bluuebunny/crossref_metadata_2025 huggingface dataset:
Healthy Food Labels Tailored to a High-Risk, Minority Population More Effectively Promote Healthy Choices than Generic Labels
Authors: Gustafson Christopher R. , Prate Michael R.
Published: September 2019

The decades-long increase in obesity in the US has led to a number of policies aimed at improving diets, which are thought to play a significant role in obesity. Many of these policies seek to influence individuals’ behaviors. Front-of-package labels providing salient, easily interpretable information to consumers have exhibited promise in helping people identify and choose healthier foods. However, behavioral economics may offer an opportunity to enhance label effectiveness. Tailoring labels to high-risk communities, including minority and rural populations, which have higher rates of diet-related diseases than the overall population, may increase the label’s effectiveness. We conducted a choice experiment with supermarket shoppers on a rural American Indian reservation to test labels tailored to the local population relative to a generic label, which had previously been identified as highly effective in the general population. Results show that while the generic label continues to be quite effective in encouraging healthier choices, the label that is tailored to the local community is more effective, resulting in a marked increase in the premium shoppers were willing to pay for a healthy item. Tailoring healthy food labeling systems using insights from behavioral economics may increase their effectiveness.
Dietary Interventions for Night Shift Workers: A Literature Review
Authors: Phoi Yan Yin , Keogh Jennifer B.
Published: September 2019

(1) Background: Night shift workers have greater risks of developing cardiometabolic diseases compared to day workers due to poor sleep quality and dietary habits, exacerbated by circadian misalignment. Assessing effects of dietary interventions on health outcomes among this group will highlight gaps for future research. (2) Methods: A search of studies was conducted on PubMed, Cochrane Library, Embase, Embase Classic, Ovid Emcare, and Google Scholar, from earliest to June 2019. The population–intervention–comparator–outcomes–study design format determined inclusion criteria. (3) Results: 756 articles were retrieved; five met inclusion and exclusion criteria. Six-hundred-and-seventy night shift workers were from healthcare, industrial, and public safety industries. Dietary interventions included two longer-term nutrition programs and three shorter-term adjustments of meal composition, type, and timing. Outcome measures were varied but included weight and cardiometabolic health measures. Nutrition programs found no weight improvement at both six and 12 months; low-density lipoprotein (LDL)-cholesterol levels decreased at six months. Triglycerides peaked after meals at 7:30 pm; glucose and insulin area under the curve peaked after meals at 11:30 pm. (4) Conclusions: Weight loss was not achieved in the studies reviewed but LDL-cholesterol improved. Future studies should investigate the effects of energy reduction and altering meal timing on cardiometabolic risk factors of night shift workers in randomised controlled trials, while assessing hunger, sleepiness, and performance.
Regulation of Gut Microbiota and Metabolic Endotoxemia with Dietary Factors
Authors: Fuke Nobuo , Nagata Naoto , Suganuma Hiroyuki , Ota Tsuguhito
Published: September 2019

Metabolic endotoxemia is a condition in which blood lipopolysaccharide (LPS) levels are elevated, regardless of the presence of obvious infection. It has been suggested to lead to chronic inflammation-related diseases such as obesity, type 2 diabetes mellitus, non-alcoholic fatty liver disease (NAFLD), pancreatitis, amyotrophic lateral sclerosis, and Alzheimer’s disease. In addition, it has attracted attention as a target for the prevention and treatment of these chronic diseases. As metabolic endotoxemia was first reported in mice that were fed a high-fat diet, research regarding its relationship with diets has been actively conducted in humans and animals. In this review, we summarize the relationship between fat intake and induction of metabolic endotoxemia, focusing on gut dysbiosis and the influx, kinetics, and metabolism of LPS. We also summarize the recent findings about dietary factors that attenuate metabolic endotoxemia, focusing on the regulation of gut microbiota. We hope that in the future, control of metabolic endotoxemia using dietary factors will help maintain human health.
Pharmacokinetic Study of NADPH Oxidase Inhibitor Ewha-18278, a Pyrazole Derivative
Authors: Lee Seul Gee , Lee Jaeok , Kim Kyung Min , Lee Kee-In , Bae Yun Soo , Lee Hwa Jeong
Published: September 2019

In a previous study, the specific NOX1/2/4 inhibitor Ewha-18278 was confirmed as a possible treatment for osteoporosis both in vitro and in vivo. Here, we investigated the pharmacokinetics (PK) of the compound by intravenous (IV) and oral administrations to rats. Dimethyl sulfoxide (DMSO)-based and diazepam injection-based formulations were used to dissolve the compound. In the latter formulation applicable to humans, the changes in PK parameters were monitored at two different concentrations (1 mg/mL and 2 mg/mL). The area under the plasma concentration-time curve from zero time to infinity (AUCinf) of Ewha-18278 was highest in the DMSO-based formulation (2 mg/mL). Also, the concentration was increased 1.6-fold at the low concentration of the diazepam injection-based formulation compared to the high concentration. There was no statistical significance in the AUCinf of the compound between DMSO-based formulation (2 mg/mL) and diazepam injection-based formulation (1 mg/mL). These results suggest that Ewha-18278 can be delivered to humans by both IV and oral routes. In addition, the diazepam injection-based formulation of Ewha-18278 appears to be a suitable candidate for dosage development for future toxicity test and clinical trial.
Evaluation of the Compatibility of Organosolv Lignin-Graphene Nanoplatelets with Photo-Curable Polyurethane in Stereolithography 3D Printing
Authors: Ibrahim Fathirrahman , Mohan Denesh , Sajab Mohd Shaiful , Bakarudin Saiful Bahari , Kaco Hatika
Published: September 2019

