistic scenarios.
Life Cycle Engineering 4.0: A Proposal to Conceive Manufacturing Systems for Industry 4.0 Centred on the Human Factor (DfHFinI4.0)
Authors: Suarez-Fernandez de Miranda Susana , Aguayo-González Francisco , Salguero-Gómez Jorge , Ávila-Gutiérrez María Jesús
Published: June 2020

Engineering 4.0 environments are characterised by the digitisation, virtualisation, and connectivity of products, processes, and facilities composed of reconfigurable and adaptive socio-technical cyber-physical manufacturing systems (SCMS), in which Operator 4.0 works in real time in VUCA (volatile, uncertain, complex and ambiguous) contexts and markets. This situation gives rise to the interest in developing a framework for the conception of SCMS that allows the integration of the human factor, management, training, and development of the competencies of Operator 4.0 as fundamental aspects of the aforementioned system. The present paper is focused on answering how to conceive the adaptive manufacturing systems of Industry 4.0 through the operation, growth, and development of human talent in VUCA contexts. With this objective, exploratory research is carried, out whose contribution is specified in a framework called Design for the Human Factor in Industry 4.0 (DfHFinI4.0). From among the conceptual frameworks employed therein, the connectivist paradigm, Ashby’s law of requisite variety and Vigotsky’s activity theory are taken into consideration, in order to enable the affective-cognitive and timeless integration of the human factor within the SCMS. DfHFinI4.0 can be integrated into the life cycle engineering of the enterprise reference architectures, thereby obtaining manufacturing systems for Industry 4.0 focused on the human factor. The suggested framework is illustrated as a case study for the Purdue Enterprise Reference Architecture (PERA) methodology, which transforms it into PERA 4.0.
Concepts and Terminologies in 4D Printing
Authors: Pei Eujin , Loh Giselle Hsiang , Nam Seokwoo
Published: June 2020

4D printing (4DP) is a promising technology that enables additive manufactured parts to be programmed for actuation, reducing the need for external power or electromechanical systems. As this area of research has grown exponentially, this review paper aims to define and establish fundamental concepts and terminologies used in the field of 4DP. The objective is to encourage researchers to adopt a more consistent approach and a standardized set of vocabulary associated with this emerging field. Even though the paper covers the most widely used definitions, the multidisciplinary nature may mean that certain words could be used interchangeably or have a different meaning in another context.
Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis
Authors: Urase Yasuyo , Nishio Mizuho , Ueno Yoshiko , Kono Atsushi K. , Sofue Keitaro , Kanda Tomonori , Maeda Takaki , Nogami Munenobu , Hori Masatoshi , Murakami Takamichi
Published: June 2020

The usefulness of sparse-sampling CT with deep learning-based reconstruction for detection of metastasis of malignant ovarian tumors was evaluated. We obtained contrast-enhanced CT images (n = 141) of ovarian cancers from a public database, whose images were randomly divided into 71 training, 20 validation, and 50 test cases. Sparse-sampling CT images were calculated slice-by-slice by software simulation. Two deep-learning models for deep learning-based reconstruction were evaluated: Residual Encoder-Decoder Convolutional Neural Network (RED-CNN) and deeper U-net. For 50 test cases, we evaluated the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as quantitative measures. Two radiologists independently performed a qualitative evaluation for the following points: entire CT image quality; visibility of the iliac artery; and visibility of peritoneal dissemination, liver metastasis, and lymph node metastasis. Wilcoxon signed-rank test and McNemar test were used to compare image quality and metastasis detectability between the two models, respectively. The mean PSNR and SSIM performed better with deeper U-net over RED-CNN. For all items of the visual evaluation, deeper U-net scored significantly better than RED-CNN. The metastasis detectability with deeper U-net was more than 95%. Sparse-sampling CT with deep learning-based reconstruction proved useful in detecting metastasis of malignant ovarian tumors and might contribute to reducing overall CT-radiation exposure.
Organic Molecular Marker from Regional Biomass Burning—Direct Application to Source Apportionment Model
Authors: Song Myoungki , Park Chaehyeong , Choi Wunseon , Park Minhan , Lee Kwangyul , Park Kihong , Park Seungshik , Bae Min-Suk
Published: June 2020

