bluuebunny/crossref_metadata_2025 huggingface dataset:
Salt Consumption in Latvian Population: A Pilot Study
Authors: Lazda Ilva , Goldmanis Māris , Siksna Inese
Published: May 2018

Background and objective: High dietary sodium intake is associated with multiple health risks, and the average sodium intake in Latvia is higher than the World Health Organization has recommended. In Latvia, no study so far has combined self-reported dietary data on sodium and potassium intake with objective measurements in 24-h urine samples. This pilot study aimed to cross-validate both methods and to assess any possible factors interfering with the collection of samples and data in large, population-based future studies of sodium and potassium intake in Latvian adults. Materials and methods: A stratified random sample of healthy Latvian adults aged 19–64 (n = 30) was drawn. Dietary data of sodium and potassium was collected using one 24-h dietary recall and a two-day food diary. Sodium and potassium excretion was measured by one 24-h urinary collection. Results: Median intake of sodium and potassium based on dietary data was 2276.4 mg/day (interquartile range (IQR), 1683.3–3979.4) and 2172.0 mg/day (IQR, 1740.6–3506.5), respectively. Median intake of sodium and potassium based on urinary data was 3500.3 mg/day (IQR, 2191.0–5535.0) and 2965.4 mg/day (IQR, 2530.2–3749.9), respectively. Urinary data showed significantly higher results than dietary records (Wilcoxon signed rank test, p = 0.023). Only 13% of the subjects did not exceed the WHO-recommended limit of 2000 mg of sodium per day, and only 33% consumed at least the recommended allowance of 3510 mg of potassium per day. Median intake of salt was 8.8 g/day (IQR, 5.5–13.8) (according to urinary data). Conclusions: The findings from the present study showed considerable underestimation of dietary sodium and potassium intake based on self-reported dietary data. Urinary data revealed more accurate results, and showed that Latvian adults exceed the amount of salt recommended and consume less potassium than recommended. The pilot study also showed that the chosen methods are adequate for implementation in large, population-based studies to evaluate dietary intake of salt, sodium, and potassium in populations of Latvian adults.
Design and Synthesis of Lactams Derived from Mucochloric and Mucobromic Acids as Pseudomonas aeruginosa Quorum Sensing Inhibitors
Authors: Almohaywi Basmah , Taunk Aditi , Wenholz Daniel S. , Nizalapur Shashidhar , Biswas Nripendra N. , Ho Kitty K. K. , Rice Scott A. , Iskander George , Black David StC. , Griffith Renate , Kumar Naresh
Published: May 2018

Bacterial infections, particularly hospital-acquired infections caused by Pseudomonas aeruginosa, have become a global threat with a high mortality rate. Gram-negative bacteria including P. aeruginosa employ N-acyl homoserine lactones (AHLs) as chemical signals to regulate the expression of pathogenic phenotypes through a mechanism called quorum sensing (QS). Recently, strategies targeting bacterial behaviour or QS have received great attention due to their ability to disarm rather than kill pathogenic bacteria, which lowers the evolutionary burden on bacteria and the risk of resistance development. In the present study, we report the design and synthesis of N-alkyl- and N-aryl 3,4 dichloro- and 3,4-dibromopyrrole-2-one derivatives through the reductive amination of mucochloric and mucobromic acid with aliphatic and aromatic amines. The quorum sensing inhibition (QSI) activity of the synthesized compounds was determined against a P. aeruginosa MH602 reporter strain. The phenolic compounds exhibited the best activity with 80% and 75% QSI at 250 µM and were comparable in activity to the positive control compound Fu-30. Computational docking studies performed using the LasR receptor protein of P. aeruginosa suggested the importance of hydrogen bonding and hydrophobic interactions for QSI.
Identifying Cancer Specific Driver Modules Using a Network-Based Method
Authors: Li Feng , Gao Lin , Wang Peizhuo , Hu Yuxuan
Published: May 2018

Detecting driver modules is a key challenge for understanding the mechanisms of carcinogenesis at the pathway level. Identifying cancer specific driver modules is helpful for interpreting the different principles of different cancer types. However, most methods are proposed to identify driver modules in one cancer, but few methods are introduced to detect cancer specific driver modules. We propose a network-based method to detect cancer specific driver modules (CSDM) in a certain cancer type to other cancer types. We construct the specific network of a cancer by combining specific coverage and mutual exclusivity in all cancer types, to catch the specificity of the cancer at the pathway level. To illustrate the performance of the method, we apply CSDM on 12 TCGA cancer types. When we compare CSDM with SpeMDP and HotNet2 with regard to specific coverage and the enrichment of GO terms and KEGG pathways, CSDM is more accurate. We find that the specific driver modules of two different cancers have little overlap, which indicates that the driver modules detected by CSDM are specific. Finally, we also analyze three specific driver modules of BRCA, BLCA, and LAML intersecting with well-known pathways. The source code of CSDM is freely accessible at https://github.com/fengli28/CSDM.git.
In-Situ Preparation of Aramid-Multiwalled CNT Nano-Composites: Morphology, Thermal Mechanical and Electric Properties
Authors: Shiju Jessy , Al-Sagheer Fakhreia , Bumajdad Ali , Ahmad Zahoor
Published: May 2018

