bluuebunny/crossref_metadata_2025 huggingface dataset:
Inactivation of Classical Swine Fever Virus in Porcine Serum Samples Intended for Antibody Detection
Authors: Meyer Denise , Petrov Anja , Becher Paul
Published: December 2019

Shipping of serum samples that were taken from pigs infected with classical swine fever (CSF) virus is frequently requested with the objective of serological analyses, not only for diagnostic purposes but also for exchange of reference materials that are used as control material of diagnostic assays. On the basis of the fact that an outbreak with CSF is associated with enormous economic losses, biological safety during the exchange of reference material is of great importance. The present study aimed to establish a pragmatic approach for reliable CSF virus (CSFV) inactivation in serum without impairing antibody detection. Considering the fact that complement inactivation through heating is routinely applied, the basic idea was to combine heat treatment with the dilution of serum in a detergent containing buffer in order to facilitate the inactivation process. The results show that treatment of serum samples with phosphate buffered saline-Tween20 (final concentration = 0.15%) along with incubation at 56 °C for 30 min inactivated CSFV and such treatment with ≤ 0.25% PBS-Tween20 does not impair subsequent antibody detection by ELISA or virus neutralization test. This minimizes the risk of virus contamination and represents a valuable contribution to a safer CSF diagnosis on a national and international level.
Pharmacists as Immunizers: The Role of Pharmacies in Promoting Immunization Campaigns and Counteracting Vaccine Hesitancy
Authors: Bragazzi Nicola Luigi
Published: December 2019

Vaccines represent fundamental public health interventions aimed to counteract or, at least, partially mitigate the severe epidemiological and economic burden generated by communicable disorders, in terms of (i) outcome-related, (ii) behavior-related productivity gains, and (iii) community externalities in developed settings as well as in developing countries. Despite their importance, several parents choose not to immunize their children due to the rising phenomenon of anti-vaccination movements that divulge vaccine-related “fake news” and “post-modern, post-factual truths”. Vaccine hesitancy represents a threat that can seriously jeopardize the implementation and success of vaccination campaigns. Within this framework, from a public health perspective, community pharmacies can play a vital role in that pharmacists can: (i) act as immunizers (vaccine distributors, educators, facilitators and administrators), (ii) improve vaccine-related health literacy and vaccination coverage rates as well as (iii) remove barriers and obstacles to the access to healthcare settings offering immunization services and (iv) counteract vaccine hesitancy.
Sub-Standard Pharmaceutical Services in Private Healthcare Facilities Serving Low-Income Settlements in Nairobi County, Kenya
Authors: Abuga Kennedy , Ongarora Dennis , Karumbi Jamlick , Olulo Millicent , Minnaard Warnyta , Kibwage Isaac
Published: December 2019

Background: Quality pharmaceutical services are an integral part of primary healthcare and a key determinant of patient outcomes. The study focuses on pharmaceutical service delivery among private healthcare facilities serving informal settlements within Nairobi County, Kenya and aims at understanding the drug procurement practices, task-shifting and ethical issues associated with drug brand preference, competition and disposal of expired drugs. Methods: Forty-five private facilities comprising of hospitals, nursing homes, health centres, medical centres, clinics and pharmacies were recruited through purposive sampling. Structured electronic questionnaires were administered to 45 respondents working within the study facilities over an 8-week period. Results: About 50% of personnel carrying out drug procurement belonged to non-pharmaceutical cadres namely; doctors, clinical officers, nurses and pharmacy assistants. Drug brand preferences among healthcare facilities and patients were mainly pegged on perceived quality and price. Unethical business competition practices were recorded, including poor professional demeanour and waiver of consultation fees veiled to undercut colleagues. Government subsidized drugs were sold at 100% profit in fifty percent of the facilities stocking them. In 44% of the facilities, the disposal of expired drugs was not in conformity to existing government regulatory guidelines. Conclusions: There is extensive task-shifting and delegation of pharmaceutical services to non-pharmaceutical cadres and poor observance of ethical guidelines in private facilities. Strict enforcement of regulations is required for optimal practices.
An Incubation System to Enhance Biogas and Methane Production: A Case Study of an Existing Biogas Plant in Umbria, Italy
Authors: Liberti Federica , Pistolesi Valentina , Mouftahi Mawaheb , Hidouri Nejib , Bartocci Pietro , Massoli Sara , Zampilli Mauro , Fantozzi Francesco
Published: December 2019

