bluuebunny/crossref_metadata_2025 huggingface dataset:
Parkinson Network Eastern Saxony (PANOS): Reaching Consensus for a Regional Intersectoral Integrated Care Concept for Patients with Parkinson’s Disease in the Region of Eastern Saxony, Germany
Authors: Loewenbrück Kai F. , Stein Doron B. , Amelung Volker E. , Bitterlich Robert , Brumme Martin , Falkenburger Björn , Fehre Annekathrin , Feige Tim , Frank Anika , Gißke Carola , Helmert Claudia , Kerkemeyer Linda , Knapp Andreas , Lang Caroline , Leuner Annegret , Lummer Carina , Minkman Mirella M. N. , Müller Gabriele , van Munster Marlena , Schlieter Hannes , Themann Peter , Zonneveld Nick , Wolz Martin
Published: September 2020

As integrated care is recognized as crucial to meet the challenges of chronic conditions such as Parkinson’s disease (PD), integrated care networks have emerged internationally and throughout Germany. One of these networks is the Parkinson Network Eastern Saxony (PANOS). PANOS aims to deliver timely and equal care to PD patients with a collaborative intersectoral structured care pathway. Additional components encompass personalized case management, an electronic health record, and communicative and educative measures. To reach an intersectoral consensus of the future collaboration in PANOS, a structured consensus process was conducted in three sequential workshops. Community-based physicians, PD specialists, therapists, scientists and representatives of regulatory authorities and statutory health insurances were asked to rate core pathway-elements and supporting technological, personal and communicative measures. For the majority of core elements/planned measures, a consensus was reached, defined as an agreement by >75% of participants. Additionally, six representatives from all partners involved in the network-design independently assessed PANOS based on the Development Model for Integrated Care (DMIC), a validated model addressing the comprehensiveness and maturity of integrated care concepts. The results show that PANOS is currently in an early maturation state but has the potential to comprehensively represent the DMIC if all planned activities are implemented successfully. Despite the favorable high level of consensus regarding the PANOS concept and despite its potential to become a balanced integrated care concept according to the DMIC, its full implementation remains a considerable challenge.
On the Use of Deep Active Semi-Supervised Learning for Fast Rendering in Global Illumination
Authors: Constantin Ibtissam , Constantin Joseph , Bigand André
Published: September 2020

Convolution neural networks usually require large labeled data-sets to construct accurate models. However, in many real-world scenarios, such as global illumination, labeling data are a time-consuming and costly human intelligent task. Semi-supervised learning methods leverage this issue by making use of a small labeled data-set and a larger set of unlabeled data. In this paper, our contributions focus on the development of a robust algorithm that combines active and deep semi-supervised convolution neural network to reduce labeling workload and to accelerate convergence in case of real-time global illumination. While the theoretical concepts of photo-realistic rendering are well understood, the increased need for the delivery of highly dynamic interactive content in vast virtual environments has increased recently. Particularly, the quality measure of computer-generated images is of great importance. The experiments are conducted on global illumination scenes which contain diverse distortions. Compared with human psycho-visual thresholds, the good consistency between these thresholds and the learning models quality measures can been seen. A comparison has also been made with SVM and other state-of-the-art deep learning models. We do transfer learning by running the convolution base of these models over our image set. Then, we use the output features of the convolution base as input to retrain the parameters of the fully connected layer. The obtained results show that our proposed method provides promising efficiency in terms of precision, time complexity, and optimal architecture.
Slurry Erosion–Corrosion Characteristics of As-Built Ti-6Al-4V Manufactured by Selective Laser Melting
Authors: Aldahash Saleh Ahmed , Abdelaal Osama , Abdelrhman Yasser
Published: September 2020

Erosion and erosion–corrosion tests of as-built Ti-6Al-4V manufactured by Selective Laser Melting were investigated using slurries composed of SiO2 sand particles and either tap water (pure water) or 3.5% NaCl solution (artificial seawater). The microhardness value of selective laser melting (SLM)ed Ti-6Al-4V alloy increased as the impact angle increased. The synergistic effect of corrosion and erosion in seawater is always higher than erosion in pure water at all impact angles. The seawater environment caused the dissolution of vanadium oxide V2O5 on the surface of SLMed Ti-6Al-4V alloy due to the presence of Cl− ions in the seawater. These findings show lower microhardness values and high mass losses under the erosion–corrosion test compared to those under the erosion test at all impact angles.
Research Progress on the Anti-Disproportionation of the ZrCo Alloy by Element Substitution
Authors: Wu Mingde , Wang Jingchuan , Li Peilong , Hu Cun , Tian Xiaofeng , Song Jiangfeng
Published: September 2020