In this work in-situ polymerization technique has been used to chemically link the functionalized multiwalled carbon nanotubes (CNTs) with aramid matrix chains. Phenylene diamine monomers were reacted in the first stage with the carboxylic acid functionalized CNTs and then amidized in-situ using terephthaloyl chloride generating chemically bonded CNTs with the matrix. Various proportions of the CNTs were used to prepare the hybrid materials. The functionalization procedure was studied by Fourier transform infrared (FTIR) spectroscopy and composite morphology investigated by scanning electron microscopy (SEM). Thermal mechanical properties of these hybrids, together with those where pristine CNTs with similar loadings were used, are compared using tensile and dynamic mechanical analysis (DMA). The tensile strength and temperature involving α-relaxations on CNT loading increased with CNT loading in both systems, but much higher values, i.e., 267 MPa and 353 °C, respectively, were obtained in the chemically bonded system, which are related to the nature of the interface developed as observed in SE micrographs. The water absorption capacity of the films was significantly reduced from 6.2 to 1.45% in the presence pristine CNTs. The inclusion of pristine CNTs increased the electric conductivity of the aramid films with a minimum threshold value at the loading of 3.5 wt % of CNTs. Such mechanically strong and thermally stable aramid and easily processable composites can be suitable for various applications including high performance films, electromagnetic shielding and radar absorption.
Paper-Based Microfluidic Platforms for Understanding the Role of Exosomes in the Pathogenesis of Major Blindness-Threatening Diseases
Authors: Hsu Min-Yen , Chiu Chun-Chih , Wang Juan-Yuan , Huang Chin-Te , Huang Yu-Fang , Liou Jyh-Cheng , Chen Chihchen , Chen Hung-Chi , Cheng Chao-Min
Published: May 2018

Emerging roles of exosomes in the pathogenesis of major blindness-threatening diseases, such as age-related macular degeneration, glaucoma, and corneal dystrophy, were discovered by aqueous humor analysis. A new diagnostic method using cellulose-based devices and microfluidic chip techniques for the isolation of exosomes from aqueous humor is less cumbersome and saves time. This method will enable more investigations for aqueous humor analysis in the future.
Animal and Plant Protein Intake and Body Mass Index and Waist Circumference in a Korean Elderly Population
Authors: Park Ki-Byeong , Park Hyun Ah , Kang Jae-Heon , Kim Kyoungwoo , Cho Young Gyu , Jang Jinyoung
Published: May 2018

Controversy exists on whether animal and plant proteins influence obesity differently. The purpose of this study was to evaluate the association between total, animal, and plant protein intake with the body mass index (BMI), waist circumference (WC), and renal function in the Korean elderly. Study participants included Korean adults aged 60 years or older from the Korean National Health and Nutrition Examination Survey in 2013–2014. Height, weight, and waist circumference were measured and the body mass index was calculated. One-day 24-hour recall data were used to estimate daily total, animal, and plant protein intake. Glomerular filtration rate (GFR) was calculated by using the Modification of Diet in Renal Disease (MDRD) equation. General linear modellings were used to assess the relationships between protein intake, BMI and WC. The mean age was 69.2 ± 0.2 years and 44.2% were male. The total daily protein intake was 1.1 ± 0.02 g/kg/day and 0.9 ± 0.02 g/kg/day for males and females, respectively. Only one third of protein intake was from animal sources. In males, BMI (regression coefficient (95% CI); −1.30 (−1.55, −1.06), p < 0.001; −0.29 (−0.52, −0.05), p = 0.016; −1.30 (−1.8, −1.02), p < 0.001, respectively) and WC (−3.87 (−4.58, −3.16), p < 0.001; −0.90 (−1.58, −0.22), p = 0.010; −3.88 (−4.68, −3.08), p < 0.001, respectively) decreased as daily intake of plant protein (g/kg/day), animal protein (g/kg/day) and total protein (g/kg/day) increased. Similar associations were shown in Korean females. GFR was not associated with protein intake regardless of protein source in both sexes. In Korean adults aged 60 years or older, the protein intake was associated with a favorable obesity index without decrease in renal function. The effect was similar in both males and females, with both animal and plant proteins.
Dietary Acid Load and Mental Health Outcomes in Children and Adolescents: Results from the GINIplus and LISA Birth Cohort Studies
Authors: Bühlmeier Judith , Harris Carla , Koletzko Sibylle , Lehmann Irina , Bauer Carl-Peter , Schikowski Tamara , Von Berg Andrea , Berdel Dietrich , Heinrich Joachim , Hebebrand Johannes , Föcker Manuel , Standl Marie , Libuda Lars
Published: May 2018

