bluuebunny/crossref_metadata_2025 huggingface dataset:
The Development of Tyrosyl-DNA Phosphodiesterase 1 Inhibitors. Combination of Monoterpene and Adamantine Moieties via Amide or Thioamide Bridges
Authors: Chepanova Arina A. , Mozhaitsev Evgenii S. , Munkuev Aldar A. , Suslov Evgeniy V. , Korchagina Dina V. , Zakharova Olga D. , Zakharenko Alexandra L. , Patel Jinal , Ayine-Tora Daniel M. , Reynisson Jóhannes , Leung Ivanhoe K. H. , Volcho Konstantin P. , Salakhutdinov Nariman F. , Lavrik Olga I.
Published: July 2019

Eleven amide and thioamide derivatives with monoterpene and adamantine substituents were synthesised. They were tested for their activity against the tyrosyl-DNA phosphodiesterase 1 DNA (Tdp1) repair enzyme with the most potent compound 47a, having an IC50 value of 0.64 µM. When tested in the A-549 lung adenocarcinoma cell line, no or very limited cytotoxic effect was observed for the ligands. However, in conjunction with topotecan, a well-established Topoisomerase 1 (Top1) poison in clinical use against cancer, derivative 46a was very cytotoxic at 5 µM concentration, displaying strong synergism. This effect was only seen for 46a (IC50—3.3 µM) albeit some other ligands had better IC50 values. Molecular modelling into the catalytic site of Tdp1 predicted plausible binding mode of 46a, effectively blocking access to the catalytic site.
Global Maximum Power Point Tracking of PV Systems under Partial Shading Condition: A Transfer Reinforcement Learning Approach
Authors: Ding Min , Lv Dong , Yang Chen , Li Shi , Fang Qi , Yang Bo , Zhang Xiaoshun
Published: July 2019

This paper aims to introduce a novel maximum power point tracking (MPPT) strategy called transfer reinforcement learning (TRL), associated with space decomposition for Photovoltaic (PV) systems under partial shading conditions (PSC). The space decomposition is used for constructing a hierarchical searching space of the control variable, thus the ability of the global search of TRL can be effectively increased. In order to satisfy a real-time MPPT with an ultra-short control cycle, the knowledge transfer is introduced to dramatically accelerate the searching speed of TRL through transferring the optimal knowledge matrices of the previous optimization tasks to a new optimization task. Four case studies are conducted to investigate the advantages of TRL compared with those of traditional incremental conductance (INC) and five other conventional meta-heuristic algorithms. The case studies include a start-up test, step change in solar irradiation with constant temperature, stepwise change in both temperature and solar irradiation, and a daily site profile of temperature and solar irradiation in Hong Kong.
Classifying Degraded Three-Dimensionally Printed Polylactic Acid Specimens Using Artificial Neural Networks based on Fourier Transform Infrared Spectroscopy
Authors: Zhang Sung-Uk
Published: July 2019

Fused filament fabrication (FFF) is commonly employed in multiple domains to realize inexpensive and flexible material extrusion systems with thermoplastic materials. Among the several types of thermoplastic materials, polylactic acid (PLA), an environment-friendly bio-plastic, is commonly used for FFF for the sake of the safety of the manufacturing process. However, thermal degradation of three-dimensionally (3D)-printed PLA products is inevitable, and it is one of the failure mechanisms of thermoplastic products. The present study focuses on the thermal degradation of 3D-printed PLA specimens. A classification methodology using artificial neural networks (ANNs) based on Fourier transform infrared (FTIR) and was developed. Under the given experimental conditions, the ANN model could classify four levels of thermal degradation. Among the FTIR spectra recorded from 650 cm−1 to 4000 cm−1, the ANN model could suggest the best wavenumber ranges for classification.
Autocorrelation Modulation-Based Audio Blind Watermarking Robust Against High Efficiency Advanced Audio Coding
Authors: Hong Yiyu , Kim Jongweon
Published: July 2019

High Efficiency Advanced Audio Coding (HE-AAC) is a lossy compression method for digital audio data which supplies high-quality audio at a very low bit rate. In this paper, the audio blind watermarking algorithm, on the basis of autocorrelation modulation, is introduced to maximize the robustness against low-bit rate HE-AAC. The watermark is embedded by modulating the normalized correlation of the original signal as well as its delayed version. The signal-to-noise ratio of before and after HE-AAC compression decides the strength of the embedding watermark. The watermarking embedding strength is guaranteed by the feedback process. The effectiveness of the proposed method is proven using the Perceptual Evaluation of Audio Quality algorithm and bit error rate of recovered watermarks under HE-AAC compression on mono, stereo and 5.1 channel audio. Experimental results show that the proposed method provides good performance in terms of imperceptibility, robustness and data payload compared with some recent state-of-the-art watermarking methods under an MPEG-2 Audio Layer III (MP3) compression attack.
Characterization and Water Content Estimation Method of Living Plant Leaves Using Terahertz Waves
Authors: Zahid Adnan , T. Abbas Hasan , Imran Muhammad A. , Qaraqe Khalid A. , Alomainy Akram , Cumming David R. S. , Abbasi Qammer H.
Published: July 2019

