bluuebunny/crossref_metadata_2025 huggingface dataset:
Annoyance in Response to Vibrations from Railways
Authors: Maclachlan Laura , Ögren Mikael , Van Kempen Elise , Hussain-Alkhateeb Laith , Persson Waye Kerstin
Published: August 2018

Rail transport is a key stepping stone in the EU’s transport policy and is pinpointed for investment and growth over the coming decades. This expanding infrastructure implies increased exposure to environmental stressors, such as noise and ground-borne vibrations. Little is known about the health impacts of exposure to these vibrations. The aim of this paper is to examine the association between annoyance from rail vibrations and the distance of residential dwelling from the railway. It reports the first results of a large epidemiological study, EpiVib, which was designed to investigate the long-term health effects of exposure to rail vibrations. The first part of this study examines a self-reported questionnaire. In total, 6894 individuals aged between 18 and 80 living within 1 km of a railway in west Sweden participated. Results presented here examine the association between distance to the railway and annoyance from vibrations and are stratified by train type. A positive association between closer distance and increased annoyance is seen. After adjustment for important modifiers, results showed that vibrations from freight trains and maintenance operations are reported to be moderately and highly annoying at distances of up to 400 m from the railway and diesel up to 300 m. Vibration from passenger and fast trains are significantly annoying up to 200 m from the track. Vibration from freight trains and maintenance operations were considered highly annoying up to 300 m from the track, diesel up to 400 m. Vibration from passenger and fast trains are not reported to be highly annoying after adjustment. Heavier, slower moving locomotives, in the form of diesel and freight trains, appear to be the source of annoyance at distances further from the railway compared to passenger and fast trains. This has implications in terms of property, transport, and infrastructure planning.
Atrazine Contamination of Drinking Water and Adverse Birth Outcomes in Community Water Systems with Elevated Atrazine in Ohio, 2006–2008
Authors: Almberg Kirsten , Turyk Mary , Jones Rachael , Rankin Kristin , Freels Sally , Stayner Leslie
Published: August 2018

Atrazine, a common water contaminant in the U.S., has been associated with adverse birth outcomes in previous studies. This study aimed to determine if atrazine concentrations in drinking water are associated with adverse birth outcomes including small for gestational age (SGA), term low birth weight (term LBW), very low birth weight (VLBW), preterm birth (PTB), and very preterm birth (VPTB). This study included 14,445 live singleton births from Ohio communities served by 22 water systems enrolled in the U.S. Environmental Protection Agency’s Atrazine Monitoring Program between 2006 and 2008. Mean gestational and trimester-specific atrazine concentrations were calculated. Significantly increased odds of term LBW birth was associated with atrazine exposure over the entire gestational period (OR 1.27, 95% CI 1.10, 1.45), as well as the first (OR 1.20, 95% CI 1.08, 1.34) and second trimesters (OR 1.13, 95% CI 1.07, 1.20) of pregnancy. We observed no evidence of an association between atrazine exposure via drinking water and SGA, VLBW, PTB, or VPTB. Our results suggest that atrazine exposure is associated with reduced birth weight among term infants and that exposure to atrazine in drinking water in early and mid-pregnancy may be most critical for its toxic effects on the fetus.
Heavy Metal Contamination Near Industrial Estate Areas in Phra Nakhon Si Ayutthaya Province, Thailand and Human Health Risk Assessment
Authors: Mingkhwan Rachaneekorn , Worakhunpiset Suwalee
Published: August 2018

Industrial activity is one of the significant sources of environmental contamination with heavy metals, especially in developing countries. Flood can also lead to the distribution of toxic substances into the environment, regarding the Thailand flood in 2011 as some industrial estates are affected, leading to concern about heavy metals from industrial wastewater contamination. We aimed to measure the levels of Cd, Cr, Cu, Ni, Mn, Pb, and Zn in river and stream water, sediment, and fish collected from the area around the industrial estates in Uthai District and Bangpa-in District of Phra Nakhon Si Ayutthaya Province, following the floods of 2011. The results revealed that heavy metal levels in water did not exceed Thailand surface water quality standards, except for Mn levels at one sampling site. Metal levels in sediment and fish samples also did not exceed published standards. The hazard quotient for fish consumption was highest for Ni (0.2178) in Trichopodus trichopterus collected from the area near the industrial estate in Bangpa-in District, while the hazard index from Cd, Cr, and Cu exposure were 0.86966, which was lower than 1, indicating that the health risks for these seven metals were within acceptable ranges.
Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
Authors: An Min , He Weijun , Degefu Dagmawi Mulugeta , Liao Zaiyi , Zhang Zhaofang , Yuan Liang
Published: August 2018