Hydrogen-induced disproportionation (HID) during the cycles of absorption and desorption leads to a serious decline in the storage capacity of the ZrCo alloy, which has been recognized as the biggest obstacle to its application. Therefore, the prerequisite of a ZrCo application is to solve its anti-disproportionation problem in the field of rapid hydrogen isotope storage. Beyond surface modification and nanoball milling, this work systematically reviews the method of element substitution, which can obviously improve the anti-disproportionation. From a micro angle, as hydrogen atoms that occupy the 8e site in the ZrCoH3 lattice are instable and are considered to be the driving force of disproportionation, researchers believe that element substitution by changing the occupation of hydrogen atoms at the 8e site can improve the anti-disproportionation of the alloy. At present, Ti/Nb substitutions for the Zr terminal among substitute elements have an excellent anti-disproportionation performance. In this work, up-to-date research studies on anti-disproportionation and its disproportionation mechanism of the ZrCo alloy are introduced by combining experiments and simulations. Moreover, the optimization of the alloy based on the occupation mechanism of 8e sites is expected to improve the anti-disproportionation of the ZrCo alloy.
Systematic Review of Geometrical Approaches and Analytical Integration for Chen’s System
Authors: Ene Remus-Daniel , Pop Camelia , Petrişor Camelia
Published: September 2020

The main goal of this paper is to present an analytical integration in connection with the geometrical frame given by the Hamilton–Poisson formulation of a specific case of Chen’s system. In this special case we construct an analytic approximate solution using the Multistage Optimal Homotopy Asymptotic Method (MOHAM). Numerical simulations are also presented in order to make a comparison between the analytic approximate solution and the corresponding numerical solution.
On the Extrinsic Principal Directions and Curvatures of Lagrangian Submanifolds
Authors: Moruz Marilena , Verstraelen Leopold
Published: September 2020

From the basic geometry of submanifolds will be recalled what are the extrinsic principal tangential directions, (first studied by Camille Jordan in the 18seventies), and what are the principal first normal directions, (first studied by Kostadin Trenčevski in the 19nineties), and what are their corresponding Casorati curvatures. For reasons of simplicity of exposition only, hereafter this will merely be done explicitly in the case of arbitrary submanifolds in Euclidean spaces. Then, for the special case of Lagrangian submanifolds in complex Euclidean spaces, the natural relationships between these distinguished tangential and normal directions and their corresponding curvatures will be established.
Healthcare-Associated SARS-CoV-2 Transmission—Experiences from a German University Hospital
Authors: Correa-Martínez Carlos L. , Schwierzeck Vera , Mellmann Alexander , Hennies Marc , Kampmeier Stefanie
Published: September 2020

During the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare systems worldwide have to prevent nosocomial SARS-CoV-2 transmission while maintaining duty of care. In our study, we characterize the transmission dynamic of SARS-CoV-2 in inpatients and healthcare workers (HCWs) at the University Hospital Münster (UHM) in northwest Germany. We identified 27 cases of healthcare-associated SARS-CoV-2 infections (4 inpatients and 23 HCWs) who had contact with patients and/or HCWs without the use of adequate PPE. The contacts of these index cases were followed up for SARS-CoV-2 infection after unprotected exposure and a quantitative measure of probability of becoming infected, the attack rate, was calculated. In addition, transmission was evaluated in the context of infection control measures established during the pandemic and we compared the epidemiological data of all index cases, including symptoms and Ct values of virology test results. The overall attack rate in the hospital setting was 1.3% (inpatients 0.9%, HCWs 1.6%). However, during an outbreak, the attack rate was 25.5% (inpatients 20.0%, HCWs 29.6%). For both scenarios, HCWs had a higher attack rate illustrating their role in healthcare-associated SARS-CoV-2 transmission. Taken together, our experiences demonstrate how infection control measures can minimize the transmission of SARS-CoV-2 in the healthcare setting.
Stearic Acid/Layered Double Hydroxides Composite Thin Films Deposited by Combined Laser Techniques
Authors: Birjega Ruxandra , Matei Andreea , Marascu Valentina , Vlad Angela , Ionita Maria Daniela , Dinescu Maria , Zăvoianu Rodica , Corobea Mihai Cosmin
Published: September 2020

We report on the investigation of stearic acid-layered double hydroxide (LDH) composite films, with controlled wettability capabilities, deposited by a combined pulsed laser deposition (PLD)-matrix-assisted pulsed laser evaporation (MAPLE) system. Two pulsed lasers working in IR or UV were used for experiments, allowing the use of proper deposition parameters (wavelength, laser fluence, repetition rate) for each organic and inorganic component material. We have studied the time stability and wettability properties of the films and we have seen that the morphology of the surface has a low effect on the wettability of the surfaces. The obtained composite films consist in stearic acid aggregates in LDH structure, exhibiting a shift to hydrophobicity after 36 months of storage.
Polyphenols vs. Coronaviruses: How Far Has Research Moved Forward?
Authors: Piccolella Simona , Crescente Giuseppina , Faramarzi Shadab , Formato Marialuisa , Pecoraro Maria Tommasina , Pacifico Severina
Published: September 2020