The pre-incubation of digestate and recycling of microbes inside a continuously stirred tank reactor (CSTR) are effective ways to optimize the anaerobic digestion process and improve the performance of biogas and methane production, also in existing biogas plants. In this study, a digestate incubation system using a nutrient mix to boost the activity of microbes was coupled to a CSTR to boost biogas and methane production. This system has been tested both on a lab scale and on an industrial scale. On a pilot scale, the system achieved an increase of +16.47 v% in biogas production with respect to the conventional anaerobic digestion process, and an increase of +2 v% in methane content (from 65.94 v% to 67.84 v%). On an industrial scale, the use of this incubation reactor with a capacity of 1 m3 has led to an increase in methane yield of 12 v%. This system allows to maintain the syntrophic relationship between acid-producing bacteria and methanogens and contemporary push the development of methanogens. Moreover, it is an economic system to be integrated into an existing biogas plant given the small volume and the simplicity of the incubation reactor.
Keller-Box Simulation for the Buongiorno Mathematical Model of Micropolar Nanofluid Flow over a Nonlinear Inclined Surface
Authors: Rafique Khuram , Anwar Muhammad Imran , Misiran Masnita , Khan Ilyas , Seikh Asiful H. , Sherif El-Sayed M. , Sooppy Nisar Kottakkaran
Published: December 2019

Brownian motion and thermophoresis diffusions are the fundamental ideas of abnormal upgrading in thermal conductivity via binary fluids (base fluid along with nanoparticles). The influence of Brownian motion and thermophoresis are focused on in the Buongiorno model. In this problem, we considered the Buongiorno model with Brownian motion and thermophoretic effects. The nonlinear ordinary differential equations are recovered from the partial differential equations of the boundary flow via compatible similarity transformations and then employed to the Keller-box scheme for numerical results. The physical quantities of our concern including skin friction, Nusselt number, and Sherwood number along with velocity, temperature and concentration profile against involved effects are demonstrated. The impacts of the involved flow parameters are drawn in graphs and tabulated forms. The inclination effect shows an inverse relation with the velocity field. Moreover, the velocity profile increases with the growth of the buoyancy effect.
Variational Assimilation of Radio Occultation Observations into Numerical Weather Prediction Models: Equations, Strategies, and Algorithms
Authors: Gorbunov Michael , Stefanescu Razvan , Irisov Vladimir , Zupanski Dusanka
Published: December 2019

We review different approaches to the variational assimilation of radio occultation (RO) observations into models of global atmospheric circulation. We derive the general equation for the bending angle that reduces to the Abel integral for a spherically layered atmosphere. We review the full 3-D observation operator for bending angles, which provides the strictest solution, but is also most computationally expensive. Commonly used is the 2-D approximation that allows treating rays as plane curve. We discuss a simple 1-D approach to the assimilation of bending angles. The observation operator based on the standard form of the Abel integral has a disadvantage, because it cannot account for waveguides. Alternative approaches use 1-D ray-tracing. The most straightforward way is to use the same framework as for the 3-D observation operator, with the refractivity field reduced to a single profile independent from the horizontal coordinates. An alternative 1-D ray-tracing approach uses the form of ray equation in a spherically layered medium that uses an invariant. The assimilation of refractivity has also 1-D and 3-D options. We derive a new simple form of the refractivity-mapping operator. We present the results of numerical tests of different 3-D and 1-D observation operators, based on Spire data.
High-Resolution Intertidal Topography from Sentinel-2 Multi-Spectral Imagery: Synergy between Remote Sensing and Numerical Modeling
Authors: Khan Md Jamal Uddin , Ansary MD Nazmuddoha , Durand Fabien , Testut Laurent , Ishaque Marufa , Calmant Stéphane , Krien Yann , Islam A.K.M. Saiful , Papa Fabrice
Published: December 2019

The intertidal zones are well recognized for their dynamic nature and role in near-shore hydrodynamics. The intertidal topography is poorly mapped worldwide due to the high cost of associated field campaigns. Here we present a combination of remote-sensing and hydrodynamic modeling to overcome the lack of in situ measurements. We derive a digital elevation model (DEM) by linking the corresponding water level to a sample of shorelines at various stages of the tide. Our shoreline detection method is fully automatic and capable of processing high-resolution imagery from state-of-the-art satellite missions, e.g., Sentinel-2. We demonstrate the use of a tidal model to infer the corresponding water level in each shoreline pixel at the sampled timestamp. As a test case, this methodology is applied to the vast coastal region of the Bengal delta and an intertidal DEM at 10 m resolution covering an area of 1134 km 2 is developed from Sentinel-2 imagery. We assessed the quality of the DEM with two independent in situ datasets and conclude that the accuracy of our DEM amounts to about 1.5 m, which is commensurate with the typical error bar of the validation datasets. This DEM can be useful for high-resolution hydrodynamic and wave modeling of the near-shore area. Additionally, being automatic and numerically effective, our methodology is compliant with near-real-time monitoring constraints.
Multiple Kernel Feature Line Embedding for Hyperspectral Image Classification
Authors: Chen Ying-Nong
Published: December 2019