With the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control water pollution. Based on the input and output urban wastewater treatment data of the 31 provinces of mainland China for the period 2011–2015, the spatial variation of urban water pollution and the efficiency of wastewater treatment plants were measured and mapped. The exploratory spatial data analysis (ESDA) model and super-efficiency data envelopment analysis (DEA) combined Malmquist index were used to achieve this goal. The following insight was obtained from the results. (1) The intensity of urban wastewater discharge increased, and the urban wastewater discharge showed a spatial agglomeration trend for the period 2011 to 2015. (2) The average inefficiency of wastewater treatment plants (WWTPs) for the study period was 39.2%. The plants’ efficiencies worsened from the eastern to western parts of the country. (3) The main reasons for the low efficiency were the lack of technological upgrade and scale-up. The technological upgrade rate was −4.8%, while the scale efficiency increases as a result of scaling up was −0.2%. Therefore, to improve the wastewater treatment efficiency of the country, the provinces should work together to increase capital investment and technological advancement.
The Combined Process of Paper Filtration and Ultrafiltration for the Pretreatment of the Biogas Slurry from Swine Manure
Authors: Zhan Yuanhang , Dong Hongmin , Yin Fubin , Yue Caide
Published: August 2018

The membrane process had been applied for the advanced treatment of pig farm biogas slurry. As studied, this physical pretreatment, with low cost and high efficiency of the suspended solids removal and nutrient retention, is required to control membrane fouling. The combined process of paper filtration and ultrafiltration in a pilot scale was applied in the present study. The main objective was to explore and identify the feasibility of the new process for the pretreatment of the separation liquid of pig farm biogas slurry. A precision identification experiment of paper filtration and the multi-batch repetitive experiments of the combined process were designed. The results showed, at the identified paper filtration precision of 50μm and an operating pressure of 0.3 bar of the ultrafiltration process, that the flux rate at the stable stage of the multi-batch operation was around 295.00 L/h. The combined process achieved an overall processing rate of 345.41 ± 18.81 L/h and a volume permeation proportion of 82.45% ± 0.85%. The TSS was removed by 95.71%, but total nitrogen (TN) and ammonia nitrogen (NH3-N) were retained by 76.29% ± 2.04% and 73.74% ± 2.10%, respectively. Comprehensively, the requirement for the pretreatment was obtained.
Physical Activity and Fundamental Motor Skill Performance of 5–10 Year Old Children in Three Different Playgrounds
Authors: Adams Jessie , Veitch Jenny , Barnett Lisa
Published: August 2018

Playgrounds provide opportunities for children to engage in physical activity and develop their fundamental motor skills. The aim of this descriptive pilot study was to examine whether playground design facilitated different levels of physical activity and fundamental motor skills. Children aged 5 to 10 (n = 57) were recruited from three independent playgrounds located in Melbourne (Australia). Whilst playing, children wore accelerometers which measured time spent in physical activity and direct observations recorded fundamental motor skills and play equipment use. A general linear model with playground type as the predictor and adjusting for monitor wear-time identified whether mean time in physical activity was different for the three playgrounds. Frequencies and a one-way ANOVA assessed whether the observed mean number of fundamental motor skills varied between playgrounds. On average, 38.1% of time (12.0 min) was spent in moderate- vigorous-intensity physical activity. Children in the traditional playground (n = 16) engaged in more moderate-intensity physical activity (9.4 min) than children in the adventure playground (n = 21), (5.6 min) (p = 0.027). There were no significant associations with vigorous-intensity physical activity or fundamental motor skills between playgrounds. Children performed few fundamental motor skills but used a wider variety of equipment in the contemporary and adventure playgrounds. Playgrounds need to maximise opportunities for children to engage in physical activity and develop fundamental motor skills.
Spatial Distribution and Contamination Assessment of Surface Heavy Metals off the Western Guangdong Province and Northeastern Hainan Island
Authors: Ge Qian , Xue Zuo George , Chu Fengyou
Published: August 2018

Surface sediments collected from the continental shelf off the western Guangdong Province and northeastern Hainan Island are analyzed for selected heavy metals contents including Cd, Cr, Cu, Pb, Zn, and As to determine spatial distribution, potential ecological risks, and sources. In addition, some of the controlling factors of heavy metals distribution are also discussed. The average heavy metals contents decrease in the order of Zn > Cr > Pb > Cu > As > Cd. The averaged pollution degree, as shown by the index of geo-accumulation (Igeo), decreases in the order of Zn > Cu > Pb > Cr > Cd > As. Due to the barrier of islands, the Igeo values of Zn, Pb, Cr, Cu, and Cd near the Hailing and Xiachuan Islands are larger than those in other areas. Meanwhile, the Igeo value of As near the coastal area off the estuary of Wanquan River is clearly larger than that in other areas. Based on the results of potential ecological risk index, Cd, Cu, and As should be paid more attention for the contamination risk in future. The results of Pearson correlation analysis and principal component analysis indicate that Zn, Cr, Pb, Cu, and Cd are mainly from the Pearl River and surrounding small rivers, whereas As originates from the Hainan Island. The grain size is one of the main controlling factors for heavy metals distribution, and the anthropogenic activity also plays an important role.
Automatic Seam-Line Detection in UAV Remote Sensing Image Mosaicking by Use of Graph Cuts
Authors: Li Ming , Li Deren , Guo Bingxuan , Li Lin , Wu Teng , Zhang Weilong
Published: August 2018