High dietary acid load may have detrimental effects on mental health during childhood and adolescence. We examined cross-sectional and prospective associations of dietary acid load and mental health problems in a population-based sample, using data from the German birth cohort studies GINIplus (German Infant Nutritional Intervention plus environmental and genetic influences on allergy development) and LISA (Influences of lifestyle-related factors on the immune system and the development of allergies in childhood). These studies included detailed assessments of dietary intake through a food frequency questionnaire (FFQ), mental health outcomes measured through the Strengths and Difficulties Questionnaire (SDQ), and covariates. Using logistic regression, cross-sectional associations between dietary acid load measured as potential renal acid load (PRAL) and SDQ subscales were assessed at age 10 years (N = 2350) and 15 years (N = 2061). Prospective associations were assessed, considering PRAL at 10 years as exposure and SDQ subscales at 15 years as outcome (N = 1685). Results indicate that children with a diet higher in PRAL have more emotional problems (OR = 1.33 (95% CI = 1.15; 1.54); p < 0.001), and show hyperactivity more often (1.22 (1.04; 1.43); p = 0.014) at 10 years. No significant associations were present either cross-sectionally at age 15 years, nor prospectively. Results were confirmed in sensitivity analyses. These findings reveal first evidence for potential relationships between PRAL and mental health in childhood, although we cannot exclude reverse causality, i.e., that dietary behavior and PRAL are influenced by mental status. Future studies should address confirmation and identify biological mechanisms.
Allelopathic Responses of Rice Seedlings under Some Different Stresses
Authors: Khanh Tran Dang , Anh La Hoang , Nghia La Tuan , Huu Trung Khuat , Bich Hien Pham , Minh Trung Do , Dang Xuan Tran
Published: May 2018

The objective of this study was to evaluate the allelopathic responses of rice seedlings under submergence stress at different temperatures (10, 25, 32, and 37 °C). The results showed that a wide range of allelopathic responses of rice seedlings depended on varieties and stress conditions, with temperature was being a key factor. It showed that the extracts of rice seedlings induced significant suppression on lettuce and radish seedling germination, but had negligible allelopathic effects on growth of barnyardgrass, whilst the emergence and growth of natural weeds was stimulated. In contrast, the root exudates of Koshihikari rice seedlings (K32) at 32 °C reduced the number of total weeds by ≈60.0% and the total dry weight of weeds by 93.0%; i.e., to a greater extent than other root exudates. Among the 13 identified phenolic acids, p-hydroxybenzoic, vanillic, syringic, sinapic and benzoic acids—at concentrations of 0.360, 0.045, 3.052, 1.309 and 5.543 μg/mL might be involved in allelopathic responses of K32, inhibiting the growth of barnyardgrass and natural weeds. Findings of the present study may provide useful information on allelopathic responses of rice under environmental stresses and thus further understand of the competitive relationships between rice and weeds under natural conditions.
An Integrated Approach to Water-Energy Nexus in Shale-Gas Production
Authors: Al-Aboosi Fadhil , El-Halwagi Mahmoud
Published: May 2018

Shale gas production is associated with significant usage of fresh water and discharge of wastewater. Consequently, there is a necessity to create proper management strategies for water resources in shale gas production and to integrate conventional energy sources (e.g., shale gas) with renewables (e.g., solar energy). The objective of this study is to develop a design framework for integrating water and energy systems including multiple energy sources, the cogeneration process and desalination technologies in treating wastewater and providing fresh water for shale gas production. Solar energy is included to provide thermal power directly to a multi-effect distillation plant (MED) exclusively (to be more feasible economically) or indirect supply through a thermal energy storage system. Thus, MED is driven by direct or indirect solar energy and excess or direct cogeneration process heat. The proposed thermal energy storage along with the fossil fuel boiler will allow for the dual-purpose system to operate at steady-state by managing the dynamic variability of solar energy. Additionally, electric production is considered to supply a reverse osmosis plant (RO) without connecting to the local electric grid. A multi-period mixed integer nonlinear program (MINLP) is developed and applied to discretize the operation period to track the diurnal fluctuations of solar energy. The solution of the optimization program determines the optimal mix of solar energy, thermal storage and fossil fuel to attain the maximum annual profit of the entire system. A case study is solved for water treatment and energy management for Eagle Ford Basin in Texas.
Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants
Authors: Yatigammana Rasika , Peiris Shelton , Gerlach Richard , Allen David Edmund
Published: May 2018

The direction of price movements are analysed under an ordered probit framework, recognising the importance of accounting for discreteness in price changes. By extending the work of Hausman et al. (1972) and Yang and Parwada (2012),This paper focuses on improving the forecast performance of the model while infusing a more practical perspective by enhancing flexibility. This is achieved by extending the existing framework to generate short term multi period ahead forecasts for better decision making, whilst considering the serial dependence structure. This approach enhances the flexibility and adaptability of the model to future price changes, particularly targeting risk minimisation. Empirical evidence is provided, based on seven stocks listed on the Australian Securities Exchange (ASX). The prediction success varies between 78 and 91 per cent for in-sample and out-of-sample forecasts for both the short term and long term.
Training Small Networks for Scene Classification of Remote Sensing Images via Knowledge Distillation
Authors: Chen Guanzhou , Zhang Xiaodong , Tan Xiaoliang , Cheng Yufeng , Dai Fan , Zhu Kun , Gong Yuanfu , Wang Qing
Published: May 2018