An increasing global aridification due to climate change has made the health monitoring of vegetation indispensable to maintaining the food supply chain. Cost-effective and smart irrigation systems are required not only to ensure the efficient distribution of water, but also to track the moisture of plant leaves, which is an important marker of the overall health of the plant. This paper presents a novel electromagnetic method to monitor the water content (WC) and characterisation in plant leaves using the absorption spectra of water molecules in the terahertz (THz) frequency for four consecutive days. We extracted the material properties of leaves of eight types of pot herbs from the scattering parameters, measured using a material characterisation kit in the frequency range of 0.75 to 1.1 THz. From the computed permittivity, it is deduced that the leaf specimens increasingly become transparent to the THz waves as they dry out with the passage of days. Moreover, the loss in weight and thickness of leaves were observed due to the natural evaporation of leaf moisture cells and change occurred in the morphology of fresh and water-stressed leaves. It is also illustrated that loss observed in WC on day 1 was in the range of 5% to 22%, and increased from 83.12% to 99.33% on day 4. Furthermore, we observed an exponential decaying trend in the peaks of the real part of the permittivity from day 1 to 4, which was reminiscent of the trend observed in the weight of all leaves. Thus, results in paper demonstrated that timely detection of water stress in leaves can help to take proactive action in relation to plants health monitoring, and for precision agriculture applications, which is of high importance to improve the overall productivity.
Reflecting on the Development of a Digital Platform for the Analysis of Fairs for Modern and Contemporary Art—Approach, Challenges, and Future Perspectives Using the Project ART|GALLERY GIS|COLOGNE as an Example
Authors: Oberste-Hetbleck Nadine
Published: July 2019

Founded in 1967 under the name Kunstmarkt Köln, today’s ART COLOGNE was the first art fair worldwide to specialize in contemporary art. Its primary objectives were to further the art trade in Germany, promote German artists, and establish a new center for the art trade in post-war Germany. Since then, the model of a ‘fair for modern and contemporary art’ has become a globally prosperous format. The starting point of this article is a discussion of an approach to establishing a digital platform for the analysis of the development of the composition of exhibitors at ART COLOGNE during its first 30 years. Its aim is to provide a useful model platform for future research into other art fairs worldwide. The project entailed locations of the participating exhibitors during the first three decades being gathered from the fair’s catalogues, georeferenced, and visualized in a digital, interactive online map named ART|GALLERY GIS|COLOGNE. Through a reactive environment, the online map with open access has, in a second phase, been embedded with further information (e.g., special exhibitions, square meter prices) from other sources. The paper considers what contextual information is required for an adequate analysis of maps, which parameters may exist (e.g., in terms of copyright laws), and what routes could be followed in terms of method (e.g., deep mapping) in contributing to the exploration of the structures of the art market through a primarily visual approach.
Mechanoregulation of Bone Remodeling and Healing as Inspiration for Self-Repair in Materials
Authors: Weinkamer Richard , Eberl Christoph , Fratzl Peter
Published: July 2019

The material bone has attracted the attention of material scientists due to its fracture resistance and ability to self-repair. A mechanoregulated exchange of damaged bone using newly synthesized material avoids the accumulation of fatigue damage. This remodeling process is also the basis for structural adaptation to common loading conditions, thereby reducing the probability of material failure. In the case of fracture, an initial step of tissue formation is followed by a mechanobiological controlled restoration of the pre-fracture state. The present perspective focuses on these mechanobiological aspects of bone remodeling and healing. Specifically, the role of the control function is considered, which describes mechanoregulation as a link between mechanical stimulation and the local response of the material through changes in structure or material properties. Mechanical forces propagate over large distances leading to a complex non-local feedback between mechanical stimulation and material response. To better understand such phenomena, computer models are often employed. As expected from control theory, negative and positive feedback loops lead to entirely different time evolutions, corresponding to stable and unstable states of the material system. After some background information about bone remodeling and healing, we describe a few representative models, the corresponding control functions, and their consequences. The results are then discussed with respect to the potential design of synthetic materials with specific self-repair properties.
Reflectance-Based Organic Pulse Meter Sensor for Wireless Monitoring of Photoplethysmogram Signal
Authors: Elsamnah Fahed , Bilgaiyan Anubha , Affiq Muhamad , Shim Chang-Hoon , Ishidai Hiroshi , Hattori Reiji
Published: July 2019