In this study, a novel multple kernel FLE (MKFLE) based on general nearest feature line embedding (FLE) transformation is proposed and applied to classify hyperspectral image (HSI) in which the advantage of multple kernel learning is considered. The FLE has successfully shown its discriminative capability in many applications. However, since the conventional linear-based principle component analysis (PCA) pre-processing method in FLE cannot effectively extract the nonlinear information, the multiple kernel PCA (MKPCA) based on the proposed multple kernel method was proposed to alleviate this problem. The proposed MKFLE dimension reduction framework was performed through two stages. In the first multple kernel PCA (MKPCA) stage, the multple kernel learning method based on between-class distance and support vector machine (SVM) was used to find the kernel weights. Based on these weights, a new weighted kernel function was constructed in a linear combination of some valid kernels. In the second FLE stage, the FLE method, which can preserve the nonlinear manifold structure, was applied for supervised dimension reduction using the kernel obtained in the first stage. The effectiveness of the proposed MKFLE algorithm was measured by comparing with various previous state-of-the-art works on three benchmark data sets. According to the experimental results: the performance of the proposed MKFLE is better than the other methods, and got the accuracy of 83.58%, 91.61%, and 97.68% in Indian Pines, Pavia University, and Pavia City datasets, respectively.
A New Fuzzy-Cluster-Based Cycle-Slip Detection Method for GPS Single-Frequency Observation
Authors: Li Zongnan , Li Min , Shi Chuang , Chen Liang , Deng Chenlong , Song Weiwei , Liu Renli , Zhang Peihua
Published: December 2019

The development of low-cost, small, modular receivers and their application in diverse scenarios with complex data quality has increased the requirements of single-frequency carrier-phase data preprocessing in real time. Different methods have been developed, but successful detection is not always ensured. The issue is crucial for high-precision positioning with Global Positioning System (GPS). Aiming at a high detection rate and low false-alarm rate, we propose a new cycle-slip detection method based on fuzzy-cluster. It consists of two steps. The first is identification of the epoch when cycle slips appear using Chi-square test based on time-differenced observations. The second is identification of the satellite which suffers from cycle slips using the fuzzy-cluster algorithm. To verify the performance of the proposed method, we compared it to a current robust method using real single-frequency data with simulated cycle slips. Results indicate that the proposed method outperforms the robust estimation method, with a higher correct-detection rate and lower undetection rate. As the number of satellites simulated with cycle slips increases, the correct-detection rate rapidly decreases from 100% to below 50% with the robust estimation method. While the correct-detection rate using the proposed method is always more than 60%, even if the number of satellites simulated with cycle slips reaches five. In addition, the proposed method always has a lower undetection rate than the robust estimation method. Simulation showed that when the number of satellites with cycle slips exceeds three, the undetection rate increases to more than 30%, reaching ~70% for the robust estimation method and less than 30% for the proposed method.
Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau
Authors: Ge Nan , Zhong Lei , Ma Yaoming , Cheng Meilin , Wang Xian , Zou Mijun , Huang Ziyu
Published: December 2019

Land surface heat fluxes consist of the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. The estimation of these fluxes is essential to the study of energy transfer in land–atmosphere systems. In this paper, Landsat 7 ETM+ SLC-on data were applied to estimate the land surface heat fluxes on the northern Tibetan Plateau using the SEBS (surface energy balance system) model, in combination with the calculation of field measurements at CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project on the Tibetan Plateau) automatic weather stations based on the combinatory method (CM) for comparison. The root mean square errors between the satellite estimations and the CM calculations for the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux were 49.2 W/m2, 46.3 W/m2, 68.2 W/m2, and 54.9 W/m2, respectively. The results reveal that land surface heat fluxes all present significant seasonal variability. Apart from the sensible heat flux, the satellite-estimated net radiation flux, soil heat flux, and latent heat flux exhibited a trend of summer > spring > autumn > winter. In summer, spring, autumn, and winter, respectively, the median values of the net radiation flux (631.8 W/m2, 583.0 W/m2, 404.4 W/m2, 314.3 W/m2), soil heat flux (40.9 W/m2, 37.9 W/m2, 26.1 W/m2, 20.5 W/m2), sensible heat flux (252.7 W/m2, 219.5 W/m2, 221.4 W/m2, 204.8 W/m2), and latent heat flux (320.1 W/m2, 298.3 W/m2, 142.3 W/m2, 75.5 W/m2) exhibited distinct seasonal diversity. From November to April, the in situ sensible heat flux is higher than the latent heat flux; the opposite is true between June and September, leaving May and October as transitional months. For water bodies, alpine meadows and other main underlying surface types, sensible and latent heat flux generally present contrasting and complementary spatial distributions. Due to the 15–60 m resolution of the Landsat 7 ETM+ data, the distribution of land surface heat fluxes can be used as an indicator of complex underlying surface types over the northern Tibetan Plateau.
Features of the Cloud Base Height and Determining the Threshold of Relative Humidity over Southeast China
Authors: Liu Yuzhi , Tang Yuhan , Hua Shan , Luo Run , Zhu Qingzhe
Published: December 2019