Scene classification, aiming to identify the land-cover categories of remotely sensed image patches, is now a fundamental task in the remote sensing image analysis field. Deep-learning-model-based algorithms are widely applied in scene classification and achieve remarkable performance, but these high-level methods are computationally expensive and time-consuming. Consequently in this paper, we introduce a knowledge distillation framework, currently a mainstream model compression method, into remote sensing scene classification to improve the performance of smaller and shallower network models. Our knowledge distillation training method makes the high-temperature softmax output of a small and shallow student model match the large and deep teacher model. In our experiments, we evaluate knowledge distillation training method for remote sensing scene classification on four public datasets: AID dataset, UCMerced dataset, NWPU-RESISC dataset, and EuroSAT dataset. Results show that our proposed training method was effective and increased overall accuracy (3% in AID experiments, 5% in UCMerced experiments, 1% in NWPU-RESISC and EuroSAT experiments) for small and shallow models. We further explored the performance of the student model on small and unbalanced datasets. Our findings indicate that knowledge distillation can improve the performance of small network models on datasets with lower spatial resolution images, numerous categories, as well as fewer training samples.
Applying Independent Component Analysis on Sentinel-2 Imagery to Characterize Geomorphological Responses to an Extreme Flood Event near the Non-Vegetated Río Colorado Terminus, Salar de Uyuni, Bolivia
Authors: Li Jiaguang , Yang Xiucheng , Maffei Carmine , Tooth Stephen , Yao Guangqing
Published: May 2018

In some internally-draining dryland basins, ephemeral river systems terminate at the margins of playas. Extreme floods can exert significant geomorphological impacts on the lower reaches of these river systems and the playas, including causing changes to flood extent, channel-floodplain morphology, and sediment dispersal. However, the characterization of these impacts using remote sensing approaches has been challenging owing to variable vegetation and cloud cover, as well as the commonly limited spatial and temporal resolution of data. Here, we use Sentinel-2 Multispectral Instrument (MSI) data to investigate the flood extent, flood patterns and channel-floodplain morphodynamics resulting from an extreme flood near the non-vegetated terminus of the Río Colorado, located at the margins of the world’s largest playa (Salar de Uyuni, Bolivia). Daily maximum precipitation frequency analysis based on a 42-year record of daily precipitation data (1976 through 2017) indicates that an approximately 40-year precipitation event (40.7 mm) occurred on 6 January 2017, and this was associated with an extreme flood. Sentinel-2 data acquired after this extreme flood were used to separate water bodies and land, first by using modified normalized difference water index (MNDWI), and then by subsequently applying independent component analysis (ICA) on the land section of the combined pre- and post-flood images to extract flooding areas. The area around the Río Colorado terminus system was classified into three categories: water bodies, wet land, and dry land. The results are in agreement with visual assessment, with an overall accuracy of 96% and Kappa of 0.9 for water-land classification and an overall accuracy of 83% and Kappa of 0.65 for dry land-wet land classification. The flood extent mapping revealed preferential overbank flow paths on the floodplain, which were closely related to geomorphological changes. Changes included the formation and enlargement of crevasse splays, channel avulsion, and the development of erosion cells (floodplain scour-transport-fill features). These changes were visualized by Sentinel-2 images along with WorldView satellite images. In particular, flooding enlarged existing crevasse splays and formed new ones, while channel avulsion occurred near the river’s terminus. Greater overbank flow on the floodplain led to rapid erosion cell development, with changes to channelized sections occurring as a result of adjustments in flow sources and intensity combined with the lack of vegetation on the fine-grained (predominantly silt, clay) sediments. This study has demonstrated how ICA can be implemented on Sentinel-2 imagery to characterize the impact of extreme floods on the lower Río Colorado, and the method has potential application in similar contexts in many other drylands.
COMS Visible Channel Calibration Using Moon Observation Data
Authors: Oh Tae-Hyeong , Kim Dohyeong
Published: May 2018

COMS (Communication, Ocean, and Meteorological Satellite) has been in operation since April 2011. The COMS MI (Meteorological Imager) has one visible and four infrared channels. Through the use of the GSICS (Global Space-based Inter-Calibration System), the KMA (Korea Meteorological Administration) has monitored the radiometric performance of the COMS visible channel through its own calibration system and the use of four different earth targets: ocean, desert, water cloud, and DCC (Deep Convective Cloud). To use the invariant target of the Moon, the KMA adopted GIRO (GSICS Implementation of the ROLO (Robotic Lunar Observatory) model), which was released by EUMETSAT. In this study, a total of 146 lunar observation data (Level 1A) with various phase angles obtained between April 2011 and December 2017 are analyzed. A degradation rate of approximately −1.52 ± 0.10% per year occurred using the GIRO method, which was a degradation of approximately 12% over the eight years (from 2011 to 2018) during COMS MI’s operational period. The lunar calibration result was in good agreement with results provided by other calibration methods such as the DCC using the RTM (Radiative Transfer Model), which was approximately −1.43 ± 0.13% per year. Selection of on-Moon pixels provided an uncertainty of approximately 0.01% per year, while that related to the phase angle (Sun-Moon-Satellite) was approximately 0.06% per year.
A Telerehabilitation System for the Selection, Evaluation and Remote Management of Therapies
Authors: Anton David , Berges Idoia , Bermúdez Jesús , Goñi Alfredo , Illarramendi Arantza
Published: May 2018