This paper compares the structural design of two organic biosensors that minimize power consumption in wireless photoplethysmogram (PPG) waveform monitoring. Both devices were fabricated on the same substrate with a red organic light-emitting diode (OLED) and an organic photodiode (OPD). Both were designed with a circular OLED at the center of the device surrounded by OPD. One device had an OLED area of 0.06 cm2, while the other device had half the area. The gap distance between the OLED and OPD was 1.65 mm for the first device and 2 mm for the second. Both devices had an OPD area of 0.16 cm2. We compared the power consumption and signal-to-noise ratio (SNR) of both devices and evaluated the PPG signal, which was successfully collected from a fingertip. The reflectance-based organic pulse meter operated successfully and at a low power consumption of 8 µW at 18 dB SNR. The device sent the PPG waveforms, via Bluetooth low energy (BLE), to a PC host at a maximum rate of 256 kbps data throughput. In the end, the proposed reflectance-based organic pulse meter reduced power consumption and improved long-term PPG wireless monitoring.
Identification of the Best 3D Viewpoint within the BIM Model: Application to Visual Tasks Related to Facility Management
Authors: Neuville Romain , Pouliot Jacynthe , Billen Roland
Published: July 2019

Visualizing building assets within building information modeling (BIM) offers significant opportunities in facility management as it can assist the maintenance and the safety of buildings. Nevertheless, taking decisions based on 3D visualization remains a challenge since the high density of spatial information inside the 3D model requires suitable visualization techniques to achieve the visual task. The occlusion is ubiquitous and, whilst solutions already exist such as transparency, none currently solve this issue with an automatic and suitable management of the camera. In this paper, we propose the first RESTful web application implementing a 3D viewpoint management algorithm and we demonstrate its usability in the visualization of assets based on a BIM model for visual counting in facility management. Via an online questionnaire, empirical tests are conducted with architects, the construction industry, engineers, and surveyors. The results show that a 3D viewpoint that maximizes the visibility of 3D geometric objects inside the viewport significantly improves the success rate, the accuracy, and the certainty of a visual counting task compared to the traditional four side points of view (i.e., from the front, back, left, and right viewpoints). Finally, this first validation lays the foundation of future investigations in the 3D viewpoint usability evaluation, both in terms of visual tasks and application domains.
A Complexity Metrics Suite for Cascading Style Sheets
Authors: Adewumi Adewole , Misra Sanjay , Damaševičius Robertas
Published: July 2019

We perform a theoretical and empirical analysis of a set of Cascading Style Sheets (CSS) document complexity metrics. The metrics are validated using a practical framework that demonstrates their viability. The theoretical analysis is performed using the Weyuker’s properties−a widely adopted approach to conducting empirical validations of metrics proposals. The empirical analysis is conducted using visual and statistical analysis of distribution of metric values, Cliff’s delta, Chi-square and Liliefors statistical normality tests, and correlation analysis on our own dataset of CSS documents. The results show that five out of the nine metrics (56%) satisfy Weyuker’s properties except for the Number of Attributes Defined per Rule Block (NADRB) metric, which satisfies six out of nine (67%) properties. In addition, the results from the statistical analysis show good statistical distribution characteristics (only the Number of Extended Rule Blocks (NERB) metric exceeds the rule-of-thumb threshold value of the Cliff’s delta). The correlation between the metric values and the size of the CSS documents is insignificant, suggesting that the presented metrics are indeed complexity rather than size metrics. The practical application of the presented CSS complexity metric suite is to assess the risk of CSS documents. The proposed CSS complexity metrics suite allows identification of CSS files that require immediate attention of software maintenance personnel.
Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm
Authors: Ünver Halil Murat , Ayan Enes
Published: July 2019

Skin lesion segmentation has a critical role in the early and accurate diagnosis of skin cancer by computerized systems. However, automatic segmentation of skin lesions in dermoscopic images is a challenging task owing to difficulties including artifacts (hairs, gel bubbles, ruler markers), indistinct boundaries, low contrast and varying sizes and shapes of the lesion images. This paper proposes a novel and effective pipeline for skin lesion segmentation in dermoscopic images combining a deep convolutional neural network named as You Only Look Once (YOLO) and the GrabCut algorithm. This method performs lesion segmentation using a dermoscopic image in four steps: 1. Removal of hairs on the lesion, 2. Detection of the lesion location, 3. Segmentation of the lesion area from the background, 4. Post-processing with morphological operators. The method was evaluated on two publicly well-known datasets, that is the PH2 and the ISBI 2017 (Skin Lesion Analysis Towards Melanoma Detection Challenge Dataset). The proposed pipeline model has achieved a 90% sensitivity rate on the ISBI 2017 dataset, outperforming other deep learning-based methods. The method also obtained close results according to the results obtained from other methods in the literature in terms of metrics of accuracy, specificity, Dice coefficient, and Jaccard index.
On the Complexity Analysis and Visualization of Musical Information
Authors: Lopes António M. , Tenreiro Machado J. A.
Published: July 2019

This paper considers several distinct mathematical and computational tools, namely complexity, dimensionality-reduction, clustering, and visualization techniques, for characterizing music. Digital representations of musical works of four artists are analyzed by means of distinct indices and visualized using the multidimensional scaling technique. The results are then correlated with the artists’ musical production. The patterns found in the data demonstrate the effectiveness of the approach for assessing the complexity of musical information.
How Digital and Oral Peer Feedback Improves High School Students’ Written Argumentation—A Case Study Exploring the Effectiveness of Peer Feedback in Geography
Authors: Morawski Michael , Budke Alexandra
Published: July 2019