Clouds play a critical role in adjusting the global radiation budget and hydrological cycle; however, obtaining accurate information on the cloud base height (CBH) is still challenging. In this study, based on Lidar and aircraft soundings, we investigated the features of the CBH and determined the thresholds of the environmental relative humidity (RH) corresponding to the observed CBHs over Southeast China from October 2017 to September 2018. During the observational period, the CBHs detected by Lidar/aircraft were commonly higher in cold months and lower in warm months; in the latter, 75.91% of the CBHs were below 2000 m. Overall, the RHs at the cloud base were mainly distributed between 70 and 90% for the clouds lower than 1000 m, in which the most concentrated RH was approximately 80%. In addition, for the clouds with a cloud base higher than 1000 m, the RH thresholds decreased dramatically with increasing CBH, where the RH thresholds at cloud bases higher than 2000 m could be lower than 60%. On average, the RH thresholds for determining the CBHs were the highest (72.39%) and lowest (63.56%) in the summer and winter, respectively, over Southeast China. Therefore, to determine the CBH, a specific threshold of RH is needed. Although the time period covered by the collected CBH data from Lidar/aircraft is short, the above analyses can provide some verification and evidence for using the RH threshold to determine the CBH.
Optimising Sampling Strategies in Coral Reefs Using Large-Area Mosaics
Authors: Lechene Marine Anna Alice , Haberstroh Anna Julia , Byrne Maria , Figueira Will , Ferrari Renata
Published: December 2019

Adequately sampling benthic cover in marine ecosystems is a challenge with most methods encompassing only a small portion of the area for which cover is estimated. Recent advances in photogrammetric techniques are providing opportunity to map expansive areas of reef. This study aimed to evaluate the adequate level of sampling for traditional quadrat-based designs at ecologically relevant scales. We used large-area (~250 m2), high-resolution (0.911 ± 0.143 mm/pixel) mosaics to assess the precision and reproducibility of quadrat-based benthic sampling and identify the most efficient strategy (size and number of quadrats). There was a strong relationship between the percent cover of benthic classes and the level of sampling effort required to adequately sample them. As expected, larger quadrats were found to be more efficient when sampling effort was expressed in number of quadrats. This study aims to identify the optimal level of sampling (least effort that would result in a given target precision) to characterize coral reef benthic communities (whatever they are) within each site. As such, the sites selected were intentionally very different and together represented the broad scale of heterogeneity found in shallow coral reef communities. Abundance data can be used in combination with the relationships presented here to determine the optimal sampling protocols for management approaches to coral reef monitoring.
Simple Yet Effective Fine-Tuning of Deep CNNs Using an Auxiliary Classification Loss for Remote Sensing Scene Classification
Authors: Bazi Yakoub , Al Rahhal Mohamad M. , Alhichri Haikel , Alajlan Naif
Published: December 2019

The current literature of remote sensing (RS) scene classification shows that state-of-the-art results are achieved using feature extraction methods, where convolutional neural networks (CNNs) (mostly VGG16 with 138.36 M parameters) are used as feature extractors and then simple to complex handcrafted modules are added for additional feature learning and classification, thus coming back to feature engineering. In this paper, we revisit the fine-tuning approach for deeper networks (GoogLeNet and Beyond) and show that it has not been well exploited due to the negative effect of the vanishing gradient problem encountered when transferring knowledge to small datasets. The aim of this work is two-fold. Firstly, we provide best practices for fine-tuning pre-trained CNNs using the root-mean-square propagation (RMSprop) method. Secondly, we propose a simple yet effective solution for tackling the vanishing gradient problem by injecting gradients at an earlier layer of the network using an auxiliary classification loss function. Then, we fine-tune the resulting regularized network by optimizing both the primary and auxiliary losses. As for pre-trained CNNs, we consider in this work inception-based networks and EfficientNets with small weights: GoogLeNet (7 M) and EfficientNet-B0 (5.3 M) and their deeper versions Inception-v3 (23.83 M) and EfficientNet-B3 (12 M), respectively. The former networks have been used previously in the context of RS and yielded low accuracies compared to VGG16, while the latter are new state-of-the-art models. Extensive experimental results on several benchmark datasets reveal clearly that if fine-tuning is done in an appropriate way, it can settle new state-of-the-art results with low computational cost.
Improvement of Air Pollution in China Inferred from Changes between Satellite-Based and Measured Surface Solar Radiation
Authors: Wang Yawen , Trentmann Jörg , Pfeifroth Uwe , Yuan Wenping , Wild Martin
Published: December 2019