Image mosaicking is one of the key technologies in data processing in the field of computer vision and digital photogrammetry. For the existing problems of seam, pixel aliasing, and ghosting in mosaic images, this paper proposes and implements an optimal seam-line search method based on graph cuts for unmanned aerial vehicle (UAV) remote sensing image mosaicking. This paper first uses a mature and accurate image matching method to register the pre-mosaicked UAV images, and then it marks the source of each pixel in the overlapped area of adjacent images and calculates the energy value contributed by the marker by using the target energy function of graph cuts constructed in this paper. Finally, the optimal seam-line can be obtained by solving the minimum value of target energy function based on graph cuts. The experimental results show that our method can realize seamless UAV image mosaicking, and the image mosaic area transitions naturally.
Identification of Oxidative Stress in Red Blood Cells with Nanoscale Chemical Resolution by Infrared Nanospectroscopy
Authors: Ruggeri Francesco S. , Marcott Curtis , Dinarelli Simone , Longo Giovanni , Girasole Marco , Dietler Giovanni , Knowles Tuomas P. J.
Published: August 2018

During their lifespan, Red blood cells (RBC), due to their inability to self-replicate, undergo an ageing degradation phenomenon. This pathway, both in vitro and in vivo, consists of a series of chemical and morphological modifications, which include deviation from the biconcave cellular shape, oxidative stress, membrane peroxidation, lipid content decrease and uncoupling of the membrane-skeleton from the lipid bilayer. Here, we use the capabilities of atomic force microscopy based infrared nanospectroscopy (AFM-IR) to study and correlate, with nanoscale resolution, the morphological and chemical modifications that occur during the natural degradation of RBCs at the subcellular level. By using the tip of an AFM to detect the photothermal expansion of RBCs, it is possible to obtain nearly two orders of magnitude higher spatial resolution IR spectra, and absorbance images than can be obtained on diffraction-limited commercial Fourier-transform Infrared (FT-IR) microscopes. Using this approach, we demonstrate that we can identify localized sites of oxidative stress and membrane peroxidation on individual RBC, before the occurrence of neat morphological changes in the cellular shape.
Developmental Programming of the Metabolic Syndrome: Can We Reprogram with Resveratrol?
Authors: Tain You-Lin , Hsu Chien-Ning
Published: August 2018

Metabolic syndrome (MetS) is a mounting epidemic worldwide. MetS can start in early life, in a microenvironment that is now known as the developmental origins of health and disease (DOHaD). The concept of DOHaD also offers opportunities for reprogramming strategies that aim to reverse programming processes in early life. Resveratrol, a polyphenolic compound has a wide spectrum of beneficial effects on human health. In this review, we first summarize the epidemiological and experimental evidence supporting the developmental programming of MetS. This review also presents an overview of the evidence linking different molecular targets of resveratrol to developmental programming of MetS-related disorders. This will be followed by studies documenting resveratrol as a reprogramming agent to protect against MetS-related disorders. Further clinical studies are required in order to bridge the gap between animal models and clinical trials in order to establish the effective dose and therapeutic duration for resveratrol as a reprogramming therapy on MetS disorders from developmental origins.
Genotyping-by-Sequencing Enhances Genetic Diversity Analysis of Crested Wheatgrass [Agropyron cristatum (L.) Gaertn.]
Authors: Baral Kiran , Coulman Bruce , Biligetu Bill , Fu Yong-Bi
Published: August 2018

Molecular characterization of unsequenced plant species with complex genomes is now possible by genotyping-by-sequencing (GBS) using recent next generation sequencing technologies. This study represents the first use of GBS application to sample genome-wide variants of crested wheatgrass [Agropyron cristatum (L.) Gaertn.] and assess the genetic diversity present in 192 genotypes from 12 tetraploid lines. Bioinformatic analysis identified 45,507 single nucleotide polymorphism (SNP) markers in this outcrossing grass species. The model-based Bayesian analysis revealed four major clusters of the samples assayed. The diversity analysis revealed 15.8% of SNP variation residing among the 12 lines, and 12.1% SNP variation present among four genetic clusters identified by the Bayesian analysis. The principal coordinates analysis and dendrogram were able to distinguish four lines of Asian origin from Canadian cultivars and breeding lines. These results serve as a valuable resource for understanding genetic variability, and will aid in the genetic improvement of this outcrossing polyploid grass species for forage production. These findings illustrate the potential of GBS application in the characterization of non-model polyploid plants with complex genomes.
Structural Prediction of the Dimeric Form of the Mammalian Translocator Membrane Protein TSPO: A Key Target for Brain Diagnostics
Authors: Zeng Juan , Guareschi Riccardo , Damre Mangesh , Cao Ruyin , Kless Achim , Neumaier Bernd , Bauer Andreas , Giorgetti Alejandro , Carloni Paolo , Rossetti Giulia
Published: August 2018