This article approaches written argumentation as a concept of promoting geographical literacy. It is argued that student-centered peer feedback is an effective method with which to improve individual students’ argumentative texts. This research uses a case-study design, which analyzed how high school students in different pairs improve their argumentation text under subject-specific criteria. For the feedback process, a subject-specific feedback sheet for students has been designed for them to review their partner’s argumentative text. The findings mainly suggest two outcomes: Different kinds of feedback in terms of interaction, content and argumentative integration of text material lead to text improvement, and that there are varying complexities of feedback acceptance in terms of subject-specific criteria. The results provide a deeper insight into how students can be prepared and rewarded for producing qualitatively high and effective feedback on argumentative texts in socio-scientific contexts with a strong focus on the (linguistic) skills they need for these procedures.
A New Low-Voltage Low-Power Dual-Mode VCII-Based SIMO Universal Filter
Authors: Safari Leila , Barile Gianluca , Ferri Giuseppe , Stornelli Vincenzo
Published: July 2019

In this paper, a new low-voltage low-power dual-mode universal filter is presented. The proposed circuit is implemented using inverting current buffer (I-CB) and second-generation voltage conveyors (VCIIs) as active building blocks and five resistors and three capacitors as passive elements. The circuit is in single-input multiple-output (SIMO) structure and can produce second-order high-pass (HP), band-pass (BP), low-pass (LP), all-pass (AP), and band-stop (BS) transfer functions. The outputs are available as voltage signals at low impedance Z ports of the VCII. The HP, BP, AP, and BS outputs are also produced in the form of current signals at high impedance X ports of the VCIIs. In addition, the AP and BS outputs are also available in inverting type. The proposed circuit enjoys a dual-mode operation and, based on the application, the input signal can be either current or voltage. It is worth mentioning that the proposed filter does not require any component matching constraint and all sensitivities are low, moreover it can be easily cascadable. The simulation results using 0.18 μm CMOS technology parameters at a supply voltage of ±0.9 V are provided to support the presented theory.
Measuring the Power Law Phase Noise of an RF Oscillator with a Novel Indirect Quantitative Scheme
Authors: Chen Xiaolong , Peng Cuiling , Huan Huiting , Nian Fushun , Yang Baoguo
Published: July 2019

In conventional phase noise metrology, the phase noise of an oscillator is measured by instruments equipped with specialized and sophisticated devices. Such hardware-based testing usually requires high-performance and costly apparatuses. In this paper, we carried out a novel phase noise measurement method based on a mathematical model. The relationship between the phase noise of a radio frequency oscillator and its power spectral density (PSD) was established, different components of the power law phase noise were analyzed in the frequency domain with their characteristic parameters. Based on the complete physical model of an oscillator, we fitted and extracted the parameters for the near-carrier Gaussian and the power law PSD with Levenberg-Marquardt optimization algorithm. The fitted parameters were used to restore the power law phase noise with considerable precision. Experimental validation showed an excellent agreement between the estimation from the proposed method and the data measured by a high-performance commercial instrument. This methodology can be potentially used to realize fast and simple phase noise measurement and reduce the overall cost of hardware.
Notes on the Economics of Residential Hybrid Energy System
Authors: Fikru Mahelet G. , Gelles Gregory , Ichim Ana-Maria , Smith Joseph D.
Published: July 2019

Despite advances in small-scale hybrid renewable energy technologies, there are limited economic frameworks that model the different decisions made by a residential hybrid system owner. We present a comprehensive review of studies that examine the techno-economic feasibility of small-scale hybrid energy systems, and we find that the most common approach is to compare the annualized life-time costs to the expected energy output and choose the system with the lowest cost per output. While practical, this type of benefit–cost analysis misses out on other production and consumption decisions that are simultaneously made when adopting a hybrid energy system. In this paper, we propose a broader and more robust theoretical framework—based on production and utility theory—to illustrate how the production of renewable energy from multiple sources affects energy efficiency, energy services, and energy consumption choices in the residential sector. Finally, we discuss how the model can be applied to guide a hybrid-prosumer’s decision-making in the US residential sector. Examining hybrid renewable energy systems within a solid economic framework makes the study of hybrid energy more accessible to economists, facilitating interdisciplinary collaborations.
Load Disaggregation Using Microscopic Power Features and Pattern Recognition
Authors: de Souza Wesley Angelino , Garcia Fernando Deluno , Marafão Fernando Pinhabel , da Silva Luiz Carlos Pereira , Simões Marcelo Godoy
Published: July 2019

