bluuebunny/crossref_metadata_2025 huggingface dataset:
Water, Sanitation and Hygiene (WASH) in Schools in Low-Income Countries: A Review of Evidence of Impact
Authors: McMichael Celia
Published: January 2019

Many schools in low-income countries have inadequate access to water facilities, sanitation and hygiene promotion. A systematic review of literature was carried out that aimed to identify and analyse the impact of water, sanitation and hygiene interventions (WASH) in schools in low-income countries. Published peer reviewed literature was systematically screened during March to June 2018 using the databases PubMed, Embase, Web of Science, the Cochrane Library, Science Direct, and Google Scholar. There were no publication date restrictions. Thirty-eight peer reviewed papers were identified that met the inclusion criteria. The papers were analysed in groups, based on four categories of reported outcomes: (i) reduction of diarrhoeal disease and other hygiene-related diseases in school students; (ii) improved WASH knowledge, attitudes and hygiene behaviours among students; (iii) reduced disease burden and improved hygiene behaviours in students’ households and communities; (iv) improved student enrolment and attendance. The typically unmeasured and unreported ‘output’ and/or ‘exposure’ of program fidelity and adherence was also examined. Several studies provide evidence of positive disease-related outcomes among students, yet other assessments did not find statistically significant differences in health or indicated that outcomes are dependent on the nature and context of interventions. Thirteen studies provide evidence of changes in WASH knowledge, attitudes and behaviours, such as hand-washing with soap. Further research is required to understand whether and how school-based WASH interventions might improve hygiene habits and health among wider family and community members. Evidence of the impact of school-based WASH programs in reducing student absence from school was mixed. Ensuring access to safe and sufficient water and sanitation and hygiene promotion in schools has great potential to improve health and education and to contribute to inclusion and equity, yet delivering school-based WASH intervention does not guarantee good outcomes. While further rigorous research will be of value, political will and effective interventions with high program fidelity are also key.
Hydrophobic Organic Pollutants in Soils and Dusts at Electronic Waste Recycling Sites: Occurrence and Possible Impacts of Polybrominated Diphenyl Ethers
Authors: Ohajinwa Chimere May , Van Bodegom Peter M. , Xie Qing , Chen Jingwen , Vijver Martina G. , Osibanjo Oladele O. , Peijnenburg Willie J.G.M.
Published: January 2019

Concerns about the adverse consequences of informal electronic waste (e-waste) recycling is increasing, because e-waste contains some hazardous substances such as polybrominated diphenyl ethers (PBDEs) which is used as flame retardants in electronics. There is dearth of information on the concentrations of PBDEs and the pattern of distribution at the various e-waste recycling sites in Nigeria. This study therefore measured the concentrations of 13 PBDE congeners, in top soils (0–10 cm) and in various dust samples from different e-waste recycling sites (burning, dismantling, repair). PBDE concentrations at e-waste sites were compared with the concentrations in samples from corresponding control sites in three study locations in Nigeria (Lagos, Ibadan, and Aba). There were significant differences in the level of PBDEs congeners between each of the e-waste recycling sites and the corresponding control sites. The levels of PBDEs at the e-waste recycling sites exceeded the levels at the controls sites by a factor of 100 s to 1000 s. In general, PBDE concentrations at the e-waste sites decreased with the intensity of the e-waste recycling activities: burning sites > dismantling sites > repair sites > control sites. Our results suggest that the informal e-waste recycling has negative impacts on the enviroment and human health.
Identifying Sexual and Labor Exploitation among Sheltered Youth Experiencing Homelessness: A Comparison of Screening Methods
Authors: Mostajabian Salina , Santa Maria Diane , Wiemann Constance , Newlin Elizabeth , Bocchini Claire
Published: January 2019

Human trafficking is a significant and growing public health concern. Subgroups of adolescents and young adults are particularly vulnerable to human trafficking, especially youth who are unstably housed or homeless. While youth experiencing trafficking come into contact with the healthcare system, they are often not identified during routine assessment due to lack of specific inquiry and low disclosure. Therefore, we utilized a mixed-methods study design to assess the differences in the identification of human trafficking among youth experiencing homelessness (n = 129) between a standard psychosocial assessment tool and a human trafficking specific assessment tool. Findings indicate that the tool developed to specifically assess for human trafficking was more likely to identify youth experiencing sexual and labor exploitation, as well as the risk factors for human trafficking. Secondly, youth reported that mistrust of the system, fear of involving the police if reported, not wanting to interact with the mental healthcare system, and stigma are barriers to disclosing human trafficking. In conclusion, healthcare providers caring for youth experiencing homelessness should adopt improved screening tools for human trafficking to reduce the risk of missed opportunities for prevention and treatment among this high-risk population of youth.
Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China
Authors: Wang Yumiao , Wu Xueling , Chen Zhangjian , Ren Fu , Feng Luwei , Du Qingyun
Published: January 2019