In this study, lignin has been extracted from oil palm empty fruit bunch (EFB) fibers via an organosolv process. The organosolv lignin obtained was defined by the presence of hydroxyl-containing molecules, such as guaiacyl and syringyl, and by the presence of phenolic molecules in lignin. Subsequently, the extracted organosolv lignin and graphene nanoplatelets (GNP) were utilized as filler and reinforcement in photo-curable polyurethane (PU), which is used in stereolithography 3D printing. The compatibility as well as the characteristic and structural changes of the composite were identified through the mechanical properties of the 3D-printed composites. Furthermore, the tensile strength of the composited lignin and graphene shows significant improvement as high as 27%. The hardness of the photo-curable PU composites measured by nanoindentation exhibited an enormous improvement for 0.6% of lignin-graphene at 92.49 MPa with 238% increment when compared with unmodified PU.
Hot-Pressed Wet-Laid Polyethylene Terephthalate Nonwoven as Support for Separation Membranes
Authors: Xia Lei , Zhang Quping , Zhuang Xupin , Zhang Shuo , Duan Chengpu , Wang Xiaoyin , Cheng Bowen
Published: September 2019

In this work, a polyethylene terephthalate (PET) nonwoven support was prepared by wet-laid and hot-press technology and used as support for separation membranes. The properties of the PET nonwoven support were studied to determine the effect of hot-pressing parameters and PET fiber ratio, and were optimized by response surface methodology. Result showed that the PET nonwoven support with 62% low melting point PET (LPET-180) fibers obtained satisfactory properties and structure after hot pressing at 220 °C under the pressure of 9 MPa for 20 s. The response surface analysis indicated that the temperature and time of hot pressing and the fiber ratio were the most important factors affecting the strength and air permeability of the PET nonwoven support. After hot pressing, the PET nonwoven support exhibited interconnected structure, small pore size, low porosity, and high strength. Then phase inversion technique was applied to prepare a polysulfone (PSF) layer on the PET nonwoven support and an ultra-thin polyamide (PA) active layer was prepared by interfacial polymerization on the PSF layer. The practicality of PET nonwoven support was verified by testing the pure water flux and retention of the PA composite membrane and the structural change of the PA composite membrane before and after use. The results proved the feasibility and remarkable application prospects of hot-pressed wet-laid PET nonwoven support as support for separation membranes.
BISSO: Biomass Interface for Superstructure Simulation and Optimization
Authors: Mangone Franco , Ferreira Jimena , Torres Ana
Published: September 2019

This paper presents a web-based tool for the optimization of biomass-to-chemicals processing pathways. The tool provides a user-friendly grpahical user interface (GUI) for building a process superstructure, offers the possibility of uploading data from Aspen Plus simulations and generates an optimization code to find the pathway that minimizes the annualized costs or maximizes the net present value. A processing pathway from residues to lactic acid is used to discuss and illustrate the main features of the tool.
Sport, Spirituality, and Religion: New Intersections
Authors: Trothen Tracy
Published: September 2019

Sport, religion, and spirituality intersect in diverse ways. As the body of interdisciplinary scholarly work addressing these intersections increases, more questions and insights are being generated, as evidenced in this collection. Five themes that arise in this Special Issue of Religions are identified and explored. Examples from each article are used to develop these themes. To whet the reader’s appetite, thought-provoking reflections are offered in this introduction to “Sport, Spirituality, and Religion: New Intersections and Global Challenges.”
Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities
Authors: Rodríguez-Martín Manuel , Rodríguez-Gonzálvez Pablo , Ruiz de Oña Crespo Esteban , González-Aguilera Diego
Published: September 2019

The three-dimensional registration of industrial facilities has a great importance for maintenance, inspection, and safety tasks and it is a starting point for new improvements and expansions in the industrial facilities context. In this paper, a comparison between the results obtained using a novel portable mobile mapping system (PMMS) and a static terrestrial laser scanner (TLS), widely used for 3D reconstruction in civil and industrial scenarios, is carried out. This comparison is performed in the context of industrial inspection tasks, specifically in the thermal and fluid-mechanics facilities in a hospital. The comparison addresses the general reconstruction of a machine room, focusing on the quantitative and qualitative analysis of different elements (e.g., valves, regulation systems, burner systems and tanks, etc.). The validation of the PMMS is provided considering the TLS as ground truth and applying a robust statistical analysis. Results come to confirm the suitability of the PMMS to perform inspection tasks in industrial facilities.
Where’s the Rock: Using Convolutional Neural Networks to Improve Land Cover Classification
Authors: Petliak Helen , Cerovski-Darriau Corina , Zaliva Vadim , Stock Jonathan
Published: September 2019