A new generation of smart meters are called cognitive meters, which are essentially based on Artificial Intelligence (AI) and load disaggregation methods for Non-Intrusive Load Monitoring (NILM). Thus, modern NILM may recognize appliances connected to the grid during certain periods, while providing much more information than the traditional monthly consumption. Therefore, this article presents a new load disaggregation methodology with microscopic characteristics collected from current and voltage waveforms. Initially, the novel NILM algorithm—called the Power Signature Blob (PSB)—makes use of a state machine to detect when the appliance has been turned on or off. Then, machine learning is used to identify the appliance, for which attributes are extracted from the Conservative Power Theory (CPT), a contemporary power theory that enables comprehensive load modeling. Finally, considering simulation and experimental results, this paper shows that the new method is able to achieve 95% accuracy considering the applied data set.
Modification of a Direct Injection Diesel Engine in Improving the Ignitability and Emissions of Diesel–Ethanol–Palm Oil Methyl Ester Blends
Authors: Mat Taib Norhidayah , Abu Mansor Mohd Radzi , Wan Mahmood Wan Mohd Faizal
Published: July 2019

Blending diesel with biofuels, such as ethanol and palm oil methyl ester (PME), enhances the fuel properties and produces improved engine performance and low emissions. However, the presence of ethanol, which has a small cetane number and low heating value, reduces the fuel ignitability. This work aimed to study the effect of injection strategies, compression ratio (CR), and air intake temperature (Ti) modification on blend ignitability, combustion characteristics, and emissions. Moreover, the best composition of diesel–ethanol–PME blends and engine modification was selected. A simulation was also conducted using Converge CFD software based on a single-cylinder direct injection compression ignition Yanmar TF90 engine parameter. Diesel–ethanol–PME blends that consist of 10% ethanol with 40% PME (D50E10B40), D50E25B25, and D50E40B10 were selected and conducted on different injection strategies, compression ratios, and intake temperatures. The results show that shortening the injection duration and increasing the injected mass has no significant effect on ignition. Meanwhile, advancing the injection timing improves the ignitability but with weak ignition energy. Therefore, increasing the compression ratio and ambient temperature helps ignite the non-combustible blends due to the high temperature and pressure. This modification allowed the mixture to ignite with a minimum CR of 20 and Ti of 350 K. Thus, blending high ethanol contents in a diesel engine can be applied by advancing the injection, increasing the CR, and increasing the ambient temperature. From the emission comparison, the most suitable mixtures that can be operated in the engine without modification is D50E25B25, and the most appropriate modification on the engine is by increasing the ambient temperature at 350 K.
Kinetic Evaluation of Lime for Medium-Temperature Desulfurization in Oxy-Fuel Conditions by Dry Sorbent Injection
Authors: Sanku Meher G. , Karlsson Hanna K. , Hulteberg Christian , Wang Wuyin , Stallmann Olaf , Karlsson Hans T.
Published: July 2019

With increasing emphasis on the control of greenhouse gases, power plants may move towards oxy-fuel technologies rather than air-fired plants. This move leads to a change in the feed to the desulfurization unit, which also needs to be adapted along with the power plant. Most existing plants already have functioning desulfurization units, which need to be retrofitted for the new conditions. In the present study, three different limes have been examined as sorbents for sulfur capture in oxy-fuel conditions with varying residence times at medium temperature (150–450 ∘ C). Parameters indicative of the kinetics and competition between SO 2 and CO 2 , like SO 2 breakthrough time, total lime conversion, yield for sulfur capture and sulfur selectivity have been evaluated. The results of this study lead to the recommendation that medium temperature desulfurization should be used for moderate SO 2 capture, in combination with already existing sulfur capture systems. The effects of CO 2 and water vapor have also been analyzed. In addition, the performance of the unit irrespective of temperature strongly depends on the lime type. In addition, absence of water vapor strongly favored the desulfurization process when there was high concentration of CO 2 .
Detecting West Texas Intermediate (WTI) Prices’ Bubble Periods
Authors: Perifanis Theodosios
Published: July 2019

Oil prices have had considerable surges and bursts since the first oil crisis of 1973. Until then its price was stable, with almost zero volatility. Since then, apart from the two oil crises of 1973 and 1978/9, oil prices had consecutive bubble episodes like the surges up to 2008 and 2014 and their successive bursts, respectively. The trace of these bubble periods is of crucial importance for policymakers, since their drivers and consequences impact global economic developments. Phillips et al. and Phillips et al. methodologies are applied to detect whether West Texas Intermediate prices experienced bubble periods. Both methodologies suggest that WTI prices experienced explosive episodes, which could be fundamentally, speculatively, or politically attributed. Some suggested periods coincide for both methods, but the second methodology seems to be more sensitive than its predecessor is, leading to better bubble detection but also to identification of non-existent bubbles. The identified bubble periods are compared to relevant research in the literature concerning their presence, duration, and explosiveness. The main goal of the research, apart from the detection of bubbles’ presence and duration, is to identify the causal underlying reasons for each explosive episode. Further, we compare the start and endpoints of each bubble episode with time-points when structural changes occurred. The contribution of the paper is that it clearly defines the bubble episodes with their corresponding drivers. The paper identifies the importance of market fundamentals’ swifts in explaining the bubble periods. The findings of the papers can help policymakers and other stakeholders to monitor oil price shifts and their underlying reasons, and then proceed with prompt actions. Since bubble episodes are fundamentally explained, then the practical utility is that by focusing on the market fundamentals, stakeholders can avoid actions that could result in market failures.
Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy
Authors: Xie Lubing , Rui Xiaoming , Li Shuai , Hu Xin
Published: July 2019