Positron emission tomography (PET) radioligands targeting the human translocator membrane protein (TSPO) are broadly used for the investigations of neuroinflammatory conditions associated with neurological disorders. Structural information on the mammalian protein homodimers—the suggested functional state of the protein—is limited to a solid-state nuclear magnetic resonance (NMR) study and to a model based on the previously-deposited solution NMR structure of the monomeric mouse protein. Computational studies performed here suggest that the NMR-solved structure in the presence of detergents is not prone to dimer formation and is furthermore unstable in its native membrane environment. We, therefore, propose a new model of the functionally-relevant dimeric form of the mouse protein, based on a prokaryotic homologue. The model, fully consistent with solid-state NMR data, is very different from the previous predictions. Hence, it provides, for the first time, structural insights into this pharmaceutically-important target which are fully consistent with experimental data.
New Directions for SMA Therapy
Authors: Messina Sonia
Published: August 2018

Spinal muscular atrophy (SMA) is a severe disorder of motor neurons and the most frequent genetic cause of mortality in childhood, due to respiratory complications. The disease occurs due to mutations in the survival motor neuron 1 (SMN1) gene that leads to a reduction in the SMN protein, causing degeneration of lower motor neurons, muscle weakness and atrophy. Recently, the Food and Drug Administration (FDA) and the European Medical Agency (EMA) approved the antisense oligonucleotide nusinersen, the first disease-modifying treatment for SMA. Encouraging results from SMN1 gene therapy studies have raised hope for other therapeutic approaches that might arise in the coming years. However, nusinersen licensing has created ethical, medical, and financial implications that will need to be addressed. In this review, the history and challenges of the new SMA therapeutic strategies are highlighted.
(S)-4-Isopropyl-5,5-diphenyloxazolidin-2-one
Authors: Mancuso Raffaella , Miliè Rossana , Ziccarelli Ida , Novello Mariangela , Della Ca’ Nicola , Gabriele Bartolo
Published: August 2018

(S)-4-Isopropyl-5,5-diphenyloxazolidin-2-one has been synthesized for the first time by the enantiospecific oxidative carbonylation of commercially available (S)-2-amino-3-methyl-1,1-diphenylbutan-1-ol. The cyclocarbonylation reaction was carried out at 100 °C in 1,2-dimethoxyethane (DME) as the solvent for 15 h, under 20 atm of a 4:1 mixture of CO–air and in the presence of the catalytic system PdI2/KI (substrate:KI:PdI2 molar ratio = 100:10:1), to give the oxazolidinone derivative in 81% isolated yield.
Application of Dendrimers for the Treatment of Infectious Diseases
Authors: Mhlwatika Zandile , Aderibigbe Blessing Atim
Published: August 2018

Dendrimers are drug delivery systems that are characterized by a three-dimensional, star-shaped, branched macromolecular network. They possess ideal properties such as low polydispersity index, biocompatibility and good water solubility. They are made up of the interior and the exterior layers. The exterior layer consists of functional groups that are useful for conjugation of drugs and targeting moieties. The interior layer exhibits improved drug encapsulation efficiency, reduced drug toxicity, and controlled release mechanisms. These unique properties make them useful for drug delivery. Dendrimers have attracted considerable attention as drug delivery system for the treatment of infectious diseases. The treatment of infectious diseases is hampered severely by drug resistance. Several properties of dendrimers such as their ability to overcome drug resistance, toxicity and control the release mechanism of the encapsulated drugs make them ideal systems for the treatment of infectious disease. The aim of this review is to discuss the potentials of dendrimers for the treatment of viral and parasitic infections.
Proteomic Approaches for the Discovery of Biofluid Biomarkers of Neurodegenerative Dementias
Authors: Carlyle Becky C. , Trombetta Bianca A. , Arnold Steven E.
Published: August 2018

Neurodegenerative dementias are highly complex disorders driven by vicious cycles of intersecting pathophysiologies. While most can be definitively diagnosed by the presence of disease-specific pathology in the brain at postmortem examination, clinical disease presentations often involve substantially overlapping cognitive, behavioral, and functional impairment profiles that hamper accurate diagnosis of the specific disease. As global demographics shift towards an aging population in developed countries, clinicians need more sensitive and specific diagnostic tools to appropriately diagnose, monitor, and treat neurodegenerative conditions. This review is intended as an overview of how modern proteomic techniques (liquid chromatography mass spectrometry (LC-MS/MS) and advanced capture-based technologies) may contribute to the discovery and establishment of better biofluid biomarkers for neurodegenerative disease, and the limitations of these techniques. The review highlights some of the more interesting technical innovations and common themes in the field but is not intended to be an exhaustive systematic review of studies to date. Finally, we discuss clear reporting principles that should be integrated into all studies going forward to ensure data is presented in sufficient detail to allow meaningful comparisons across studies.
Determination of Soil Salt Content Using a Probability Neural Network Model Based on Particle Swarm Optimization in Areas Affected and Non-Affected by Human Activities
Authors: Fu Chengbiao , Gan Shu , Yuan Xiping , Xiong Heigang , Tian Anhong
Published: August 2018