Telerehabilitation systems that support physical therapy sessions anywhere can help save healthcare costs while also improving the quality of life of the users that need rehabilitation. The main contribution of this paper is to present, as a whole, all the features supported by the innovative Kinect-based Telerehabilitation System (KiReS). In addition to the functionalities provided by current systems, it handles two new ones that could be incorporated into them, in order to give a step forward towards a new generation of telerehabilitation systems. The knowledge extraction functionality handles knowledge about the physical therapy record of patients and treatment protocols described in an ontology, named TrhOnt, to select the adequate exercises for the rehabilitation of patients. The teleimmersion functionality provides a convenient, effective and user-friendly experience when performing the telerehabilitation, through a two-way real-time multimedia communication. The ontology contains about 2300 classes and 100 properties, and the system allows a reliable transmission of Kinect video depth, audio and skeleton data, being able to adapt to various network conditions. Moreover, the system has been tested with patients who suffered from shoulder disorders or total hip replacement.
Ultrasonic Phased Array Compressive Imaging in Time and Frequency Domain: Simulation, Experimental Verification and Real Application
Authors: Bai Zhiliang , Chen Shili , Jia Lecheng , Zeng Zhoumo
Published: May 2018

Embracing the fact that one can recover certain signals and images from far fewer measurements than traditional methods use, compressive sensing (CS) provides solutions to huge amounts of data collection in phased array-based material characterization. This article describes how a CS framework can be utilized to effectively compress ultrasonic phased array images in time and frequency domains. By projecting the image onto its Discrete Cosine transform domain, a novel scheme was implemented to verify the potentiality of CS for data reduction, as well as to explore its reconstruction accuracy. The results from CIVA simulations indicate that both time and frequency domain CS can accurately reconstruct array images using samples less than the minimum requirements of the Nyquist theorem. For experimental verification of three types of artificial flaws, although a considerable data reduction can be achieved with defects clearly preserved, it is currently impossible to break Nyquist limitation in the time domain. Fortunately, qualified recovery in the frequency domain makes it happen, meaning a real breakthrough for phased array image reconstruction. As a case study, the proposed CS procedure is applied to the inspection of an engine cylinder cavity containing different pit defects and the results show that orthogonal matching pursuit (OMP)-based CS guarantees the performance for real application.
Smart Waste Collection System with Low Consumption LoRaWAN Nodes and Route Optimization
Authors: Lozano Álvaro , Caridad Javier , De Paz Juan Francisco , Villarrubia González Gabriel , Bajo Javier
Published: May 2018

New solutions for managing waste have emerged due to the rise of Smart Cities and the Internet of Things. These solutions can also be applied in rural environments, but they require the deployment of a low cost and low consumption sensor network which can be used by different applications. Wireless technologies such as LoRa and low consumption microcontrollers, such as the SAM L21 family make the implementation and deployment of this kind of sensor network possible. This paper introduces a waste monitoring and management platform used in rural environments. A prototype of a low consumption wireless node is developed to obtain measurements of the weight, filling volume and temperature of a waste container. This monitoring allows the progressive filling data of every town container to be gathered and analysed as well as creating alerts in case of incidence. The platform features a module for optimising waste collection routes. This module dynamically generates routes from data obtained through the deployed nodes to save energy, time and consequently, costs. It also features a mobile application for the collection fleet which guides every driver through the best route—previously calculated for each journey. This paper presents a case study performed in the region of Salamanca to evaluate the efficiency and the viability of the system’s implementation. Data used for this case study come from open data sources, the report of the Castilla y León waste management plan and data from public tender procedures in the region of Salamanca. The results of the case study show a developed node with a great lifetime of operation, a large coverage with small deployment of antennas in the region, and a route optimization system which uses weight and volume measured by the node, and provides savings in cost, time and workforce compared to a static collection route approach.
Multiband Envelope Spectra Extraction for Fault Diagnosis of Rolling Element Bearings
Authors: Duan Jie , Shi Tielin , Zhou Hongdi , Xuan Jianping , Zhang Yongxiang
Published: May 2018