The epidemic, caused by SARS-CoV-2 at the beginning of 2020, led us to a serious change in our lifestyle that for about three months has confined us to our homes, far from our laboratory routine. In this period, the belief that the work of a researcher should never stop has been the driving force in writing the present paper. It aims at reviewing the recent scientific knowledge about in vitro experimental data that focused on the antiviral role of phenols and polyphenols against different species of coronaviruses (CoVs), pointing up the viral targets potentially involved. In the current literature scenario, the papain-like and the 3-chymotrypsin-like proteases seem to be the most deeply investigated and a number of isolated natural (poly)phenols has been screened for their efficacy.
Click Decoration of Bombyx mori Silk Fibroin for Cell Adhesion Control
Authors: Teramoto Hidetoshi , Shirakawa Minori , Tamada Yasushi
Published: September 2020

Silk fibroin produced by the domesticated silkworm, Bombyx mori, has been studied widely as a substrate for tissue engineering applications because of its mechanical robustness and biocompatibility. However, it is often difficult to precisely tune silk fibroin’s biological properties due to the lack of easy, reliable, and versatile methodologies for decorating it with functional molecules such as those of drugs, polymers, peptides, and enzymes necessary for specific applications. In this study we applied an azido-functionalized silk fibroin, AzidoSilk, produced by a state-of-the-art biotechnology, genetic code expansion, to produce silk fibroin decorated with cell-repellent polyethylene glycol (PEG) chains for controlling the cell adhesion property of silk fibroin film. Azido groups can act as selective handles for chemical reactions such as a strain-promoted azido-alkyne cycloaddition (SPAAC), known as a click chemistry reaction. We found that azido groups in AzidoSilk film were selectively decorated with PEG chains using SPAAC. The PEG-decorated film demonstrated decreased cell adhesion depending on the lengths of the PEG chains. Azido groups in AzidoSilk can be decomposed by UV irradiation. By partially decomposing azido groups in AzidoSilk film in a spatially controlled manner using photomasks, cells could be spatially arranged on the film. These results indicated that SPAAC could be an easy, reliable, and versatile methodology to produce silk fibroin substrates having adequate biological properties.
Dietary Soy Protein Isolate Attenuates Intestinal Immunoglobulin and Mucin Expression in Young Mice Compared with Casein
Authors: Zeng Bin , Wang Dongyang , Wang Hailong , Chen Ting , Luo Junyi , Xi Qianyun , Sun Jiajie , Zhang Yongliang
Published: September 2020

Dietary protein sources have profound effects on children and young animals, and are important for the gut barrier function and immune resilience. Milk and soy are the main sources of protein for children and young animals after weaning. The objective of this study was to compare the effects of dairy and soy proteins on the intestinal barrier in early development. Weanling C57BL/6 mice were fed AIN-93G diets prepared with casein or soy protein isolate (SPI) for 21 days. Compared with those fed with the casein diet, mice fed with the SPI diet did not change their body weight and organ coefficients, but increased their feed intake and ratio of feed to gain. SPI lowered the level of luminal secretory immunoglobulin A (SIgA) and downregulated the levels of IL-4, IL-13, polymeric immunoglobulin receptor (Pigr), Janus kinase 1 (Jak1), signal transducer and activator of transcription 6 (Stat6), and transforming growth factor-β (Tgfb) in the mouse ileum. Western blotting of ileal proteins confirmed that SPI suppressed the activation of the JAK1/STAT6 signaling pathway. Furthermore, SPI attenuated intestinal mucin production, as demonstrated by the decreased numbers of intestinal goblet cells and the reduced relative expression levels of mucin 1 (Muc1), mucin 2 (Muc2), trefoil factor 3 (Tff3), glucose-regulated protein 94 (Grp94), and anterior gradient homolog 2 (Agr2). The results indicated that the SPI diet could attenuate mouse intestinal immunity, as demonstrated by decreased SIgA and mucin production in the intestine. Therefore, we suggest that our findings should be of consideration when SPI or casein are used as dietary protein sources.
Control Measures for SARS-CoV-2: A Review on Light-Based Inactivation of Single-Stranded RNA Viruses
Authors: Hadi Joshua , Dunowska Magdalena , Wu Shuyan , Brightwell Gale
Published: September 2020