The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, geological maps, and satellite images. Twelve factors were selected as independent variables using correlation coefficient analysis and the neighborhood rough set (NRS) method. In total, 288 soil landslides were mapped using field surveys, historical records, and satellite images. The landslides were randomly divided into two datasets: 70% of all landslides were selected as the original training dataset and 30% were used for validation. Then, SMOTE was employed to generate datasets with sizes ranging from two to thirty times that of the training dataset to establish and compare the four machine learning methods for landslide susceptibility mapping. In addition, we used slope units to subdivide the terrain to determine the landslide susceptibility. Finally, the landslide susceptibility maps were validated using statistical indexes and the area under the curve (AUC). The results indicated that the performances of the four machine learning methods showed different levels of improvement as the sample sizes increased. The RF model exhibited a more substantial improvement (AUC improved by 24.12%) than did the ANN (18.94%), SVM (17.77%), and LR (3.00%) models. Furthermore, the ANN model achieved the highest predictive ability (AUC = 0.98), followed by the RF (AUC = 0.96), SVM (AUC = 0.94), and LR (AUC = 0.79) models. This approach significantly improves the performance of machine learning techniques for landslide susceptibility mapping, thereby providing a better tool for reducing the impacts of landslide disasters.
Dietary Supplement Use Among Chinese Primary School Students: A Cross-Sectional Study in Hunan Province
Authors: Liu Hanmei , Zhang Shiya , Zou Hanshuang , Pan Yuanlin , Yang Qiping , Ouyang Yufeng , Luo Jing , Lin Qian
Published: January 2019

Dietary supplement use is increasing globally, especially among children. However, few studies have been conducted to examine dietary supplement use among Chinese children. The aim of this study was to examine the prevalence of dietary supplement use and the associated factors in primary school students. A cross-sectional study was conducted in four primary schools in Hunan province, China. A total of 706 Chinese parents/caregivers of school children aged 6–12 years old were enrolled. Self-administrated questionnaires were used to collect information about the children’s dietary supplement use, and their socio-demographic characteristics. The prevalence of dietary supplement use in primary school students was 20.4%. Calcium (16.7%), vitamin C (9.2%), and vitamin D (8.5%) were the most commonly used types of dietary supplement. The main reasons for parents/caregivers to purchase dietary supplements for their children were immunity improvement (43.6%), and for growth promotion (36.5%). Some caregivers (26.4%) purchased dietary supplements online, including from dubious or unknown sellers. However, 37.5% of caregivers did not receive formal guidance on supplementation even if they purchased their supplements through formal channels. Parents/caregivers were unclear about the appropriate choices for children’s dietary supplement use. Guidelines and counseling regarding dietary supplements for children may be helpful in public health work.
Modification Effects of Population Expansion, Ageing, and Adaptation on Heat-Related Mortality Risks Under Different Climate Change Scenarios in Guangzhou, China
Authors: Liu Tao , Ren Zhoupeng , Zhang Yonghui , Feng Baixiang , Lin Hualiang , Xiao Jianpeng , Zeng Weilin , Li Xing , Li Zhihao , Rutherford Shannon , Xu Yanjun , Lin Shao , Nasca Philip C. , Du Yaodong , Wang Jinfeng , Huang Cunrui , Jia Peng , Ma Wenjun
Published: January 2019

(1) Background: Although the health effects of future climate change have been examined in previous studies, few have considered additive impacts of population expansion, ageing, and adaptation. We aimed to quantify the future heat-related years of life lost (YLLs) under different Representative Concentration Pathways (RCP) scenarios and global-scale General Circulation Models (GCMs), and further to examine relative contributions of population expansion, ageing, and adaptation on these projections. (2) Methods: We used downscaled and bias-corrected projections of daily temperature from 27 GCMs under RCP2.6, 4.5, and 8.5 scenarios to quantify the potential annual heat-related YLLs in Guangzhou, China in the 2030s, 2060s, and 2090s, compared to those in the 1980s as a baseline. We also explored the modification effects of a range of population expansion, ageing, and adaptation scenarios on the heat-related YLLs. (3) Results: Global warming, particularly under the RCP8.5 scenario, would lead to a substantial increase in the heat-related YLLs in the 2030s, 2060s, and 2090s for the majority of the GCMs. For the total population, the annual heat-related YLLs under the RCP8.5 in the 2030s, 2060s, and 2090s were 2.2, 7.0, and 11.4 thousand, respectively. The heat effects would be significantly exacerbated by rapid population expansion and ageing. However, substantial heat-related YLLs could be counteracted by the increased adaptation (75% for the total population and 20% for the elderly). (4) Conclusions: The rapid population expansion and ageing coinciding with climate change may present an important health challenge in China, which, however, could be partially counteracted by the increased adaptation of individuals.
Vitamin D Status and Mortality: A Systematic Review of Observational Studies
Authors: Heath Alicia K , Kim Iris Y , Hodge Allison M , English Dallas R , Muller David C
Published: January 2019