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.
In-Line Nanostructuring of Glass Fibres Using Different Carbon Allotropes for Structural Health Monitoring Application
Authors: Müller Michael Thomas , Eichhorn Kristina , Gohs Uwe , Heinrich Gert
Published: July 2019

By the in-line nanostructuring of glass fibres (GF) during the glass fibre melt spinning process, the authors achieve an electro-mechanical-response-sensor. The glass fibre interphase was functionalized with different highly electrically conductive carbon allotropes such as carbon nanotubes, graphene nanoplatelets, or conductive carbon black. On-line structural health monitoring is demonstrated in continuous glass fibre-reinforced polypropylene composites during a static or dynamic three-point bending test. The different carbon fillers exhibit qualitative differences in their signal quality and sensitivity due to the differences in the aspect ratio of the nanoparticles, the film homogeneity, and the associated electrically conductive network density in the interphase. The occurrence of irreversible signal changes during dynamic loading may be attributed to filler reorientation processes caused by polymer creeping or to the destruction of the electrically conductive paths due to the presence of cracks in the glass fibre interphase. Further, the authors found that sensor embedding hardly influences the tensile properties of continuous GF reinforced polypropylene (PP) composite.
Tensile Behavior of Unidirectional Bamboo/Coir Fiber Hybrid Composites
Authors: Tran Le Quan Ngoc , Fuentes Carlos , Verpoest Ignace , Van Vuure Aart Willem
Published: July 2019

Natural fibers, such as bamboo, flax, hemp, and coir, are usually different in terms of microstructure and chemical composition. The mechanical properties of natural fibers strongly depend on the organization of cell walls and the cellulose micro-fibril angle in the dominant cell wall layers. Bamboo, flax, and hemp are known for high strength and stiffness, while coir has high elongation to failure. Based on the unique properties of the fibers, fiber hybridization is expected to combine the advantages of different natural fibers for composite applications. In this paper, a study on bamboo/coir fiber hybrid composites was carried out to investigate the hybrid effect of tough coir fibers and brittle bamboo fibers in the composites. The tensile behavior of unidirectional composites of bamboo fibers, coir fibers, and hybrid bamboo/coir fibers with a thermoplastic matrix was studied. The correlation between the tensile properties of the fibers and of the hybrid composites was analyzed to understand the hybrid effects. In addition, the failure mode and fracture morphology of the hybrid composites were examined. The results suggested that, with a low bamboo fiber fraction, a positive hybrid effect with an increase of composite strain to failure was obtained, which can be attributed to the high strain to failure of the coir fibers; the bamboo fibers provided high stiffness and strength to the composites.
3D Numerical Simulation of Hydro-Acoustic Waves Registered during the 2012 Negros-Cebu Earthquake
Authors: Cecioni Claudia , Romano Alessandro , Bellotti Giorgio , De Girolamo Paolo
Published: July 2019

The paper investigates on the hydro-acoustic waves propagation caused by the underwater earthquake, occurred on 6 February 2012, between the Negros and Cebu islands, in the Philippines. Hydro-acoustic waves are pressure waves that propagate at the sound celerity in water. These waves can be triggered by the sudden vertical sea-bed movement, due to underwater earthquakes. The results of three dimensional numerical simulations, which solve the wave equation in a weakly compressible sea water domain are presented. The hydro-acoustic signal is compared to an underwater acoustic signal recorded during the event by a scuba diver, who was about 12 km far from the earthquake epicenter.
Determination of Rainfall Thresholds for Landslide Prediction Using an Algorithm-Based Approach: Case Study in the Darjeeling Himalayas, India
Authors: Teja Togaru Surya , Dikshit Abhirup , Satyam Neelima
Published: July 2019

Landslides are one of the most devastating and commonly recurring natural hazards in the Indian Himalayas. They contribute to infrastructure damage, land loss and human casualties. Most of the landslides are primarily rainfall-induced and the relationship has been well very well-established, having been commonly defined using empirical-based models which use statistical approaches to determine the parameters of a power-law equation. One of the main drawbacks using the traditional empirical methods is that it fails to reduce the uncertainties associated with threshold calculation. The present study overcomes these limitations by identifying the precipitation condition responsible for landslide occurrence using an algorithm-based model. The methodology involves the use of an automated tool which determines cumulated event rainfall–rainfall duration thresholds at various exceedance probabilities and the associated uncertainties. The analysis has been carried out for the Kalimpong Region of the Darjeeling Himalayas using rainfall and landslide data for the period 2010–2016. The results signify that a rainfall event of 48 hours with a cumulated event rainfall of 36.7 mm can cause landslides in the study area. Such a study is the first to be conducted for the Indian Himalayas and can be considered as a first step in determining more reliable thresholds which can be used as part of an operational early-warning system.
Generational Differences: A Comparison of Weight-Related Cognitions and Behaviors of Generation X and Millennial Mothers of Preschool Children
Authors: Xiong Ruiying , Spaccarotella Kim , Quick Virginia , Byrd-Bredbenner Carol
Published: July 2019