SARS-CoV-2 is a single-stranded RNA virus classified in the family Coronaviridae. In this review, we summarize the literature on light-based (UV, blue, and red lights) sanitization methods for the inactivation of ssRNA viruses in different matrixes (air, liquid, and solid). The rate of inactivation of ssRNA viruses in liquid was higher than in air, whereas inactivation on solid surfaces varied with the type of surface. The efficacy of light-based inactivation was reduced by the presence of absorptive materials. Several technologies can be used to deliver light, including mercury lamp (conventional UV), excimer lamp (UV), pulsed-light, and light-emitting diode (LED). Pulsed-light technologies could inactivate viruses more quickly than conventional UV-C lamps. Large-scale use of germicidal LED is dependent on future improvements in their energy efficiency. Blue light possesses virucidal potential in the presence of exogenous photosensitizers, although femtosecond laser (ultrashort pulses) can be used to circumvent the need for photosensitizers. Red light can be combined with methylene blue for application in medical settings, especially for sanitization of blood products. Future modelling studies are required to establish clearer parameters for assessing susceptibility of viruses to light-based inactivation. There is considerable scope for improvement in the current germicidal light-based technologies and practices.
Least Quartic Regression Criterion to Evaluate Systematic Risk in the Presence of Co-Skewness and Co-Kurtosis
Authors: Arbia Giuseppe , Bramante Riccardo , Facchinetti Silvia
Published: September 2020

This article proposes a new method for the estimation of the parameters of a simple linear regression model which is based on the minimization of a quartic loss function. The aim is to extend the traditional methodology, based on the normality assumption, to also take into account higher moments and to provide a measure for situations where the phenomenon is characterized by strong non-Gaussian distribution like outliers, multimodality, skewness and kurtosis. Although the proposed method is very general, along with the description of the methodology, we examine its application to finance. In fact, in this field, the contribution of the co-moments in explaining the return-generating process is of paramount importance when evaluating the systematic risk of an asset within the framework of the Capital Asset Pricing Model. We also illustrate a Monte Carlo test of significance on the estimated slope parameter and an application of the method based on the top 300 market capitalization components of the STOXX® Europe 600. A comparison between the slope coefficients evaluated using the ordinary Least Squares (LS) approach and the new Least Quartic (LQ) technique shows that the perception of market risk exposure is best captured by the proposed estimator during market turmoil, and it seems to anticipate the market risk increase typical of these periods. Moreover, by analyzing the out-of-sample risk-adjusted returns we show that the proposed method outperforms the ordinary LS estimator in terms of the most common performance indices. Finally, a bootstrap analysis suggests that significantly different Sharpe ratios between LS and LQ yields and Value at Risk estimates can be considered more accurate in the LQ framework. This study adds insights into market analysis and helps in identifying more precisely potentially risky assets whose extreme behavior is strongly dependent on market behavior.
Multi-Site and Multi-Year Remote Records of Operative Temperatures with Biomimetic Loggers Reveal Spatio-Temporal Variability in Mountain Lizard Activity and Persistence Proxy Estimates
Authors: Hugon Florèn , Liquet Benoit , D’Amico Frank
Published: September 2020

Commonly, when studies deal with the effects of climate change on biodiversity, mean value is used more than other parameters. However, climate change also leads to greater temperature variability, and many papers have demonstrated its importance in the implementation of biodiversity response strategies. We studied the spatio-temporal variability of activity time and persistence index, calculated from operative temperatures measured at three sites over three years, for a mountain endemic species. Temperatures were recorded with biomimetic loggers, an original remote sensing technology, which has the same advantages as these tools but is suitable for recording biological organisms data. Among the 42 tests conducted, 71% were significant for spatial variability and 28% for temporal variability. The differences in daily activity times and in persistence indices demonstrated the effects of the micro-habitat, habitat, slope, altitude, hydrography, and year. These observations have highlighted the great variability existence in the environmental temperatures experienced by lizard populations. Thus, our study underlines the importance to implement multi-year and multi-site studies to quantify the variability and produce more representative results. These studies can be facilitated by the use of biomimetic loggers, for which a user guide is provided in the last part of this paper.
Simulations of Leaf BSDF Effects on Lidar Waveforms
Authors: Roth Benjamin D. , Goodenough Adam A. , Brown Scott D. , van Aardt Jan A. , Saunders M. Grady , Krause Keith
Published: September 2020

Establishing linkages between light detection and ranging (lidar) data, produced from interrogating forest canopies, to the highly complex forest structures, composition, and traits that such forests contain, remains an extremely difficult problem. Radiative transfer models have been developed to help solve this problem and test new sensor platforms in a virtual environment. Many forest canopy studies include the major assumption of isotropic (Lambertian) reflecting and transmitting leaves or non-transmitting leaves. Here, we study when these assumptions may be valid and evaluate their associated impacts/effects on the lidar waveform, as well as its dependence on wavelength, lidar footprint, view angle, and leaf angle distribution (LAD), by using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) remote sensing radiative transfer simulation model. The largest effects of Lambertian assumptions on the waveform are observed at visible wavelengths, small footprints, and oblique interrogation angles relative to the mean leaf angle. For example, a 77% increase in return signal was observed with a configuration of a 550 nm wavelength, 10 cm footprint, and 45° interrogation angle to planophile leaves. These effects are attributed to (i) the bidirectional scattering distribution function (BSDF) becoming almost purely specular in the visible, (ii) small footprints having fewer leaf angles to integrate over, and (iii) oblique angles causing diminished backscatter due to forward scattering. Non-transmitting leaf assumptions have the greatest error for large footprints at near-infrared (NIR) wavelengths. Regardless of leaf angle distribution, all simulations with non-transmitting leaves with a 5 m footprint and 1064 nm wavelength saw around a 15% reduction in return signal. We attribute the signal reduction to the increased multiscatter contribution for larger fields of view, and increased transmission at NIR wavelengths. Armed with the knowledge from this study, researchers will be able to select appropriate sensor configurations to account for or limit BSDF effects in forest lidar data.
Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study
Authors: Albert Justin Amadeus , Owolabi Victor , Gebel Arnd , Brahms Clemens Markus , Granacher Urs , Arnrich Bert
Published: September 2020

Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.
Laplacian Scores-Based Feature Reduction in IoT Systems for Agricultural Monitoring and Decision-Making Support
Authors: Tsapparellas Giorgos , Jin Nanlin , Dai Xuewu , Fehringer Gerhard
Published: September 2020

Internet of things (IoT) systems generate a large volume of data all the time. How to choose and transfer which data are essential for decision-making is a challenge. This is especially important for low-cost and low-power designs, for example Long-Range Wide-Area Network (LoRaWan)-based IoT systems, where data volume and frequency are constrained by the protocols. This paper presents an unsupervised learning approach using Laplacian scores to discover which types of sensors can be reduced, without compromising the decision-making. Here, a type of sensor is a feature. An IoT system is designed and implemented for a plant-monitoring scenario. We have collected data and carried out the Laplacian scores. The analytical results help choose the most important feature. A comparative study has shown that using fewer types of sensors, the accuracy of decision-making remains at a satisfactory level.
Assessment of Smoke Contamination in Grapevine Berries and Taint in Wines Due to Bushfires Using a Low-Cost E-Nose and an Artificial Intelligence Approach
Authors: Fuentes Sigfredo , Summerson Vasiliki , Gonzalez Viejo Claudia , Tongson Eden , Lipovetzky Nir , Wilkinson Kerry L. , Szeto Colleen , Unnithan Ranjith R.
Published: September 2020

Bushfires are increasing in number and intensity due to climate change. A newly developed low-cost electronic nose (e-nose) was tested on wines made from grapevines exposed to smoke in field trials. E-nose readings were obtained from wines from five experimental treatments: (i) low-density smoke exposure (LS), (ii) high-density smoke exposure (HS), (iii) high-density smoke exposure with in-canopy misting (HSM), and two controls: (iv) control (C; no smoke treatment) and (v) control with in-canopy misting (CM; no smoke treatment). These e-nose readings were used as inputs for machine learning algorithms to obtain a classification model, with treatments as targets and seven neurons, with 97% accuracy in the classification of 300 samples into treatments as targets (Model 1). Models 2 to 4 used 10 neurons, with 20 glycoconjugates and 10 volatile phenols as targets, measured: in berries one hour after smoke (Model 2; R = 0.98; R2 = 0.95; b = 0.97); in berries at harvest (Model 3; R = 0.99; R2 = 0.97; b = 0.96); in wines (Model 4; R = 0.99; R2 = 0.98; b = 0.98). Model 5 was based on the intensity of 12 wine descriptors determined via a consumer sensory test (Model 5; R = 0.98; R2 = 0.96; b = 0.97). These models could be used by winemakers to assess near real-time smoke contamination levels and to implement amelioration strategies to minimize smoke taint in wines following bushfires.
A New Roadway Eventual Obstacle Detection System Based on Computer Vision
Authors: Gonzalez-de-Soto Mariano , Mora Rocio , Martín-Jiménez José Antonio , Gonzalez-Aguilera Diego
Published: September 2020

A new roadway eventual obstacle detection system based on computer vision is described and evaluated. This system uses low-cost hardware and open-source software to detect and classify moving elements in roads using infra-red and colour video images as input data. This solution represents an important advancement to prevent road accidents due to eventual obstacles which have considerably increased in the past decades, mainly with wildlife. The experimental evaluation of the system demonstrated that the proposed solution detects and classifies correctly different types of moving obstacles on roads, working robustly under different weather and illumination conditions.
Current-Mode Self-Amplified CMOS Sensor Intended for 2D Temperature Microgradients Measurement and Imaging
Authors: Santos Patrick M. , Monteiro Davies W. L. , Salles Luciana P.
Published: September 2020