Epidemiological evidence suggests that vitamin D deficiency is associated with increased mortality, but it is unclear whether this is explained by reverse causation, and if there are specific causes of death for which vitamin D might be important. We conducted a systematic review of observational studies investigating associations between circulating 25-hydroxyvitamin D (25(OH)D) concentration and all-cause or cause-specific mortality in generally healthy populations. Relevant studies were identified using PubMed and EMBASE searches. After screening 722 unique records and removing those that were ineligible, 84 articles were included in this review. The vast majority of studies reported inverse associations between 25(OH)D concentration and all-cause mortality. This association appeared to be non-linear, with progressively lower mortality with increasing 25(OH)D up to a point, beyond which there was no further decrease. There is moderate evidence that vitamin D status is inversely associated with cancer mortality and death due to respiratory diseases, while for cardiovascular mortality, there is weak evidence of an association in observational studies, which is not supported by the data from intervention or Mendelian randomization studies. The relationship between vitamin D status and other causes of death remains uncertain due to limited data. Larger long-term studies are required to clarify these associations.
Flexural Strength Prediction Models for Soil–Cement from Unconfined Compressive Strength at Seven Days
Authors: Linares-Unamunzaga Alaitz , Pérez-Acebo Heriberto , Rojo Marta , Gonzalo-Orden Hernán
Published: January 2019

Soil–cement is an environmentally friendly road construction technique for base and subbase materials, which allows employing soils placed in the right-of-way of the road or in the surroundings, by improving its engineering properties. With this technique, it is possible to reduce the over-exploitation of quarries, the necessity of landfills and the pollutant gas emission due to the reduction of aggregate fabrication and transport. The manufacturing of soil–cement is generally controlled by means of the Uniaxial Compressive Strength (UCS) test at seven days, according to the regulations of each country. Nonetheless, one of the properties that best defines the performance of soil–cement is the Flexural Strength (FS) at long term, usually at 90 days. The aim of this paper is to develop new equations to correlate the UCS and the FS at long term and the UCS at seven days and at 90 days. Obtained results validate the proposed models and, hence, the flexural strength can be predicted from the Uniaxial Compressive Strength at seven days, allowing, if necessary, correcting measures (recalculation or rejection) in early stages of the curing time to be taken.
Material Characterizations of Gr-Based Magnetorheological Elastomer for Possible Sensor Applications: Rheological and Resistivity Properties
Authors: Shabdin Muhammad Kashfi , Abdul Rahman Mohd Azizi , Mazlan Saiful Amri , Ubaidillah  , Hapipi Norhiwani Mohd , Adiputra Dimas , Abdul Aziz Siti Aishah , Bahiuddin Irfan , Choi Seung-Bok
Published: January 2019

Considering persistent years, many researchers continuously seek an optimum way to utilize the idea of magnetorheology (MR) materials to be practically used for everyday life, particularly concerning resistivity sensing application. The rheology and resistivity of a graphite (Gr)-based magnetorheological elastomer (Gr-MRE) were experimentally evaluated in the present research. Magnetorheological elastomer (MRE) samples were prepared by adding Gr as a new additive during MRE fabrication. The effect of additional Gr on the rheological and resistivity properties were investigated and compared with those of typical MREs without a Gr additive. Morphological aspects of Gr-MRE were characterized using field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDX). Rheological properties under different magnetic fields were evaluated using a parallel-plate rheometer. Subsequently, the resistivity of all samples was measured under different applied forces and magnetic fields. From the resistivity evaluation, two relationship curves resistance (R) under different applied forces (F) and different magnetic fields (B) were established and plotted by using an empirical model. It was observed from the FESEM images that the presence of Gr fractions arrangement contributes to the conductivity of MRE. It was also observed that, with the addition of Gr, rheological properties such as the field-dependent modulus can be improved, particularly at low strain amplitudes. It is also demonstrated that the addition of Gr in MRE can contribute to the likely use of force detection in tactile sensing devices.
One-Step Synthesis of Silver Nanowires with Ultra-Long Length and Thin Diameter to Make Flexible Transparent Conductive Films
Authors: Li Yuxiu , Yuan Ximin , Yang Hongwei , Chao Yunxiu , Guo Shuailong , Wang Chuan
Published: January 2019

