bluuebunny/crossref_metadata_2025 huggingface dataset:
Plant Ribonuclease J: An Essential Player in Maintaining Chloroplast RNA Quality Control for Gene Expression
Authors: Hotto Amber M. , Stern David B. , Schuster Gadi
Published: March 2020

RNA quality control is an indispensable but poorly understood process that enables organisms to distinguish functional RNAs from nonfunctional or inhibitory ones. In chloroplasts, whose gene expression activities are required for photosynthesis, retrograde signaling, and plant development, RNA quality control is of paramount importance, as transcription is relatively unregulated. The functional RNA population is distilled from this initial transcriptome by a combination of RNA-binding proteins and ribonucleases. One of the key enzymes is RNase J, a 5′→3′ exoribonuclease and an endoribonuclease that has been shown to trim 5′ RNA termini and eliminate deleterious antisense RNA. In the absence of RNase J, embryo development cannot be completed. Land plant RNase J contains a highly conserved C-terminal domain that is found in GT-1 DNA-binding transcription factors and is not present in its bacterial, archaeal, and algal counterparts. The GT-1 domain may confer specificity through DNA and/or RNA binding and/or protein–protein interactions and thus be an element in the mechanisms that identify target transcripts among diverse RNA populations. Further understanding of chloroplast RNA quality control relies on discovering how RNase J is regulated and how its specificity is imparted.
Experimental Study on the Effect of ASP Flooding on Improving Oil Recovery in Low Permeability Reservoirs Based on a Partial Quality Tool
Authors: Huang Bin , Hu Xinyu , Fu Cheng , Zhou Quan
Published: March 2020

In order to solve the problem of the poor oil displacement effect of high molecular weight alkali/surfactant/polymer (ASP) solution in low permeability reservoirs, Daqing Oilfield uses a partial quality tool to improve the oil displacement effect in low permeability reservoirs. In the formation, the partial quality tool degrades the polymer through active shearing action, reducing the molecular weight of the polymer, to improve the matching degree to the low permeability oil layer and the oil recovery. In order to study the ability of the partial quality tool to improve the oil displacement effect, the matching degree of high molecular weight ASP solution to low permeability cores is studied, and the ability of quality control tools to change the molecular weight is studied. Then, experimental research on the pressure and oil displacement effect of high molecular weight ASP solution before and after the actions of the partial quality tool is carried out. The results show that ASP solutions with molecular weights of 1900 × 104 and 2500 × 104 have a poor oil displacement effect in low permeability reservoirs. After the action of the partial quality tool, the injection pressure is reduced by 5.22 MPa, and the oil recovery is increased by 7.79%. The injection pressure of the ASP solution after shearing by the partial quality tool is lower than that of the ASP solution with the same molecular weight and concentration without shearing, but the oil recovery is lower. On the whole, the use of the partial quality tool can obviously improve the oil displacement effect in low permeability reservoirs.
Optimization of Sintering Parameters of 316L Stainless Steel for In-Situ Nitrogen Absorption and Surface Nitriding Using Response Surface Methodology
Authors: Ali Sadaqat , Abdul Rani Ahmad Majdi , Ahmad Mufti Riaz , Ahmed Syed Waqar , Baig Zeeshan , Hastuty Sri , Razak Muhammad Al’Hapis Abdul , Abdu Aliyu Abdul Azeez
Published: March 2020

This research investigates the simultaneous sintering and surface nitriding of 316L stainless steel alloy using powder metallurgy method. The influence of sintering temperature and dwell time are investigated for maximum nitrogen absorption, densification and increased microhardness using response surface methodology (RSM). In this study, 316L stainless steel powder was compacted at 800 MPa and sintered at two different temperatures of 1150 and 1200 °C with varying dwell times of 1, 3, 5 and 8 h in nitrogen atmosphere. The sintered compacts were then characterized for their microstructure, densification, microhardness and nitrogen absorption. The results revealed that increased dwell time assisted nitrogen to diffuse into stainless steel matrix along with the creation of nitride layer onto the sample surface. The microhardness and density also increased with increasing dwell time. A densification of 7.575 g/cm3 and microhardness of 235 HV were obtained for the samples sintered at 1200 °C temperature with 8 h dwell time. The simultaneous sintering and surface nitriding technique developed in this research work can help in improving corrosion resistance of this material and controlling leaching of metal ions for its potential use in biomedical applications.
Phenolic Compounds Extraction of Arbutus unedo L.: Process Intensification by Microwave Pretreatment
Authors: Alexandre Agostinho M. R. C. , Matias Ana A. , Bronze Maria Rosário , Cocero Maria Jose , Mato Rafael
Published: March 2020