This paper presents the design of a current-mode CMOS self-amplified imager operating in dark conditions, for thermal imaging, which provides an innovative solution for precision thermal contact mapping. Possible applications of this imager range from 3D CMOS integrated circuits to the study of in-vivo biological samples. It can provide a thermal map, static or dynamic, for the measurement of temperature microgradients. Some adaptations are required for the optimization of this self-amplified image sensor since it responds exclusively to the dark currents of the photodiodes throughout the array. The sensor is designed in a standard CMOS process and requires no post-processing steps. The optimized image sensor operates with integration times as low as one μs and can achieve both SNR and dynamic range compatible to those of sensors available on the market, estimated as 87dB and 75dB, respectively; noise equivalent temperature difference can be as low as 10mK; and detection errors as low as ±1%. Furthermore, under optimal conditions the self-amplification process enables a simple form of CDS, enhancing the overall sensor noise performance.
Study of the Influence of Winding and Sensor Design on Ultra-High Frequency Partial Discharge Signals in Power Transformers
Authors: Beura Chandra Prakash , Beltle Michael , Tenbohlen Stefan
Published: September 2020

Ultra-high frequency (UHF) partial discharge (PD) measurements in power transformers are becoming popular because of the advantages of the method. Therefore, it is necessary to improve the basic understanding of the propagation of signals inside the transformer tank and the factors that influence the sensitivity of the measurement. Since the winding represents a major obstacle to the propagation of the UHF signals, it is necessary to study the effect of winding design on signal propagation. Previous research activities have studied these effects using simplified models, and it is essential to consider the complexity of propagation in a complete transformer tank. Additionally, the quality of UHF PD measurements depends, to a large extent, on the sensitivity of the UHF sensors. In this contribution, a simulation model consisting of a simple, grounded enclosure with multiple winding designs is used to study the propagation characteristics of UHF signals when an artificial PD source is placed inside the winding. After analysis of the results, the winding designs are incorporated in an existing and validated simulation model of a 420 kV power transformer and analyzed to observe the influence in a more complex structure. Two commonly used sensor designs are also used in the simulation model to receive the signals. In all cases, the propagation and signal characteristics are analyzed and compared to determine the influence of the winding and sensor design on the UHF signals. It is found that the level of detail of winding design has a significant impact on the propagation characteristics. However, the attenuation characteristics of the UHF signals received by the two sensor designs are similar, with the electric field distribution around the sensor being the key difference.
Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders
Authors: Ni Qin , Fan Zhuo , Zhang Lei , Nugent Chris D. , Cleland Ian , Zhang Yuping , Zhou Nan
Published: September 2020

Activity recognition has received considerable attention in many research fields, such as industrial and healthcare fields. However, many researches about activity recognition have focused on static activities and dynamic activities in current literature, while, the transitional activities, such as stand-to-sit and sit-to-stand, are more difficult to recognize than both of them. Consider that it may be important in real applications. Thus, a novel framework is proposed in this paper to recognize static activities, dynamic activities, and transitional activities by utilizing stacked denoising autoencoders (SDAE), which is able to extract features automatically as a deep learning model rather than utilize manual features extracted by conventional machine learning methods. Moreover, the resampling technique (random oversampling) is used to improve problem of unbalanced samples due to relatively short duration characteristic of transitional activity. The experiment protocol is designed to collect twelve daily activities (three types) by using wearable sensors from 10 adults in smart lab of Ulster University, the experiment results show the significant performance on transitional activity recognition and achieve the overall accuracy of 94.88% on three types of activities. The results obtained by comparing with other methods and performances on other three public datasets verify the feasibility and priority of our framework. This paper also explores the effect of multiple sensors (accelerometer and gyroscope) to determine the optimal combination for activity recognition.
Pattern Recognition of Cognitive Load Using EEG and ECG Signals
Authors: Xiong Ronglong , Kong Fanmeng , Yang Xuehong , Liu Guangyuan , Wen Wanhui
Published: September 2020

The matching of cognitive load and working memory is the key for effective learning, and cognitive effort in the learning process has nervous responses which can be quantified in various physiological parameters. Therefore, it is meaningful to explore automatic cognitive load pattern recognition by using physiological measures. Firstly, this work extracted 33 commonly used physiological features to quantify autonomic and central nervous activities. Secondly, we selected a critical feature subset for cognitive load recognition by sequential backward selection and particle swarm optimization algorithms. Finally, pattern recognition models of cognitive load conditions were constructed by a performance comparison of several classifiers. We grouped the samples in an open dataset to form two binary classification problems: (1) cognitive load state vs. baseline state; (2) cognitive load mismatching state vs. cognitive load matching state. The decision tree classifier obtained 96.3% accuracy for the cognitive load vs. baseline classification, and the support vector machine obtained 97.2% accuracy for the cognitive load mismatching vs. cognitive load matching classification. The cognitive load and baseline states are distinguishable in the level of active state of mind and three activity features of the autonomic nervous system. The cognitive load mismatching and matching states are distinguishable in the level of active state of mind and two activity features of the autonomic nervous system.
Design of Surface Enhanced Raman Scattering (SERS) Nanosensor Array
Authors: Mandelbaum Yaakov , Mottes Raz , Zalevsky Zeev , Zitoun David , Karsenty Avi
Published: September 2020