The air pollution crisis in China has become a global concern due to its profound effects on the global environment and human health. To significantly improve the air quality, mandatory reductions were imposed on pollution emissions and energy consumption within the framework of the 11th and 12th Five Year Plans of China. This study takes the first step to quantify the implications of recent pollution control efforts for surface solar radiation (SSR), the primary energy source for our planet. The observed bias between satellite-retrieved and surface-observed SSR time series is proposed as a useful indicator for the radiative effects of aerosol changes. This is due to the fact that the effects of temporal variations of aerosols are neglected in satellite retrievals but well captured in surface observations of SSR. The implemented pollution control measures and actions have successfully brought back SSR by an average magnitude of 3.5 W m−2 decade−1 for the whole of China from 2008 onwards. Regionally, effective pollution regulations are indicated in the East Coast regions of South and North China, including the capital Beijing, with the SSR brightening induced by aerosol reduction of 7.5 W m−2 decade−1, 5.2 W m−2 decade−1, and 5.9 W m−2 decade−1, respectively. Seasonally, the SSR recovery in China mainly occurs in the warm seasons of spring and summer, with the magnitudes induced by the aerosol radiative effects of 5.9 W m−2 decade−1 and 4.7 W m−2 decade−1, respectively.
Aerosol Optical Radiation Properties in Kunming (the Low–Latitude Plateau of China) and Their Relationship to the Monsoon Circulation Index
Authors: Wang Haoyue , Zhang Chunyang , Yu Ke , Tang Xiao , Che Huizheng , Bian Jianchun , Wang Shanshan , Zhou Bin , Liu Rui , Deng Xiaoguang , Ma Xunhao , Yang Zhe , Cao Xiaohang , Lu Yuehua , Wang Yuzhu , Wang Weiguo
Published: December 2019

Based on the Langley method and the EuroSkyRad (ESR) pack retrieval scheme, we carried out the retrieval of the aerosol properties for the CE–318 sunphotometer observation data from March 2012 to February 2014 in Kunming, China, and we explored the possible mechanisms of the seasonal variations. The seasonal variation of the aerosol optical depth (AOD) was unimodal and reached a maximum in summer. The retrieval analysis of the Angstrom exponent (α) showed the aerosol types were continental, biomass burning (BB), and urban/industrial (UI); the content of the desert dust (DD) was low, and it may have contained a sea–salt (SS) aerosol due to the influence of the summer monsoon. All the aerosol particle spectra in different seasons showed a bimodal structure. The maximum and submaximal values were located near 0.2 μm and 4 μm, respectively, and the concentration of the aerosol volume was the highest in summer. In summer, aerosol particles have a strong scattering power but a weak absorption power; this pattern is the opposite in winter. The synergistic effect of the East Asian monsoon and the South Asian monsoon seasonal oscillations can have an important impact on the variation of the aerosol properties. The oscillation variation characteristic of the total vertical columnar water vapor (CWV) and the monsoon index was completely consistent. The aerosol types and sources in the Yunnan–Kweichow Plateau and the optical radiation properties were closely related to the monsoon circulation activities during different seasons and were different from other regions in China.
Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle
Authors: Zhang Xueyan
Published: December 2019

Carbon sink trading is an important aspect of carbon trading in China, and can have important significance in offsetting carbon emissions and improving ecological compensation. The use of unmanned aerial vehicles (UAVs) offers new opportunities for shrub carbon sink and accounts as a substitute for time-consuming and expensive plot investigations to estimate the carbon sink by using the aboveground carbon stock monitored by UAV. However, the UAV-based estimation of the aboveground carbon stock of densely planted shrubs still faces certain challenges. The specific objectives of this research are as follows: (1) to test the statistical relationship between the aboveground carbon stock and volume of a densely planted shrub belt, and (2) to develop a model to estimate aboveground carbon stock by monitoring the volume of the densely planted shrub belt using a UAV. The study showed that (i) the aboveground carbon stock would increase with the increase in the volume of the shrub belt, (ii) an estimation model of the aboveground carbon stock of the densely planted shrub belt was developed ( R 2 = 0.89 ,   P < 0.01 ), and (iii) the validation assessment to estimate aboveground carbon stock by using the UAV-based estimation model produced a coefficient of determination of R2 = 0.74 and an overall root mean square error of 18.79 kg CO2e. Good prediction ability of the model was determined using leave-one-out cross-validation (LOOCV). This output information is valuable for the design of operations in the framework of precise carbon-sink accounting of shrubs. In addition, a method using an UAV was developed and validated for the quick estimation of aboveground carbon stock for densely planted shrubs, thereby providing a potential alternative to time-consuming and expensive plot investigations of aboveground carbon-stock accounting, which is necessary for shrub projects in the carbon trading market in China.
Object Identification and Safe Route Recommendation Based on Human Flow for the Visually Impaired
Authors: Kajiwara Yusuke , Kimura Haruhiko
Published: December 2019