Arbutus unedo L., commonly known as the strawberry-tree fruit, is an endemic species of the Mediterranean flora. Microwave extraction technology has been considered as a fast and “green” method for the production of extracts rich in bioactive compounds, although the energy consumption is high. To overcome this bottleneck, microwave was used as a pretreatment procedure in short time periods. This technique promotes the burst of intracellular vacuoles leading to an increase in the lixiviation of phenolic compounds. Different approaches were tested, namely a solvent-free irradiation (SFI), a solvent-assisted irradiation (SAI) and a pressurized solvent-assisted irradiation (PSAI). After irradiation, a solid–liquid extraction procedure was performed using a mixture of water and ethanol. A kinetic evaluation of the total phenolic content (TPC) was performed using the Folin–Ciocalteu method. For the total anthocyanin content, a UV-spectrophotometric method was used. HPLC-UV and LC-MS were used for TPC and identification of present compounds. Microwave irradiation led to an increase in TPC of extracts after SAI (52%) and PSAI (66%) along with a reduction in time of extraction from 30 min to less than 2 min. The anthocyanin content also increased by 66% for the SAI and PSAI extractions.
Investigation of the Superposition Effect of Oil Vapor Leakage and Diffusion from External Floating-Roof Tanks Using CFD Numerical Simulations and Wind-Tunnel Experiments
Authors: Fang Jie , Huang Weiqiu , Huang Fengyu , Fu Lipei , Zhang Gao
Published: March 2020

Based on computational fluid dynamics (CFD) and Realizable k-ε turbulence model, we established a numerical simulation method for wind and vapor-concentration fields of various external floating-roof tanks (EFRTs) (single, two, and four) and verified its feasibility using wind-tunnel experiments. Subsequently, we analysed superposition effects of wind speed and concentration fields for different types of EFRTs. The results show that high concentrations of vapor are found near the rim gap of the floating deck and above the floating deck surface. At different ambient wind speeds, interference between tanks is different. When the ambient wind speed is greater than 2 m/s, vapor concentration in leeward area of the rear tank is greater than that between two tanks, which makes it easy to reach explosion limit. It is suggested that more monitoring should be conducted near the bottom area of the rear tank and upper area on the left of the floating deck. Superposition in a downwind direction from the EFRTs becomes more obvious with an increase in the number of EFRTs; vapor superposition occurs behind two leeward tanks after leakage from four large EFRTs. Considering safety, environmental protection, and personnel health, appropriate measures should be taken at these positions for timely monitoring, and control.
Antidiabetic and Antilipidemic Activity of Root Extracts of Salacia oblonga against Streptozotocin-Induced Diabetes in Wistar Rats
Authors: Deepak Kakara Gift Kumar , Challa Surekha , Suhasin Ganta , Nagesewara Rao Reddy Neelapu , Elansary Hosam O. , El-Ansary Diaa O.
Published: March 2020

Salacia oblonga is used to treat diabetes, hypocholesteremia, gonorrhea, rheumatism, asthma, inflammation, oxidative stress, etc. In the present study, the antidiabetic activity of S. oblonga methanolic root extracts collected from three geographical locations, viz., Eleshwaram (Andhra Pradesh), Thoothukudi (Tamil Nadu), and Karwar (Karnataka), was studied in vitro. Among the three extracts, S. oblonga root extracts from Eleshwaram showed maximum α-glucosidase and α-amylase inhibitory activities, indicating better antidiabetic activity. Acute toxicity studies of S. oblonga carried out in Albino Wistar rats showed no toxicity. Further, in vivo studies showed antidiabetic and antilipidemic activities in Albino Wistar rats with induced type II diabetes mellitus. Type II diabetes mellitus was induced in the experimental rats by intraperitoneal injection of nicotinamide and streptozotocin. The rats were orally fed different doses (ranging from 0 to 400 mg/kg body weight) of S. oblonga root extracts from Eleshwaram for 14 days. Blood glucose, lipid, bilirubin, and creatinine levels were analyzed on day 0, 7, and 14. The S. oblonga root extract from Eleshwaram decreased the glucose levels in a dose-dependent manner as well as the lipid, creatinine, and bilirubin levels in diabetic rats. Thus, the present study demonstrates antidiabetic and antilipidemic properties of S. oblonga root extracts.
Monitoring of Fruit and Vegetable Waste Composting Process: Relationship between Microorganisms and Physico-Chemical Parameters
Authors: Ghinea Cristina , Leahu Ana
Published: March 2020

The aim of this study was to investigate and evaluate the composting potential of fruit and vegetable waste with sawdust in different combinations and to establish the relationship between microorganisms and physico-chemical parameters. Three samples were made with the C/N ratios of 50 (sample 1), 45 (sample 2), and 30 (sample 3) by adding fruit waste (apple, banana, orange, and kiwi peels) and vegetable waste (cabbage leaves, potato and carrot peels). The total amount of fruit and vegetable waste was approximately 2 kg in each sample to which different quantities of sawdust were added (1.23, 0.14, and 0.203 kg) in order to obtain the C/N ratios proposed and to limit the odor. Composting process was monitored over 70 days, while physico-chemical and microbiological analyses were performed. Results showed that in the first week pH is acidic and electrical conductivity values are high for all three samples, and then the pH values increase during the composting process, while electrical conductivity values decrease. The nitrogen content is low in all samples and will decrease during the first five weeks of the composting process, then begin to increase slightly. Cr, Cu, Ni, and Zn values in the all three compost samples are below threshold values. During the composing process the microbial communities are constantly changing. The compost was successfully obtained and meets the requirement standards for agricultural use. It can be concluded that there is statistically significant association between the microorganisms and physico-chemical indicators.
Hydrothermal Polymerization Catalytic Process Effect of Various Organic Wastes on Reaction Time, Yield, and Temperature
Authors: Mackintosh Alexis F. , Shin Taesung , Yang Hyunik , Choe Kangil
Published: March 2020