An advanced Surface-Enhanced Raman Scattering (SERS) Nanosensor Array, dedicated to serve in the future as a pH imager for the real-time detection of chemical reaction, is presented. The full flow of elementary steps—architecture, design, simulations, fabrication, and preliminary experimental results of structural characterization (Focused Ion Beam (FIB), TEM and SEM)—show an advanced SERS pixel array that is capable of providing spatially resolved measurements of chemical pH in a fluid target that became more than desirable in this period. Ultimately, the goal will be to provide real-time monitoring of a chemical reaction. The pixels consist of a nanostructured substrate composed of an array of projections or cavities. The shape of the nanostructures and the thickness of the metallic (Ag or Au) layer can be tuned to give maximal enhancement at the desired wavelength. The number and arrangement of nanostructures is optimized to obtain maximal responsivity.
“We Force Ourselves”: Productivity, Workplace Culture, and HRI Prevention in Florida’s Citrus Groves
Authors: Morera Maria C. , Gusto Cody , Monaghan Paul F. , Tovar-Aguilar José Antonio , Roka Fritz M.
Published: September 2020

Efforts to disseminate heat-related illness (HRI) prevention practices among Latino farmworkers represent a critical occupational safety strategy in Florida. Targeted initiatives, however, require understanding the workplace dynamics that guide agricultural safety behaviors. This article reports focus group data collected in 2018 from citrus harvesters in central Florida and provides an in-depth perspective on the workplace culture that shapes their implementation of heat safety measures. Results indicate that citrus harvesters regularly suffered HRI symptoms yet rarely reported or sought treatment for their injuries. In some cases, the risks of developing HRI were accepted as a facet of agricultural work and harvesters blamed themselves for their illnesses. Implementation of safety practices hinged less on knowledge than on the availability of water and rest breaks and the quality of employer-employee relations and exchanges. Thus, trust was a determinant of workers’ attitudes toward management that contributed to a harvesting operation’s safety climate. Results highlight the difficulties of putting into practice measures that are not rewarded by the workplace culture and suggest that the extent to which intervention strategies promote not only individual safety behaviors but organizational accountability may predict their effectiveness.
Isokinetic Dynamometry as a Tool to Predict Shoulder Injury in an Overhead Athlete Population: A Systematic Review
Authors: Bagordo Andrea , Ciletti Kimberly , Kemp-Smith Kevin , Simas Vini , Climstein Mike , Furness James
Published: September 2020

Prospective and cross-sectional studies have used pre-season isokinetic dynamometry strength and endurance measurements of shoulder internal rotation (IR) and external rotation (ER) to determine if they can be correlated to injury. However, to date, no review has provided a synthesis of all available literature on this topic. The aim of this systematic review was to identify isokinetic dynamometry studies that assess shoulder IR and ER strength and endurance in the overhead athletic population in relation to shoulder injury. Electronic databases (PubMed, CINAHL, and SportDiscus) were searched through September 2019 using pre-determined search terms. Both prospective and cross-sectional studies were included in this review. Studies were assessed for quality using either Appraisal Tool for Cross-sectional Studies (AXIS) or Critical Appraisal Skills Programme (CASP). Data on outcome measures of strength and endurance peak torque (PT) and ratios (ER:IR) were extracted and further analysed using a best evidence synthesis approach. A total of 13 articles met the inclusion criteria. Conflicting evidence was found when reviewing all studies without differentiating by study type. Prospective study designs revealed strong evidence that reduced IR endurance and reduced strength ratios are predictive of shoulder injury. Cross-sectional literature showed only conflicting and limited evidence for all outcome measures. At this stage, more research is needed in individual sporting populations using prospective cohort designs.
Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles
Authors: Cai Junpeng , Chen Dewang , Jiang Shixiong , Pan Weijing
Published: September 2020

With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based on the next destination of EV users’ trip, the strategy established a dynamic-area model to match charging stations with users’ travel demand intelligently. In the dynamic area, the Dijkstra algorithm is used to find the charging station with the shortest trip. Then, the area extension algorithm and the charging station attribution algorithm were developed to improve the robustness of the dynamic area. The two algorithms can automatically adjust the area size according to the number of charging stations in the dynamic area to reduce the number of nodes traversed by the Dijkstra algorithm. Finally, simulation examples were used to verify the effectiveness of the proposed model and algorithms. The results showed that the proposed intelligent charging guidance strategy can meet the travel demand of users. It is a promising technique in smart cities to find better travel trips with less travel distance and less computed time.
Entrepreneurial Experience and Performance: From the Aspect of Sustainable Growth of Enterprises
Authors: Peng Huatao , Zhou Chen , Liu Yang
Published: September 2020