It is difficult for visually impaired people to move indoors and outdoors. In 2018, world health organization (WHO) reported that there were about 253 million people around the world who were moderately visually impaired in distance vision. A navigation system that combines positioning and obstacle detection has been actively researched and developed. However, when these obstacle detection methods are used in high-traffic passages, since many pedestrians cause an occlusion problem that obstructs the shape and color of obstacles, these obstacle detection methods significantly decrease in accuracy. To solve this problem, we developed an application “Follow me!”. The application recommends a safe route by machine learning the gait and walking route of many pedestrians obtained from the monocular camera images of a smartphone. As a result of the experiment, pedestrians walking in the same direction as visually impaired people, oncoming pedestrians, and steps were identified with an average accuracy of 0.92 based on the gait and walking route of pedestrians acquired from monocular camera images. Furthermore, the results of the recommended safe route based on the identification results showed that the visually impaired people were guided to a safe route with 100% accuracy. In addition, visually impaired people avoided obstacles that had to be detoured during construction and signage by walking along the recommended route.
Towards the Exploitation of Physical Compliance in Segmented and Electrically Actuated Robotic Legs: A Review Focused on Elastic Mechanisms
Authors: Chen Jie , Liang Zhongchao , Zhu Yanhe , Liu Chong , Zhang Lei , Hao Lina , Zhao Jie
Published: December 2019

Physical compliance has been increasingly used in robotic legs, due to its advantages in terms of the mechanical regulation of leg mechanics and energetics and the passive response to abrupt external disturbances during locomotion. This article presents a review of the exploitation of physical compliance in robotic legs. Particular attention has been paid to the segmented, electrically actuated robotic legs, such that a comparable analysis can be provided. The utilization of physical compliance is divided into three main categories, depending on the setting locations and configurations, namely, (1) joint series compliance, (2) joint parallel compliance, and (3) leg distal compliance. With an overview of the representative work related to each category, the corresponding working principles and implementation processes of various physical compliances are explained. After that, we analyze in detail some of the structural characteristics and performance influences of the existing designs, including the realization method, compliance profile, damping design, and quantitative changes in terms of mechanics and energetics. In parallel, the design challenges and possible future works associated with physical compliance in robotic legs are also identified and proposed. This article is expected to provide useful paradigmatic implementations and design guidance for physical compliance for researchers in the construction of novel physically compliant robotic legs.
Assessment of DSMs Using Backpack-Mounted Systems and Drone Techniques to Characterise Ancient Underground Cellars in the Duero Basin (Spain)
Authors: López-Cuervo Medina Serafín , Pérez-Martín Enrique , Herrero Tejedor Tomás R. , Prieto Juan F. , Velasco Jesús , Conejo Martín Miguel Ángel , Ezquerra-Canalejo Alejandra , Aguirre de Mata Julián
Published: December 2019

In this study, a backpack-mounted 3D mobile scanning system and a fixed-wing drone (UAV) have been used to register terrain data on the same space. The study area is part of the ancient underground cellars in the Duero Basin. The aim of this work is to characterise the state of the roofs of these wine cellars by obtaining digital surface models (DSM) using the previously mentioned systems to detect any possible cases of collapse, using four geomatic products obtained with these systems. The results obtained from the process offer sufficient quality to generate valid DSMs in the study area or in a similar area. One limitation of the DSMs generated by backpack MMS is that the outcome depends on the distance of the points to the axis of the track and on the irregularities in the terrain. Specific parameters have been studied, such as the measuring distance from the scanning point in the laser scanner, the angle of incidence with regard to the ground, the surface vegetation, and any irregularities in the terrain. The registration speed and the high definition of the terrain offered by these systems produce a model that can be used to select the correct conservation priorities for this unique space.
Cu(I) Coordination Complex Precursor for Randomized CuOx Microarray Loaded on Carbon Nanofiber with Excellent Electrocatalytic Performance for Electrochemical Glucose Detection
Authors: Motoc Sorina , Cretu Carmen , Costisor Otilia , Baciu Anamaria , Manea Florica , Szerb Elisabeta I.
Published: December 2019

A homoleptic ionic Cu(I) coordination complex that was based on 2,2′-biquinoline ligand functionalized with long alkyl chains (Cu(I)–C18) was used as a precursor to modify a carbon nanofiber paste electrode (Cu–C18/CNF). Randomized copper oxide microelectrode arrays dispersed within carbon nanofiber paste (CuOx/CNF) were obtained by electrochemical treatment of Cu–C18/CNF while using cyclic voltammetry (CV). The CuOx/CNF exhibited high electrocatalytic activity towards glucose oxidation at +0.6 V and +1.2 V vs. Ag/AgCl. Infrared Spectroscopy (FTIR) and scanning electron microscopy (SEM) characterized the electrodes composition. Cyclic voltammetry (CV), square wave-voltammetry (SWV), and multiple-pulsed amperometry (MPA) techniques provided optimized conditions for glucose oxidation and detection. A preconcentration step that involved 10 minutes accumulation at open circuit potential before SWV running led to the lowest limit of detection and the highest sensitivity for glucose detection (5419.77 µA·mM−1·cm−2 at + 1.1 V vs. Ag/AgCl) vs. Cu-based electrodes reported to date in literature.
Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research
Authors: Heun John T. , Attalah Said , French Andrew N. , Lehner Kevin R. , McKay John K. , Mullen Jack L. , Ottman Michael J. , Andrade-Sanchez Pedro
Published: December 2019