Traditional partial least squares regression (PLSR) and artificial neural networks (ANN) have been widely applied to estimate salt content from spectral reflectance in many different saline environments around the world. However, these methods entail a great amount of calculation, and their accuracy is low. To overcome these problems, a probability neural network (PNN) model based on particle swarm optimization was used in this study to build soil salt content models. Furthermore, there is a clear correlation between the level of human activities and the degree of salinization of an environment. This paper is the first to discuss this matter. Here, the performance of the PNN model to estimate soil salt content from reflectance data was investigated in areas non-affected (Area A) and affected (Area B) by human activities. The study area is located in Xingjinag, China. Different mathematical procedures, five wave band intervals, and two types of signal input sources were used for cross analysis. The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to deviation (RPD) index values were compared to verify the reliability of the model. Particle swarm optimization was used to adjust the optimal smoothing parameters of the PNN model and to avoid the long training processes required by the traditional ANN. The results show that the optimal wave band interval of the PNN is between 1000 nm and 1350 nm in Area A and between 400 nm and 700 nm in Area B. The reciprocal (1/R) transformation after Savitzky-Golay (SG) smoothing of the signal source is optimal for both areas. The RPD for both is greater than 30, which shows that the PNN model is applicable to areas with and without human activities and the prediction results are very good. The results indicated that the optimal wave band intervals for PNN modeling differed in areas affected and non-affected by human activities. The optimal interval of the artificial activities region falls in the visible light portion of the spectrum, and the optimized wave band region without human activities falls in the near-infrared short-wave portion of the spectrum.
An Improved Spatial and Temporal Reflectance Unmixing Model to Synthesize Time Series of Landsat-Like Images
Authors: Ma Jianhang , Zhang Wenjuan , Marinoni Andrea , Gao Lianru , Zhang Bing
Published: August 2018

The trade-off between spatial and temporal resolution limits the acquisition of dense time series of Landsat images, and limits the ability to properly monitor land surface dynamics in time. Spatiotemporal image fusion methods provide a cost-efficient alternative to generate dense time series of Landsat-like images for applications that require both high spatial and temporal resolution images. The Spatial and Temporal Reflectance Unmixing Model (STRUM) is a kind of spatial-unmixing-based spatiotemporal image fusion method. The temporal change image derived by STRUM lacks spectral variability and spatial details. This study proposed an improved STRUM (ISTRUM) architecture to tackle the problem by taking spatial heterogeneity of land surface into consideration and integrating the spectral mixture analysis of Landsat images. Sensor difference and applicability with multiple Landsat and coarse-resolution image pairs (L-C pairs) are also considered in ISTRUM. Experimental results indicate the image derived by ISTRUM contains more spectral variability and spatial details when compared with the one derived by STRUM, and the accuracy of fused Landsat-like image is improved. Endmember variability and sliding-window size are factors that influence the accuracy of ISTRUM. The factors were assessed by setting them to different values. Results indicate ISTRUM is robust to endmember variability and the publicly published endmembers (Global SVD) for Landsat images could be applied. Only sliding-window size has strong influence on the accuracy of ISTRUM. In addition, ISTRUM was compared with the Spatial Temporal Data Fusion Approach (STDFA), the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the Hybrid Color Mapping (HCM) and the Flexible Spatiotemporal DAta Fusion (FSDAF) methods. ISTRUM is superior to STDFA, slightly superior to HCM in cases when the temporal change is significant, comparable with ESTARFM and a little inferior to FSDAF. However, the computational efficiency of ISTRUM is much higher than ESTARFM and FSDAF. ISTRUM can to synthesize Landsat-like images on a global scale.
Estimation of Size-Fractionated Primary Production from Satellite Ocean Colour in UK Shelf Seas
Authors: Curran Kieran , Brewin Robert J. W. , Tilstone Gavin H. , Bouman Heather A. , Hickman Anna
Published: August 2018

Satellite ocean-colour based models of size-fractionated primary production (PP) have been developed for the oceans on a global level. Uncertainties exist as to whether these models are accurate for temperate Shelf seas. In this paper, an existing ocean-colour based PP model is tuned using a large in situ database of size-fractionated measurements from the Celtic Sea and Western English Channel of chlorophyll-a (Chl a) and the photosynthetic parameters, the maximum photosynthetic rate ( P m B ) and light limited slope ( α B ). Estimates of size fractionated PP over an annual cycle in the UK shelf seas are compared with the original model that was parameterised using in situ data from the open ocean and a climatology of in situ PP from 2009 to 2015. The Shelf Sea model captured the seasonal patterns in size-fractionated PP for micro- and picophytoplankton, and generally performed better than the original open ocean model, except for nanophytoplankton PP which was over-estimated. The overestimation in PP is in part due to errors in the parameterisation of the biomass profile during summer, stratified conditions. Compared to the climatology of in situ data, the shelf sea model performed better when phytoplankton biomass was high, but overestimated PP at low Chl a.
WiFi Indoor Localization with CSI Fingerprinting-Based Random Forest
Authors: Wang Yanzhao , Xiu Chundi , Zhang Xuanli , Yang Dongkai
Published: August 2018