In the uncertain entrepreneurial ecosystem, scholarly knowledge is bounded by the sustainable growth of entrepreneurial enterprises. Moreover, there is a lack of consensus in academic circles on the relationship between entrepreneurial experience and entrepreneurial performance. In adopting the meta-analysis method, we found a significant relationship between entrepreneurial experience and entrepreneurial performance based on an investigation of 45 independent samples (N = 18,752). We also examined theoretically derived moderators of this relationship referring to firm age, industry condition and experience type to test whether the moderating effects can explain the inconsistent research results on the relationship between entrepreneurial experience and entrepreneurial performance. The relationship was stronger for the high-tech industry than for low-tech industry, for the early business stage than for late business stage and for start-up experience compared to management experience, work experience and industry experience. Our research findings are meaningful for practitioners to achieve sustainable growth by better preserving and coordinating entrepreneurial experience in a dynamic environment. Further, these findings are also important for future research to analyze the factors triggering the heterogeneity of entrepreneurial experience and to investigate the extent to which the start-up experience is more capable of promoting entrepreneurial performance.
Methodology and Application of Spatial Vulnerability Assessment for Evacuation Shelters in Disaster Planning
Authors: Sritart Hiranya , Miyazaki Hiroyuki , Kanbara Sakiko , Hara Takashi
Published: September 2020

Evacuation shelters are the most important means for safeguarding people in hazardous areas and situations, and thus minimizing losses, particularly those due to a disaster. Therefore, evacuation shelter assignment and evacuation planning are some of the critical factors for reducing vulnerability and increasing resilience in disaster risk reduction. However, an imbalance of shelter distribution and spatial heterogeneity of a population are the critical issues limiting the accessibility of evacuation shelters in real situations. In this study, we propose a methodology for spatial assessment to reduce vulnerability and evaluate the spatial distribution of both shelter demand and resources, considering spatial accessibility. The method was applied to the case study of Mabi, in the context of a disaster caused by the 2018 flooding. We applied this approach to evaluate the area and identified the vulnerability of the evacuation shelters and the residents. The proposed method revealed that 54.55% of the designated evacuation shelters and 59% of the total population were physically vulnerable to the flood. The results highlight, using GIS maps, that the total shelter capacity was significantly decreased to 43.86%. The outcome assessment addressed specific vulnerable shelters and the imbalance between the demand for and resources of each shelter. Accordingly, this study provides practical information and a valuable reference for supporting local governments and stakeholders to improve future disaster planning, prevention, and preparedness.
Role of Seaweed in Diets of Samoa and Kiribati: Exploring Key Motivators for Consumption
Authors: Butcher Hayley , Burkhart Sarah , Paul Nicholas , Tiitii Ulusapeti , Tamuera Karibanang , Eria Taati , Swanepoel Libby
Published: September 2020

Edible seaweeds have significant potential to contribute to sustainable diets that promote health of Pacific Islanders in ecologically, economically, and socially acceptable ways. No studies to date have investigated motivators for and the consumption of edible green seaweed from the genus Caulerpa (sea grapes) in Samoa and Kiribati. An observational, cross-sectional study utilized an interviewer-administered questionnaire to explore consumption behaviors and the role of sea grapes in the current diets of individuals in Samoa and Kiribati. Of the total 145 participants (n = 79, 54.5% Samoa; n = 66, 45.5% Kiribati), half (n = 76, 52%) reported consuming sea grapes. A significantly greater proportion of Samoans (n = 56, 70.9%) reported consumption than I-Kiribati participants (n = 20, 30.3%). A greater proportion of consumers were male (n = 47, 61.8%). Samoan consumers reported consumption of sea grapes with a higher diversity of foods and being related to traditional events or ceremonies. Motivators for consumption varied between countries, with Samoan consumers reporting strong agreement for taste and value for money, and identified sea grapes as nutritious food, as influences on consumption. Easy access was a motivator in Kiribati only. The findings of this study are underpinned by the degree of food security and differences in culture in Samoa and Kiribati. Future public health efforts to integrate traditional fresh food into local food systems will need to work within the existing social parameters in each respective country.
Evaluation of the Human Settlements Environment of Public Housing Community: A Case Study of Guangzhou
Authors: Wu Fan , Liu Yue , Zeng Yingyan , Yan Hui , Zhang Yi , Li Ling-Hin
Published: September 2020

With the improvement of social housing policies and an increase in the quantity of public housing stock, issues such as poor property management service, poor housing quality, and insufficient public services remain to be resolved. This study focuses on the human settlement environments of public housing communities in Guangzhou and establishes an evaluation system containing built environments and housing environments satisfaction criteria. In our analysis, the evaluation system was modified using data collected from surveys through factor analysis, which reduced dimensions to the indoor environment, the community environment, and social relations. Moreover, multivariable regression analysis was performed to identify the differences of needs among residents with different living environments and family backgrounds. The result shows that housing area, transportation resources, and public services have met the basic needs of residents who were generally satisfied with the community environment of their public housing. However, acoustic insulation and community amenities in the city were found to be relatively poor and still have space for improvement. Further, requirements on indoor housing environments and social relations of residents living alone need more attention. Specific recommendations based on this study can be used as a reference for future public housing construction and improvements.