Using sensors and electronic systems for characterization of plant traits provides valuable digital inputs to support complex analytical modeling in genetics research. In field applications, frequent sensor deployment enables the study of the dynamics of these traits and their interaction with the environment. This study focused on implementing lidar (light detection and ranging) technology to generate 2D displacement data at high spatial resolution and extract plant architectural parameters, namely canopy height and cover, in a diverse population of 252 maize (Zea mays L.) genotypes. A prime objective was to develop the mechanical and electrical subcomponents for field deployment from a ground vehicle. Data reduction approaches were implemented for efficient same-day post-processing to generate by-plot statistics. The lidar system was successfully deployed six times in a span of 42 days. Lidar data accuracy was validated through independent measurements in a subset of 75 experimental units. Manual and lidar-derived canopy height measurements were compared resulting in root mean square error (RMSE) = 0.068 m and r2 = 0.81. Subsequent genome-wide association study (GWAS) analyses for quantitative trait locus (QTL) identification and comparisons of genetic correlations and heritabilities for manual and lidar-based traits showed statistically significant associations. Low-cost, field-ready lidar of computational simplicity make possible timely phenotyping of diverse populations in multiple environments.
Development of a Sensor to Measure Physician Consultation Times
Authors: Gabl Roman , Stummer Florian
Published: December 2019

The duration of patient–physician contact is an important factor for the optimisation of treatment processes in healthcare systems. Available methods can be labour-intensive and the quality is, in many cases, poor. A part of this research project is to develop a sensor system, which allows the detection of people passing through a door, including the direction. For this purpose, two time of flight sensors are combined with a door sensor and a motion detection sensor (for redundancy) on one single side of the door frame. The period between two single measurements could be reduced to 50 ms, which allows the measurement of walking speed up to 2 ms − 1 . The accuracy of the time stamp for each event is less than one second and ensures a precise documentation of the consultation time. This paper presents the development of the sensor system, the miniaturisation of the installation and first measurement results, as well as the measurement’s concept of quality analysis, including multiple door applications. In future steps, the sensor system will be deployed at different medical practices to determine the exact duration of the patient–physician interaction over a longer time period.
Anomaly Detections for Manufacturing Systems Based on Sensor Data—Insights into Two Challenging Real-World Production Settings
Authors: Kammerer Klaus , Hoppenstedt Burkhard , Pryss Rüdiger , Stökler Steffen , Allgaier Johannes , Reichert Manfred
Published: December 2019

To build, run, and maintain reliable manufacturing machines, the condition of their components has to be continuously monitored. When following a fine-grained monitoring of these machines, challenges emerge pertaining to the (1) feeding procedure of large amounts of sensor data to downstream processing components and the (2) meaningful analysis of the produced data. Regarding the latter aspect, manifold purposes are addressed by practitioners and researchers. Two analyses of real-world datasets that were generated in production settings are discussed in this paper. More specifically, the analyses had the goals (1) to detect sensor data anomalies for further analyses of a pharma packaging scenario and (2) to predict unfavorable temperature values of a 3D printing machine environment. Based on the results of the analyses, it will be shown that a proper management of machines and their components in industrial manufacturing environments can be efficiently supported by the detection of anomalies. The latter shall help to support the technical evangelists of the production companies more properly.
High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
Authors: Su Jingxin , Miyazaki Ryuji , Tamaki Toru , Kaneda Kazufumi
Published: December 2019

As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model.
Frying Oil Evaluation by a Portable Sensor Based on Dielectric Constant Measurement
Authors: Liu Mei , Qin Xiangzheng , Chen Zhanghao , Tang Lei , Borom Brandon , Cao Ning , Barnes Daniel , Cheng Kai , Chen Jinbo , Wang Tao , Rao Jinjun
Published: December 2019

A portable capacitive sensor was designed to assess frying oil degradation by measuring the changes in electrical capacitance. An interdigital electrode (IDE) was designed to be implemented as the testing probe (as IDEs are resistive to parasitic capacitance), together with an adjacent capacitive chip Pcap01 and a further microprocessor STM32, which were used as the data-processing elements. Experimental results demonstrated that viscosity could be a useful frying oil quality indicator, and also proved a preliminary correlation between IDE capacitance and oils’ total polar materials. This implies that IDE capacitance could be a suitable metric for conveniently assessing frying oil degradation. The designed capacitance sensor is light in weight, cost effective, and has excellent potential for simple, inexpensive, on-the-spot testing of the current quality of frying oil.
Critical Evaluation of Laboratory Potentiometric Electronic Tongues for Pharmaceutical Analysis—An Overview
Authors: Łabańska Małgorzata , Ciosek-Skibińska Patrycja , Wróblewski Wojciech
Published: December 2019