WiFi fingerprinting indoor positioning systems have extensive applied prospects. However, a vast amount of data in a particular environment has to be gathered to establish a fingerprinting database. Deficiencies of these systems are the lack of universality of multipath effects and a burden of heavy workload on fingerprint storage. Thus, this paper presents a novel Random Forest fingerprinting localization (RFFP) method using channel state information (CSI), which utilizes the Random Forest model trained in the offline stage as fingerprints in order to economize memory space and possess a good anti-multipath characteristic. Furthermore, a series of specific experiments are conducted in a microwave anechoic chamber and an office to detail the localization performance of RFFP with different wireless channel circumstances, system parameters, algorithms, and input datasets. In addition, compared with other algorithms including K-Nearest-Neighbor (KNN), Weighted K-Nearest-Neighbor (WKNN), REPTree, CART, and J48, the RFFP method provides far greater classification accuracy as well as lower mean location error. The proposed method offers outstanding comprehensive performance including accuracy, robustness, low workload, and better anti-multipath-fading.
SWCTI: Surface Water Content Temperature Index for Assessment of Surface Soil Moisture Status
Authors: Hong Zhiming , Zhang Wen , Yu Changhui , Zhang Dongying , Li Linyi , Meng Lingkui
Published: August 2018

The vegetation supply water index (VSWI = NDVI/LST) is an effective metric estimating soil moisture in areas with moderate to dense vegetation cover. However, the normalized difference vegetation index (NDVI) exhibits a long water stress lag and the land surface temperature (LST), sensitive to water stress, does not contribute considerably to surface soil moisture monitoring due to the constraints of the mathematical characteristics of VSWI: LST influences VSWI less when LST value is sufficiently high. This paper mathematically analyzes the characteristics of VSWI and proposes a new operational dryness index (surface water content temperature index, SWCTI) for the assessment of surface soil moisture status. SWCTI uses the surface water content index (SWCI), which provides a more accurate estimation of surface soil moisture than that of NDVI, as the numerator and the modified surface temperature, which has a greater influence on SWCTI than that of LST, as the denominator. The validation work includes comparison of SWCTI with in situ soil moisture and other remote sensing indices. The results show SWCTI demonstrates the highest correlation with in situ soil moisture; the highest correlation R = 0.801 is found between SWCTI and the 0–5 cm soil moisture in a sandy loam. SWCTI is a functional and effective method that has a great potential in surface soil moisture monitoring.
Automatic Outcome in Manual Dexterity Assessment Using Colour Segmentation and Nearest Neighbour Classifier
Authors: Oña Edwin Daniel , Sánchez-Herrera Patricia , Cuesta-Gómez Alicia , Martinez Santiago , Jardón Alberto , Balaguer Carlos
Published: August 2018

Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity evaluation. The score is the maximum number of cubes that a person is able to displace during a time window. In a previous paper, an automated version of the Box and Blocks Test using a Microsoft Kinect sensor was presented, and referred to as the Automated Box and Blocks Test (ABBT). In this paper, the feasibility of ABBT as an automated tool for manual dexterity assessment is discussed. An algorithm, based on image segmentation in CIELab colour space and the Nearest Neighbour (NN) rule, was developed to improve the reliability of automatic cube counting. A pilot study was conducted to assess the hand motor function in people with Parkinson’s disease (PD). Three functional assessments were carried out. The success rate in automatic cube counting was studied by comparing the manual (BBT) and the automatic (ABBT) methods. The additional information provided by the ABBT was analysed to discuss its clinical significance. The results show a high correlation between manual (BBT) and automatic (ABBT) scoring. The lowest average success rate in cube counting for ABBT was 92%. Additionally, the ABBT acquires extra information from the cubes’ displacement, such as the average velocity and the time instants in which the cube was detected. The analysis of this information can be related to indicators of health status (coordination and dexterity). The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user’s performance.
Equivalent Circuit Modeling for a Valveless Piezoelectric Pump
Authors: Zhang Jianhui , Wang Yuan , Huang Jun
Published: August 2018