While machine learning techniques have been increasingly applied to land cover classification problems, these techniques have not focused on separating exposed bare rock from soil covered areas. Therefore, we built a convolutional neural network (CNN) to differentiate exposed bare rock (rock) from soil cover (other). We made a training dataset by mapping exposed rock at eight test sites across the Sierra Nevada Mountains (California, USA) using USDA’s 0.6 m National Aerial Inventory Program (NAIP) orthoimagery. These areas were then used to train and test the CNN. The resulting machine learning approach classifies bare rock in NAIP orthoimagery with a 0.95 F 1 score. Comparatively, the classical OBIA approach gives only a 0.84 F 1 score. This is an improvement over existing land cover maps, which underestimate rock by almost 90%. The resulting CNN approach is likely scalable but dependent on high-quality imagery and high-performance algorithms using representative training sets informed by expert mapping. As image quality and quantity continue to increase globally, machine learning models that incorporate high-quality training data informed by geologic, topographic, or other topical maps may be applied to more effectively identify exposed rock in large image collections.
Monitoring Beach Topography and Nearshore Bathymetry Using Spaceborne Remote Sensing: A Review
Authors: Salameh Edward , Frappart Frédéric , Almar Rafael , Baptista Paulo , Heygster Georg , Lubac Bertrand , Raucoules Daniel , Almeida Luis , Bergsma Erwin , Capo Sylvain , De Michele Marcello , Idier Deborah , Li Zhen , Marieu Vincent , Poupardin Adrien , Silva Paulo , Turki Imen , Laignel Benoit
Published: September 2019

With high anthropogenic pressure and the effects of climate change (e.g., sea level rise) on coastal regions, there is a greater need for accurate and up-to-date information about the topography of these systems. Reliable topography and bathymetry information are fundamental parameters for modelling the morpho-hydrodynamics of coastal areas, for flood forecasting, and for coastal management. Traditional methods such as ground, ship-borne, and airborne surveys suffer from limited spatial coverage and temporal sampling due to logistical constraints and high costs which limit their ability to provide the needed information. The recent advancements of spaceborne remote sensing techniques, along with their ability to acquire data over large spatial areas and to provide high frequency temporal monitoring, has made them very attractive for topography and bathymetry mapping. In this review, we present an overview of the current state of spaceborne-based remote sensing techniques used to estimate the topography and bathymetry of beaches, intertidal, and nearshore areas. We also provide some insights about the potential of these techniques when using data provided by new and future satellite missions.
Long-Term Changes of Open-Surface Water Bodies in the Yangtze River Basin Based on the Google Earth Engine Cloud Platform
Authors: Deng Yue , Jiang Weiguo , Tang Zhenghong , Ling Ziyan , Wu Zhifeng
Published: September 2019

The spatiotemporal changes of open-surface water bodies in the Yangtze River Basin (YRB) have profound influences on sustainable economic development, and are also closely relevant to water scarcity in China. However, long-term changes of open-surface water bodies in the YRB have remained poorly characterized. Taking advantage of the Google Earth Engine (GEE) cloud platform, this study processed 75,593 scenes of Landsat images to investigate the long-term changes of open-surface water bodies in the YRB from 1984 to 2018. In this study, we adopted the percentile-based image composite method to collect training samples and proposed a multiple index water detection rule (MIWDR) to quickly extract the open-surface water bodies. The results indicated that (1) the MIWDR is suitable for the long-term and large-scale Landsat water bodies mapping, especially in the urban regions. (2) The areas of permanent water bodies and seasonal water bodies were 29,076.70 km2 and 21,526.24 km2, accounting for 57.46% and 42.54% of the total open-surface water bodies in the YRB, respectively. (3) The permanent water bodies in the YRB increased along with the decreases in the seasonal water bodies from 1984 to 2018. In general, the total open-surface surface water bodies in the YRB experienced an increasing trend, with an obvious spatial heterogeneity. (4) The changes of open-surface water bodies were associated with the climate changes and intense human activities in the YRB, however, the influences varied among different regions and need to be further investigated in the future.
Crop Water Content of Winter Wheat Revealed with Sentinel-1 and Sentinel-2 Imagery
Authors: Han Dong , Liu Shuaibing , Du Ying , Xie Xinrui , Fan Lingling , Lei Lei , Li Zhenhong , Yang Hao , Yang Guijun
Published: September 2019