High aspect ratio silver nanowires (AgNWs) with ultra-long length and thin diameter were synthesized through bromine ion (Br−)-assisted one-step synthesis method. The bromine ions were used as pivotal passivating agent. When the molar ratio of Br−/Cl− was 1:4, the average diameter of AgNWs was as low as ~40 nm, the average length was as high as ~120 μm, and the aspect ratio reached 2500. Networks of AgNWs were fabricated using as-prepared high-quality AgNWs as conducting material and hydroxyethyl cellulose (HEC) as the adhesive polymer. As a result, a low sheet resistance down to ~3.5 Ω sq−1 was achieved with a concomitant transmittance of 88.20% and a haze of 4.12%. The ultra-low sheet resistance of conductive film was attributed to the long and thin AgNWs being able to form a more effective network. The adhesion of the AgNWs to the substrate was 0/5B (ISO/ASTM). The insights given in this paper provide the key guidelines for bromine ion-assisted synthesis of long and thin AgNWs, and further designing low-resistance AgNW-based conductive film for optoelectronic devices.
Low-Loss and Light Substrate Integrated Waveguide Using 3D Printed Honeycomb Structure
Authors: Kim Yeonju , Tentzeris Manos M. , Lim Sungjoon
Published: January 2019

This article proposes a low-loss and light 3D-printed substrate-integrated waveguide (SIW). Despite the use of lossy polylactic acid (PLA) material, insertion loss is reduced, and bandwidth is increased due to a honeycomb substrate similar to air. To demonstrate the proposed concept, we fabricated microstrip-fed SIWs with solid PLA and honeycomb substrates, and compared their performance numerically and experimentally. Average measured insertion loss from 3.4 to 5.5 GHz for the honeycomb SIW is 1.38 dB, whereas SIW with solid PLA is 3.15 dB. Light weight is an additional advantage of the proposed structure.
Microwave Hydrothermal Carbonization of Rice Straw: Optimization of Process Parameters and Upgrading of Chemical, Fuel, Structural and Thermal Properties
Authors: Nizamuddin Sabzoi , Qureshi Sundus Saeed , Baloch Humair Ahmed , Siddiqui Muhammad Tahir Hussain , Takkalkar Pooja , Mubarak Nabisab Mujawar , Dumbre Deepa K. , Griffin Gregory J. , Madapusi Srinivasan , Tanksale Akshat
Published: January 2019

The process parameters of microwave-induced hydrothermal carbonization (MIHTC) play an important role on the hydrothermal chars (hydrochar) yield. The effect of reaction temperature, reaction time, particle size and biomass to water ratio was optimized for hydrochar yield by modeling using the central composite design (CCD). Further, the rice straw and hydrochar at optimum conditions have been characterized for energy, chemical, structural and thermal properties. The optimum condition for hydrochar synthesis was found to be at a 180 °C reaction temperature, a 20 min reaction time, a 1:15 weight per volume (w/v) biomass to water ratio and a 3 mm particle size, yielding 57.9% of hydrochar. The higher heating value (HHV), carbon content and fixed carbon values increased from 12.3 MJ/kg, 37.19% and 14.37% for rice straw to 17.6 MJ/kg, 48.8% and 35.4% for hydrochar. The porosity, crystallinity and thermal stability of the hydrochar were improved remarkably compared to rice straw after MIHTC. Two characteristic peaks from XRD were observed at 2θ of 15° and 26°, whereas DTG peaks were observed at 50–150 °C and 300–350 °C for both the materials. Based on the results, it can be suggested that the hydrochar could be potentially used for adsorption, carbon sequestration, energy and agriculture applications.
Highlighting the Role of Dielectric Thickness and Surface Topography on Electrospreading Dynamics
Authors: Chamakos Nikolaos T. , Sema Dionysios G. , Papathanasiou Athanasios G.
Published: January 2019

The electrospreading behavior of a liquid drop on a solid surface is of fundamental interest in many technological processes. Here we study the effect of the solid topography as well as the dielectric thickness on the dynamics of electrostatically-induced spreading by performing experiments and simulations. In particular, we use an efficient continuum-level modeling approach which accounts for the solid substrate and the electric field distribution coupled with the liquid interfacial shape. Although spreading dynamics depend on the solid surface topography, when voltage is applied electrospreading is independent of the geometric details of the substrate but highly depends on the solid dielectric thickness. In particular, electrospreading dynamics are accelerated with thicker dielectrics. The latter comes to be added to our recent work by Kavousanakis et al., Langmuir, 2018, which also highlights the key role of the dielectric thickness on electrowetting-related phenomena.
UP1306: A Composition Containing Standardized Extracts of Acacia catechu and Morus alba for Arthritis Management
Authors: Yimam Mesfin , Horm Teresa , Wright Laura , Jiao Ping , Hong Mei , Brownell Lidia , Jia Qi
Published: January 2019