To reduce fine particulate matter (PM2.5) level, the sources of PM2.5 in terms of the composition thereof needs to be identified. In this study, the experimental burning of ten types of biomass that are typically used in Republic of Korea, collected at the regional area were to investigate the indicated organic speciation and the results obtained therefrom were applied to the chemical mass balance (CMB) model for the study area. As a result, the organic molecular markers for the biomass burning were identified as they were varying according to chemical speciation of woods and herbaceous plants and depending upon the hard- and soft characteristics of specimens. Based on the source profile from biomass burning, major sources of PM2.5 in the study area of the present study appeared as sources of biomass burning, the secondary ions, secondary particulate matters, which is including long-distance transport, wherein the three sources occupied most over 84% of entire PM2.5. In regard to the subject area distinguished into residential area and on roads, the portion of the biomass burning appeared higher in residential area than on roads, whereas the generation from vehicles of gasoline engine and burning of meats in restaurants, etc. appeared higher on roads comparing to the residential area.
The Experimental Study on Mechanical Behavior of Conveyor Belt Rubber Bearings
Authors: Wu Yifeng , Zhang Yan , Li Aiqun , Zhang Guodong
Published: June 2020

Fabric core conveyor belt rubber bearing (CBRB) with low cost and a simple manufacturing process has been proposed to further popularize seismic isolation technology in low-rise buildings, and four samples of such bearings have been produced, including four-layer, five-layer, five-layer with inner pattern and six-layer fabric core CBRBs. The vertical compression and the compression shear test are carried out to evaluate the performances of the four bearings. Results show that the vertical stiffness of the CBRB increases as the number of fabric core layer increases, while the damping ratio decreases, and the bearings can withstand a vertical pressure of 10 MPa. In addition, these bearings work very well within 100% shear strain, and the horizontal stiffness of the bearings decreases with increasing shear strain. In the meantime, as the number of fabric core layer increases, the effective horizontal stiffness of the bearings increases under 4 MPa compressive stress, and the damping ratio coefficient of the bearing is about 15%, when bearing sliding does not occur. The ultimate shear strain reached up to 200% for the four-layer bearing with obvious interlayer cracks, which means that the bonding quality between layers is the key influencing factor on the ultimate shear strain. In short, the proposed low-cost bearing has low horizontal stiffness and good energy dissipation capacity, so it is suitable for low-rise buildings in economically underdeveloped, high intensity areas, which can significantly improve their earthquake resistance and reduce casualties and property losses.
Chemical and Mechanical Roughening Treatments of a Supra-Nano Composite Resin Surface: SEM and Topographic Analysis
Authors: Puleio Francesco , Rizzo Giuseppina , Nicita Fabiana , Lo Giudice Fabrizio , Tamà Cristina , Marenzi Gaetano , Centofanti Antonio , Raffaele Marcello , Santonocito Dario , Risitano Giacomo
Published: June 2020

Background: Repairing a restoration is a more advantageous and less invasive alternative to its total makeover. The aim of this study was to analyze the effects of chemical and mechanical surface treatments aimed at increasing the roughness of a supra-nano composite resin. Methods: 27 cylindrical blocks of microhybrid composite were made. The samples were randomly divided into nine groups (n = 3). The samples’ surface was treated differently per each group: acid etching (35% H3PO4, 30 s and 60 s), diamond bur milling, sandblasting and the combination of mechanical treatment and acid etching. The samples’ surface was observed by a scanning electron microscope (SEM) and a confocal microscope for observational study, and surface roughness (Ra) was recorded for quantitative analysis. Results: The images of the samples sandblasted with Al2O3 showed the greatest irregularity and the highest number of microcavities. The surfaces roughened by diamond bur showed evident parallel streaks and sporadic superficial microcavities. No significant roughness differences were recorded between other groups. The difference in roughness between the control group, diamond bur milled group and sandblasted group was statistically significant. (p < 0.01). Comparison between the diamond bur milled group and the sandblasted group was also significant (p < 0.01). Conclusion: According to our results, sandblasting is the best treatment to increase the surface roughness of a supra-nano composite.
A Social Life Cycle Assessment Framework for Additive Manufacturing Products
Authors: Naghshineh Bardia , Lourenço Francisco , Godina Radu , Jacinto Celeste , Carvalho Helena
Published: June 2020