The purpose of this study is to optimize the processing conditions (temperature, pressure, process time, yield rate) for the conversion of biomass to a high-energy density biofuel. The hydrothermal polymerization (HTP) catalytic process has been developed for production of biofuel via hydrothermal processing using an acid-based catalyst. This study has shown that the HTP catalytic process for a reference feedstock lowered the temperature by 10 to 40 °C, reduced the pressure requirement by 1 to 2 MPa, increased the rate of yield by 22%, and shortened the total processing time by up to 3 h when compared to the conventional hydrothermal carbonization (HTC) process. FTIR spectrum analysis of the HTP catalytic biofuel has shown that lignin in the biomass is preserved, while the pure HTC process destroyed the lignin in the biomass. GC/MS analysis of the process liquid determined the changes of the intermediate soluble components as a function of time. By measuring the 2,5-hydroxymethyl furfuralde concentration in solution, an endpoint determination could be made. This study also determined the approximate analysis of the HTP biofuel from various organic wastes such as cotton, cow manure, wood waste, paper waste, sugarcane bagasse waste, and food waste.
Analysis of the Degradation Process of Alginate-Based Hydrogels in Artificial Urine for Use as a Bioresorbable Material in the Treatment of Urethral Injuries
Authors: Kurowiak Jagoda , Kaczmarek-Pawelska Agnieszka , Mackiewicz Agnieszka G. , Bedzinski Romuald
Published: March 2020

Hydrogels from natural polymers such as sodium alginate have great potential in regenerative medicine because of their biocompatibility, biodegradability, mechanical properties, bioresorption ability, and relatively low cost. Sodium alginate, a polysaccharide derived from brown seaweed, is the most widely investigated and used biomaterial in biomedical applications. Alginate dressings are also useful as a delivery platform in order to provide a controlled release of therapeutic substances (e.g., pain-relieving, antibacterial, and anti-inflammatory agents). In our work, we aimed to analyze process of degradation of alginate hydrogels. We also describe an original hybrid crosslinking process by using not one, as usual, but a mixture of two crosslinking agents (calcium chloride and barium chloride). We proved that different crosslinking agents allow producing hydrogels with a spectrum of mechanical properties, similar to the urethra tissue. Hydrogels were formed using a dip-coating technique, and then examined by mechanical testing, FTIR (Fourier-Transform Infrared Spectroscopy), and resorption on artificial urine. Obtained hydrogels have a different degradation rate in artificial urine, and they can be used as a material for healing of urethra injuries, especially urethra strictures, which significantly affect the quality of life of patients.
Synthesis, Electrical Properties and Na+ Migration Pathways of Na2CuP1.5As0.5O7
Authors: ALQarni Ohud S. A. , Marzouki Riadh , Ben Smida Youssef , Alghamdi Majed M. , Avdeev Maxim , Belhadj Tahar Radhouane , Zid Mohamed Faouzi
Published: March 2020

A new member of sodium metal diphosphate-diarsenate, Na2CuP1.5As0.5O7, was synthesized as polycrystalline powder by a solid-state route. X-ray diffraction followed by Rietveld refinement show that the studied material, isostructural with β-Na2CuP2O7, crystallizes in the monoclinic system of the C2/c space group with the unit cell parameters a = 14.798(2) Å; b = 5.729(3) Å; c = 8.075(2) Å; β = 115.00(3)°. The structure of the studied material is formed by Cu2P4O15 groups connected via oxygen atoms that results in infinite chains, wavy saw-toothed along the [001] direction, with Na+ ions located in the inter-chain space. Thermal study using DSC analysis shows that the studied material is stable up to the melting point at 688 °C. The electrical investigation, using impedance spectroscopy in the 260–380 °C temperature range, shows that the Na2CuP1.5As0.5O7 compound is a fast-ion conductor with σ350 °C = 2.28 10−5 Scm−1 and Ea = 0.6 eV. Na+ ions pathways simulation using bond-valence site energy (BVSE) supports the fast three-dimensional mobility of the sodium cations in the inter-chain space.
Clinicians’ Publication Output: Self-Report Survey and Bibliometric Analysis
Authors: Ganasegeran Kurubaran , Ch’ng Alan Swee Hock , Jamil Mohd Fadzly Amar , Looi Irene
Published: March 2020

The uncertainties around disease management and control measures have not only motivated clinicians to keep abreast of new evidence available in the scholarly literature, but also to be rigorously engaged in medical research, dissemination and knowledge transfer. We aimed to explore clinicians’ publication output from the Malaysian perspective. A self-report survey and bibliometric analysis was conducted. A total of 201/234 clinicians participated in the survey. Items consisted of demographics, researching habits, publication output and level of importance of journal selection metrics. Descriptive, bivariate and multivariate analyses were conducted. Bibliometric analysis using retrieved records from PubMed between 2009 and October 2019 was conducted and co-occurrence and co-authorship analyses were executed. Self-reported publication output was 16.9%. In the logistic regression model, publication output was significantly higher amongst consultants or clinical specialists (aOR = 2.5, 95% CI 1.1–10.0, p = 0.023); clinicians previously involved in research (aOR = 4.2, 95% CI 1.5–11.4, p = 0.004); clinicians who ever used reference citation managers (aOR = 3.2, 95% CI 1.3–7.7, p = 0.010); and journal publication speed (aOR = 2.9, 95% CI 1.2–7.1, p = 0.019). Most clinicians published original research papers (76.4%) in international journals (78.2%). Published papers were mostly observational studies, genetic, stroke and health services or systems research. In conclusion, socio-demographics, researching habits and journal selection metrics were significantly associated with self-reported publication output. Real outputs from bibliometrics were predominantly focused across five clusters.
Cain and Abel: Re-Imagining the Immigration ‘Crisis’
Authors: Doukhan Abi
Published: March 2020