Various kinds of the models had been proposed to explain the relationship between the performance and the structural parameters of valveless piezoelectric pumps, so as to evaluate the functional performance such devices. Among the models, the equivalent circuit model, which converts the multi-field problem of a valveless piezoelectric pump system into a simple circuit problem, is the most simple and clear one. Therefore, the proposed structure and working principle of the valveless piezoelectric pump with multistage Y-shape treelike bifurcate tubes are analyzed; then, the equivalent circuit model of the valveless piezoelectric pump is established based on the working principles of this pump and liquid-electric analogy theory. Finally, an experimental study of the pump is carried out, with a comparative analysis of the experimental results and the simulation results of the generated equivalent circuit. The experimental results show that with a driving voltage of 100 V and frequency of 6 Hz, the maximum flow rate of the valveless piezoelectric pump is 1.16 mL/min. Meanwhile, the output current of equivalent circuit also reaches its peak at the frequency of 6 Hz, therefore, indicating a good predictive ability of this model in calculating the maximum output flow rate and best working frequency of valveless piezoelectric pumps.
A Robust Terrain Aided Navigation Using the Rao-Blackwellized Particle Filter Trained by Long Short-Term Memory Networks
Authors: Lee Jungshin , Bang Hyochoong
Published: August 2018

Terrain-aided navigation (TAN) is a technology that estimates the position of the vehicle by comparing the altitude measured by an altimeter and height from the digital elevation model (DEM). The particle filter (PF)-based TAN has been commonly used to obtain stable real-time navigation solutions in cases where the unmanned aerial vehicle (UAV) operates at a high altitude. Even though TAN performs well on rough and unique terrains, its performance degrades in flat and repetitive terrains. In particular, in the case of PF-based TAN, there has been no verified technique for deciding its terrain validity. Therefore, this study designed a Rao-Blackwellized PF (RBPF)-based TAN, used long short-term memory (LSTM) networks to endure flat and repetitive terrains, and trained the noise covariances and measurement model of RBPF. LSTM is a modified recurrent neural network (RNN), which is an artificial neural network that recognizes patterns from time series data. Using this, this study tuned the noise covariances and measurement model of RBPF to minimize the navigation errors in various flight trajectories. This paper designed a TAN algorithm based on combining RBPF and LSTM and confirmed that it can enable a more precise navigation performance than conventional RBPF based TAN through simulations.
A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks
Authors: Sha Chao , Wang Qi-Wei , Zhang Lu , Wang Ru-Chuan
Published: August 2018

To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data Collectors (MDCs), the network is firstly divided into several regions with the help of the Virtual Scan Line (VSL). Then, the MDCs and the Wireless Charging Vehicles (WCVs) are employed in each region for high efficient data collection and energy replenishment. In order to ensure the integrity of data collection and reduce the rate of packet loss, a speed adjustment scheme for MDC is also proposed. In addition, by calculating the adaptive threshold of the recharging request, those nodes with different energy consumption rates are recharged in a timely way that avoids their premature death. Finally, the limited battery capacity of WCVs and their energy consumption while moving are also taken into account, and an adaptive recharging scheme based on maximum benefit is proposed. Experimental results show that the energy consumption is effectively balanced in DCMRB. Furthermore, this can not only enhance the efficiency of data collection, but also prolong the network lifetime compared with the Energy Starvation Avoidance Online Charging scheme (ESAOC), Greedy Mobile Scheme based on Maximum Recharging Benefit (GMS-MRB) and First-Come First-Served (FCFS) methods.
Energy Efficient Policies for Data Transmission in Disruption Tolerant Heterogeneous IoT Networks
Authors: Stamatakis George , Tragos Elias Z. , Traganitis Apostolos
Published: August 2018

The Internet-of-things facilitates the development of many groundbreaking applications. A large number of these applications involve mobile end nodes and a sparsely deployed network of base stations that operate as gateways to the Internet. Most of the mobile nodes, at least within city areas, are connected through low power wide area networking technologies (LPWAN) using public frequencies. Mobility and sparse network coverage result in long delays and intermittent connectivity for the end nodes. Disruption Tolerant Networks and utilization of heterogeneous wireless interfaces have emerged as key technologies to tackle the problem at hand. The first technology renders communication resilient to intermittent connectivity by storing and carrying data while the later increases the communication opportunities of the end nodes and at the same time reduces energy consumption whenever short-range communication is possible. However, one has to consider that end nodes are typically both memory and energy constrained devices which makes finding an energy efficient data transmission policy for heterogeneous disruption tolerant networks imperative. In this work we utilize information related to the spatial availability of network resources and localization information to formulate the problem at hand as a dynamic programming problem. Next, we utilize the framework of Markov Decision Processes to derive approximately optimal and suboptimal data transmission policies. We also prove that we can achieve improved packet transmission policies and reduce energy consumption, extending battery lifetime. This is achieved by knowing the spatial availability of heterogeneous network resources combined with the mobile node’s location information. Numerical resultsshow significant gains achieved by utilizing the derived approximately optimal and suboptimal policies.
Cytotoxic Desulfated Saponin from Holothuria atra Predicted to Have High Binding Affinity to the Oncogenic Kinase PAK1: A Combined In Vitro and In Silico Study
Authors: Shahinozzaman Md , Ishii Takahiro , Takano Ryo , Halim Mohammad A. , Hossain Md Amzad , Tawata Shinkichi
Published: August 2018