Electronic tongue systems equipped with cross-sensitive potentiometric sensors have been applied to pharmaceutical analysis, due to the possibility of various applications and developing new formulations. Many studies already proved the complementarity between the electronic tongue and classical analysis such as dissolution tests indicated by Pharmacopeias. However, as a new approach to study pharmaceuticals, electronic tongues lack strict testing protocols and specification limits; therefore, their results can be improperly interpreted and inconsistent with the reference studies. Therefore, all aspects of the development, measurement conditions, data analysis, and interpretation of electronic tongue results were discussed in this overview. The critical evaluation of the effectiveness and reliability of constructed devices may be helpful for a better understanding of electronic tongue systems development and for providing strict testing protocols.
An Accurate Calibration Means for the Phase Measuring Deflectometry System
Authors: Han Hao , Wu Shiqian , Song Zhan
Published: December 2019

Calibration is a critical step for the phase measuring deflectometry system. Existing calibration methods are mainly optimizing the calibration parameters with respect to the 2D re-projection error criterion. However, such a procedure cannot reduce metric errors in the practical application. Therefore, an accurate and practical calibration method is proposed. In which, conventional calibration means is first applied for the primary calibration. Then, a precise square planar mirror is used for the optimization of system calibration parameters. All the intrinsic and extrinsic parameters are considered as a global multi-objective optimization problem. Three metric error criteria are introduced to evaluate the 3D reconstruction accuracy of the reference mirror. Compared with classical calibration means, which apply the parameter optimization in 2D image space to minimize the re-projection errors, the proposed optimization approach is executed in 3D space directly. An experiment and comparison are conducted to verify that the proposed optimal calibration approach can effectively reduce the system deviation and to improve the system measurement accuracy.
Hough Transform and Clustering for a 3-D Building Reconstruction with Tomographic SAR Point Clouds
Authors: Liu Hui , Pang Lei , Li Fang , Guo Ziye
Published: December 2019

Tomographic synthetic aperture radar (TomoSAR) produces 3-D point clouds with unavoidable noise or false targets that seriously deteriorate the quality of 3-D images and the building reconstruction over urban areas. In this paper, a Hough transform was adopted to detect the outline of a building; however, on one hand, the obtained outline of a building with Hough transform is broken, and on the other hand, some of these broken lines belong to the same segment of a building outline, but the parameters of these lines are slightly different. These problems will lead to that segment of a building outline being represented by multiple different parameters in the Hough transform. Therefore, an unsupervised clustering method was employed for clustering these line parameters. The lines gathered in the same cluster were considered to correspond to a same segment of a building outline. In this way, different line parameters corresponding to a segment of a building outline were integrated into one and then the continuous outline of the building in cloud points was obtained. Steps of the proposed data processing method were as follows. First, the Hough transform was made use of to detect the lines on the tomography plane in TomoSAR point clouds. These detected lines lay on the outline of the building, but they were broken due to the density variation of point clouds. Second, the lines detected using the Hough transform were grouped as a date set for training the building outline. Unsupervised clustering was utilized to classify the lines in several clusters. The cluster number was automatically determined via the unsupervised clustering algorithm, which meant the number of straight segments of the building edge was obtained. The lines in each cluster were considered to belong to the same straight segment of the building outline. Then, within each cluster, which represents a part or a segment of the building edge, a repaired straight line was constructed. Third, between each two clusters or each two segments of the building outline, the joint point was estimated by extending the two segments. Therefore, the building outline was obtained as completely as possible. Finally, taking the estimated building outline as the clustering center, supervised learning algorithm was used to classify the building cloud point and the noise (or false targets), then the building cloud point was refined. Then, our refined and unrefined data were fed into the neural network for building the 3-D construction. The comparison results show the correctness and the effectiveness of our improved method.
Multi-Electrode Array with a Planar Surface for Cell Patterning by Microprinting
Authors: Slavík Jan , Skopalík Josef , Provazník Ivo , Hubálek Jaromír
Published: December 2019

Multielectrode arrays (MEAs) are devices for non-invasive electrophysiological measurements of cell populations. This paper describes a novel fabrication method of MEAs with a fully planar surface. The surface of the insulation layer and the surface of the electrodes were on one plane; we named this device the planar MEA (pMEA). The main advantage of the pMEA is that it allows uniform contact between the pMEA surface and a substrate for positioning of microfluidic channels or microprinting of a cell adhesive layer. The fabrication of the pMEA is based on a low adhesive Au sacrificial peel-off layer. In divergence from conventional MEAs with recessed electrodes, the electrodes of the pMEA lead across the sloped edge of the insulation layer. To make this, the profile of the edge of the insulation layer was measured and the impedance of the planar electrodes was characterized. The impedance of the pMEA was comparable with the impedance of conventional MEA electrodes. The pMEA was tested for patterning HL-1 cells with a combination of imprinting fibronectin and coating by antifouling poly (l-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG). The HL-1 cells remained patterned even at full confluency and presented spontaneous and synchronous beating activity.