Additive Manufacturing (AM) is viewed as a disruptive technology with the potential to replace many manufacturing processes. With its rapid proliferation in recent years, it is crucial to understand how to measure this technology’s social impacts. There are many studies available in the existing literature regarding the economic and environmental impacts of AM technology. However, research regarding the social impacts of this technology is still scarce. To this end, this research has developed a framework based on Social Life Cycle Assessment (SLCA) methodology to measure AM products’ social impacts throughout their life cycle stages. The proposed framework includes an underlying mathematical model that was developed to allow for the aggregation of indicator scores. Additionally, cut-off scores were determined to differentiate between positive and negative social impacts. This framework can be applied to case studies, which provides a final score that quantifies the social impacts of an AM product throughout all its life cycle stages. It also provides scores for each stakeholder category and life cycle stage, which facilitates the identification of hotspots that require attention from organizations.
Local Buckling and Resistance of Continuous Steel Beams with Thin-Walled I-Shaped Cross-Sections
Authors: Szychowski Andrzej , Brzezińska Karolina
Published: June 2020

In modern steel construction, thin-walled elements with Class 4 cross-sections are commonly used. For the sake of the computation of such elements according to European Eurocode 3 (EC3), simplified computational models are applied. These models do not account for important parameters that affect the behavior of a structure susceptible to local stability loss. This study discussed the effect of local buckling on the design ultimate resistance of a continuous beam with a thin-walled Class 4 I-shaped cross-section. In the investigations, a more accurate computational model was employed. A new calculation model was proposed, based on the analysis of local buckling separately for the span segment and the support segment of the first span, which are characterized by different distributions of bending moments. Critical stress was determined using the critical plate method (CPM), taking into account the effect of the mutual elastic restraint of the cross-section walls. The stability analysis also accounted for the effect of longitudinal stress variation resulting from the varied distribution of bending moments along the continuous beam length. The results of the calculations were compared with the numerical simulations using the finite element method. The obtained results showed very good congruence. The phenomena mentioned above are not taken into consideration in the computational model provided in EC3. Based on the critical stress calculated as above, “local” critical moments were determined. These constitute a limit on the validity of the Vlasov theory of thin-walled bars. Design ultimate resistance of the I-shaped cross-section was determined from the plastic yield condition of the most compressed edge under the assumptions specified in the study. Detailed calculations were performed for I-sections welded from thin metal sheets, and for sections made from two cold-formed channels (2C). The impact of the following factors on the critical resistance and design ultimate resistance of the midspan and support cross-sections was analyzed: (1) longitudinal stress variation, (2) relative plate slenderness of the flange, and (3) span length of the continuous beam. The results were compared with the outcomes obtained for box sections with the same contour dimensions, and also with those produced acc. EC3. It was shown that compared with calculations acc. EC3, those performed in accordance with the CPM described much more accurately the behavior of the uniformly loaded continuous beam with a thin-walled section. This could lead to a more effective design of structures of this class.
SNR Enhancement of an Electrically Small Antenna Using a Non-Foster Matching Circuit
Authors: Lee Yong-Hyeok , Cho Sung-yong , Chung Jae-Young
Published: June 2020

A non-Foster circuit (NFC) is known as an active broadband matching technique to improve the impedance matching bandwidth of an electrically small antenna (ESA). There has been a vast amount of papers that report the generation of negative impedance using an NFC and its effectiveness on broadband antenna matching. However, only a few discussed its impact on the signal-to-noise-ratio (SNR), which is one of the most important figures-of-merit for a wireless communication system. In this paper, the SNR enhancement due to an NFC was measured and discussed. An NFC was carefully designed to have a low dissipation loss and to meet the stability conditions. The optimized NFC design was fabricated and applied to an ESA length of λ⁄15 at a frequency range of 150 to 300 MHz. The measured results showed that the NFC enhanced the received power of the antenna system by more than 17 dB. However, due to the noise added by the NFC, the SNR enhancement was not guaranteed for some frequency points. Nevertheless, an average of 7.3 dB of SNR improvement over the frequency band of interest is possible based on the experiment result.
Compressive Sensing Imaging Based on Modulation of Atmospheric Scattering Medium
Authors: Lei Xuelin , Ma Xiaoshan , Yang Zhen , Peng Xiaodong , Li Yun , Ni Wei
Published: June 2020