Bearing fault features are presented as repetitive transient impulses in vibration signals. Narrowband demodulation methods have been widely used to extract the repetitive transients in bearing fault diagnosis, for which the key factor is to accurately locate the optimal band. A multitude of criteria have been constructed to determine the optimal frequency band for demodulation. However, these criteria can only describe the strength of transient impulses, and cannot differentiate fault-related impulses and interference impulses that are cyclically generated in the signals. Additionally, these criteria are easily affected by the independent transitions and background noise in industrial locales. Therefore, the large values of the criteria may not appear in the optimal frequency band. To overcome these problems, a new method, referred to as multiband envelope spectra extraction (MESE), is proposed in this paper, which can extract all repetitive transient features in the signals. The novelty of MESE lies in the following aspects: (1) it can fuse envelope spectra at multiple narrow bands. The potential bands are selected based on Jarque-Bera statistics of narrowband envelope spectra; and (2) fast independent component analysis (fastICA) is introduced to extract the independent source spectra, which are fault- or interference-related. The multi-band strategy will preserve all impulse features and make the method more robust. Meanwhile, as a blind source separation technique, the fastICA can suppress some in-band noise and make the diagnosis more accurate. Several simulated and experimental signals are used to validate the efficiency of the proposed method. The results show that MESE is effective for enhanced fault diagnosis of rolling element bearings. Bearing faults can be detected even in a harsh environment.
Shoe-Insole Technology for Injury Prevention in Walking
Authors: Nagano Hanatsu , Begg Rezaul K.
Published: May 2018

Impaired walking increases injury risk during locomotion, including falls-related acute injuries and overuse damage to lower limb joints. Gait impairments seriously restrict voluntary, habitual engagement in injury prevention activities, such as recreational walking and exercise. There is, therefore, an urgent need for technology-based interventions for gait disorders that are cost effective, willingly taken-up, and provide immediate positive effects on walking. Gait control using shoe-insoles has potential as an effective population-based intervention, and new sensor technologies will enhance the effectiveness of these devices. Shoe-insole modifications include: (i) ankle joint support for falls prevention; (ii) shock absorption by utilising lower-resilience materials at the heel; (iii) improving reaction speed by stimulating cutaneous receptors; and (iv) preserving dynamic balance via foot centre of pressure control. Using sensor technology, such as in-shoe pressure measurement and motion capture systems, gait can be precisely monitored, allowing us to visualise how shoe-insoles change walking patterns. In addition, in-shoe systems, such as pressure monitoring and inertial sensors, can be incorporated into the insole to monitor gait in real-time. Inertial sensors coupled with in-shoe foot pressure sensors and global positioning systems (GPS) could be used to monitor spatiotemporal parameters in real-time. Real-time, online data management will enable ‘big-data’ applications to everyday gait control characteristics.
A Hybrid DV-Hop Algorithm Using RSSI for Localization in Large-Scale Wireless Sensor Networks
Authors: Cheikhrouhou Omar , M. Bhatti Ghulam , Alroobaea Roobaea
Published: May 2018

With the increasing realization of the Internet-of-Things (IoT) and rapid proliferation of wireless sensor networks (WSN), estimating the location of wireless sensor nodes is emerging as an important issue. Traditional ranging based localization algorithms use triangulation for estimating the physical location of only those wireless nodes that are within one-hop distance from the anchor nodes. Multi-hop localization algorithms, on the other hand, aim at localizing the wireless nodes that can physically be residing at multiple hops away from anchor nodes. These latter algorithms have attracted a growing interest from research community due to the smaller number of required anchor nodes. One such algorithm, known as DV-Hop (Distance Vector Hop), has gained popularity due to its simplicity and lower cost. However, DV-Hop suffers from reduced accuracy due to the fact that it exploits only the network topology (i.e., number of hops to anchors) rather than the distances between pairs of nodes. In this paper, we propose an enhanced DV-Hop localization algorithm that also uses the RSSI values associated with links between one-hop neighbors. Moreover, we exploit already localized nodes by promoting them to become additional anchor nodes. Our simulations have shown that the proposed algorithm significantly outperforms the original DV-Hop localization algorithm and two of its recently published variants, namely RSSI Auxiliary Ranging and the Selective 3-Anchor DV-hop algorithm. More precisely, in some scenarios, the proposed algorithm improves the localization accuracy by almost 95%, 90% and 70% as compared to the basic DV-Hop, Selective 3-Anchor, and RSSI DV-Hop algorithms, respectively.
Application of a Portable Multi-Analyte Biosensor for Organic Acid Determination in Silage
Authors: Pilas Johanna , Yazici Yasemen , Selmer Thorsten , Keusgen Michael , Schöning Michael J.
Published: May 2018

Multi-analyte biosensors may offer the opportunity to perform cost-effective and rapid analysis with reduced sample volume, as compared to electrochemical biosensing of each analyte individually. This work describes the development of an enzyme-based biosensor system for multi-parametric determination of four different organic acids. The biosensor array comprises five working electrodes for simultaneous sensing of ethanol, formate, d-lactate, and l-lactate, and an integrated counter electrode. Storage stability of the biosensor was evaluated under different conditions (stored at +4 °C in buffer solution and dry at −21 °C, +4 °C, and room temperature) over a period of 140 days. After repeated and regular application, the individual sensing electrodes exhibited the best stability when stored at −21 °C. Furthermore, measurements in silage samples (maize and sugarcane silage) were conducted with the portable biosensor system. Comparison with a conventional photometric technique demonstrated successful employment for rapid monitoring of complex media.
A Cooperative Search and Coverage Algorithm with Controllable Revisit and Connectivity Maintenance for Multiple Unmanned Aerial Vehicles
Authors: Liu Zhong , Gao Xiaoguang , Fu Xiaowei
Published: May 2018