Osteoarthritis (OA) is characterized by progressive articular cartilage degradation. Although there have been significant advances in OA management, to date, there are no effective treatment options to modify progression of the disease. We believe these unmet needs could be bridged by nutrients from natural products. Collagen induced arthritis in rats was developed and utilized to evaluate anti-inflammatory and cartilage protection activity of orally administered botanical composition, UP1306 (50 mg/kg) and Methotrexate (75 µg/kg) daily for three weeks. Objective arthritis severity markers, urine, synovial lavage, and serum were collected. At necropsy, the hock joint from each rat was collected for histopathology analysis. Urinary cartilage degradation marker (CTX-II), pro-inflammatory cytokines (tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and IL-6), and proteases (Matrix Metallopeptidase 3 (MMP3) and 13) were measured. Rats treated with UP1306 showed statistically significant improvements in arthritis severity markers, including uCTX-II (91.4% vs. collagen-induced arthritis (CIA)), serum IL-1β, TNF-α, and IL-6 levels as well as synovial MMP-13. The histopathology data were also well aligned with the severity score of arthritis for both UP1306 and Methotrexate. UP1306, a botanical composition that contains a standardized blend of extracts from the heartwood of Acacia catechu and the root bark of Morus alba, could potentially be considered as a dietary supplement product for the management of arthritis.
Metabolomic Salivary Signature of Pediatric Obesity Related Liver Disease and Metabolic Syndrome
Authors: Troisi Jacopo , Belmonte Federica , Bisogno Antonella , Pierri Luca , Colucci Angelo , Scala Giovanni , Cavallo Pierpaolo , Mandato Claudia , Di Nuzzi Antonella , Di Michele Laura , Delli Bovi Anna Pia , Guercio Nuzio Salvatore , Vajro Pietro
Published: January 2019

Pediatric obesity-related metabolic syndrome (MetS) and nonalcoholic fatty liver disease (NAFLD) are increasingly frequent conditions with a still-elusive diagnosis and low-efficacy treatment and monitoring options. In this study, we investigated the salivary metabolomic signature, which has been uncharacterized to date. In this pilot-nested case-control study over a transversal design, 41 subjects (23 obese patients and 18 normal weight (NW) healthy controls), characterized based on medical history, clinical, anthropometric, and laboratory data, were recruited. Liver involvement, defined according to ultrasonographic liver brightness, allowed for the allocation of the patients into four groups: obese with hepatic steatosis ([St+], n = 15) and without hepatic steatosis ([St–], n = 8), and with (n = 10) and without (n = 13) MetS. A partial least squares discriminant analysis (PLS-DA) model was devised to classify the patients’ classes based on their salivary metabolomic signature. Pediatric obesity and its related liver disease and metabolic syndrome appear to have distinct salivary metabolomic signatures. The difference is notable in metabolites involved in energy, amino and organic acid metabolism, as well as in intestinal bacteria metabolism, possibly reflecting diet, fatty acid synthase pathways, and the strict interaction between microbiota and intestinal mucins. This information expands the current understanding of NAFLD pathogenesis, potentially translating into better targeted monitoring and/or treatment strategies in the future.
Enhanced Foamability with Shrinking Microfibers in Linear Polymer
Authors: Kim Eric S. , Park Heon E. , Lopez-Barron Carlos R. , Lee Patrick C.
Published: January 2019

Strain hardening has important roles in understanding material structures and polymer processing methods, such as foaming, film forming, and fiber extruding. A common method to improve strain hardening behavior is to chemically branch polymer structures, which is costly, thus preventing users from controlling the degree of behavior. A smart microfiber blending technology, however, would allow cost-efficient tuning of the degree of strain hardening. In this study, we investigated the effects of compounding polymers with microfibers for both shear and extensional rheological behaviors and characteristics and thus for the final foam morphologies formed by batch physical foaming with carbon dioxide. Extensional rheometry showed that compounding of in situ shrinking microfibers significantly enhanced strain hardening compared to compounding of nonshrinking microfibers. Shear rheometry with linear viscoelastic data showed a greater increase in both the loss and storage modulus in composites with shrinking microfibers than in those with nonshrinking microfibers at low frequencies. The batch physical foaming results demonstrated a greater increase in the cell population density and expansion ratio with in situ shrinking microfibers than with nonshrinking microfibers. The enhancement due to the shrinkage of compounded microfibers decreasing with temperature implies that the strain hardening can be tailored by changing processing conditions.
Near-Real-Time Flood Forecasting Based on Satellite Precipitation Products
Authors: Belabid Nasreddine , Zhao Feng , Brocca Luca , Huang Yanbo , Tan Yumin
Published: January 2019