Long-distance imaging in time-varying scattering media, such as atmosphere, is a significant challenge. Light is often heavily diffused while propagating through scattering media, because of which the clear imaging of objects concealed by media becomes difficult. In this study, instead of suppressing diffusion by multiple scattering, we used natural randomness of wave propagation through atmospheric scattering media as an optimal and instantaneous compressive imaging mechanism. A mathematical model of compressive imaging based on the modulation of atmospheric scattering media was established. By using the Monte Carlo method, the atmospheric modulation matrix was obtained, and the numerical simulation of modulation imaging of atmospheric scattering media was performed. Comparative experiments show that the atmospheric matrix can achieve the same modulation effect as the Hadamard and Gaussian random matrices. The effectiveness of the proposed optical imaging approach was demonstrated experimentally by loading the atmospheric measurement matrix onto a digital micromirror device to perform single pixel compressive sensing measurements. Our work provides a new direction to ongoing research in the field of imaging through scattering media.
Synthesis of Multiwalled Carbon Nanotubes on Stainless Steel by Atmospheric Pressure Microwave Plasma Chemical Vapor Deposition
Authors: Li Dashuai , Tong Ling , Gao Bo
Published: June 2020

In this paper, we synthesize carbon nanotubes (CNTs) by using atmospheric pressure microwave plasma chemical vapor deposition (AMPCVD). In AMPCVD, a coaxial plasma generator provides 200 W 2.45 GHz microwave plasma at atmospheric pressure to decompose the precursor. A high-temperature tube furnace provides a suitable growth temperature for the deposition of CNTs. Optical fiber spectroscopy was used to measure the compositions of the argon–ethanol–hydrogen plasma. A comparative experiment of ethanol precursor decomposition, with and without plasma, was carried out to measure the role of the microwave plasma, showing that the 200 W microwave plasma can decompose 99% of ethanol precursor at any furnace temperature. CNTs were prepared on a stainless steel substrate by using the technology to decompose ethanol with the plasma power of 200 W at the temperatures of 500, 600, 700, and 800 °C; CNT growth increases with the increase in temperature. Prepared CNTs, analyzed by SEM and HRTEM, were shown to be multiwalled and tangled with each other. The measurement of XPS and Raman spectroscopy indicates that many oxygenated functional groups have attached to the surface of the CNTs.
Origin of Compositional Diversity of Marine Tephra during the Late Middle Pleistocene B-KY1 Baekdusan Volcanic Eruption
Authors: Chun Jong-Hwa , Cheong Daekyo
Published: June 2020

The focus of this study was the Baekdusan-Kita 1 (B-KY1) eruption during the late Middle Pleistocene. We identified B-KY1 tephra between the Toya and Aso-1 tephras in the ODP 794A core from the Japan Basin of the East Sea/Japan Sea. The stratigraphic position of the B-KY1 tephra correlated exactly with the first B-KY1 to be identified, in the 20EEZ-1 core from the Kita–Yamato Trough. However, B-KY1 tephra in the ODP 794A core showed a wide range of geochemical compositions. The textural characteristics of B-KY1 tephra in the ODP 794A core was characterized by higher content of fine-grained bubble-wall shards than that of the B-KY1 tephra in the 20EEZ-1 core. The difference in B-KY1 tephra between the two coring sites may reflect shifts in wind direction during volcanic eruptions. We refined the eruption age of the B-KY1 tephra by examining distinct sedimentary facies related to the start of the penultimate deglaciation of this region at ca. 135 ka. The findings of this study suggest that the compositional diversity of B-KY1 tephra may have been influenced by subsequent mixing of comendite and comenditic trachyte magma with injected pantelleritic magma during the late Middle Pleistocene Baekdusan volcanic eruption.
Biomechanically-Informed Training: The Four Pillars for Knee and ACL Injury Prevention Built Upon Behavior Change and Motivation Principles
Authors: Donnelly Cyril J. , Jackson Ben S. , Gucciardi Daniel F. , Reinbolt Jeff
Published: June 2020