Sea cucumbers have long been utilized in foods and Asiatic folk medicines for their nutritive and health benefits. Herein, three sea cucumber species were investigated and Holothuria atra showed the highest cytotoxicity among these. Next, a desulfated saponin, desulfated echinoside B (DEB), was purified from H. atra through bioassay-guided fractionation. LC-ESI-MS (Liquid chromatography-electrospray ionization mass spectrometry) analysis also showed H. atra to be a rich source of saponins. DEB showed cytotoxicity on cancer cells with IC50 values of 0.5–2.5 µM, and on brine shrimps with an IC50 value of 9.2 µM. In molecular docking studies, DEB was found to bind strongly with the catalytic domain of PAK1 (p21-activated kinase 1) and it showed binding energy of −8.2 kcal/mol compared to binding energy of −7.7 kcal/mol for frondoside A (FRA). Both of them bind to the novel allosteric site close to the ATP-binding cleft. Molecular dynamics (MD) simulation demonstrated that DEB can form a more stable complex with PAK1, remaining inside the allosteric binding pocket and forming the maximum number of hydrogen bonds with the surrounding residues. Moreover, important ligand binding residues were found to be less fluctuating in the DEB-PAK1 complex than in the FRA-PAK1 complex throughout MD simulation. Our experimental and computational studies showed that both DEB and FRA can act as natural allosteric PAK1 inhibitors and DEB appeared to be more promising than FRA.
Uncovering ‘Community’: Challenging an Elusive Concept in Development and Disaster Related Work
Authors: Titz Alexandra , Cannon Terry , Krüger Fred
Published: August 2018

In all areas of academic or practical work related to disaster risk, climate change and development more generally, community and its adjunct community-based have become the default terminology when referring to the local level or working ‘with the people’. The terms are applied extensively to highlight what is believed to be a people-centred, participatory, or grassroot-level approach. Today, despite, or because of, its inherent ambiguity, ‘community’ tends to be used almost inflationarily. This paper aims to analyse the way the concept of ‘community’ has come into fashion, and to critically reflect on the problems that come with it. We are raising significant doubts about the usefulness of ‘community’ in development- and disaster-related work. Our approach is to first consider how ‘community’ has become popular in research and with humanitarian agencies and other organisations based on what can be considered a ‘moral licence’ that supposedly guarantees that the actions being taken are genuinely people-centred and ethically justified. We then explore several theoretical approaches to ‘community’, highlight the vast scope of different (and contested) views on what ‘community’ entails, and explain how ‘community’ is framing practical attempts to mitigate vulnerability and inequity. We demonstrate how these attempts are usually futile, and sometimes harmful, due to the blurriness of ‘community’ concepts and their inherent failure to address the root causes of vulnerability. From two antagonistic positions, we finally advocate more meaningful ways to acknowledge vulnerable people’s views and needs appropriately.
“I Know I Am, But What Are You?”: Public Perceptions of Unions, Members and Joining Intentions
Authors: Gibney Ray , Masters Marick , Aybat Ozge , Amlie Thomas
Published: August 2018

Respondent’s perceptions of demographic, social and behavioral characteristics of union members were analyzed in comparison to the statistical data regarding union members. Respondents also provided perceptions regarding unions themselves as well as future joining intentions. Overall, respondents accurately identified some characteristics of union members and were incorrect on others. General union image was poor as well as future joining intentions. The results of this analysis suggest that union density declines in the private sector will continue.
Assessing the Potential of Rural Settlement Land Consolidation in China: A Method Based on Comprehensive Evaluation of Restricted Factors
Authors: Zhang Mengdi , Wang Xiao , Zhang Zengxiang , Zhao Xiaoli
Published: August 2018

Rural settlement land consolidation potential calculation is the basic work of land consolidation. An accurate potential is essential to rural development planners and policy makers as a project target or prediction. The traditional calculation methods include the per capita/household construction land method, idle rural residential land method, and comprehensive evaluation method. Though there have been some improvements, the potential for calculation methods on a national level is still limited. This article illustrates a new method for calculating the consolidation potential of rural settlement land, based on field data and the restructuring restrictions applicable to each rural land parcel in China. The field data was from Shandong Province because it lies within the country’s biggest grain-producing area with the largest distribution density of rural settlements. It is an excellent representative sample for rural settlement land consolidation, offering a microcosm of rural development in China. For the study’s comprehensive evaluation system, due to the lack of nationwide field survey data, the potential of Shandong Province was chosen as the standard value. We selected indicators concerning land resources, depopulation, transportation accessibility, local economic development, urbanization, and natural conditions to build an evaluation system. We then calculated the potential of each province according to their coefficients and field data from Shandong Province. Every province except Taiwan (for which no data were available) was divided into five zones for rural settlement land consolidation: the most-suitable zone, suitable zone, general zone, restricted zone, and most-restricted zone. The total rate of land consolidation is estimated at 0.24 for 2010 and forecast at 0.33 for 2020, while those years’ respective consolidation potentials are 32,777.92 km2 and 44,707.81 km2. The rate is the total rural settlement land before land consolidation divided by added cultivated land after consolidation. The higher the rate, more effective the land consolidation is.