This study aims to efficiently estimate the crop water content of winter wheat using high spatial and temporal resolution satellite-based imagery. Synthetic-aperture radar (SAR) data collected by the Sentinel-1 satellite and optical imagery from the Sentinel-2 satellite was used to create inversion models for winter wheat crop water content, respectively. In the Sentinel-1 approach, several enhanced radar indices were constructed by Sentinel-1 backscatter coefficient of imagery, and selected the one that was most sensitive to soil water content as the input parameter of a water cloud model. Finally, a water content inversion model for winter wheat crop was established. In the Sentinel-2 approach, the gray relational analysis was used for several optical vegetation indices constructed by Sentinel-2 spectral feature of imagery, and three vegetation indices were selected for multiple linear regression modeling to retrieve the wheat crop water content. 58 ground samples were utilized in modeling and verification. The water content inversion model based on Sentinel-2 optical images exhibited higher verification accuracy (R = 0.632, RMSE = 0.021 and nRMSE = 19.65%) than the inversion model based on Sentinel-1 SAR (R = 0.433, RMSE = 0.026 and nRMSE = 21.24%). This study provides a reference for estimating the water content of wheat crops using data from the Sentinel series of satellites.
A Wearable In-Ear EEG Device for Emotion Monitoring
Authors: Athavipach Chanavit , Pan-ngum Setha , Israsena Pasin
Published: September 2019

For future healthcare applications, which are increasingly moving towards out-of-hospital or home-based caring models, the ability to remotely and continuously monitor patients’ conditions effectively are imperative. Among others, emotional state is one of the conditions that could be of interest to doctors or caregivers. This paper discusses a preliminary study to develop a wearable device that is a low cost, single channel, dry contact, in-ear EEG suitable for non-intrusive monitoring. All aspects of the designs, engineering, and experimenting by applying machine learning for emotion classification, are covered. Based on the valence and arousal emotion model, the device is able to classify basic emotion with 71.07% accuracy (valence), 72.89% accuracy (arousal), and 53.72% (all four emotions). The results are comparable to those measured from the more conventional EEG headsets at T7 and T8 scalp positions. These results, together with its earphone-like wearability, suggest its potential usage especially for future healthcare applications, such as home-based or tele-monitoring systems as intended.
Design of Cavity-Backed Bow-Tie Antenna with Matching Layer for Human Body Application
Authors: Jeong Jinho , Park Kihoon , Lee Changmin
Published: September 2019

This paper presents the broadband antenna for the microwave radiometric sensing of internal body temperature. For broadband operation, the bow-tie antenna was designed and backed with a cylindrical cavity, which decreased environmental electromagnetic interference and also improved the directivity of the antenna. The broadband impedance-transforming balun in microstrip form was also designed to feed the bow-tie antenna, and was located inside the cavity. An impedance-matching dielectric layer (IMDL) was introduced on top of the bow-tie antenna, for impedance match with the human body with high permittivity. The fabricated antenna was measured in free space with the IMDL removed, showing an input reflection coefficient lower than −10 dB from 2.64 to > 3.60 GHz with antenna gain over 6.0 dBi and radiation efficiency over 74.7% from 2.7 to 3.5 GHz. The IMDL was re-installed on the cavity-backed bow-tie antenna to measure the antenna performance for the human head with relative permittivity of about 40. The measured reflection coefficient was as low as −28.9 dB at 2.95 GHz and lower than −10 dB from 2.65 to > 3.5 GHz. It was also shown that the designed antenna recovered a good impedance match by adjusting the permittivity and thickness of the IMDL for the different parts of the human body with different permittivities.
New Single-Layered Paper-Based Microfluidic Devices for the Analysis of Nitrite and Glucose Built via Deposition of Adhesive Tape
Authors: Yu Peng , Deng Muhan , Yang Yi
Published: September 2019

A simple, low-cost technique has been developed for the rapid fabrication of single-layered paper-based microfluidic devices (μPADs). This technique, for the first time, made use of the deposition of patterned adhesive tape into the filter paper to construct hydrophobic barriers, with the help of toluene. Unlike other reported multi-layered μPADs that merely made use of adhesive tape as a separate layer for sealing or fluid flow controlling, the patterned adhesive tape was simultaneously dissolved and penetrated into the filter paper, which resulted in the successful transfer of the pattern from the tape to the filter paper. To demonstrate the effectiveness of this approach, nitrite and glucose were individually measured; detection limits as low as 0.015 ± 0.004 mM and 0.022 ± 0.006 mM were reported for nitrite and glucose, respectively. Multiplexed analysis of both analytes was also carried out with respective detection limits of 0.048 ± 0.005 mM and 0.025 ± 0.006 mM for nitrite and glucose. The application of the method was demonstrated by measuring nitrite and glucose in spiked artificial urine samples and satisfied recovery results were obtained.
Noninvasive Suspicious Liquid Detection Using Wireless Signals
Authors: Deng Jiewen , Sun Wanrong , Guan Lei , Zhao Nan , Khan Muhammad Bilal , Ren Aifeng , Zhao Jianxun , Yang Xiaodong , Abbasi Qammer H.
Published: September 2019