Injury prevention frameworks are critical for preventing musculoskeletal injury and improving rehabilitation outcomes. However, their relative successes in translation arguably rely on two interlinked components: (1) the quality of the empirical evidence used to develop the intervention (content), and (2) the effective application of behavior change and motivation principles to optimise participant adherence and engagement (delivery). The purpose of this commentary is to develop an injury prevention and rehabilitation framework using the best available physics-based simulation, biomechanics, and behavior change research. The intervention as a whole is entitled biomechanically-informed training (BIT). While investigators have previously examined the relative merits of different training genres (e.g., plyometric, balance, resistance), what makes BIT novel is that it explicitly targets the biomechanical mechanisms that mitigate musculoskeletal injury risk (i.e., force) in ways that are underpinned by established behavior change principles. The four pillars of BIT refer to focused exercise use, irrespective of the training genre, to improve an individual’s: (1) knee flexion dynamics, (2) dynamic trunk control, (3) gastrocnemius muscle strength, and (4) hip muscular strength. We also present experimental data from two independent training studies verifying the efficacy of BIT for the prevention of knee and anterior cruciate ligament (ACL) injury.
Eco-Physiological Traits and Phenylpropanoid Profiling on Potted Vitis vinifera L. cv Pinot Noir Subjected to Ascophyllum nodosum Treatments under Post-Veraison Low Water Availability
Authors: Salvi Linda , Brunetti Cecilia , Cataldo Eleonora , Storchi Paolo , Mattii Giovan Battista
Published: June 2020

In Mediterranean regions, extreme weather conditions during the growing season may alter grapevine physiology and metabolism, thus modifying the quality of wines. The objective of this study was to investigate the effects of Ascophyllum nodosum treatments on plant physiology and berry metabolism in Vitis vinifera exposed to water stress. The experiment was performed on potted vines subjected to two irrigation regimes (well-watered, WW, and water stressed, WS) both associated with A. nodosum treatments (SWE), compared with control plants (CTRL). Gas exchanges, chlorophyll fluorescence, and water relations were monitored on SWE and CTRL leaves, both in WW and WS vines at three times. Moreover, the quantification of secondary metabolites and their partitioning were performed in berry skins. Plants treated with A. nodosum extract showed higher photosynthesis and stomatal conductance than CTRL in both irrigation regimes and maintained a better plant hydraulic conductivity at the end of the sampling period. In addition, secondary metabolites in berry skins and their partitioning were significantly affected by the treatments in both irrigation regimes. Our results suggest that foliar application of A. nodosum extract may help the acclimation of grapevines to post-veraison water stress, likely improving plant physiological and biochemical performances under environmental constraints.
Unconstrained Bilingual Scene Text Reading Using Octave as a Feature Extractor
Authors: Tadesse Direselign Addis , Liu Chuan-Ming , Ta Van-Dai
Published: June 2020

Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the frequency of input images at feature extraction, which slows down the system, requires more memory, and recognizes text inaccurately. In this paper, we proposed an octave convolution (OctConv) feature extractor and a time-restricted attention encoder-decoder module for end-to-end scene text reading. The OctConv can extract features by factorizing the input image based on their frequency. It is a direct replacement of convolutions, orthogonal and complementary, for reducing redundancies and helps to boost the reading text through low memory requirements at a faster speed. In the text reading process, features are first extracted from the input image using Feature Pyramid Network (FPN) with OctConv Residual Network with depth 50 (ResNet50). Then, a Region Proposal Network (RPN) is applied to predict the location of the text area by using extracted features. Finally, a time-restricted attention encoder-decoder module is applied after the Region of Interest (RoI) pooling is performed. A bilingual real and synthetic scene text dataset is prepared for training and testing the proposed model. Additionally, well-known datasets including ICDAR2013, ICDAR2015, and Total Text are used for fine-tuning and evaluating its performance with previously proposed state-of-the-art methods. The proposed model shows promising results on both regular and irregular or curved text detection and reading tasks.
Combined Vital Tooth Whitening: Effect of Number of In-Office Sessions on the Duration of Home Whitening. A Randomized Clinical Trial
Authors: Amengual-Lorenzo José , Montiel-Company José María , Labaig-Rueda Carlos , Agustín-Panadero Rubén , Solá-Ruíz María Fernanda , Peydro-Herrero Marta
Published: June 2020