Floods, storms and hurricanes are devastating for human life and agricultural cropland. Near-real-time (NRT) discharge estimation is crucial to avoid the damages from flood disasters. The key input for the discharge estimation is precipitation. Directly using the ground stations to measure precipitation is not efficient, especially during a severe rainstorm, because precipitation varies even in the same region. This uncertainty might result in much less robust flood discharge estimation and forecasting models. The use of satellite precipitation products (SPPs) provides a larger area of coverage of rainstorms and a higher frequency of precipitation data compared to using the ground stations. In this paper, based on SPPs, a new NRT flood forecasting approach is proposed to reduce the time of the emergency response to flood disasters to minimize disaster damage. The proposed method allows us to forecast floods using a discharge hydrograph and to use the results to map flood extent by introducing SPPs into the rainfall–runoff model. In this study, we first evaluated the capacity of SPPs to estimate flood discharge and their accuracy in flood extent mapping. Two high temporal resolution SPPs were compared, integrated multi-satellite retrievals for global precipitation measurement (IMERG) and tropical rainfall measurement mission multi-satellite precipitation analysis (TMPA). The two products are evaluated over the Ottawa watershed in Canada during the period from 10 April 2017 to 10 May 2017. With TMPA, the results showed that the difference between the observed and modeled discharges was significant with a Nash–Sutcliffe efficiency (NSE) of −0.9241 and an adapted NSE (ANSE) of −1.0048 under high flow conditions. The TMPA-based model did not reproduce the shape of the observed hydrographs. However, with IMERG, the difference between the observed and modeled discharges was improved with an NSE equal to 0.80387 and an ANSE of 0.82874. Also, the IMERG-based model could reproduce the shape of the observed hydrographs, mainly under high flow conditions. Since IMERG products provide better accuracy, they were used for flood extent mapping in this study. Flood mapping results showed that the error was mostly within one pixel compared with the observed flood benchmark data of the Ottawa River acquired by RadarSat-2 during the flood event. The newly developed flood forecasting approach based on SPPs offers a solution for flood disaster management for poorly or totally ungauged watersheds regarding precipitation measurement. These findings could be referred to by others for NRT flood forecasting research and applications.
A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery
Authors: Frantz David , Stellmes Marion , Hostert Patrick
Published: January 2019

Analysis Ready Data (ARD) have undergone the most relevant pre-processing steps to satisfy most user demands. The freely available software FORCE (Framework for Operational Radiometric Correction for Environmental monitoring) is capable of generating Landsat ARD. An essential step of generating ARD is atmospheric correction, which requires water vapor data. FORCE relies on a water vapor database obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). However, two major drawbacks arise from this strategy: (1) The database has to be compiled for each study area prior to generating ARD; and (2) MODIS and Landsat commissioning dates are not well aligned. We have therefore compiled an application-ready global water vapor database to significantly increase the operational readiness of ARD production. The free dataset comprises daily water vapor data for February 2000 to July 2018 as well as a monthly climatology that is used if no daily value is available. We systematically assessed the impact of using this climatology on surface reflectance outputs. A global random sample of Landsat 5/7/8 imagery was processed twice (i) using daily water vapor (reference) and (ii) using the climatology (estimate), followed by computing accuracy, precision, and uncertainty (APU) metrics. All APU measures were well below specification, thus the fallback usage of the climatology is generally a sound strategy. Still, the tests revealed that some considerations need to be taken into account to help quantify which sensor, band, climate, and season are most or least affected by using a fallback climatology. The highest uncertainty and bias is found for Landsat 5, with progressive improvements towards newer sensors. The bias increases from dry to humid climates, whereas uncertainty increases from dry and tropic to temperate climates. Uncertainty is smallest during seasons with low variability, and is highest when atmospheric conditions progress from a dry to a wet season (and vice versa).
Earth Observation and Machine Learning to Meet Sustainable Development Goal 8.7: Mapping Sites Associated with Slavery from Space
Authors: Foody Giles M. , Ling Feng , Boyd Doreen S. , Li Xiaodong , Wardlaw Jessica
Published: January 2019

A large proportion of the workforce in the brick kilns of the Brick Belt of Asia are modern-day slaves. Work to liberate slaves and contribute to UN Sustainable Development Goal 8.7 would benefit from maps showing the location of brick kilns. Previous work has shown that brick kilns can be accurately identified and located visually from fine spatial resolution remote-sensing images. Furthermore, via crowdsourcing, it would be possible to map very large areas. However, concerns over the ability to maintain a motivated crowd to allow accurate mapping over time together with the development of advanced machine learning methods suggest considerable potential for rapid, accurate and repeatable automated mapping of brick kilns. This potential is explored here using fine spatial resolution images of a region of Rajasthan, India. A contemporary deep-learning classifier founded on region-based convolution neural networks (R-CNN), the Faster R-CNN, was trained to classify brick kilns. This approach mapped all of the brick kilns within the study area correctly, with a producer’s accuracy of 100%, but at the cost of substantial over-estimation of kiln numbers. Applying a second classifier to the outputs substantially reduced the over-estimation. This second classifier could be visual classification, which, as it focused on a relatively small number of sites, should be feasible to acquire, or an additional automated classifier. The result of applying a CNN classifier to the outputs of the original classification was a map with an overall accuracy of 94.94% with both low omission and commission error that should help direct anti-slavery activity on the ground. These results indicate that contemporary Earth observation resources and machine learning methods may be successfully applied to help address slavery from space.
Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China
Authors: Wang Xinbing , Miao Yuxin , Dong Rui , Chen Zhichao , Guan Yanjie , Yue Xuezhi , Fang Zheng , Mulla David
Published: January 2019