Conventional liquid detection instruments are very expensive and not conducive to large-scale deployment. In this work, we propose a method for detecting and identifying suspicious liquids based on the dielectric constant by utilizing the radio signals at a 5G frequency band. There are three major experiments: first, we use wireless channel information (WCI) to distinguish between suspicious and nonsuspicious liquids; then we identify the type of suspicious liquids; and finally, we distinguish the different concentrations of alcohol. The K-Nearest Neighbor (KNN) algorithm is used to classify the amplitude information extracted from the WCI matrix to detect and identify liquids, which is suitable for multimodal problems and easy to implement without training. The experimental result analysis showed that our method could detect more than 98% of the suspicious liquids, identify more than 97% of the suspicious liquid types, and distinguish up to 94% of the different concentrations of alcohol.
Thumbnail Tensor—A Method for Multidimensional Data Streams Clustering with an Efficient Tensor Subspace Model in the Scale-Space
Authors: Cyganek Bogusław
Published: September 2019

In this paper an efficient method for signal change detection in multidimensional data streams is proposed. A novel tensor model is suggested for input signal representation and analysis. The model is built from a part of the multidimensional stream by construction of the representing orthogonal tensor subspaces, computed with the higher-order singular value decomposition (HOSVD). Parts of the input data stream from successive time windows are then compared with the model, which is either updated or rebuilt, depending on the result of the proposed statistical inference rule. Due to processing of the input signal tensor in the scale-space, the thumbnail like output is obtained. Because of this, the method is called a thumbnail tensor. The method was experimentally verified on annotated video databases and on real underwater sequences. The results show a significant improvement over other methods both in terms of accuracy as well as in speed of operation time.
A Pheromone-Inspired Monitoring Strategy Using a Swarm of Underwater Robots
Authors: Li Guannan , Chen Chao , Geng Chao , Li Meng , Xu Hongli , Lin Yang
Published: September 2019

The advent of the swarm makes it feasible to dynamically monitor a wide area for maritime applications. The crucial problems of underwater swarm monitoring are communication and behavior coordination. To tackle these problems, we propose a wide area monitoring strategy that searches for static targets of interest simultaneously. Traditionally, an underwater robot adopts either acoustic communication or optical communication. However, the former is low in bandwidth and the latter is short in communication range. Our strategy coordinates underwater robots through indirect communication, which is inspired by social insects that exchange information by pheromone. The indirect communication is established with the help of a set of underwater communication nodes. We adopt a virtual pheromone-based controller and provide a set of rules to integrate the area of interest into the pheromone. Based on the information in the virtual pheromone, behavior laws are developed to guide the swarm to monitor and search with nearby information. In addition, a robot can improve its performance when using additional far-away pheromone information. The monitoring strategy is further improved by adopting a swarm evolution scheme which automatically adjusts the visiting period. Experimental results show that our strategy is superior to the random strategy in most cases.
Monitoring of Adult Zebrafish Heart Regeneration Using High-Frequency Ultrasound Spectral Doppler and Nakagami Imaging
Authors: Yeo Sunmi , Yoon Changhan , Lien Ching-Ling , Song Tai-Kyong , Shung K. Kirk
Published: September 2019

This paper reports the feasibility of Nakagami imaging in monitoring the regeneration process of zebrafish hearts in a noninvasive manner. In addition, spectral Doppler waveforms that are typically used to access the diastolic function were measured to validate the performance of Nakagami imaging. A 30-MHz high-frequency ultrasound array transducer was used to acquire backscattered echo signal for spectral Doppler and Nakagami imaging. The performances of both methods were validated with flow and tissue-mimicking phantom experiments. For in vivo experiments, both spectral Doppler and Nakagami imaging were simultaneously obtained from adult zebrafish with amputated hearts. Longitudinal measurements were performed for five zebrafish. From the experiments, the E/A ratio measured using spectral Doppler imaging increased at 3 days post-amputation (3 dpa) and then decreased to the value before amputation, which were consistent with previous studies. Similar results were obtained from the Nakagami imaging where the Nakagami parameter value increased at 3 dpa and decreased to its original value. These results suggested that the Nakagami and spectral Doppler imaging would be useful techniques in monitoring the regeneration of heart or tissues.
Sensitivity-Enhanced Extrinsic Fabry–Perot Interferometric Fiber-Optic Microcavity Strain Sensor
Authors: Ma Zhibo , Cheng Shaolei , Kou Wanying , Chen Haibin , Wang Wei , Zhang Xiongxing , Guo Tongxin
Published: September 2019

This study presents an extrinsic Fabry–Perot interferometric (EFPI) fiber-optic strain sensor with a very short cavity. The sensor consists of two vertically cut standard single-mode fibers (SMFs) and a glass capillary with a length of several centimeters. The two SMFs penetrate into the glass capillary and are fixed at its two ends with the use of ultraviolet (UV) curable adhesives. Based on the use of the lengthy glass capillary sensitive element, the strain sensitivity can be greatly enhanced. Experiments showed that the microcavity EPFI strain sensor with initial cavity lengths of 20 μm, 30 μm, and 40 μm, and a capillary length of 40 mm, can yield respective cavity length–strain sensitivities of 15.928 nm/με, 25.281 nm/με, and 40.178 nm/με, while its linearity was very close to unity for strain measurements spanning a range in excess of 3500 με. Furthermore, the strain–temperature cross-sensitivity was extremely low.
Calibration of Displacement Laser Interferometer Systems for Industrial Metrology
Authors: Haitjema Han
Published: September 2019