Background: In cases of moderate to severe dental discoloration, vital tooth whitening usually requires a prolonged treatment time if it is to obtain satisfactory outcomes. Variations in the clinical efficacy of whitening products in terms of their concentration and application time mean that we need to be aware of the real bleaching capacity of each whitening method and each product. This randomized clinical trial aimed to analyze with a spectrophotometer the effect of the number of in-office vital tooth whitening sessions (one or two) on the number of weeks of ensuing home whitening until color stability was obtained. Methods: Twenty patients with moderate/severe discoloration were treated with combined vital tooth whitening. Ten patients were treated with a single in-office session consisting of two applications of a product containing 40% hydrogen peroxide, followed by home treatment with individualized splints and a 16% carbamide peroxide gel (Group 1S). The other ten patients (Group 2S) were treated in two in-office sessions with two applications of the same product as Group 1S, followed in the same way by home treatment. Results: Comparing the two groups (1S and 2S), no significant differences in Euclidean distance (ΔE) were found after in-office whitening, or when color stabilization was obtained and home whitening ceased. Significant differences in the number of weeks of home whitening until color stabilization reached the same outcomes were found between 1S and 2S; 1S required a mean of 11.6 weeks home whitening, while 2S required 8.2 weeks. Conclusions: Combined tooth whitening with two in-office sessions significantly reduces the number of weeks (by three to four weeks) of subsequent home tooth whitening needed to reach color stabilization.
Surface Muscle Segmentation Using 3D U-Net Based on Selective Voxel Patch Generation in Whole-Body CT Images
Authors: Kamiya Naoki , Oshima Ami , Zhou Xiangrong , Kato Hiroki , Hara Takeshi , Miyoshi Toshiharu , Matsuo Masayuki , Fujita Hiroshi
Published: June 2020

This study aimed to develop and validate an automated segmentation method for surface muscles using a three-dimensional (3D) U-Net based on selective voxel patches from whole-body computed tomography (CT) images. Our method defined a voxel patch (VP) as the input images, which consisted of 56 slices selected at equal intervals from the whole slices. In training, one VP was used for each case. In the test, multiple VPs were created according to the number of slices in the test case. Segmentation was then performed for each VP and the results of each VP merged. The proposed method achieved a segmentation accuracy mean dice coefficient of 0.900 for 8 cases. Although challenges remain in muscles adjacent to visceral organs and in small muscle areas, VP is useful for surface muscle segmentation using whole-body CT images with limited annotation data. The limitation of our study is that it is limited to cases of muscular disease with atrophy. Future studies should address whether the proposed method is effective for other modalities or using data with different imaging ranges.
A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future
Authors: Bécue Adrien , Maia Eva , Feeken Linda , Borchers Philipp , Praça Isabel
Published: June 2020

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.
A Deep Learning-Based Perception Algorithm Using 3D LiDAR for Autonomous Driving: Simultaneous Segmentation and Detection Network (SSADNet)
Authors: Lee Yongbeom , Park Seongkeun
Published: June 2020

In this paper, we propose a deep learning-based perception method in autonomous driving systems using a Light Detection and Ranging(LiDAR) point cloud data, which is called a simultaneous segmentation and detection network (SSADNet). SSADNet can be used to recognize both drivable areas and obstacles, which is necessary for autonomous driving. Unlike the previous methods, where separate networks were needed for segmentation and detection, SSADNet can perform segmentation and detection simultaneously based on a single neural network. The proposed method uses point cloud data obtained from a 3D LiDAR for network input to generate a top view image consisting of three channels of distance, height, and reflection intensity. The structure of the proposed network includes a branch for segmentation and a branch for detection as well as a bridge connecting the two parts. The KITTI dataset, which is often used for experiments on autonomous driving, was used for training. The experimental results show that segmentation and detection can be performed simultaneously for drivable areas and vehicles at a quick inference speed, which is appropriate for autonomous driving systems.
An Application Study on Road Surface Monitoring Using DTW Based Image Processing and Ultrasonic Sensors
Authors: Sharma Sunil Kumar , Phan Haidang , Lee Jaesun
Published: June 2020

Road surface monitoring is an essential problem in providing smooth road infrastructure to commuters. This paper proposed an efficient road surface monitoring using an ultrasonic sensor and image processing technique. A novel cost-effective system, which includes ultrasonic sensors sensing with GPS for the detection of the road surface conditions, was designed and proposed. Dynamic time warping (DTW) technique was incorporated with ultrasonic sensors to improve the classification and accuracy of road surface detecting conditions. A new algorithm, HANUMAN, was proposed for automatic recognition and calculation of pothole and speed bumps. Manual inspection was performed and comparison was undertaken to validate the results. The proposed system showed better efficiency than the previous systems with a 95.50% detection rate for various road surface irregularities. The novel framework will not only identify the road irregularities, but also help in decreasing the number of accidents by alerting drivers.