This essay proposes to interpret the significance of the so-called immigration crisis in the light of the ancient story of Cain and Abel. Much more than a mere conflict between brothers, this essay will argue that the story of Cain and Abel presents two archetypal ways of dwelling in the world: the sedentary and the nomadic. As such, the story sheds a shocking new light on our present crisis, deeply problematizing the sedentary and revealing in an amazing tour de force, the hidden potentialities of the nomadic and the powerful rejuvenating force that comes with its inclusion and welcoming in the sedentary landscape that characterizes our Western societies.
Water Recovery from Floor Cleaning Operations of Industrial or Public Areas: The Results of a Field Test
Authors: Ruffino Barbara
Published: March 2020

Water resources are increasingly under pressure because of human activities and economic development. Moreover, accelerated urbanization and the expansion of drinking water supply and sanitation systems contribute to this rising demand. The development of water reuse solutions is an urgent issue. This study presents a solution for the reuse of wastewaters generated from floor cleaning operations of industrial or public areas. A portable device containing a grid, for coarse filtration, and a 300-L reaction chamber to carry out the sequential processes of coagulation, flocculation and settling, was employed for a field test. In the field test the wastewater coming from the tank of a cleaning machine, used for floor cleaning in an industrial site, was treated and reused for the same purpose for a total of 110 times. The quality of the treated wastewater was monitored cycle after cycle and the results of the test demonstrated that the treated water was suitable to be reused for the same purpose, even after a large number of cycles, provided that a finishing treatment was eventually supplemented in order to reduce the residual concentration of organic substances. It was demonstrated that, under standard operating conditions, that is a wastewater with a total suspended solid (TSS) content of 800 mg/L, and on the grounds of the results found in the test, that is a TSS removal efficiency of 98% and a sludge total solid (TS) content of 6%, the whole volume of the cleaning machine tank was completely renewed with fresh water after 60 cycles. Eventually, the combination of treatment and reuse operations allowed to save approximately 18,000 L of fresh water over a series of 60 cleaning cycles. The proposed treatment allowed not only to save fresh water but even to reduce the cost of water usage by approximately 50%. In fact, thanks to this treatment, the cost of a single cubic meter of water decreased from approximately 6 €/m3, which included supply of fresh water and discharge to the public sewer, to approximately 3 €/m3.
On Computations in Renewal Risk Models—Analytical and Statistical Aspects
Authors: Strini Josef Anton , Thonhauser Stefan
Published: March 2020

We discuss aspects of numerical methods for the computation of Gerber-Shiu or discounted penalty-functions in renewal risk models. We take an analytical point of view and link this function to a partial-integro-differential equation and propose a numerical method for its solution. We show weak convergence of an approximating sequence of piecewise-deterministic Markov processes (PDMPs) for deriving the convergence of the procedures. We will use estimated PDMP characteristics in a subsequent step from simulated sample data and study its effect on the numerically computed Gerber-Shiu functions. It can be seen that the main source of instability stems from the hazard rate estimator. Interestingly, results obtained using MC methods are hardly affected by estimation.
Estimation of the Particulate Organic Carbon to Chlorophyll-a Ratio Using MODIS-Aqua in the East/Japan Sea, South Korea
Authors: Lee Dabin , Son SeungHyun , Joo HuiTae , Kim Kwanwoo , Kim Myung Joon , Jang Hyo Keun , Yun Mi Sun , Kang Chang-Keun , Lee Sang Heon
Published: March 2020

In recent years, the change of marine environment due to climate change and declining primary productivity have been big concerns in the East/Japan Sea, Korea. However, the main causes for the recent changes are still not revealed clearly. The particulate organic carbon (POC) to chlorophyll-a (chl-a) ratio (POC:chl-a) could be a useful indicator for ecological and physiological conditions of phytoplankton communities and thus help us to understand the recent reduction of primary productivity in the East/Japan Sea. To derive the POC in the East/Japan Sea from a satellite dataset, the new regional POC algorithm was empirically derived with in-situ measured POC concentrations. A strong positive linear relationship (R2 = 0.6579) was observed between the estimated and in-situ measured POC concentrations. Our new POC algorithm proved a better performance in the East/Japan Sea compared to the previous one for the global ocean. Based on the new algorithm, long-term POC:chl-a ratios were obtained in the entire East/Japan Sea from 2003 to 2018. The POC:chl-a showed a strong seasonal variability in the East/Japan Sea. The spring and fall blooms of phytoplankton mainly driven by the growth of large diatoms seem to be a major factor for the seasonal variability in the POC:chl-a. Our new regional POC algorithm modified for the East/Japan Sea could potentially contribute to long-term monitoring for the climate-associated ecosystem changes in the East/Japan Sea. Although the new regional POC algorithm shows a good correspondence with in-situ observed POC concentrations, the algorithm should be further improved with continuous field surveys.
Multi-Temporal Sentinel-1 Backscatter and Coherence for Rainforest Mapping
Authors: Pulella Andrea , Aragão Santos Rodrigo , Sica Francescopaolo , Posovszky Philipp , Rizzoli Paola
Published: March 2020