Precision nitrogen (N) management (PNM) strategies are urgently needed for the sustainability of rain-fed maize (Zea mays L.) production in Northeast China. The objective of this study was to develop an active canopy sensor (ACS)-based PNM strategy for rain-fed maize through improving in-season prediction of yield potential (YP0), response index to side-dress N based on harvested yield (RIHarvest), and side-dress N agronomic efficiency (AENS). Field experiments involving six N rate treatments and three planting densities were conducted in three growing seasons (2015–2017) in two different soil types. A hand-held GreenSeeker sensor was used at V8-9 growth stage to collect normalized difference vegetation index (NDVI) and ratio vegetation index (RVI). The results indicated that NDVI or RVI combined with relative plant height (NDVI*RH or RVI*RH) were more strongly related to YP0 (R2 = 0.44–0.78) than only using NDVI or RVI (R2 = 0.26–0.68). The improved N fertilizer optimization algorithm (INFOA) using in-season predicted AENS optimized N rates better than the N fertilizer optimization algorithm (NFOA) using average constant AENS. The INFOA-based PNM strategies could increase marginal returns by 212 $ ha−1 and 70 $ ha−1, reduce N surplus by 65% and 62%, and improve N use efficiency (NUE) by 4%–40% and 11%–65% compared with farmer’s typical N management in the black and aeolian sandy soils, respectively. It is concluded that the ACS-based PNM strategies have the potential to significantly improve profitability and sustainability of maize production in Northeast China. More studies are needed to further improve N management strategies using more advanced sensing technologies and incorporating weather and soil information.
Security and Accuracy of Fingerprint-Based Biometrics: A Review
Authors: Yang Wencheng , Wang Song , Hu Jiankun , Zheng Guanglou , Valli Craig
Published: January 2019

Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper.
Symplectic Effective Order Numerical Methods for Separable Hamiltonian Systems
Authors: Ahmad Junaid , Habib Yousaf , Rehman Shafiq ur , Arif Azqa , Shafiq Saba , Younas Muhammad
Published: January 2019

A family of explicit symplectic partitioned Runge-Kutta methods are derived with effective order 3 for the numerical integration of separable Hamiltonian systems. The proposed explicit methods are more efficient than existing symplectic implicit Runge-Kutta methods. A selection of numerical experiments on separable Hamiltonian system confirming the efficiency of the approach is also provided with good energy conservation.
Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center
Authors: Memon Sheeba , Huang Jiawei , Saajid Hussain , Khuda Bux Naadiya , Saleem Arshad , Aljeroudi Yazan
Published: January 2019

Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstances as well as the reduction of failures. However, under dynamic traffic, current load-balancing schemes use the fixed parameter setting, resulting in suboptimal performances. Therefore, we propose a multi-level dynamic traffic load-balancing (MDTLB) protocol, which uses an adaptive approach of parameter setting. The simulation results show that the MDTLB outperforms the state-of-the-art schemes in terms of both the flow completion time and throughput in typical data center applications.
Information Security Methods—Modern Research Directions
Authors: Shelupanov Alexander , Evsyutin Oleg , Konev Anton , Kostyuchenko Evgeniy , Kruchinin Dmitry , Nikiforov Dmitry
Published: January 2019

In Tomsk University of Control Systems and Radioelectronics (TUSUR) one of the main areas of research is information security. The work is carried out by a scientific group under the guidance of Professor Shelupanov. One of the directions is the development of a comprehensive approach to assessing the security of the information systems. This direction includes the construction of an information security threats model and a protection system model, which allow to compile a complete list of threats and methods of protection against them. The main directions of information security tools development are dynamic methods of biometrics, methods for generating prime numbers for data encryption, steganography, methods and means of data protection in Internet of Things (IoT) systems. The article presents the main results of research in the listed areas of information security. The resultant properties in symmetric cryptography are based on the properties of the power of the generating functions. The authors have obtained symmetric principles for the development of primality testing algorithms, as discussed in the Appendix.
Two Variables Shivley’s Matrix Polynomials
Authors: He Fuli , Bakhet Ahmed , Hidan M. , Abdalla M.
Published: January 2019