A ‘generation’ is an identifiable group sharing birth years and significant life events at critical developmental ages. There is a paucity of literature examining how parental cognitions and lifestyle behaviors differ by generation and whether generational differences are substantial enough to warrant consideration during the development of health interventions. This study compared generational differences in weight-related cognitions and lifestyle behaviors of mothers of young children who were categorized as Generation X (born 1965–1981, n = 158) and Generation Y (aka Millennials; born 1982–1999, n = 162). Survey results indicated that Generation X had significantly higher family affluence; thus, this was controlled in subsequent analyses. Analysis of covariance indicated that Millennials had more positive expectations about the benefits of engaging in healthy eating and physical activity than comparators, but not significantly so. Millennial mothers placed significantly higher value on physical activity for themselves than Generation X mothers, but both generations were neutral on the value of personal physical activity. No generational differences were noted in self-efficacy of mothers for promoting childhood obesity-prevention practices to children and self-efficacy for personally engaging in weight-protective behaviors. Millennial mothers had significantly more family meals/week, however generations did not differ on the value placed on family meals, where family meals were eaten, or whether media devices were used at mealtime. Few differences were noted between the generations for most child feeding behaviors, except that Millennials reported placing significantly less pressure on children to eat. Mothers’ modeling of weight-related behaviors as a means for children’s observational learning about healthy eating, physical activity, and sedentary behaviors did not differ by generational group. The eating behaviors of mothers differed little between generations. Millennial mothers allowed significantly more media devices in children’s bedrooms and personally engaged in more screen time daily than comparators. Overall, the two generational groups were more similar than different in weight-related cognitions as well as for personal and parenting lifestyle behaviors. The results suggest that tailoring interventions for individuals at a similar life-stage (e.g., mothers of young children) by generation may not be warranted.
The Number of Adverse Childhood Experiences Is Associated with Emotional and Behavioral Problems among Adolescents
Authors: Lackova Rebicova Miriama , Dankulincova Veselska Zuzana , Husarova Daniela , Madarasova Geckova Andrea , van Dijk Jitse P. , Reijneveld Sijmen A.
Published: July 2019

This study aims to examine the association of adverse childhood experiences (ACE) with emotional and behavioral problems (EBP) among adolescents and the degree to which this association is stronger for more ACE. In addition, we assessed whether socioeconomic position (SEP) modifies the association of ACE with EBP. We obtained data from 341 adolescents aged 10–16 (mean age = 13.14 years; 44.0% boys), the baseline of a cohort study. We measured EBP with the strengths and difficulties questionnaire and socioeconomic position (SEP) with self-reported financial status. We used generalized linear models to analyze the association between ACE (0 vs. 1–2 vs. 3 and more) and EBP, and the modifying effect of SEP. Adolescents with 1–2 ACE (regression coefficient: 0.19; 95%-confidence interval (CI): 0.06–0.32) and with 3 ACE and over (0.35; 0.17–0.54) reported more overall problems compared with adolescents without ACE. Moreover, adolescents with 1–2 ACE (0.16; −0.01–0.32, and 0.16; 0.03–0.29) and with 3 and over ACE (0.33; 0.10–0.56, and 0.28; 0.09–0.47) reported more emotional problems and behavioral problems, respectively. The interactions of SEP with ACE were not significant. ACE are related to EBP among adolescents, with a clear dose-response association, and this association similarly holds for all SEP categories.
Socioeconomic Differences and the Potential Role of Tribes in Young People’s Food and Drink Purchasing Outside School at Lunchtime
Authors: Kapetanaki Ariadne Beatrice , Wills Wendy J. , Danesi Giada , Spencer Neil H.
Published: July 2019

Socioeconomic deprivation has been linked to food consumption practices, but studies investigating the food environment around schools provide mixed findings. Peer influence and marketing cues are considered important influencers of young people’s behaviors. This study used a tribal theory lens to investigate the factors affecting pupils’ purchasing and consumption of food/drinks outside schools at lunchtime. A survey was conducted with 243 pupils from seven UK secondary schools of differing socioeconomic status (SES). A purchasing recall questionnaire (PRQ) was developed and administered online at the participating schools to capture food and drink purchasing, intake, and expenditure. No significant differences were found in terms of energy and nutrients consumed or food/drink expenditure between pupils from schools of lower and higher SES. Enjoyment of food shopping with friends was linked with higher food energy intake and spend. Higher susceptibility to peer influence was associated with greater influence from food advertising and endorsements. Without ignoring the impact that SES can have on young people’s food choices, we suggest that tribal theory can be additionally used to understand pupils’ eating behaviors and we present implications for social marketers and policy makers.
BP–ANN Model Coupled with Particle Swarm Optimization for the Efficient Prediction of 2-Chlorophenol Removal in an Electro-Oxidation System
Authors: Mei Yu , Yang Jiaqian , Lu Yin , Hao Feilin , Xu Dongmei , Pan Hua , Wang Jiade
Published: July 2019