This paper reports recent advancements in the field of Synthetic Aperture Radar (SAR) for forest mapping by using interferometric short-time-series. In particular, we first present how the interferometric capabilities of the Sentinel-1 satellites constellation can be exploited for the monthly mapping of the Amazon rainforest. Indeed, the evolution in time of the interferometric coherence can be properly modeled as an exponential decay and the retrieved interferometric parameters can be used, together with the backscatter, as input features to the machine learning Random Forests classifier. Furthermore, we present an analysis on the benefits of the use of textural information, derived from Sentinel-1 backscatter, in order to enhance the classification accuracy. These textures are computed through the Sum And Difference Histograms methodology and the final classification accuracy, resulting by adding them to the aforementioned features, is a thematic map that exceeds an overall agreement of 85 % , when validated using the optical external reference Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC) map. The experiments presented in the final part of the paper are enriched with a further analysis and discussion on the selected scenes using updated multispectral Sentinel-2 acquisitions.
Retrospective InSAR Analysis of East London during the Construction of the Lee Tunnel
Authors: Scoular Jennifer , Ghail Richard , Mason Philippa , Lawrence James , Bellhouse Matthew , Holley Rachel , Morgan Tom
Published: March 2020

The Lee Tunnel was constructed as the first part of the Thames Tideway Improvement scheme, between 2010 and 2016. With tunnelling for the East section of the main Thames Tideway Tunnel, which joins the Lee Tunnel at Abbey Mills Pumping Station, beginning in early 2020, this paper investigates patterns of deformation in East London during construction of the Lee Tunnel. An unexpected geological feature, later identified as a drift filled hollow, was discovered during tunnelling. This study demonstrates that had eight years of ERS Persistent Scatterer Interferometry (PSI) data been analysed prior to tunnelling, the unusual pattern of displacement may have been recognised and further targeted borehole investigations taken place before the launch of the tunnel boring machine. Results also show how areas of different land use, including cemeteries and historic landfill, exhibit differences in settlement behaviour, compared with surrounding terraced housing. This research highlights the challenges in interpreting PSI results in an urban area with ongoing construction and the value of a long archive of data, which now spans almost three decades in London, that can be used to establish a baseline prior to construction.
A Sequential Autoencoder for Teleconnection Analysis
Authors: He Jiena , Eastman J. Ronald
Published: March 2020

Many aspects of the earth system are known to have preferred patterns of variability, variously known in the atmospheric sciences as modes or teleconnections. Approaches to discovering these patterns have included principal components analysis and empirical orthogonal teleconnection (EOT) analysis. The latter is very effective but is computationally intensive. Here, we present a sequential autoencoder for teleconnection analysis (SATA). Like EOT, it discovers teleconnections sequentially, with subsequent analyses being based on residual series. However, unlike EOT, SATA uses a basic linear autoencoder as the primary tool for analysis. An autoencoder is an unsupervised neural network that learns an efficient neural representation of input data. With SATA, the input is an image time series and the neural representation is a unidimensional time series. SATA then locates the 0.5% of locations with the strongest correlation with the neural representation and averages their temporal vectors to characterize the teleconnection. Evaluation of the procedure showed that it is several orders of magnitude faster than other approaches to EOT, produces teleconnection patterns that are more strongly correlated to well-known teleconnections, and is particularly effective in finding teleconnections with multiple centers of action (such as dipoles).
Pre-Event Deformation and Failure Mechanism Analysis of the Pusa Landslide, China with Multi-Sensor SAR Imagery
Authors: Chen Liquan , Zhao Chaoying , Kang Ya , Chen Hengyi , Yang Chengsheng , Li Bin , Liu Yuanyuan , Xing Aiguo
Published: March 2020

The Pusa landslide, in Guizhou, China, occurred on 28 August 2017, caused 26 deaths with 9 missing. However, few studies about the pre-event surface deformation are provided because of the complex landslide formation and failure mechanism. To retrieve the precursory signal of this landslide, we recovered pre-event deformation with multi-sensor synthetic aperture radar (SAR) imagery. First, we delineated the boundary and source area of the Pusa landslide based on the coherence and SAR intensity maps. Second, we detected the line-of-sight (LOS) deformation rate and time series before the Pusa landslide with ALOS/PALSAR-2 and Sentinel-1A/B SAR imagery data, where we found that the onset of the deformation is four months before landslide event. Finally, we conceptualized the failure mechanism of the Pusa landslide as the joint effects of rainfall and mining activity. This research provides new insights into the failure mechanism and early warning of rock avalanches.
Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns
Authors: Madokoro Hirokazu , Nakasho Kazuhisa , Shimoi Nobuhiro , Woo Hanwool , Sato Kazuhito
Published: March 2020