The principal object of this paper is to introduce two variable Shivley’s matrix polynomials and derive their special properties. Generating matrix functions, matrix recurrence relations, summation formula and operational representations for these polynomials are deduced. Finally, Some special cases and consequences of our main results are also considered.
Multi-Criteria Decision-Making Method Based on Single-Valued Neutrosophic Schweizer–Sklar Muirhead Mean Aggregation Operators
Authors: Zhang Huanying , Wang Fei , Geng Yushui
Published: January 2019

Schweizer–Sklar (SS) operation can make information aggregation more flexible, and the Muirhead mean (MM) operator can take into account the correlation between inputs by a variable parameter. Because traditional MM is only available for real numbers and single-valued neutrosophic set (SVNS) can better express incomplete and uncertain information in decision systems, in this paper, we applied MM operators to single-valued neutrosophic sets (SVNSs) and presented two new MM aggregation operators with the SS operation, i.e., a single-valued neutrosophic SS Muirhead mean (SVNSSMM) operator and a weighted single-valued neutrosophic SS MM (WSVNSSMM) operator. We listed some properties of them and some particular cases about various parameter values. We also proposed the multi-criteria decision-making method based on the WSVNSSMM operator in SVNS. At last, we illustrated the feasibility of this method using a numerical example of company investment.
Overexpression of the Interferon-Inducible Isoform 4 of NCOA7 Dissects the Entry Route of Enveloped Viruses and Demonstrates that HIV Enters Cells via Fusion at the Plasma Membrane
Authors: Herold Nikolas
Published: January 2019

The HIV-1 entry-route is a matter of ongoing controversy, and there is evidence for fusion either at the cell surface or from within endosomes. A recent report demonstrated that isoform 4 of nuclear receptor coactivator 7 (NCOA7iso4) interacts with endolysosomal vacuolar-type H+-ATPase (V-ATPase), increasing lytic activity and thereby severely affecting the entry of vesicular stomatitis virus glycoprotein (VSV-G)-mediated, but not HIV-Env-mediated, entry and infection. As basal expression of NCOA7iso4 is low in the absence of type-1 interferons, its overexpression is a novel tool to study viral entry.
Evaluation of Gridded Precipitation Datasets over Arid Regions of Pakistan
Authors: Ahmed Kamal , Shahid Shamsuddin , Wang Xiaojun , Nawaz Nadeem , Khan Najeebullah
Published: January 2019

The rough topography, harsh climate, and sparse monitoring stations have limited hydro-climatological studies in arid regions of Pakistan. Gauge-based gridded precipitation datasets provide an opportunity to assess the climate where stations are sparsely located. Though, the reliability of these datasets heavily depends on their ability to replicate the observed temporal variability and distribution patterns. Conventional correlation or error analyses are often not enough to justify the variability and distribution of precipitation. In the present study, mean bias error, mean absolute error, modified index of agreement, and Anderson–Darling test have been used to evaluate the performance of four widely used gauge-based gridded precipitation data products, namely, Global Precipitation Climatology Centre (GPCC), Climatic Research Unit (CRU); Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation (APHRODITE), Center for Climatic Research—University of Delaware (UDel) at stations located in semi-arid, arid, and hyper-arid regions in the Balochistan province of Pakistan. The result revealed that the performance of different products varies with climate. However, GPCC precipitation data was found to perform much better in all climatic regions in terms of most of the statistical assessments conducted. As the temporal variability and distribution of precipitation are very important in many hydrological and climatic applications, it can be expected that the methods used in this study can be useful for the better assessment of gauge-based data for various applications.
Immune Evolution Particle Filter for Soil Moisture Data Assimilation
Authors: Ju Feng , An Ru , Sun Yaxing
Published: January 2019

Data assimilation (DA) has been widely used in land surface models (LSM) to improve model state estimates. Among various DA methods, the particle filter (PF) with Markov chain Monte Carlo (MCMC) has become increasingly popular for estimating the states of the nonlinear and non-Gaussian LSMs. However, the standard PF always suffers from the particle impoverishment problem, characterized by loss of particle diversity. To solve this problem, an immune evolution particle filter with MCMC simulation inspired by the biological immune system, entitled IEPFM, is proposed for DA in this paper. The merit of this approach is in imitating the antibody diversity preservation mechanism to further improve particle diversity, thus increasing the accuracy of estimates. Furthermore, the immune memory function refers to promise particle evolution process towards optimal estimates. Effectiveness of the proposed approach is demonstrated by the numerical simulation experiment using a highly nonlinear atmospheric model. Finally, IEPFM is applied to a soil moisture (SM) assimilation experiment, which assimilates in situ observations into the Variable Infiltration Capacity (VIC) model to estimate SM in the MaQu network region of the Tibetan Plateau. Both synthetic and real case experiments demonstrate that IEPFM mitigates particle impoverishment and provides more accurate assimilation results compared with other popular DA algorithms.