In this paper, we mainly study a cooperative search and coverage algorithm for a given bounded rectangle region, which contains several unknown stationary targets, by a team of unmanned aerial vehicles (UAVs) with non-ideal sensors and limited communication ranges. Our goal is to minimize the search time, while gathering more information about the environment and finding more targets. For this purpose, a novel cooperative search and coverage algorithm with controllable revisit mechanism is presented. Firstly, as the representation of the environment, the cognitive maps that included the target probability map (TPM), the uncertain map (UM), and the digital pheromone map (DPM) are constituted. We also design a distributed update and fusion scheme for the cognitive map. This update and fusion scheme can guarantee that each one of the cognitive maps converges to the same one, which reflects the targets’ true existence or absence in each cell of the search region. Secondly, we develop a controllable revisit mechanism based on the DPM. This mechanism can concentrate the UAVs to revisit sub-areas that have a large target probability or high uncertainty. Thirdly, in the frame of distributed receding horizon optimizing, a path planning algorithm for the multi-UAVs cooperative search and coverage is designed. In the path planning algorithm, the movement of the UAVs is restricted by the potential fields to meet the requirements of avoiding collision and maintaining connectivity constraints. Moreover, using the minimum spanning tree (MST) topology optimization strategy, we can obtain a tradeoff between the search coverage enhancement and the connectivity maintenance. The feasibility of the proposed algorithm is demonstrated by comparison simulations by way of analyzing the effects of the controllable revisit mechanism and the connectivity maintenance scheme. The Monte Carlo method is employed to validate the influence of the number of UAVs, the sensing radius, the detection and false alarm probabilities, and the communication range on the proposed algorithm.
Poaching Detection Technologies—A Survey
Authors: Kamminga Jacob , Ayele Eyuel , Meratnia Nirvana , Havinga Paul
Published: May 2018

Between 1960 and 1990, 95% of the black rhino population in the world was killed. In South Africa, a rhino was killed every 8 h for its horn throughout 2016. Wild animals, rhinos and elephants, in particular, are facing an ever increasing poaching crisis. In this paper, we review poaching detection technologies that aim to save endangered species from extinction. We present requirements for effective poacher detection and identify research challenges through the survey. We describe poaching detection technologies in four domains: perimeter based, ground based, aerial based, and animal tagging based technologies. Moreover, we discuss the different types of sensor technologies that are used in intruder detection systems such as: radar, magnetic, acoustic, optic, infrared and thermal, radio frequency, motion, seismic, chemical, and animal sentinels. The ultimate long-term solution for the poaching crisis is to remove the drivers of demand by educating people in demanding countries and raising awareness of the poaching crisis. Until prevention of poaching takes effect, there will be a continuous urgent need for new (combined) approaches that take up the research challenges and provide better protection against poaching in wildlife areas.
Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction
Authors: Chen Peng , Yang Yixin , Wang Yong , Ma Yuanliang
Published: May 2018

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.
Extrinsic Calibration of a Laser Galvanometric Setup and a Range Camera
Authors: Sels Seppe , Bogaerts Boris , Vanlanduit Steve , Penne Rudi
Published: May 2018

Currently, galvanometric scanning systems (like the one used in a scanning laser Doppler vibrometer) rely on a planar calibration procedure between a two-dimensional (2D) camera and the laser galvanometric scanning system to automatically aim a laser beam at a particular point on an object. In the case of nonplanar or moving objects, this calibration is not sufficiently accurate anymore. In this work, a three-dimensional (3D) calibration procedure that uses a 3D range sensor is proposed. The 3D calibration is valid for all types of objects and retains its accuracy when objects are moved between subsequent measurement campaigns. The proposed 3D calibration uses a Non-Perspective-n-Point (NPnP) problem solution. The 3D range sensor is used to calculate the position of the object under test relative to the laser galvanometric system. With this extrinsic calibration, the laser galvanometric scanning system can automatically aim a laser beam to this object. In experiments, the mean accuracy of aiming the laser beam on an object is below 10 mm for 95% of the measurements. This achieved accuracy is mainly determined by the accuracy and resolution of the 3D range sensor. The new calibration method is significantly better than the original 2D calibration method, which in our setup achieves errors below 68 mm for 95% of the measurements.
Mass Spectrometric Determination of the Effect of Surface Deactivation on Membranes Used for In-Situ Sampling of Cerebrospinal Fluid (CSF)
Authors: Undin Torgny , P. Dahlin Andreas , Bergquist Jonas , Bergström Lind Sara
Published: May 2018