This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. The linear characteristic between loads and output was obtained from a load test to evaluate sensor output characteristics. Moreover, the output values change linearly concomitantly with speed to attain the sensor with the equivalent load. We obtained benchmark datasets of continuous and discontinuous behavior patterns from ten subjects. Recognition targets using our sensor prototype and their monitoring system comprise five behavior patterns: sleeping, longitudinal sitting, lateral sitting, terminal sitting, and leaving the bed. We compared machine learning algorithms of five types to recognize five behavior patterns. The experimentally obtained results revealed that the proposed sensor system improved recognition accuracy for both datasets. Moreover, we achieved improved recognition accuracy after integration of learning datasets as a general discriminator.
Comparison of Spectrum Estimation Methods for the Accurate Evaluation of Sea State Parameters
Authors: Rossi Giovanni Battista , Crenna Francesco , Piscopo Vincenzo , Scamardella Antonio
Published: March 2020

The monitoring of sea state conditions, either for weather forecasting or ship seakeeping analysis, requires the reliable assessment of the sea spectra encountered by the ship, either as a final result or intermediate step for the measurement of the relevant wave-motion parameters. In current analyses, different spectrum estimation methods, namely the Welch, Thomson and ARMA models, have been applied and compared based on a set of random wave signals, with different durations, representative of several sea state conditions. Subsequently, two sea spectrum reconstruction techniques were described and applied in order to detect the main sea state parameters, namely the significant wave height, the mean wave period and the spectrum peak enhancement factor. The performances of both spectral analysis and sea state reconstruction methods are discussed in order to provide some preliminary guidelines for practical application purposes. In this respect, based on current results, the Welch and Thomson methods seem to be the most promising techniques, combined with the nonlinear least-square reconstruction technique.
Partial Discharge Localization Using Time Reversal: Application to Power Transformers
Authors: Karami Hamidreza , Azadifar Mohammad , Mostajabi Amirhossein , Rubinstein Marcos , Karami Hossein , Gharehpetian Gevork B. , Rachidi Farhad
Published: March 2020

In this work, we present a novel technique to locate partial discharge (PD) sources based on the concept of time reversal. The localization of the PD sources is of interest for numerous applications, including the monitoring of power transformers, Gas Insulated Substations, electric motors, super capacitors, or any other device or system that can suffer from PDs. To the best of the authors’ knowledge, this is the first time that the concept of time reversal is applied to localize PD sources. Partial discharges emit both electromagnetic and acoustic waves. The proposed method can be used to localize PD sources using either electromagnetic or acoustic waves. As a proof of concept, we present only the results for the electromagnetic case. The proposed method consists of three general steps: (1) recording of the waves from the PD source(s) via proper sensor(s), (2) the time-reversal and back-propagation of the recorded signal(s) into the medium using numerical simulations, and (3) the localization of focal spots. We demonstrate that, unlike the conventional techniques based on the time difference of arrival, the proposed time reversal method can accurately localize PD sources using only one sensor. As a result, the proposed method is much more cost effective compared to existing techniques. The performance of the proposed method is tested considering practical scenarios in which none of the former developed methods can provide reasonable results. Moreover, the proposed method has the unique advantage of being able to locate multiple simultaneous PD sources and doing so with a single sensor. The efficiency of the method against the variation in the polarization of the PDs, their length, and against environmental noise is also investigated. Finally, the validity of the proposed procedure is tested against experimental observations.
Salivary Cortisol Determination on Smartphone-Based Differential Pulse Voltammetry System
Authors: Liu Jingjing , Xu Ning , Men Hong , Li Shuang , Lu Yanli , Low Sze Shin , Li Xin , Zhu Lihang , Cheng Chen , Xu Gang , Liu Qingjun
Published: March 2020

Cortisol is commonly used as a significant biomarker of psychological or physical stress. With the accelerated pace of life, non-invasive cortisol detection at the point of care (POC) is in high demand for personal health monitoring. In this paper, an ultrasensitive immunosensor using gold nanoparticles/molybdenum disulfide/gold nanoparticles (AuNPs/MoS2/AuNPs) as transducer was explored for non-invasive salivary cortisol monitoring at POC with the miniaturized differential pulse voltammetry (DPV) system based on a smartphone. Covalent binding of cortisol antibody (CORT-Ab) onto the AuNPs/MoS2/AuNPs transducer was achieved through the self-assembled monolayer of specially designed polyethylene glycol (PEG, SH-PEG-COOH). Non-specific binding was avoided by passivating the surface with ethanolamine. The miniaturized portable DPV system was utilized for human salivary cortisol detection. A series current response of different cortisol concentrations decreased and exhibited a linear range of 0.5–200 nM, the detection limit of 0.11 nM, and high sensitivity of 30 μA M−1 with a regression coefficient of 0.9947. Cortisol was also distinguished successfully from the other substances in saliva. The recovery ratio of spiked human salivary cortisol and the variation of salivary cortisol level during one day indicated the practicability of the immunosensor based on the portable system. The results demonstrated the excellent performance of the smartphone-based immunosensor system and its great potential application for non-invasive human salivary cortisol detection at POC.
Local Wireless Sensor Networks Positioning Reliability Under Sensor Failure
Authors: Díez-González Javier , Álvarez Rubén , Prieto-Fernández Natalia , Perez Hilde
Published: March 2020