Electro-oxidation is an effective approach for the removal of 2-chlorophenol from wastewater. The modeling of the electrochemical process plays an important role in improving the efficiency of electrochemical treatment and increasing our understanding of electrochemical treatment without increasing the cost. The backpropagation artificial neural network (BP–ANN) model was applied to predict chemical oxygen demand (COD) removal efficiency and total energy consumption (TEC). Current density, pH, supporting electrolyte concentration, and oxidation–reduction potential (ORP) were used as input parameters in the 2-chlorophenol synthetic wastewater model. Prediction accuracy was increased by using particle swarm optimization coupled with BP–ANN to optimize weight and threshold values. The particle swarm optimization BP–ANN (PSO–BP–ANN) for the efficient prediction of COD removal efficiency and TEC for testing data showed high correlation coefficient of 0.99 and 0.9944 and a mean square error of 0.0015526 and 0.0023456. The weight matrix analysis indicated that the correlation of the five input parameters was a current density of 18.85%, an initial pH 21.11%, an electrolyte concentration 19.69%, an oxidation time of 21.30%, and an ORP of 19.05%. The analysis of removal kinetics indicated that oxidation–reduction potential (ORP) is closely correlated with the chemical oxygen demand (COD) and total energy consumption (TEC) of the electro-oxidation degradation of 2-chlorophenol in wastewater.
Process Analysis of Anaerobic Fermentation Exposure to Metal Mixtures
Authors: Tian Yonglan , Zhang Huayong , Zheng Lei , Li Shusen , Hao He , Yin Meixiao , Cao Yudong , Huang Hai
Published: July 2019

Anaerobic fermentation is a cost-effective biowaste disposal approach. During fermentation, microorganisms require a trace amount of metals for optimal growth and performance. This study investigated the effects of metal mixtures on biogas properties, process stability, substrate degradation, enzyme activity, and microbial communities during anaerobic fermentation. The addition of iron (Fe), nickel (Ni), and zinc (Zn) into a copper (Cu)-stressed fermentation system resulted in higher cumulative biogas yields, ammonia nitrogen (NH4+-N) concentrations and coenzyme F420 activities. Ni and Zn addition enhanced process stability and acetate utilization. The addition of these metals also improved and brought forward the peak daily biogas yields as well as increased CH4 content to 88.94 and 86.58%, respectively. Adding Zn into the Cu-stressed system improved the abundance of Defluviitoga, Fibrobacter and Methanothermobacter, the degradation of cellulose, and the transformation of CO2 to CH4. The bacterial and archaeal communities were responsible for the degradation of lignocelluloses and CH4 production during the fermentation process. This study supports the reutilization of heavy metal-contaminated biowaste and provides references for further research on heavy metals impacted anaerobic fermentation.
Calcium Homeostasis Is Modified in Skeletal Muscle Fibers of Small Ankyrin1 Knockout Mice
Authors: Pierantozzi Enrico , Szentesi Péter , Al-Gaadi Dána , Oláh Tamás , Dienes Beatrix , Sztretye Mónika , Rossi Daniela , Sorrentino Vincenzo , Csernoch László
Published: July 2019

Small Ankyrins (sAnk1) are muscle-specific isoforms generated by the Ank1 gene that participate in the organization of the sarcoplasmic reticulum (SR) of striated muscles. Accordingly, the volume of SR tubules localized around the myofibrils is strongly reduced in skeletal muscle fibers of 4- and 10-month-old sAnk1 knockout (KO) mice, while additional structural alterations only develop with aging. To verify whether the lack of sAnk1 also alters intracellular Ca2+ handling, cytosolic Ca2+ levels were analyzed in stimulated skeletal muscle fibers from 4- and 10-month-old sAnk1 KO mice. The SR Ca2+ content was reduced in sAnk1 KO mice regardless of age. The amplitude of the Ca2+ transients induced by depolarizing pulses was decreased in myofibers of sAnk1 KO with respect to wild type (WT) fibers, while their voltage dependence was not affected. Furthermore, analysis of spontaneous Ca2+ release events (sparks) on saponin-permeabilized muscle fibers indicated that the frequency of sparks was significantly lower in fibers from 4-month-old KO mice compared to WT. Furthermore, both the amplitude and spatial spread of sparks were significantly smaller in muscle fibers from both 4- and 10-month-old KO mice compared to WT. These data suggest that the absence of sAnk1 results in an impairment of SR Ca2+ release, likely as a consequence of a decreased Ca2+ store due to the reduction of the SR volume in sAnk1 KO muscle fibers.