Displacement laser interferometer systems are widely used for the calibration of machine tools and CMMs (Coordinate Measuring Machines). Additionally, they are often the workhorse in dimensional calibration laboratories, where they act as the basic metrological traceability link for many calibrations. This paper gives a review of the calibration of such systems, where several approaches, such as the calibrations of separate components or the system as a whole, are reviewed. The calibrations discussed are: the laser frequency, the counting system, software evaluation of the environmental conditions, environmental and material temperature sensor calibration and the calibration of optics that is part of the system. For these calibrations considerations are given about the ways these can be carried out and about establishing the re-calibration intervals.
Novel Operation Strategy to Obtain a Fast Gas Sensor for Continuous ppb-Level NO2 Detection at Room Temperature Using ZnO—A Concept Study with Experimental Proof
Authors: Wagner Ricarda , Schönauer-Kamin Daniela , Moos Ralf
Published: September 2019

A novel sensor operation concept for detecting ppb-level NO2 concentrations at room temperature is introduced. Today’s research efforts are directed to make the sensors as fast as possible (low response and recovery times). Nevertheless, hourly mean values can hardly be precisely calculated, as the sensors are still too slow and show baseline drifts. Therefore, the integration error becomes too large. The suggested concept follows exactly the opposite path. The sensors should be made as slow as possible and operated as resistive gas dosimeters. The adsorption/desorption equilibrium should be completely shifted to the adsorption side during a sorption phase. The gas-sensitive material adsorbs each NO2 molecule (dose) impinging and the sensor signal increases linearly with the NO2 dose. The actual concentration value results from the time derivative, which makes the response very fast. When the NO2 adsorption capacity of the sensor material is exhausted, it is regenerated with ultraviolet (UV) light and the baseline is reached again. Since the baseline is newly redefined after each regeneration step, no baseline drift occurs. Because each NO2 molecule that reaches the sensor material contributes to the sensor signal, a high sensitivity results. The sensor behavior of ZnO known so far indicates that ZnO may be suitable to be applied as a room-temperature chemiresistive NO2 dosimeter. Because UV enhances desorption of sorbed gas species from the ZnO surface, regeneration by UV light should be feasible. An experimental proof demonstrating that the sensor concept works at room temperature for ppb-level NO2 concentrations and low doses is given.
Critical Location Spatial-Temporal Coverage Optimization in Visual Sensor Network
Authors: Xiong Yonghua , Li Jing , Lu Manjie
Published: September 2019

Coverage and network lifetime are two fundamental research issues in visual sensor networks. In some surveillance scenarios, there are some critical locations that demand to be monitored within a designated period. However, with limited sensor nodes resources, it may not be possible to meet both coverage and network lifetime requirements. Therefore, in order to satisfy the network lifetime constraint, sometimes the coverage needs to be traded for network lifetime. In this paper, we study how to schedule sensor nodes to maximize the spatial-temporal coverage of the critical locations under the constraint of network lifetime. First, we analyze the sensor node scheduling problem for the spatial-temporal coverage of the critical locations and establish a mathematical model of the node scheduling. Next, by analyzing the characteristics of the model, we propose a Two-phase Spatial-temporal Coverage-enhancing Method (TSCM). In phase one, a Particle Swarm Optimization (PSO) algorithm is employed to organize the directions of sensor nodes to maximize the number of covered critical locations. In the second phase, we apply a Genetic Algorithm (GA) to get the optimal working time sequence of each sensor node. New coding and decoding strategies are devised to make GA suitable for this scheduling problem. Finally, simulations are conducted and the results show that TSCM has better performance than other approaches.
Acoustic Coupling between Resonator Tubes in Quartz-Enhanced Photoacoustic Spectrophones Employing a Large Prong Spacing Tuning Fork
Authors: Dello Russo Stefano , Giglio Marilena , Sampaolo Angelo , Patimisco Pietro , Menduni Giansergio , Wu Hongpeng , Dong Lei , Passaro Vittorio M. N. , Spagnolo Vincenzo
Published: September 2019

A theoretical model describing the acoustic coupling between two resonator tubes in spectrophones exploiting custom-made quartz tuning forks (QTFs) is proposed. The model is based on an open-end correction to predict the optimal tube length. A calculation of the sound field distribution from one tube exit allowed for the estimation of the optimal radius as a function of the QTF prong spacing and the sound wavelength. The theoretical predictions have been confirmed using experimental studies employing a custom QTF with a fundamental flexural mode resonance frequency of 15.8 kHz and a quality factor of 15,000 at atmospheric pressure. The spacing between the two prongs was 1.5 mm. Spectrophones mounting this QTF were implemented for the quartz-enhanced photoacoustic detection of water vapor in air in the mid-infrared spectral range.
A Qualitative Analysis of a USB Camera for AGV Control
Authors: Puppim de Oliveira Diogo , Pereira Neves dos Reis Wallace , Morandin Junior Orides
Published: September 2019