Local Positioning Systems are collecting high research interest over the last few years. Its accurate application in high-demanded difficult scenarios has revealed its stability and robustness for autonomous navigation. In this paper, we develop a new sensor deployment methodology to guarantee the system availability in case of a sensor failure of a five-node Time Difference of Arrival (TDOA) localization method. We solve the ambiguity of two possible solutions in the four-sensor TDOA problem in each combination of four nodes of the system by maximizing the distance between the two possible solutions in every target possible location. In addition, we perform a Genetic Algorithm Optimization in order to find an optimized node location with a trade-off between the system behavior under failure and its normal operating condition by means of the Cramer Rao Lower Bound derivation in each possible target location. Results show that the optimization considering sensor failure enhances the average values of the convergence region size and the location accuracy by 31% and 22%, respectively, in case of some malfunction sensors regarding to the non-failure optimization, only suffering a reduction in accuracy of less than 5% under normal operating conditions.
Study on Weight Function Distribution of Hybrid Gas-Liquid Two-Phase Flow Electromagnetic Flowmeter
Authors: Jiang Yulin
Published: March 2020

The electromagnetic flowmeter is usually used for single-phase fluid parameter measurement. When the measured fluid is gas-liquid two-phase flow, the geometry of the sensor measurement space will change with the movement of the gas, which will cause measurement errors. The weight function distribution is an important parameter to analyze such measurement errors. The traditional method for calculating the weight function of gas-liquid two-phase flow involves complex dimensional space transformation, which is difficult to understand and apply. This paper presents a new method for calculating the weight function of the gas-liquid two-phase flow electromagnetic flowmeter. Firstly, based on the measurement principle of the electromagnetic flowmeter, a general model of weight function of the gas-liquid two-phase flow electromagnetic flowmeter is built. Secondly, the bubbles in the fluid are regarded as the “isolated” points in the flow field. According to the physical connection between the “field” of the measured fluid and the “source” of the sensor electrode, the Green’s function expression based on gas-liquid two-phase flow is established. Then, combined with the boundary conditions of the measurement space of the electromagnetic flowmeter, the Green’s function is analyzed. Finally, the general model of weight function is solved by using the expression of Green’s function, then the expression of the weight function of the electromagnetic flowmeter is obtained when the measured fluid is hybrid gas-liquid two-phase flow. The simulation results show that the proposed method can reasonably describe the influence of the gas in the measured fluid on the output signal of the sensor, and the experimental results also indirectly prove the rationality of this method.
Evaluation of the Use of Compressed Sensing in Data Harvesting for Vehicular Sensor Networks
Authors: Martinez Juan Antonio , Ruiz Pedro Miguel , Skarmeta Antonio F.
Published: March 2020

We propose a new harvesting approach for Vehicular Sensor Networks based on compressed sensing (CS) technology called Compressed Sensing-based Vehicular Data Harvesting (CS-VDH). This compression technology allows for the reduction of the information volume that nodes must send back to the fusion center and also an accurate recovery of the original data, even in absence of several original measurements. Our proposed method, thanks to a proper design of a delay function, orders the transmission of these measurements, being the nodes farther from the fusion center, the ones starting this transmission. This way, intermediate nodes are more likely to introduce their measurements in a packet traversing the network and to apply the CS technology. This way the contribution is twofold, adding different measurements to traversing packets, we reduce the total overload of the network, and also reducing the size of the packets thanks to the applied compression technology. We evaluate our solution by using ns-2 simulations in a realistic vehicular environment generated by SUMO, a well-known traffic simulator tool in the Vehicular Network domain. Our simulations show that CS-VDH outperforms Delay-Bounded Vehicular Data Gathering (DB-VDG), a well-known protocol for data gathering in vehicular sensor networks which considers a specific delay bound. We also evaluated the proper design of our delay function, as well as the accuracy in the reconstruction of the original data. Regarding this latter topic, our experiments proved that our proposed solution can recover sampled data with little error while still reducing the amount of information traveling through the vehicular network.
VersaVIS—An Open Versatile Multi-Camera Visual-Inertial Sensor Suite
Authors: Tschopp Florian , Riner Michael , Fehr Marius , Bernreiter Lukas , Furrer Fadri , Novkovic Tonci , Pfrunder Andreas , Cadena Cesar , Siegwart Roland , Nieto Juan
Published: March 2020

Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as an inertial measurement unit (IMU) can boost robustness and accuracy. However, for a tight sensor fusion, accurate time synchronization of the sensors is often crucial. Changing exposure times, internal sensor filtering, multiple clock sources and unpredictable delays from operation system scheduling and data transfer can make sensor synchronization challenging. In this paper, we present VersaVIS, an Open Versatile Multi-Camera Visual-Inertial Sensor Suite aimed to be an efficient research platform for easy deployment, integration and extension for many mobile robotic applications. VersaVIS provides a complete, open-source hardware, firmware and software bundle to perform time synchronization of multiple cameras with an IMU featuring exposure compensation, host clock translation and independent and stereo camera triggering. The sensor suite supports a wide range of cameras and IMUs to match the requirements of the application. The synchronization accuracy of the framework is evaluated on multiple experiments achieving timing accuracy of less than 1   ms . Furthermore, the applicability and versatility of the sensor suite is demonstrated in multiple applications including visual-inertial SLAM, multi-camera applications, multi-modal mapping, reconstruction and object based mapping.
Novel Magnetic Field Modulation Concept Using Multiferroic Heterostructure for Magnetoresistive Sensors
Authors: Pan Long , Pan Mengchun , Hu Jiafei , Hu Yueguo , Che Yulu , Yu Yang , Wang Nan , Qiu Weicheng , Li Peisen , Peng Junping , Jiang Jianzhong
Published: March 2020