In this paper, a strategy for structured monitoring of surface modifications to control protein adsorption to membrane structures is presented. The already established on-surface enzymatic digestion (oSED) method combined with nano-liquid chromatography and tandem mass spectrometry (LC-MS/MS) analysis was employed for the analysis of proteins in ventricular cerebrospinal fluid (vCSF) from neurointensive care patients. Protein adsorption was studied by in-situ sampling in a temporally resolved manner on both immobilized native and Pluronic-deactivated membranes. Deactivation was significantly reducing the protein adsorption but it also induced novel selective properties of the surface. The proposed versatile strategy will facilitate protein-biomaterial, protein-polymer, protein-protein interaction studies in the future.
An Analysis of the Adequacy of Protection Afforded by the Convention on the Rights of Persons with Disabilities (CRPD) in Situations of Armed Conflict
Authors: Mugabi Ivan K.
Published: May 2018

This essay aims to describe the contrasting approaches to disability described by international humanitarian law (IHL) and international human rights law (IHRL) with the aim of pointing out the approaches/models of disability underpinning two legal regimes. The limits of those approaches/models in the treatment and protection of persons with disabilities shall be investigated and established. Ultimately, the paper considers the possibility of recommending a unified approach/model that should underpin both IHL and IHRL in addressing aspects of disability.
Land Valuation Sustainable Model of Urban Planning Development: A Case Study in Badajoz, Spain
Authors: Codosero Rodas José Maria , Naranjo Gómez José Manuel , Castanho Rui Alexandre , Cabezas José
Published: May 2018

The urban planning development process in urban territories has multiple consequences, not only in spatial structure but also in land valuation patterns. The economic value of land encompassed in municipal planning—which is associated with a certain urbanized use—increases as the planning processes evolve over these lands. For economic land valuation to comply with the required parameters of urban and territorial sustainable development, it is pivotal that in the determination of land value there are no expectations of difficult or impossible realizations, in order to eliminate any speculative element from the valuation. The land valuation model presented in the current study complies with this premise, proposing a sustainable land valuation model based on the evolution of urban planning development, achieving maximum value when it is fully urbanized. The main objective of the present work is to analyze how land value increases as municipal planning develops and to suggest a sustainable valuation model for land with urban use. Contextually, through a case study analysis, the development of municipal planning has been divided over time into four urban states: (i) land without detailed planning; (ii) land with detailed planning; (iii) land with re-parceling; and (iv) urbanized land. In this regard, the gradual evolution of land value which has reached different states over time has been determined, as has scenarios where the value has increased up to the value of urbanized land.
Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China
Authors: Liu Yuanxin , Li FengYun , Yu Xinhua , Yuan Jiahai , Zhou Dong
Published: May 2018

In recent years, new energy sources have ushered in tremendous opportunities for development. The difficulties to finance new energy enterprises (NEEs) can be estimated through issuing corporate bonds. However, there are few scientific and reasonable methods to assess the credit risk of NEE bonds, which is not conducive to the healthy development of NEEs. Based on this, this paper analyzes the advantages and risks of NEEs issuing bonds and the main factors affecting the credit risk of NEE bonds, constructs a hybrid model for assessing the credit risk of NEE bonds based on factor analysis and logistic regress analysis techniques, and verifies the applicability and effectiveness of the model employing relevant data from 46 Chinese NEEs. The results show that the main factors affecting the credit risk of NEE bonds are internal factors involving the company’s profitability, solvency, operational ability, growth potential, asset structure and viability, and external factors including macroeconomic environment and energy policy support. Based on the empirical results and the exact situation of China’s NEE bonds, this article finally puts forward several targeted recommendations.
The Bio-Inspired Optimization of Trading Strategies and Its Impact on the Efficient Market Hypothesis and Sustainable Development Strategies
Authors: Dreżewski Rafał , Dziuban Grzegorz , Pająk Karol
Published: May 2018

In this paper, the evolutionary algorithm for the optimization of Forex market trading strategies is proposed. The introduction to issues related to the financial markets and the evolutionary algorithms precedes the main part of the paper, in which the proposed trading system is presented. The system uses the evolutionary algorithm for optimization of a parameterized greedy strategy, which is then used as an investment strategy on the Forex market. In the proposed system, a model of the Forex market was developed, including all elements that are necessary for simulating realistic trading processes. The proposed evolutionary algorithm contains several novel mechanisms that were introduced to optimize the greedy strategy. The most important of the proposed techniques are the mechanisms for maintaining the population diversity, a mechanism for protecting the best individuals in the population, the mechanisms preventing the excessive growth of the population, the mechanisms of the initialization of the population after moving the time window and a mechanism of choosing the best strategies used for trading. The experiments, conducted with the use of real-world Forex market data, were aimed at testing the quality of the results obtained using the proposed algorithm and comparing them with the results obtained by the buy-and-hold strategy. By comparing our results with the results of the buy-and-hold strategy, we attempted to verify the validity of the efficient market hypothesis. The credibility of the hypothesis would have more general implications for many different areas of our lives, including future sustainable development policies.