The increasing use of Automated Guided Vehicles (AGV) in the industry points to a search for better techniques and technologies to adapt to market requirements. Proper position control and movement give an AGV greater movement accuracy and greater lateral oscillations stability and vibration. It leads to smaller corridors and leaner plants, to more relaxed shipment devices, and to greater safety in the transport of fragile loads, for instance. AGV control techniques are not new, but new sensors’ applications are possible, such as USB cameras. In this sense, it is necessary to ensure the sensor is adequate to control system requirements. This work addresses AGVs driven by passive floor demarcations. It presents a qualitative analysis of a USB camera as sensors for AGV control, not yet a common industrial application. We performed the experiments with a small AGV prototype on an eight-shaped lane, varying both camera parameters and AGV parameters, such as linear speed. The AGV uses a USB camera with different image processing settings—different morphological filters structuring elements shapes and sizes, and three different image resolutions—to analyze the factors that affect line detection and control processing. This paper’s main contribution is a qualitative and quantitative analysis for the different sensor configurations. In addition, it discusses the influence sources on camera image as a position sensor. Furthermore, the experiments confirm sensor pertinence for the proposed control system.
Enhanced Distributed Fiber Optic Vibration Sensing and Simultaneous Temperature Gradient Sensing Using Traditional C-OTDR and Structured Fiber with Scattering Dots
Authors: Hicke Konstantin , Eisermann René , Chruscicki Sebastian
Published: September 2019

We present results demonstrating several beneficial effects on distributed fiber optic vibration sensing (DVS) functionality and performance resulting from utilizing standard single mode optical fiber (SMF) with femtosecond laser-inscribed equally-spaced simple scattering dots. This modification is particularly useful when using traditional single-wavelength amplitude-based coherent optical time domain reflectometry (C-OTDR) as sensing method. Local sensitivity is increased in quasi-distributed interferometric sensing zones which are formed by the fiber segments between subsequent pairs of the scattering dots. The otherwise nonlinear transfer function is overwritten with that of an ordinary two-beam interferometer. This linearizes the phase response to monotonous temperature variations. Furthermore, sensitivity fading is mitigated and the demodulation of low-frequency signals is enabled. The modification also allows for the quantitative determination of local temperature gradients directly from the C-OTDR intensity traces. The dots’ reflectivities and thus the induced attenuation can be tuned via the inscription process parameters. Our approach is a simple, robust and cost-effective way to gain these sensing improvements without the need for more sophisticated interrogator technology or more complex fiber structuring, e.g., based on ultra-weak FBG arrays. Our claims are substantiated by experimental evidence.
Road Extraction from Unmanned Aerial Vehicle Remote Sensing Images Based on Improved Neural Networks
Authors: Li Yuxia , Peng Bo , He Lei , Fan Kunlong , Li Zhenxu , Tong Ling
Published: September 2019

Roads are vital components of infrastructure, the extraction of which has become a topic of significant interest in the field of remote sensing. Because deep learning has been a popular method in image processing and information extraction, researchers have paid more attention to extracting road using neural networks. This article proposes the improvement of neural networks to extract roads from Unmanned Aerial Vehicle (UAV) remote sensing images. D-Linknet was first considered for its high performance; however, the huge scale of the net reduced computational efficiency. With a focus on the low computational efficiency problem of the popular D-LinkNet, this article made some improvements: (1) Replace the initial block with a stem block. (2) Rebuild the entire network based on ResNet units with a new structure, allowing for the construction of an improved neural network D-Linknetplus. (3) Add a 1 × 1 convolution layer before DBlock to reduce the input feature maps, reducing parameters and improving computational efficiency. Add another 1 × 1 convolution layer after DBlock to recover the required number of output channels. Accordingly, another improved neural network B-D-LinknetPlus was built. Comparisons were performed between the neural nets, and the verification were made with the Massachusetts Roads Dataset. The results show improved neural networks are helpful in reducing the network size and developing the precision needed for road extraction.
Ambulatory Assessment of the Dynamic Margin of Stability Using an Inertial Sensor Network
Authors: Guaitolini Michelangelo , Aprigliano Federica , Mannini Andrea , Micera Silvestro , Monaco Vito , Sabatini Angelo Maria
Published: September 2019

Loss of stability is a precursor to falling and therefore represents a leading cause of injury, especially in fragile people. Thus, dynamic stability during activities of daily living (ADLs) needs to be considered to assess balance control and fall risk. The dynamic margin of stability (MOS) is often used as an indicator of how the body center of mass is located and moves relative to the base of support. In this work, we propose a magneto-inertial measurement unit (MIMU)-based method to assess the MOS of a gait. Six young healthy subjects were asked to walk on a treadmill at different velocities while wearing MIMUs on their lower limbs and pelvis. We then assessed the MOS by computing the lower body displacement with respect to the leading inverse kinematics approach. The results were compared with those obtained using a camera-based system in terms of root mean square deviation (RMSD) and correlation coefficient (ρ). We obtained a RMSD of ≤1.80 cm and ρ ≥ 0.85 for each walking velocity. The findings revealed that our method is comparable to camera-based systems in terms of accuracy, suggesting that it may represent a strategy to assess stability during ADLs in unstructured environments.
Fusing Object Information and Inertial Data for Activity Recognition
Authors: Diete Alexander , Stuckenschmidt Heiner
Published: September 2019