The low frequency magnetic field detection ability of magnetoresistive (MR)sensor is seriously affected by 1/f noise. At present, the method to suppress the influence of low frequency noise is mainly to modulate the measured magnetic field by mechanical resonance. In this paper, a novel modulation concept employing a magnetoelectric coupling effect is proposed. A design method of modulation structure based on an equivalent magnetic circuit model (EMCM) and a single domain model of in-plane moment was established. An EMCM was established to examine the relationship between the permeability of flux modulation film (FMF) and modulation efficiency, which was further verified through a finite element simulation model (FESM). Then, the permeability modulated by the voltage of a ferroelectric/ferromagnetic (FE/FM) multiferroic heterostructure was theoretically studied. Combining these studies, the modulation structure and the material were further optimized, and a FeSiBPC/PMN-PT sample was prepared. Experimental results show that the actual magnetic susceptibility modulation ability of FeSiBPC/PMN-PT reached 150 times, and is in good agreement with the theoretical prediction. A theoretical modulation efficiency higher than 73% driven by a voltage of 10 V in FeSiBPC/PMN-PT can be obtained. These studies show a new concept for magnetoelectric coupling application, and establish a new method for magnetic field modulation with a multiferroic heterostructure.
Pressure-Sensitive Insoles for Real-Time Gait-Related Applications
Authors: Martini Elena , Fiumalbi Tommaso , Dell’Agnello Filippo , Ivanić Zoran , Munih Marko , Vitiello Nicola , Crea Simona
Published: March 2020

Wearable robotic devices require sensors and algorithms that can recognize the user state in real-time, in order to provide synergistic action with the body. For devices intended for locomotion-related applications, shoe-embedded sensors are a common and convenient choice, potentially advantageous for performing gait assessment in real-world environments. In this work, we present the development of a pair of pressure-sensitive insoles based on optoelectronic sensors for the real-time estimation of temporal gait parameters. The new design makes use of a simplified sensor configuration that preserves the time accuracy of gait event detection relative to previous prototypes. The system has been assessed relatively to a commercial force plate recording the vertical component of the ground reaction force (vGRF) and the coordinate of the center of pressure along the so-called progression or antero-posterior plane (CoPAP) in ten healthy participants during ground-level walking at two speeds. The insoles showed overall median absolute errors (MAE) of 0.06 (0.02) s and 0.04 (0.02) s for heel-strike and toe-off recognition, respectively. Moreover, they enabled reasonably accurate estimations of the stance phase duration (2.02 (2.03) % error) and CoPAP profiles (Pearson correlation coefficient with force platform ρCoP = 0.96 (0.02)), whereas the correlation with vGRF measured by the force plate was lower than that obtained with the previous prototype (ρvGRF = 0.47 (0.20)). These results confirm the suitability of the insoles for online sensing purposes such as timely gait phase estimation and discrete event recognition.
Image-Based Phenotyping of Flowering Intensity in Cool-Season Crops
Authors: Zhang Chongyuan , Craine Wilson , McGee Rebecca , Vandemark George , Davis James , Brown Jack , Hulbert Scot , Sankaran Sindhuja
Published: March 2020

The timing and duration of flowering are key agronomic traits that are often associated with the ability of a variety to escape abiotic stress such as heat and drought. Flowering information is valuable in both plant breeding and agricultural production management. Visual assessment, the standard protocol used for phenotyping flowering, is a low-throughput and subjective method. In this study, we evaluated multiple imaging sensors (RGB and multiple multispectral cameras), image resolution (proximal/remote sensing at 1.6 to 30 m above ground level/AGL), and image processing (standard and unsupervised learning) techniques in monitoring flowering intensity of four cool-season crops (canola, camelina, chickpea, and pea) to enhance the accuracy and efficiency in quantifying flowering traits. The features (flower area, percentage of flower area with respect to canopy area) extracted from proximal (1.6–2.2 m AGL) RGB and multispectral (with near infrared, green and blue band) image data were strongly correlated (r up to 0.89) with visual rating scores, especially in pea and canola. The features extracted from unmanned aerial vehicle integrated RGB image data (15–30 m AGL) could also accurately detect and quantify large flowers of winter canola (r up to 0.84), spring canola (r up to 0.72), and pea (r up to 0.72), but not camelina or chickpea flowers. When standard image processing using thresholds and unsupervised machine learning such as k-means clustering were utilized for flower detection and feature extraction, the results were comparable. In general, for applicability of imaging for flower detection, it is recommended that the image data resolution (i.e., ground sampling distance) is at least 2–3 times smaller than that of the flower size. Overall, this study demonstrates the feasibility of utilizing imaging for monitoring flowering intensity in multiple varieties of evaluated crops.