In the field of pervasive computing, wearable devices have been widely used for recognizing human activities. One important area in this research is the recognition of activities of daily living where especially inertial sensors and interaction sensors (like RFID tags with scanners) are popular choices as data sources. Using interaction sensors, however, has one drawback: they may not differentiate between proper interaction and simple touching of an object. A positive signal from an interaction sensor is not necessarily caused by a performed activity e.g., when an object is only touched but no interaction occurred afterwards. There are, however, many scenarios like medicine intake that rely heavily on correctly recognized activities. In our work, we aim to address this limitation and present a multimodal egocentric-based activity recognition approach. Our solution relies on object detection that recognizes activity-critical objects in a frame. As it is infeasible to always expect a high quality camera view, we enrich the vision features with inertial sensor data that monitors the users’ arm movement. This way we try to overcome the drawbacks of each respective sensor. We present our results of combining inertial and video features to recognize human activities on different types of scenarios where we achieve an F 1 -measure of up to 79.6%.
Super Sub-Nyquist Single-Pixel Imaging by Means of Cake-Cutting Hadamard Basis Sort
Authors: Yu Wen-Kai
Published: September 2019

Single-pixel imaging via compressed sensing can reconstruct high-quality images from a few linear random measurements of an object known a priori to be sparse or compressive, by using a point/bucket detector without spatial resolution. Nevertheless, random measurements still have blindness, limiting the sampling ratios and leading to a harsh trade-off between the acquisition time and the spatial resolution. Here, we present a new compressive imaging approach by using a strategy we call cake-cutting, which can optimally reorder the deterministic Hadamard basis. The proposed method is capable of recovering images of large pixel-size with dramatically reduced sampling ratios, realizing super sub-Nyquist sampling and significantly decreasing the acquisition time. Furthermore, such kind of sorting strategy can be easily combined with the structured characteristic of the Hadamard matrix to accelerate the computational process and to simultaneously reduce the memory consumption of the matrix storage. With the help of differential modulation/measurement technology, we demonstrate this method with a single-photon single-pixel camera under the ulta-weak light condition and retrieve clear images through partially obscuring scenes. Thus, this method complements the present single-pixel imaging approaches and can be applied to many fields.
Higher Education, Widening Access and Market Failure: Towards a Dual Pricing Mechanism in England
Authors: McCaig Colin , Lightfoot Nicola
Published: September 2019

Over a period of around fifteen years English higher education has become characterised by an increasingly marketise and differentiated system, most recently with the encouragement of new “challenger” providers potentially creating price competition for undergraduate degrees. This paper explores shifting patterns of enrolments between different institution types (those requiring high entry grades and those requiring lower entry grades) for evidence of how these types may be responding to the new market conditions. We introduce the concept of a “dual-pricing” mechanism to model how different institution types may be reacting. Dual pricing would be exemplified as a situation where entry requirements (a “price” based on qualification tariff points required for entry) and tuition-fee are matched in a linear hierarchy of institutions: Only the most prestigious institutions offering the courses demanding the highest entry qualifications (tariff) would command the highest fee (in this case a maxima of £9250 per annum), with fees demanded by institutions requiring lower entry requirements tapering off towards £6000 per year. This dual-pricing mechanism is discussed here as a policy aim, and the intention of this paper is to locate it in relation to market failure (defined as the failing of a market intervention to meet that policy aim). This paper’s critique of the marketised direction of travel in English higher education (HE) policymaking is that a dual-price mechanism would seriously undermine efforts to widen access for underrepresented social groups, particularly those from low income households who may be more likely to access low-cost provision rather than more transformative HE opportunities (supposedly those deriving from having a degree from a more prestigious institution), even if they met the entry requirements for higher-cost provision.
Optimal Environmental Tax Rate in an Open Economy with Labor Migration—An E-DSGE Model Approach
Authors: Chan Ying Tung
Published: September 2019

Recent research has started to apply environmental dynamic stochastic general equilibrium (E-DSGE) models for climate policy analysis. However, all of the studies assume a closed economy setting, where there is no interaction of the economy with an outside economy; this paper fills the gap by constructing a two-city E-DSGE model that features labor migration. With the model, we solve for the optimal environmental tax rate determined by a Ramsey social planner, who maximizes household utility and takes into account the policy’s impact on labor migration. We find the following. (i) The optimal environmental tax rate should be more volatile and procyclical than the rates predicted in the aforementioned literature. (ii) In the closed economy setting, a higher environmental tax rate would always dampen production, while in our setting, it could stimulate output through deterring labor outflow and attracting labor inflow. (iii) We complement the existing literature by emphasizing that the optimal environmental tax rate in a city should respond not only to the shocks that occur internally, but also to those that occur in the opponent city. In particular, we find that it is optimal to reduce the environmental tax rate if a positive total factor productivity (TFP) shock occurs in the neighbor city.